TMJ MRI structural features and horizontal condylar angle across a seven-type disc-condyle classification: a retrospective cross-sectional study with patient-clustered GEE and ROC analysis

TMJ MRI structural features and horizontal condylar angle across a seven-type disc-condyle classification: a retrospective cross-sectional study with patient-clustered GEE and ROC analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article TMJ MRI structural features and horizontal condylar angle across a seven-type disc-condyle classification: a retrospective cross-sectional study with patient-clustered GEE and ROC analysis Hang Li, Lili Wei, Fang Wang, Bo Li This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9389404/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 8 You are reading this latest preprint version Abstract Background MRI findings in temporomandibular joint disc displacement are commonly described using individual structural markers, whereas integrated disc-condyle classification frameworks remain limited. This study aimed to characterize magnetic resonance imaging structural features and horizontal condylar angle across a seven-type disc-condyle classification and to evaluate their associations and discriminatory performance for anterior disc displacement and anterior disc displacement without reduction. Methods This single-center retrospective cross-sectional study included 310 patients, contributing 568 temporomandibular joint sides. Joints were classified as normal disc position, anterior disc displacement with reduction, or anterior disc displacement without reduction, with anterior, anterolateral, and anteromedial subtypes. Disc deformation, condylar position, condylar morphology, condylar bone status, and horizontal condylar angle were assessed. Associations and discrimination were evaluated using patient-clustered generalized estimating equation models and receiver operating characteristic analysis. Results Compared with nondisplaced joints, displaced joints showed greater disc deformation, more frequent condylar abnormalities, and higher horizontal condylar angle values. In multivariable analyses, horizontal condylar angle, posterior condylar position, and condylar bone status were independently associated with anterior disc displacement. Disc deformation grade, condylar morphology grade, condylar bone status, and anterior condylar position were independently associated with anterior disc displacement without reduction. Apparent area under the curve values were 0.833 for anterior disc displacement and 0.923 for anterior disc displacement without reduction, whereas horizontal condylar angle alone showed only moderate discrimination. Conclusions Temporomandibular joint disc displacement is characterized by coordinated abnormalities of disc deformation, condylar position, condylar morphology, condylar bone status, and horizontal condylar angle. The seven-type framework may support more refined magnetic resonance imaging-based structural stratification, whereas horizontal condylar angle is better interpreted as a complementary quantitative marker rather than a standalone diagnostic threshold. Temporomandibular joint Magnetic resonance imaging Anterior disc displacement Disc displacement without reduction Horizontal condylar angle Disc-condyle classification Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Background Temporomandibular disorders (TMDs) comprise a heterogeneous spectrum of conditions. Among intra-articular TMDs, anterior disc displacement (ADD) is common, and ADD without reduction (ADDwoR) is often associated with pain, joint sounds, and functional limitation. Magnetic resonance imaging (MRI) is routinely used to determine disc position and reduction status and to characterize disc morphology, and it remains central to the assessment of disc-condyle derangement [ 1 , 2 ]. However, the clinical interpretability of MRI-based findings remains limited in several respects. First, prior studies have often focused on specific imaging markers—such as condylar position, condylar morphology, disc morphology, joint space, or angular parameters such as the horizontal condylar angle (HCA)—with limited integration of these features into a unified disc-condyle classification framework [ 3 – 6 ]. Second, ADD classifications vary across studies, and coronal MRI assessment of mediolateral disc displacement is not consistently incorporated, which may constrain stratification of complex disc-condyle patterns [ 2 , 6 – 8 ]. Prior MRI-based work has also shown that rotational disc displacement is not uncommon and that coronal classification should not be overlooked, particularly in joints with displacement with reduction [ 1 , 9 ]. Third, reported associations between HCA and disc displacement have varied across studies, potentially reflecting differences in classification schemes and limited adjustment for co-occurring structural MRI features [ 3 , 5 , 6 ]. To address these gaps, we applied a seven-type MRI-based disc-condyle classification integrating reduction status (with vs without reduction) and coronal displacement direction (anterior/anteromedial/anterolateral), yielding normal disc position plus six ADD subtypes. This framework was intended not only to refine descriptive classification, but also to determine whether incorporating the coronal mediolateral component could reveal subtype-specific patterns of co-occurring structural abnormality that may not be captured by a binary reducing/nonreducing scheme alone. We then characterized MRI structural features and HCA across the seven disc-condyle groups, assessed HCA reliability, and used patient-clustered univariable and multivariable generalized estimating equation (GEE) models together with ROC analysis to evaluate associations, independent correlates, and discriminatory performance for distinguishing normal disc position from ADD and reducing from nonreducing displacement. Methods Study design and ethics This retrospective cross-sectional study was approved by the Ethics Committee of School & Hospital of Stomatology, Wuhan University (Approval No. WDKQ2026-B04) and was conducted in accordance with the Declaration of Helsinki. The requirement for informed consent was waived by the Ethics Committee of School & Hospital of Stomatology, Wuhan University because of the retrospective design and the use of anonymized imaging data. Study population We screened consecutive patients who underwent clinically indicated temporomandibular joint (TMJ) MRI in the Department of Radiology at our institution between July 2023 and December 2024. Inclusion criteria were: (1) diagnostic TMJ MRI available for review and (2) no prior TMJ-related treatment before imaging. Exclusion criteria were: (1) other confirmed TMJ diseases, (2) congenital craniofacial developmental deformities, (3) recent maxillofacial trauma, (4) inadequate head positioning precluding reliable measurement of the horizontal condylar angle (HCA), and (5) suboptimal image quality. MRI acquisition protocol MRI was performed on a 1.5-T system (uMR 580, United Imaging Healthcare, China) with a dedicated 4-channel TMJ surface coil. Proton density-weighted imaging (PDWI) was obtained in closed- and open-mouth positions at maximal comfortable opening; the remaining sequences were obtained in the closed-mouth position. Sequences and acquisition parameters are summarized in Supplementary Table S1 . MRI image analysis (1) Image interpretation and reliability assessment All images were interpreted and measured on a PACS workstation by two radiologists (Reader A, mid-level; Reader B, senior), both blinded to clinical information and to each other's results. For reliability assessment, 50 TMJ sides were randomly selected. Reader A re-evaluated the images after an interval of at least 4 weeks to assess intraobserver reliability, including repeated HCA measurements, and Reader B independently assessed the same sample to assess interobserver reliability. In the full dataset, all imaging variables were assessed by Reader A, and equivocal cases were resolved by consensus with Reader B. HCA reliability was quantified using the intraclass correlation coefficient (ICC; absolute agreement, single measure) with 95% confidence intervals, using a two-way mixed-effects model for intraobserver reliability [ICC(3,1)] and a two-way random-effects model for interobserver reliability [ICC(2,1)]. Agreement for categorical and ordinal variables was assessed using Cohen's kappa with 95% confidence intervals: unweighted kappa for nominal variables (the seven-type disc-condyle classification and condylar position) and quadratic weighted kappa for ordinal variables (disc deformation grade, condylar morphology grade, and condylar bone status grade). As an ancillary analysis, agreement between CBCT and MRI for condylar findings was explored in 50 patients who had both examinations, with one TMJ side included per patient. Unweighted Cohen’s kappa was used for condylar position, and quadratic weighted kappa was used for condylar morphology and condylar bone status grades. (2) Disc-condyle classification Based on expert consensus [ 10 ], each TMJ was classified into one of seven MRI-based disc-condyle groups (Fig. 1 ): NDP (normal disc position); ADDwR-A/AL/AM (ADD with reduction, anterior/anterolateral/anteromedial); and ADDwoR-A/AL/AM (ADD without reduction, anterior/anterolateral/anteromedial). NDP was defined as a posterior band located near the condylar apex in the closed-mouth position, without medial or lateral protrusion, with the intermediate zone interposed between the condyle and the articular eminence on mouth opening. ADDwR was defined as an anteriorly positioned posterior band in the closed-mouth position, approximately anterior to the 11:30 clock-face position, with normalization on mouth opening [ 10 , 11 ]. ADDwoR was defined as a posterior band remaining anterior to the condyle in both closed- and open-mouth positions. “AL” and “AM” indicate additional anterolateral and anteromedial displacement on coronal MRI, respectively. Throughout the manuscript and in all figures and tables, groups are referred to using these abbreviations. For analysis, ADD included all displaced groups. Oblique sagittal (closed- and open-mouth) and oblique coronal (closed-mouth) proton density-weighted images (PDWI) illustrate representative disc-condyle patterns. (A,B) Normal disc position. (C,D) Anterior disc displacement with reduction (ADDwR). (E,F) Anterior disc displacement without reduction (ADDwoR). (G) Lateral disc displacement on coronal PDWI. (H) Medial disc displacement on coronal PDWI. (3) Classification of disc morphology and condylar position, morphology, and osseous status Disc morphology was classified on closed-mouth PDWI using disc length, band integrity, and extent of deformation, yielding five descriptive types that were collapsed into four analytic grades. Grade I (approximately normal) required identifiable anterior, intermediate, and posterior bands and included biconcave morphology (a V-shaped superior border with an inverted V-shaped inferior border) and concave-shaped morphology (a V-shaped superior border with a smoothly arched concave inferior border). Grade II corresponded to mildly folded morphology, defined by mild undulation of the intermediate zone with preserved band recognizability. Grade III corresponded to a shortened folded disc with recognizable bands. Grade IV represented severe deformation with poorly recognizable bands (ovoid, triangular, sheet-like, or otherwise unclassifiable). Five-type distributions were reported descriptively, whereas the four-grade variable was used in regression analyses. Representative MRI examples of disc morphology patterns and grading are shown in Fig. 2 . Condylar position was classified as anterior, concentric, or posterior using the Pullinger and Hollender method [ 11 ]. Condylar morphology was categorized as approximately normal, beak-shaped (anterior osteophyte without reduced condylar height), or shortened (a small condyle with reduced height). Condylar osseous findings were initially recorded as six items (normal, cortical discontinuity, sclerosis/hyperplasia with osteophytes, erosion/defect, cystic change, and bone marrow edema) and were then collapsed into three analytic categories: approximately normal (normal or mild wear, including cortical discontinuity or surface irregularity), degenerative change (sclerosis/hyperplasia with osteophytes, cystic change, or bone marrow edema), and severe destruction (extensive erosion or large-area osseous defects). Representative MRI examples of condylar position, condylar morphology, and condylar osseous status are shown in Fig. 3 . Closed-mouth oblique sagittal PDWI shows representative disc morphology patterns and analytic grades: (A) biconcave (Grade I); (B) concave-shaped (Grade I); (C) mildly folded (Grade II); (D) shortened folded (Grade III); and (E,F) severe deformation (Grade IV; two examples). Representative sagittal images illustrate condylar position, morphology, and osseous status. (A,B) PDWI showing approximately normal osseous status and morphology, with concentric (A) and posterior (B) condylar position. (C) PDWI showing sclerosis/hyperplasia with osteophyte formation (beak-shaped condyle) and anterior condylar position. (D) T2WI-FS showing cystic change (hyperintense focus). (E) PDWI showing severe osseous destruction. (F) PDWI showing a shortened condyle. (4) HCA measurement HCA was measured on closed-mouth axial T2-weighted images at the slice showing the maximal cross-sectional area of the condyle. The condylar long axis was defined as the line connecting the medial and lateral poles of the condyle. HCA was defined as the angle between the condylar long axis and the line connecting the most anterior points of both auricles. A schematic illustration of the measurement is shown in Fig. 4 . Each measurement was performed twice, and the mean value was used for analysis. The yellow line connects the most anterior points of both auricles and serves as the horizontal reference line. The white line represents the extended condylar long axis, defined as the line connecting the medial and lateral poles of the condyle. The angle between the two lines is defined as the horizontal condylar angle (HCA). Statistical analysis Descriptive analyses were performed at the joint level. Continuous variables are presented as mean ± standard deviation (SD) when approximately normally distributed or as median (interquartile range [IQR]) otherwise; normality and variance homogeneity were assessed using the Shapiro-Wilk and Levene tests. Exploratory comparisons across the seven disc-condyle groups used one-way ANOVA or Welch ANOVA, as appropriate, followed by Tukey or Games-Howell post hoc tests with multiplicity adjustment. Categorical variables are presented as n (%) and were compared using the chi-square test or Fisher's exact test, with Bonferroni correction where appropriate. Because some patients contributed bilateral joints, these groupwise P values were considered descriptive only; inferential conclusions were based on patient-clustered GEE models. To account for within-patient bilateral correlation, we used patient-clustered GEE logistic regression with a logit link, exchangeable working correlation structure, and robust variance. Two contrasts were modeled: ADD (NDP vs all displaced groups) and ADDwoR (ADDwR-A/AL/AM vs ADDwoR-A/AL/AM). For each contrast, both univariable and multivariable analyses were performed. Variables in the multivariable models were prespecified on the basis of clinical relevance and study objectives. HCA was modeled continuously (per 1° increase); condylar position was entered with concentric position as the reference category; and condylar morphology grade, condylar bone status grade, and disc deformation grade were entered as ordered variables. Discrimination was assessed using ROC analysis. For the multivariable models, ROC curves were constructed from individual predicted probabilities, and AUC 95% CIs were estimated by patient-level cluster bootstrap. Univariate ROC analysis was also performed for HCA alone. Sensitivity analyses additionally adjusted for age and sex. Given the retrospective cross-sectional design, these analyses were used to assess associations with current disc-condyle status and in-sample discrimination rather than to predict future outcomes. During manuscript preparation, the authors used ChatGPT (OpenAI) to assist with language refinement, structural editing, and formatting of the manuscript. The authors reviewed and edited all outputs as needed and take full responsibility for the content of the manuscript. Results 1. Study population A total of 310 patients (234 women and 76 men) were included, contributing 568 TMJ sides. Baseline characteristics by disc-condyle group are shown in Supplementary Table S2. 2. Reliability In the randomly selected 50 TMJ sides, intraobserver and interobserver agreement for all imaging classifications and grades, as well as the reliability of HCA measurements, are summarized in Table 1 . In an ancillary comparison of 50 patients who underwent both examinations, CBCT and MRI showed good agreement for condylar position, condylar morphology grade, and condylar bone status grade (Supplementary Table S3). Table 1 Intra- and interobserver agreement (n = 50 TMJ sides) Measure Intra Agree., % Intra κ/ICC (95% CI) Inter Agree., % Inter κ/ICC (95% CI) Disc–condyle relationship classification (seven-type) 90.0 0.873 (0.756–0.973) 88.0 0.850 (0.727–0.950) Disc deformation grade (4-level) 92.0 0.966 (0.924–0.992) 86.0 0.938 (0.878–0.975) Condylar position (3-category) 92.0 0.861 (0.710–0.967) 90.0 0.829 (0.671–0.964) Condylar morphology grade (3-level) 94.0 0.775 (0.396–1.000) 94.0 0.731 (0.242–1.000) Condylar bone status grade (3-level) 94.0 0.878 (0.567–1.000) 88.0 0.752 (0.464–0.917) HCA (°) — 0.869 (0.736–0.946) — 0.806 (0.672–0.880) CI, confidence interval. “Agree., %” indicates observed agreement (categorical/ordinal variables only). Unweighted Cohen’s κ was used for nominal variables and quadratic weighted κ for ordinal variables. HCA reliability was assessed using ICC. “—” indicates not applicable. 3. Comparisons of disc morphology and condylar imaging features across groups Contingency tables summarized imaging-feature distributions across the seven disc-condyle groups. Disc morphology, disc deformation grade, condylar position, condylar morphology grade, and condylar bone status grade differed across groups (chi-square test, P < 0.001; because some patients contributed bilateral joints, these P values are descriptive only). Disc morphology distributions are presented in Table 2 , and groupwise distributions of disc deformation grade, condylar position, morphology, and bone status are presented in Table 3 . A graded pattern was observed along the disc-condyle spectrum. NDP was dominated by biconcave discs, Grade I disc deformation, concentric condylar position, and largely normal condylar morphology and osseous status. Across ADDwR-A/AL/AM, disc morphology was mainly biconcave, concave-shaped, or mildly folded, corresponding predominantly to Grade I deformation, with Grade II as the second most common category; posterior condylar position was more frequent; and osseous status remained largely normal. In ADDwoR-A/AL/AM, shortened folded and severely deformed discs were more prominent, and disc deformation was mainly distributed in Grades III and IV; degenerative change and severe destruction were more frequent, with severe destruction relatively more common in ADDwoR-A. Compared with ADDwR-A/AL/AM, abnormal condylar morphology was more frequent in ADDwoR-A/AL/AM. Within ADDwoR, beak-shaped condyles were particularly common in ADDwoR-AL/ADDwoR-AM, whereas shortened condyles were relatively more common in ADDwoR-A. These distributional findings motivated subsequent patient-clustered univariable and multivariable GEE analyses to evaluate associations with ADD and ADDwoR after accounting for within-patient bilateral correlation. Table 2 Disc morphology distribution by disc–condyle group, n (%). Group N (TMJ sides) Biconcave Concave-shaped Mildly folded Shortened folded Severe deformation NDP 133 130 (97.7) 3 (2.3) 0 (0.0) 0 (0.0) 0 (0.0) ADDwR-A 85 33 (38.8) 27 (31.8) 23 (27.1) 1 (1.2) 1 (1.2) ADDwR-AL 64 15 (23.4) 30 (46.9) 10 (15.6) 2 (3.1) 7 (10.9) ADDwR-AM 62 27 (43.5) 19 (30.6) 9 (14.5) 0 (0.0) 7 (11.3) ADDwoR-A 81 3 (3.7) 1 (1.2) 10 (12.3) 30 (37.0) 37 (45.7) ADDwoR-AL 75 4 (5.3) 13 (17.3) 11 (14.7) 23 (30.7) 24 (32.0) ADDwoR-AM 68 2 (2.9) 3 (4.4) 8 (11.8) 16 (23.5) 39 (57.4) Values are n (%) within each group. Grade I includes biconcave and concave-shaped discs; Grade II, mildly folded discs; Grade III, shortened folded discs; Grade IV, severely deformed discs. Abbreviations: NDP, normal disc position; ADDwR, anterior disc displacement with reduction; ADDwoR, anterior disc displacement without reduction; A, anterior; AL, anterolateral; AM, anteromedial. Table 3 Condylar imaging features distribution by disc–condyle group, n (%). Group sizes are provided in Table 2 . Group Condylar position Condylar morphology grade Condylar bone status grade Concentric Posterior Anterior Normal Beak-shaped Shortened Normal Degenerative Destruction NDP 78 (58.6) 42 (31.6) 13 (9.8) 133 (100.0) 0 (0.0) 0 (0.0) 125 (94.0) 8 (6.0) 0 (0.0) ADDwR-A 4 (4.7) 80 (94.1) 1 (1.2) 84 (98.8) 0 (0.0) 1 (1.2) 78 (91.8) 7 (8.2) 0 (0.0) ADDwR-AL 9 (14.1) 54 (84.4) 1 (1.6) 64 (100.0) 0 (0.0) 0 (0.0) 59 (92.2) 5 (7.8) 0 (0.0) ADDwR-AM 14 (22.6) 42 (67.7) 6 (9.7) 62 (100.0) 0 (0.0) 0 (0.0) 56 (90.3) 6 (9.7) 0 (0.0) ADDwoR-A 16 (19.8) 44 (54.3) 21 (25.9) 63 (77.8) 9 (11.1) 9 (11.1) 38 (46.9) 31 (38.3) 12 (14.8) ADDwoR-AL 19 (25.3) 37 (49.3) 19 (25.3) 55 (73.3) 14 (18.7) 6 (8.0) 39 (52.0) 35 (46.7) 1 (1.3) ADDwoR-AM 21 (30.9) 33 (48.5) 14 (20.6) 48 (70.6) 16 (23.5) 4 (5.9) 35 (51.5) 28 (41.2) 5 (7.4) Values are n (%) within each group. Abbreviations: NDP, normal disc position; ADDwR, anterior disc displacement with reduction; ADDwoR, anterior disc displacement without reduction; A, anterior; AL, anterolateral; AM, anteromedial. 4. HCA across groups HCA differed across disc-condyle groups (Table 4 and Fig. 5). Descriptive post hoc comparisons suggested similar HCA values among NDP, ADDwR-A, and ADDwR-AL; higher values in ADDwR-AM, ADDwoR-A, and ADDwoR-AL; and the highest values in ADDwoR-AM. When stratified by reduction status, HCA showed a graded increase from NDP to ADDwR and ADDwoR. When HCA was categorized as 0–9 degrees, 10–30 degrees, and > 30 degrees, the distribution also differed across groups (chi-square test, P 30 degrees increased across displaced groups and was highest in ADDwoR-AM (Table 4 ). These unadjusted patterns were further examined in patient-clustered multivariable GEE models that accounted for within-patient bilateral correlation. Table 4 Mean HCA and categorical distribution by disc–condyle group, n (%). Group sizes are provided in Table 2 . Group HCA, mean ± SD (°) 0–9°, n (%) 10–30°, n (%) > 30°, n (%) NDP 18.0 ± 6.7 13 (9.8) 119 (89.5) 1 (0.8) ADDwR-A 20.0 ± 8.2 9 (10.6) 68 (80.0) 8 (9.4) ADDwR-AL 18.1 ± 8.0 7 (10.9) 52 (81.2) 5 (7.8) ADDwR-AM 26.2 ± 9.8 2 (3.2) 39 (62.9) 21 (33.9) ADDwoR-A 27.4 ± 10.9 4 (4.9) 49 (60.5) 28 (34.6) ADDwoR-AL 25.4 ± 12.5 6 (8.0) 44 (58.7) 25 (33.3) ADDwoR-AM 34.3 ± 12.0 1 (1.5) 26 (38.2) 41 (60.3) Values are n (%) within each group unless otherwise indicated. Abbreviations: HCA, horizontal condylar angle; SD, standard deviation; NDP, normal disc position; ADDwR, anterior disc displacement with reduction; ADDwoR, anterior disc displacement without reduction; A, anterior; AL, anterolateral; AM, anteromedial. Figure 5. Raincloud plot of HCA across the seven disc-condyle groups. Raincloud plots show the distribution of HCA across the seven MRI-based disc-condyle groups. The half-violin indicates distribution density, dots represent individual TMJ sides, and the overlaid boxplot summarizes the distribution. Abbreviations: NDP, normal disc position; ADDwR, anterior disc displacement with reduction; ADDwoR, anterior disc displacement without reduction; A, anterior; AL, anterolateral; AM, anteromedial. 5. Univariable and multivariable GEE logistic regression and ROC analysis Patient-clustered univariable and multivariable GEE logistic regression models are summarized in Table 5 . In the ADD analysis, univariable GEE showed significant associations for HCA, posterior condylar position, and condylar bone status grade. In the multivariable ADD model, HCA, posterior condylar position, and condylar bone status grade remained independently associated with ADD, whereas anterior condylar position was not statistically significant. Condylar morphology grade and disc deformation grade were not included because the NDP group showed no variability for these variables. In the ADDwoR analysis, univariable GEE showed significant associations for HCA, condylar position, condylar morphology grade, condylar bone status grade, and disc deformation grade. In the multivariable ADDwoR model, higher disc deformation grade, condylar morphology grade, and condylar bone status grade remained independently associated with ADDwoR. Relative to concentric position, anterior condylar position was independently associated with ADDwoR, whereas posterior condylar position was not statistically significant after adjustment. HCA showed a positive trend but did not remain independently associated in the multivariable model. ROC curves based on model-derived individual probabilities are shown in Fig. 6 . The apparent AUCs were 0.833 (95% CI, 0.783–0.880) for the ADD model and 0.923 (95% CI, 0.895–0.948) for the ADDwoR model, indicating good in-sample discrimination for both contrasts, particularly for ADDwoR. In sensitivity analyses additionally adjusting for age and sex, neither covariate was statistically significant, and the effect estimates for the main imaging variables were materially unchanged. Given the cross-sectional design, these ROC results reflect discrimination of current disc-condyle status rather than prediction of future progression or outcomes. In univariate ROC analysis, HCA showed moderate discrimination for both ADD and ADDwoR, with AUCs of 0.688 (95% CI, 0.631–0.741) and 0.684 (95% CI, 0.629–0.736), respectively (Fig. 6 ). The Youden index-based reference cutoffs were 26° for ADD and 28° for ADDwoR. These findings indicate that HCA alone is insufficient for precise classification but may still provide supportive discriminatory information as a quantitative imaging marker, and is therefore better interpreted as a complementary imaging indicator rather than a standalone diagnostic threshold. (A) ADD: AUC = 0.688 for HCA alone and 0.833 for the multivariable GEE model. (B) ADDwoR: AUC = 0.684 for HCA alone and 0.923 for the multivariable GEE model. Model-based ROC curves were constructed from individual predicted probabilities and reflect discrimination of current disc-condyle status in this cross-sectional dataset. Table 5 Patient-clustered univariable and multivariable GEE logistic regression models for ADD and ADDwoR Predictor ADD univariable OR (95% CI) P value ADD multivariable OR (95% CI) P value ADDwoR univariable OR (95% CI) P value ADDwoR multivariable OR (95% CI) P value HCA (per 1° increase) 1.06 (1.04–1.08) < 0.001 1.07 (1.04–1.09) < 0.001 1.07 (1.05–1.09) < 0.001 1.03 (1.00–1.05) 0.072 Condylar position: posterior vs concentric 3.49 (2.26–5.38) < 0.001 4.57 (2.80–7.46) < 0.001 0.32 (0.19–0.56) < 0.001 0.67 (0.27–1.68) 0.397 Condylar position: anterior vs concentric 1.88 (0.99–3.59) 0.056 1.56 (0.74–3.31) 0.245 3.28 (1.39–7.73) 0.007 3.38 (1.11–10.34) 0.033 Condylar bone status grade (per 1-grade increase) 3.15 (1.97–5.04) < 0.001 3.40 (1.86–6.22) < 0.001 9.08 (5.37–15.37) < 0.001 4.38 (2.46–7.79) < 0.001 Condylar morphology grade (per 1-grade increase) — — — — 30.78 (3.71–255.22) 0.001 8.98 (2.36–34.21) 0.001 Disc deformation grade (4-level, per 1-grade increase) — — — — 4.18 (3.19–5.49) < 0.001 3.87 (2.89–5.19) < 0.001 OR, odds ratio; CI, confidence interval; HCA, horizontal condylar angle; NDP, normal disc position. “Concentric” denotes the reference category for condylar position. “—” indicates not estimable or not included. In the ADD analyses, condylar morphology grade and disc deformation grade were not estimable and were therefore not included, because the NDP reference group showed no variability for these variables (all Grade I / normal pattern). Discussion In this study, using a relatively large TMJ MRI dataset, we applied a seven-type disc-condyle classification integrating sagittal reduction status and coronal displacement direction and characterized disc morphology, disc deformation grade, condylar position, condylar morphology grade, condylar bone status grade, and HCA across these groups. Overall, MRI findings showed a graded structural distribution across the disc-condyle categories, with more severe disc deformation, shifts in condylar positional composition, more frequent abnormal condylar morphology and osseous change, and higher HCA values in the displaced groups, particularly in the nonreducing subtypes. This pattern is consistent with the recognized natural history of TMJ disc displacement and with prior longitudinal MRI observations, although the present cross-sectional study was not designed to establish temporal progression. In patient-clustered multivariable GEE analyses accounting for bilateral correlation, HCA, posterior condylar position, and condylar bone status grade remained independently associated with ADD. In contrast, disc deformation grade, condylar morphology grade, condylar bone status grade, and anterior condylar position were independently associated with ADDwoR, whereas HCA showed a positive trend but did not retain independent significance after adjustment. Collectively, these findings support a multidimensional MRI-based characterization of ADD and ADDwoR, in which disc displacement is typically accompanied by co-occurring changes in disc morphology, condylar position, condylar morphology, osseous status, and HCA rather than being interpreted on the basis of any single isolated imaging finding [ 1 , 12 ]. With respect to disc morphology and disc deformation, ADDwR was predominantly characterized by Grade I morphology, with Grade II as the second most common category, suggesting that disc architecture was relatively better preserved in the reducing groups. By contrast, the ADDwoR groups were dominated by Grade III and Grade IV morphology, indicating a greater burden of structural disc abnormality in the nonreducing groups. This distribution is consistent with prior longitudinal MRI evidence showing that nonreducing joints tend to exhibit more severe disc shortening and deformation than reducing joints [ 13 ]. Although the grading scheme used in the present study was defined independently on the basis of the current dataset and analytic objectives, the overall morphologic distribution was broadly comparable to that described by Hu et al., with relatively preserved configurations predominating in ADDwR and shortened folded or more severely deformed discs more common in ADDwoR [ 13 ]. The articular disc has been described as a fibrous, viscoelastic structure that supports normal force distribution [ 14 ]. Repetitive abnormal loading and altered disc-condyle mechanics may progressively disturb this normal stress distribution, leading to folding, shortening, and loss of the normal biconcave configuration. More severe deformation may also be associated with a lower likelihood of disc recapture, which may partly contribute to the predominance of higher-grade deformation in the nonreducing groups. Notably, Grade IV morphology was more frequent in ADDwR-AL and ADDwR-AM than in ADDwR-A, and ADDwoR-AM showed the highest proportion overall. These findings suggest that displacement with a mediolateral component, particularly nonreducing anteromedial displacement, may represent a more complex form of disc-condyle derangement. The proposed seven-type framework may also help refine MRI-based structural stratification by capturing subtype-specific patterns of co-occurring structural abnormalities beyond a binary reducing/nonreducing classification. Given the cross-sectional design, however, this interpretation remains hypothesis-generating and should be tested in studies incorporating three-dimensional quantitative assessment and longitudinal follow-up. Regarding condylar features, the NDP group most commonly showed a concentric condylar position with largely normal condylar morphology and osseous status. In the ADDwR groups, posterior condylar position was more frequent, whereas in ADDwoR the relative proportions of concentric and anterior positions increased compared with ADDwR. This distribution is broadly consistent with prior reports and with Chen et al., who found significant associations of disc position and morphology with condylar position and bone morphology, although disc displacement did not invariably lead to condylar osseous change [ 15 ]. It is also in line with Li and Zhang, who reported posterior condylar position and abnormal condylar morphology as significant correlates of symptomatic TMJs [ 16 , 17 ]. Moreover, degenerative change and severe destruction were more prevalent in ADDwoR, together with higher proportions of shortened and beak-shaped condyles. This pattern is likewise consistent with prior evidence linking disc displacement, particularly ADDwoR, to condylar erosion and other advanced osseous abnormalities [ 15 – 20 ]. In the present study, HCA measurement showed good reliability, which provides important support for its use as a quantitative imaging marker. This is noteworthy because formal reliability assessment has been lacking in much of the previous literature on HCA. HCA also differed across the disc-condyle groups and showed an overall increase from NDP to ADDwR and ADDwoR. In the categorical analyses, NDP clustered mainly within the 10–30 degree range, whereas the proportion of HCA > 30 degrees increased across displaced groups. These findings are broadly consistent with prior reports showing that higher HCA values are more frequently observed in joints with disc displacement and osseous abnormality [ 3 , 5 ]. More recent axial MRI work has likewise shown that angular changes of the condyle and related structures can be demonstrated in association with anterior disc displacement, further supporting the relevance of axial angular metrics in TMJ internal derangement [ 21 ]. One possible explanation is that altered disc-condyle mechanics in displaced joints may be accompanied by rotational reorientation of the condyle, which is reflected by an increased HCA. Beyond this overall gradient, our data further suggest that the increase in HCA is not uniformly distributed across all displaced joints. Rather, subtypes with anteromedial displacement tended to show both higher mean HCA values and a higher proportion of HCA > 30 degrees, particularly ADDwoR-AM. This pattern may indicate greater structural complexity in joints with a medial displacement component. A possible explanation is that, because the medial aspect of the glenoid fossa provides relatively limited space, a medially displaced disc may occupy part of the medial joint compartment and mechanically displace the condyle, resulting in rotational reorientation and a larger HCA. Given the retrospective cross-sectional design, however, this interpretation remains hypothesis-generating. Our patient-clustered GEE analyses further clarify how these MRI features contribute across different levels of disc-condyle derangement. In univariable analyses, HCA, condylar position, condylar morphology grade, condylar bone status grade, and disc deformation grade all showed discriminatory information when considered individually. After joint modeling, however, the pattern differed between the two modeled contrasts. In the ADD contrast, posterior condylar position, HCA, and condylar bone status grade remained the principal independent imaging correlates after adjustment, with posterior condylar position showing a particularly strong association (OR, 4.57) and condylar bone status grade also contributing substantially (OR, 3.40 per grade increase). This pattern suggests that, at the broader level of distinguishing normal joints from joints with disc displacement, the most informative MRI features are those reflecting overall disc-condyle imbalance, including altered condylar positional composition, increasing condylar rotational alignment, and associated osseous abnormality. By contrast, in the ADDwoR contrast, disc deformation grade, condylar morphology grade, condylar bone status grade, and anterior condylar position remained independently associated after adjustment, whereas HCA showed a positive trend but no longer retained independent significance (P = 0.072). This difference suggests that the distinction between reducing and nonreducing displacement is characterized less by generalized imbalance and more by direct structural deterioration of the disc-condyle complex, particularly worsening disc deformation, condylar remodeling, and osseous change. This overall pattern is broadly consistent with the recent semiquantitative MRI study by Liao et al. [ 8 ], in which nonreducing joints also showed more advanced structural abnormalities. However, their multivariable analysis identified fold-curved disc configuration, displacement degree, and joint effusion grade as independent correlates of ADDwoR [ 8 ], whereas the independently associated features in our study were not identical. This difference may partly reflect differences in analytic framework, because the present study applied a seven-type disc-condyle classification incorporating both reduction status and coronal displacement direction, thereby permitting a more granular comparison of co-occurring structural changes than binary ADDwR/ADDwoR models alone [ 1 , 7 , 22 ]. The relationship between the univariable and multivariable findings is also informative. The loss of independent significance of HCA in the ADDwoR multivariable model does not indicate that HCA is uninformative; rather, it suggests that part of the information captured by HCA overlaps with that conveyed more directly by disc deformation, condylar morphology, condylar bone status, and condylar position when these variables are considered jointly. The ROC findings support this interpretation. HCA alone showed only moderate discrimination for both ADD and ADDwoR (AUCs, 0.688 and 0.684, respectively), whereas the final multivariable models achieved substantially higher AUCs (0.833 and 0.923, respectively), particularly for ADDwoR. Accordingly, HCA is unlikely to serve as a standalone diagnostic threshold, but it still provides useful quantitative structural information within a broader MRI-based assessment. Conversely, the stronger discrimination of the multivariable models indicates that current disc-condyle status is better characterized by the combined MRI pattern of disc deformation, condylar position, condylar morphology, osseous change, and HCA than by any single isolated imaging feature. Given the retrospective cross-sectional design, these findings should be interpreted as reflecting discrimination of current disc-condyle status rather than prediction of future progression or outcomes. Our findings may also have ancillary practical implications in routine TMJ imaging assessment. Many patients presenting to TMJ clinics have already undergone CBCT before MRI is considered. In the present study, condylar position, morphology, and osseous status showed generally good agreement between CBCT and MRI, suggesting that these condylar features can be assessed with reasonable consistency across the two modalities. Because our patient-clustered GEE analyses identified condylar structural features as relevant correlates of both ADD and ADDwoR, and because prior studies have likewise linked condylar abnormalities to disc displacement and more advanced internal derangement [ 15 – 19 ], CBCT-derived condylar findings may provide useful preliminary information when considering whether further TMJ MRI is warranted. This interpretation is also broadly consistent with recent CBCT-based studies [ 23 , 24 ] and recent 3T MRI evidence [ 25 ]. However, this secondary analysis was not designed as a formal modality-comparison or triage study, and such information should therefore be regarded as complementary rather than a substitute for MRI, because MRI remains necessary for direct assessment of disc position, reduction status, and disc morphology [ 12 ]. Several limitations should be acknowledged. First, this was a single-center retrospective cross-sectional study. Although patient-clustered GEE models were used to account for bilateral within-patient correlation, the temporal sequence and causal direction among disc displacement, HCA, disc deformation, condylar remodeling, and osseous change cannot be determined. This is particularly relevant because prior MRI and semiquantitative studies, including longitudinal or follow-up observations, suggest that disc deformation and associated structural abnormalities may evolve over time rather than remain static [ 8 , 13 ]. In addition, the NDP group was derived from a clinically referred MRI cohort rather than from an asymptomatic healthy control population; therefore, the findings should be interpreted as contrasts within a clinical imaging population rather than as direct comparisons with the general population. Second, although the proposed classification framework improves clinical applicability and permits more granular stratification of disc-condyle derangement, it remains subject to the spatial resolution of routine MRI, oblique-plane prescription, slice thickness, and reader judgment, and some within-subtype heterogeneity in accompanying structural features may therefore remain. Third, the ROC-derived cutoffs from this single-center sample, including the Youden index-based reference thresholds for HCA, should not be interpreted as universal diagnostic thresholds. In addition, HCA measurement may be influenced by head positioning, axial slice selection, and planning variability, underscoring the need for further standardization of acquisition and measurement procedures before broader clinical application [ 3 , 5 ]. Future work should validate this classification framework and the multivariable models in multicenter prospective cohorts and should further determine, through longitudinal follow-up, whether HCA and other MRI features have value not only for discrimination of current disc-condyle status but also for risk stratification of ADD onset and transition from reducing to nonreducing displacement states [ 8 , 13 ]. Incorporation of more granular quantitative imaging features, including three-dimensional or surface-based descriptors of condylar morphology, disc shape, joint geometry, and broader MRI-based structural features, may further refine structural characterization beyond the semiquantitative variables used here [ 26 , 27 ]. Together with external validation, model recalibration, and assessment of clinical utility, such work will help define the appropriate clinical role of HCA thresholds and integrated MRI-based models in TMJ imaging. Overall, TMJ disc displacement was characterized by coordinated abnormalities of disc deformation, condylar position, condylar morphology, condylar bone status, and HCA. The proposed seven-type framework may help refine MRI-based structural stratification by capturing subtype-specific patterns of co-occurring structural abnormalities beyond a binary reducing/nonreducing classification. HCA provides complementary quantitative information, but it is insufficient as a standalone diagnostic threshold. Conclusions Temporomandibular joint disc displacement is characterized by coordinated abnormalities of disc deformation, condylar position, condylar morphology, condylar bone status, and horizontal condylar angle on magnetic resonance imaging. The proposed seven-type disc-condyle classification may support more refined structural stratification than a binary reducing/nonreducing framework alone by capturing subtype-specific patterns of co-occurring abnormalities. Horizontal condylar angle provides complementary quantitative information, but its standalone discriminatory performance is limited and it is better interpreted within an integrated magnetic resonance imaging assessment. These findings are relevant to the imaging-based evaluation of temporomandibular joint internal derangement and may help improve structural interpretation of current disc-condyle status. Abbreviations ADD anterior disc displacement ADDwR anterior disc displacement with reduction ADDwoR anterior disc displacement without reduction AL anterolateral AM anteromedial AUC area under the curve CBCT cone-beam computed tomography CI confidence interval GEE generalized estimating equation HCA horizontal condylar angle ICC intraclass correlation coefficient IQR interquartile range MRI magnetic resonance imaging NDP normal disc position OR odds ratio PACS picture archiving and communication system PDWI proton density-weighted imaging ROC receiver operating characteristic SD standard deviation TMJ temporomandibular joint TMD temporomandibular disorder T2WI-FS T2-weighted imaging with fat suppression Declarations Ethics approval and consent to participate This retrospective cross-sectional study was approved by the Ethics Committee of School & Hospital of Stomatology, Wuhan University (Approval No. WDKQ2026-B04). The requirement for informed consent was waived by the Ethics Committee of School & Hospital of Stomatology, Wuhan University because of the retrospective design and the use of anonymized imaging data. The study was conducted in accordance with the Declaration of Helsinki. Consent for publication Not applicable. Availability of data and materials The datasets generated and/or analyzed during the current study are not publicly available because they contain clinical imaging data derived from human participants and are subject to privacy and ethical restrictions. De-identified data may be available from the corresponding author on reasonable request, subject to approval by the relevant institutional and ethics requirements. Competing interests The authors declare that they have no competing interests. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Authors’ contributions H.L. contributed to study design, image evaluation, data collection, and drafting of the manuscript. L.W. contributed to image evaluation and revision of the manuscript. F.W. contributed to data interpretation and revision of the manuscript. B.L. conceived and supervised the study and contributed to study design, data interpretation, and revision of the manuscript. All authors read and approved the final manuscript. Acknowledgements Not applicable. Clinical trial number Not applicable. References Larheim TA, Hol C, Løseth G, Arvidsson LZ. Temporomandibular joint pathologies: pictorial review. Br J Radiol. 2024;97(1153):53–67. 10.1093/bjr/tqad021 . Hegab AF, AbdAl Hameed HI, Karam KS. Classification of temporomandibular joint internal derangement based on magnetic resonance imaging and clinical findings of 435 patients contributing to a nonsurgical treatment protocol. Sci Rep. 2021;11:20917. 10.1038/s41598-021-00456-7 . 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Cross-sectional and longitudinal assessment of subchondral cysts in temporomandibular joints: Clinical and MRI study with a mean follow-up of 66 months. J Prosthodont Res. 2023;67(3):392–9. 10.2186/jpr.JPR_D_22_00089 . Mizuhashi F, Ogura I, Mizuhashi R, Watarai Y, Suzuki T, Kawana M, et al. Bone Changes in Mandibular Condyle of Temporomandibular Dysfunction Patients Recognized on Magnetic Resonance Imaging. J Imaging. 2025;12(1):5. 10.3390/jimaging12010005 . Naralan ME, Çakir B. Axial MRI evaluation of temporomandibular joint condylar and lateral pterygoid muscle angles in anterior disc displacement. Sci Rep. 2025;15(1):40044. 10.1038/s41598-025-23800-7 . Zhou L, Tao K, Ma J, Pan X, Zhang K, Feng J. Relationship between temporomandibular joint space and articular disc displacement. BMC Oral Health. 2025;25(1):611. 10.1186/s12903-025-05991-7 . Yu W, Jeon HH, Kim S, Dayo A, Mupparapu M, Boucher NS. Correlation between TMJ Space Alteration and Disc Displacement: A Retrospective CBCT and MRI Study. Diagnostics (Basel). 2023;14(1):44. 10.3390/diagnostics14010044 . Osama A, Musa M, Zhang HJ, Zheng CD, Nasih M, Ren YH, et al. Cone-Beam Computed Tomography as a Diagnostic Tool for TMJ Morphological Alterations in Disc Displacement. Int Dent J. 2025;75(5):100908. 10.1016/j.identj.2025.100908 . Özel Ş, Tunç S, Şenol AU. Association between clinical findings and 3T MRI features in temporomandibular joint disorders. BMC Oral Health. 2025;25(1):921. 10.1186/s12903-025-06283-w . Tang R, Chen W, Xu N, Yuan X, Bai X, Zhang B, et al. Condylar alteration in three subtypes of temporomandibular disorder based on U-HRCT: a cross-sectional study. BMC Oral Health. 2025;25(1):1930. 10.1186/s12903-025-07557-z . Ramesh E, Ganesan A, Gauthaman J, Lakshmi KC, Kannan S. Comparison of medic and 3D DESS with routine MRI to assess the diagnostic efficacy in symptomatic temporomandibular disorders: a cross sectional observational study. Sci Rep. 2025;15(1):33468. 10.1038/s41598-025-11650-2 . Additional Declarations No competing interests reported. Supplementary Files SupplementaryTables.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 19 May, 2026 Reviews received at journal 01 May, 2026 Reviewers agreed at journal 01 May, 2026 Reviewers invited by journal 01 May, 2026 Editor assigned by journal 01 May, 2026 Editor invited by journal 20 Apr, 2026 Submission checks completed at journal 17 Apr, 2026 First submitted to journal 17 Apr, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9389404","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":637105603,"identity":"324364c7-2d7e-4871-9cd4-9736e1e7ed6b","order_by":0,"name":"Hang Li","email":"","orcid":"","institution":"State Key Laboratory of Oral \u0026 Maxillofacial Reconstruction and Regeneration","correspondingAuthor":false,"prefix":"","firstName":"Hang","middleName":"","lastName":"Li","suffix":""},{"id":637105604,"identity":"ebf630ba-142f-4aa8-8599-c3e1abb14976","order_by":1,"name":"Lili Wei","email":"","orcid":"","institution":"State Key Laboratory of Oral \u0026 Maxillofacial Reconstruction and Regeneration","correspondingAuthor":false,"prefix":"","firstName":"Lili","middleName":"","lastName":"Wei","suffix":""},{"id":637105605,"identity":"be8d328e-ba3b-465d-849e-fbb6707b99df","order_by":2,"name":"Fang Wang","email":"","orcid":"","institution":"State Key Laboratory of Oral \u0026 Maxillofacial Reconstruction and Regeneration","correspondingAuthor":false,"prefix":"","firstName":"Fang","middleName":"","lastName":"Wang","suffix":""},{"id":637105606,"identity":"fcb2a33d-cbd8-4529-9c05-336ff4ee5d7e","order_by":3,"name":"Bo Li","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAArklEQVRIiWNgGAWjYBACPmYeEGXDYACieIjRwgbRkkaKFoiyw6RoYec9+ODnjvOJ2yUSGB+8bWOQNyfsML5kw94ztxN3zkhgNpzbxmC4s4GgFh4zaca227kbbiSwSfO2MSQYHCBOyzmQFvbfpGg5ALaFmUgtIL+0JddvOPOwWXLOOQnDDYS08POfBYZYm52xwfHkgx/elNnIE7QFCTA2AAkJ4tWPglEwCkbBKMANADFpORJ7StgIAAAAAElFTkSuQmCC","orcid":"","institution":"State Key Laboratory of Oral \u0026 Maxillofacial Reconstruction and Regeneration","correspondingAuthor":true,"prefix":"","firstName":"Bo","middleName":"","lastName":"Li","suffix":""}],"badges":[],"createdAt":"2026-04-11 16:23:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9389404/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9389404/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109100033,"identity":"1dcc3457-b558-4b67-879f-01664b660431","added_by":"auto","created_at":"2026-05-12 14:19:49","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":264079,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRepresentative images of the disc-condyle classification.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOblique sagittal (closed- and open-mouth) and oblique coronal (closed-mouth) proton density-weighted images (PDWI) illustrate representative disc-condyle patterns. (A,B) Normal disc position. (C,D) Anterior disc displacement with reduction (ADDwR). (E,F) Anterior disc displacement without reduction (ADDwoR). (G) Lateral disc displacement on coronal PDWI. (H) Medial disc displacement on coronal PDWI.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-9389404/v1/fd72322149de03e550904f7b.png"},{"id":109099780,"identity":"0af66845-79da-4356-a517-f113a2ee9ed7","added_by":"auto","created_at":"2026-05-12 14:18:21","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":744868,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRepresentative disc morphology patterns and grading.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eClosed-mouth oblique sagittal PDWI shows representative disc morphology patterns and analytic grades: (A) biconcave (Grade I); (B) concave-shaped (Grade I); (C) mildly folded (Grade II); (D) shortened folded (Grade III); and (E,F) severe deformation (Grade IV; two examples).\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9389404/v1/62fdb91ea1a1c64a2a1ec9af.png"},{"id":109100006,"identity":"9293f044-943c-45ac-815e-87e983be626d","added_by":"auto","created_at":"2026-05-12 14:19:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":772646,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRepresentative examples of condylar position, morphology, and osseous status.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRepresentative sagittal images illustrate condylar position, morphology, and osseous status. (A,B) PDWI showing approximately normal osseous status and morphology, with concentric (A) and posterior (B) condylar position. (C) PDWI showing sclerosis/hyperplasia with osteophyte formation (beak-shaped condyle) and anterior condylar position. (D) T2WI-FS showing cystic change (hyperintense focus). (E) PDWI showing severe osseous destruction. (F) PDWI showing a shortened condyle.\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-9389404/v1/04f21e9812e405ca21d3eaa3.png"},{"id":109099950,"identity":"6f7fecad-4eef-4320-92bd-a6b3c5bbc20b","added_by":"auto","created_at":"2026-05-12 14:19:30","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":217290,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSchematic illustration of HCA measurement.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe yellow line connects the most anterior points of both auricles and serves as the horizontal reference line. The white line represents the extended condylar long axis, defined as the line connecting the medial and lateral poles of the condyle. The angle between the two lines is defined as the horizontal condylar angle (HCA).\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9389404/v1/08a6243f697b47f3280cdb5a.png"},{"id":109099926,"identity":"3b5bfc17-02e3-4777-9a3f-737746f085d7","added_by":"auto","created_at":"2026-05-12 14:19:20","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":524903,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eRaincloud plot of HCA across the seven disc-condyle groups.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaincloud plots show the distribution of HCA across the seven MRI-based disc-condyle groups. The half-violin indicates distribution density, dots represent individual TMJ sides, and the overlaid boxplot summarizes the distribution. Abbreviations: NDP, normal disc position; ADDwR, anterior disc displacement with reduction; ADDwoR, anterior disc displacement without reduction; A, anterior; AL, anterolateral; AM, anteromedial.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9389404/v1/11606e510d754c48e131939b.png"},{"id":109100034,"identity":"17ec74c3-9abd-4d03-8adc-870b75878ba4","added_by":"auto","created_at":"2026-05-12 14:19:50","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":949871,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eROC curves for discrimination of current disc-condyle status using HCA alone and patient-clustered multivariable GEE models.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(A) ADD: AUC = 0.688 for HCA alone and 0.833 for the multivariable GEE model. (B) ADDwoR: AUC = 0.684 for HCA alone and 0.923 for the multivariable GEE model. Model-based ROC curves were constructed from individual predicted probabilities and reflect discrimination of current disc-condyle status in this cross-sectional dataset.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9389404/v1/8bb0a6de5ce61bcc7c484641.png"},{"id":109100284,"identity":"0279c36a-2989-49bd-bd9e-ed7abad635c3","added_by":"auto","created_at":"2026-05-12 14:20:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3907591,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9389404/v1/5b5136d2-2e45-4704-9461-c861933efd9e.pdf"},{"id":109099845,"identity":"33bb27f6-d008-4a97-ab97-9e4107718c9b","added_by":"auto","created_at":"2026-05-12 14:19:03","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":52157,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTables.docx","url":"https://assets-eu.researchsquare.com/files/rs-9389404/v1/e9a197b016c9f8ed3d9175d6.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"TMJ MRI structural features and horizontal condylar angle across a seven-type disc-condyle classification: a retrospective cross-sectional study with patient-clustered GEE and ROC analysis","fulltext":[{"header":"Background","content":"\u003cp\u003eTemporomandibular disorders (TMDs) comprise a heterogeneous spectrum of conditions. Among intra-articular TMDs, anterior disc displacement (ADD) is common, and ADD without reduction (ADDwoR) is often associated with pain, joint sounds, and functional limitation. Magnetic resonance imaging (MRI) is routinely used to determine disc position and reduction status and to characterize disc morphology, and it remains central to the assessment of disc-condyle derangement [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, the clinical interpretability of MRI-based findings remains limited in several respects. First, prior studies have often focused on specific imaging markers—such as condylar position, condylar morphology, disc morphology, joint space, or angular parameters such as the horizontal condylar angle (HCA)—with limited integration of these features into a unified disc-condyle classification framework [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e]. Second, ADD classifications vary across studies, and coronal MRI assessment of mediolateral disc displacement is not consistently incorporated, which may constrain stratification of complex disc-condyle patterns [\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e–\u003cspan class=\"CitationRef\"\u003e8\u003c/span\u003e]. Prior MRI-based work has also shown that rotational disc displacement is not uncommon and that coronal classification should not be overlooked, particularly in joints with displacement with reduction [\u003cspan class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e9\u003c/span\u003e]. Third, reported associations between HCA and disc displacement have varied across studies, potentially reflecting differences in classification schemes and limited adjustment for co-occurring structural MRI features [\u003cspan class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eTo address these gaps, we applied a seven-type MRI-based disc-condyle classification integrating reduction status (with vs without reduction) and coronal displacement direction (anterior/anteromedial/anterolateral), yielding normal disc position plus six ADD subtypes. This framework was intended not only to refine descriptive classification, but also to determine whether incorporating the coronal mediolateral component could reveal subtype-specific patterns of co-occurring structural abnormality that may not be captured by a binary reducing/nonreducing scheme alone. We then characterized MRI structural features and HCA across the seven disc-condyle groups, assessed HCA reliability, and used patient-clustered univariable and multivariable generalized estimating equation (GEE) models together with ROC analysis to evaluate associations, independent correlates, and discriminatory performance for distinguishing normal disc position from ADD and reducing from nonreducing displacement.\u003c/p\u003e "},{"header":"Methods","content":"\u003cp\u003eStudy design and ethics\u003c/p\u003e\u003cp\u003eThis retrospective cross-sectional study was approved by the Ethics Committee of School \u0026amp; Hospital of Stomatology, Wuhan University (Approval No. WDKQ2026-B04) and was conducted in accordance with the Declaration of Helsinki. The requirement for informed consent was waived by the Ethics Committee of School \u0026amp; Hospital of Stomatology, Wuhan University because of the retrospective design and the use of anonymized imaging data.\u003c/p\u003e\u003cp\u003eStudy population\u003c/p\u003e\u003cp\u003eWe screened consecutive patients who underwent clinically indicated temporomandibular joint (TMJ) MRI in the Department of Radiology at our institution between July 2023 and December 2024. Inclusion criteria were: (1) diagnostic TMJ MRI available for review and (2) no prior TMJ-related treatment before imaging. Exclusion criteria were: (1) other confirmed TMJ diseases, (2) congenital craniofacial developmental deformities, (3) recent maxillofacial trauma, (4) inadequate head positioning precluding reliable measurement of the horizontal condylar angle (HCA), and (5) suboptimal image quality.\u003c/p\u003e\u003cp\u003eMRI acquisition protocol\u003c/p\u003e\u003cp\u003eMRI was performed on a 1.5-T system (uMR 580, United Imaging Healthcare, China) with a dedicated 4-channel TMJ surface coil. Proton density-weighted imaging (PDWI) was obtained in closed- and open-mouth positions at maximal comfortable opening; the remaining sequences were obtained in the closed-mouth position. Sequences and acquisition parameters are summarized in Supplementary Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eMRI image analysis\u003c/p\u003e\u003cp\u003e(1) Image interpretation and reliability assessment\u003c/p\u003e\u003cp\u003eAll images were interpreted and measured on a PACS workstation by two radiologists (Reader A, mid-level; Reader B, senior), both blinded to clinical information and to each other's results. For reliability assessment, 50 TMJ sides were randomly selected. Reader A re-evaluated the images after an interval of at least 4 weeks to assess intraobserver reliability, including repeated HCA measurements, and Reader B independently assessed the same sample to assess interobserver reliability. In the full dataset, all imaging variables were assessed by Reader A, and equivocal cases were resolved by consensus with Reader B.\u003c/p\u003e\u003cp\u003eHCA reliability was quantified using the intraclass correlation coefficient (ICC; absolute agreement, single measure) with 95% confidence intervals, using a two-way mixed-effects model for intraobserver reliability [ICC(3,1)] and a two-way random-effects model for interobserver reliability [ICC(2,1)]. Agreement for categorical and ordinal variables was assessed using Cohen's kappa with 95% confidence intervals: unweighted kappa for nominal variables (the seven-type disc-condyle classification and condylar position) and quadratic weighted kappa for ordinal variables (disc deformation grade, condylar morphology grade, and condylar bone status grade).\u003c/p\u003e\u003cp\u003eAs an ancillary analysis, agreement between CBCT and MRI for condylar findings was explored in 50 patients who had both examinations, with one TMJ side included per patient. Unweighted Cohen’s kappa was used for condylar position, and quadratic weighted kappa was used for condylar morphology and condylar bone status grades.\u003c/p\u003e\u003cp\u003e(2) Disc-condyle classification\u003c/p\u003e\u003cp\u003eBased on expert consensus [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e], each TMJ was classified into one of seven MRI-based disc-condyle groups (Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e): NDP (normal disc position); ADDwR-A/AL/AM (ADD with reduction, anterior/anterolateral/anteromedial); and ADDwoR-A/AL/AM (ADD without reduction, anterior/anterolateral/anteromedial). NDP was defined as a posterior band located near the condylar apex in the closed-mouth position, without medial or lateral protrusion, with the intermediate zone interposed between the condyle and the articular eminence on mouth opening. ADDwR was defined as an anteriorly positioned posterior band in the closed-mouth position, approximately anterior to the 11:30 clock-face position, with normalization on mouth opening [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. ADDwoR was defined as a posterior band remaining anterior to the condyle in both closed- and open-mouth positions. “AL” and “AM” indicate additional anterolateral and anteromedial displacement on coronal MRI, respectively. Throughout the manuscript and in all figures and tables, groups are referred to using these abbreviations. For analysis, ADD included all displaced groups.\u003c/p\u003e\u003cp\u003eOblique sagittal (closed- and open-mouth) and oblique coronal (closed-mouth) proton density-weighted images (PDWI) illustrate representative disc-condyle patterns. (A,B) Normal disc position. (C,D) Anterior disc displacement with reduction (ADDwR). (E,F) Anterior disc displacement without reduction (ADDwoR). (G) Lateral disc displacement on coronal PDWI. (H) Medial disc displacement on coronal PDWI.\u003c/p\u003e\u003cp\u003e(3) Classification of disc morphology and condylar position, morphology, and osseous status\u003c/p\u003e\u003cp\u003eDisc morphology was classified on closed-mouth PDWI using disc length, band integrity, and extent of deformation, yielding five descriptive types that were collapsed into four analytic grades. Grade I (approximately normal) required identifiable anterior, intermediate, and posterior bands and included biconcave morphology (a V-shaped superior border with an inverted V-shaped inferior border) and concave-shaped morphology (a V-shaped superior border with a smoothly arched concave inferior border). Grade II corresponded to mildly folded morphology, defined by mild undulation of the intermediate zone with preserved band recognizability. Grade III corresponded to a shortened folded disc with recognizable bands. Grade IV represented severe deformation with poorly recognizable bands (ovoid, triangular, sheet-like, or otherwise unclassifiable). Five-type distributions were reported descriptively, whereas the four-grade variable was used in regression analyses. Representative MRI examples of disc morphology patterns and grading are shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eCondylar position was classified as anterior, concentric, or posterior using the Pullinger and Hollender method [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e]. Condylar morphology was categorized as approximately normal, beak-shaped (anterior osteophyte without reduced condylar height), or shortened (a small condyle with reduced height). Condylar osseous findings were initially recorded as six items (normal, cortical discontinuity, sclerosis/hyperplasia with osteophytes, erosion/defect, cystic change, and bone marrow edema) and were then collapsed into three analytic categories: approximately normal (normal or mild wear, including cortical discontinuity or surface irregularity), degenerative change (sclerosis/hyperplasia with osteophytes, cystic change, or bone marrow edema), and severe destruction (extensive erosion or large-area osseous defects). Representative MRI examples of condylar position, condylar morphology, and condylar osseous status are shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eClosed-mouth oblique sagittal PDWI shows representative disc morphology patterns and analytic grades: (A) biconcave (Grade I); (B) concave-shaped (Grade I); (C) mildly folded (Grade II); (D) shortened folded (Grade III); and (E,F) severe deformation (Grade IV; two examples).\u003c/p\u003e\u003cp\u003eRepresentative sagittal images illustrate condylar position, morphology, and osseous status. (A,B) PDWI showing approximately normal osseous status and morphology, with concentric (A) and posterior (B) condylar position. (C) PDWI showing sclerosis/hyperplasia with osteophyte formation (beak-shaped condyle) and anterior condylar position. (D) T2WI-FS showing cystic change (hyperintense focus). (E) PDWI showing severe osseous destruction. (F) PDWI showing a shortened condyle.\u003c/p\u003e\u003cp\u003e(4) HCA measurement\u003c/p\u003e\u003cp\u003eHCA was measured on closed-mouth axial T2-weighted images at the slice showing the maximal cross-sectional area of the condyle. The condylar long axis was defined as the line connecting the medial and lateral poles of the condyle. HCA was defined as the angle between the condylar long axis and the line connecting the most anterior points of both auricles. A schematic illustration of the measurement is shown in Fig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e. Each measurement was performed twice, and the mean value was used for analysis.\u003c/p\u003e\u003cp\u003eThe yellow line connects the most anterior points of both auricles and serves as the horizontal reference line. The white line represents the extended condylar long axis, defined as the line connecting the medial and lateral poles of the condyle. The angle between the two lines is defined as the horizontal condylar angle (HCA).\u003c/p\u003e\u003ch2\u003eStatistical analysis\u003c/h2\u003e\u003cp\u003eDescriptive analyses were performed at the joint level. Continuous variables are presented as mean ± standard deviation (SD) when approximately normally distributed or as median (interquartile range [IQR]) otherwise; normality and variance homogeneity were assessed using the Shapiro-Wilk and Levene tests. Exploratory comparisons across the seven disc-condyle groups used one-way ANOVA or Welch ANOVA, as appropriate, followed by Tukey or Games-Howell post hoc tests with multiplicity adjustment. Categorical variables are presented as n (%) and were compared using the chi-square test or Fisher's exact test, with Bonferroni correction where appropriate. Because some patients contributed bilateral joints, these groupwise P values were considered descriptive only; inferential conclusions were based on patient-clustered GEE models.\u003c/p\u003e\u003cp\u003eTo account for within-patient bilateral correlation, we used patient-clustered GEE logistic regression with a logit link, exchangeable working correlation structure, and robust variance. Two contrasts were modeled: ADD (NDP vs all displaced groups) and ADDwoR (ADDwR-A/AL/AM vs ADDwoR-A/AL/AM). For each contrast, both univariable and multivariable analyses were performed. Variables in the multivariable models were prespecified on the basis of clinical relevance and study objectives. HCA was modeled continuously (per 1° increase); condylar position was entered with concentric position as the reference category; and condylar morphology grade, condylar bone status grade, and disc deformation grade were entered as ordered variables. Discrimination was assessed using ROC analysis. For the multivariable models, ROC curves were constructed from individual predicted probabilities, and AUC 95% CIs were estimated by patient-level cluster bootstrap. Univariate ROC analysis was also performed for HCA alone. Sensitivity analyses additionally adjusted for age and sex. Given the retrospective cross-sectional design, these analyses were used to assess associations with current disc-condyle status and in-sample discrimination rather than to predict future outcomes.\u003c/p\u003e\u003cp\u003eDuring manuscript preparation, the authors used ChatGPT (OpenAI) to assist with language refinement, structural editing, and formatting of the manuscript. The authors reviewed and edited all outputs as needed and take full responsibility for the content of the manuscript.\u003c/p\u003e"},{"header":"Results","content":" \u003cp\u003e1. Study population\u003c/p\u003e \u003cp\u003eA total of 310 patients (234 women and 76 men) were included, contributing 568 TMJ sides. Baseline characteristics by disc-condyle group are shown in Supplementary Table S2.\u003c/p\u003e \u003cp\u003e2. Reliability\u003c/p\u003e \u003cp\u003eIn the randomly selected 50 TMJ sides, intraobserver and interobserver agreement for all imaging classifications and grades, as well as the reliability of HCA measurements, are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In an ancillary comparison of 50 patients who underwent both examinations, CBCT and MRI showed good agreement for condylar position, condylar morphology grade, and condylar bone status grade (Supplementary Table S3).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eIntra- and interobserver agreement (n\u0026thinsp;=\u0026thinsp;50 TMJ sides)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMeasure\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntra Agree., %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eIntra κ/ICC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eInter Agree., %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInter κ/ICC (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisc\u0026ndash;condyle relationship classification (seven-type)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e90.0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.873 (0.756\u0026ndash;0.973)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88.0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.850 (0.727\u0026ndash;0.950)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDisc deformation grade (4-level)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92.0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.966 (0.924\u0026ndash;0.992)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e86.0\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.938 (0.878\u0026ndash;0.975)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCondylar position (3-category)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e92.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.861 (0.710\u0026ndash;0.967)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e90.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.829 (0.671\u0026ndash;0.964)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCondylar morphology grade (3-level)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e94.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.775 (0.396\u0026ndash;1.000)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e94.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.731 (0.242\u0026ndash;1.000)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCondylar bone status grade (3-level)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e94.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.878 (0.567\u0026ndash;1.000)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e88.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.752 (0.464\u0026ndash;0.917)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHCA (\u0026deg;)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.869 (0.736\u0026ndash;0.946)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.806 (0.672\u0026ndash;0.880)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eCI, confidence interval. \u0026ldquo;Agree., %\u0026rdquo; indicates observed agreement (categorical/ordinal variables only). Unweighted Cohen\u0026rsquo;s κ was used for nominal variables and quadratic weighted κ for ordinal variables. HCA reliability was assessed using ICC. \u0026ldquo;\u0026mdash;\u0026rdquo; indicates not applicable.\u003c/p\u003e \u003cp\u003e3. Comparisons of disc morphology and condylar imaging features across groups\u003c/p\u003e\u003cp\u003eContingency tables summarized imaging-feature distributions across the seven disc-condyle groups. Disc morphology, disc deformation grade, condylar position, condylar morphology grade, and condylar bone status grade differed across groups (chi-square test, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; because some patients contributed bilateral joints, these P values are descriptive only). Disc morphology distributions are presented in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and groupwise distributions of disc deformation grade, condylar position, morphology, and bone status are presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eA graded pattern was observed along the disc-condyle spectrum. NDP was dominated by biconcave discs, Grade I disc deformation, concentric condylar position, and largely normal condylar morphology and osseous status. Across ADDwR-A/AL/AM, disc morphology was mainly biconcave, concave-shaped, or mildly folded, corresponding predominantly to Grade I deformation, with Grade II as the second most common category; posterior condylar position was more frequent; and osseous status remained largely normal. In ADDwoR-A/AL/AM, shortened folded and severely deformed discs were more prominent, and disc deformation was mainly distributed in Grades III and IV; degenerative change and severe destruction were more frequent, with severe destruction relatively more common in ADDwoR-A. Compared with ADDwR-A/AL/AM, abnormal condylar morphology was more frequent in ADDwoR-A/AL/AM. Within ADDwoR, beak-shaped condyles were particularly common in ADDwoR-AL/ADDwoR-AM, whereas shortened condyles were relatively more common in ADDwoR-A. These distributional findings motivated subsequent patient-clustered univariable and multivariable GEE analyses to evaluate associations with ADD and ADDwoR after accounting for within-patient bilateral correlation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDisc morphology distribution by disc\u0026ndash;condyle group, n (%).\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eN (TMJ sides)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBiconcave\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eConcave-shaped\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMildly folded\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eShortened folded\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eSevere deformation\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNDP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e133\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e130 (97.7)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (2.3)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADDwR-A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (38.8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27 (31.8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e23 (27.1)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1 (1.2)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (1.2)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwR-AL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e64\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e15 (23.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e30 (46.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e10 (15.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e2 (3.1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e7 (10.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwR-AM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e62\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e27 (43.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e19 (30.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e9 (14.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e7 (11.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwoR-A\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e81\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3 (3.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1 (1.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e10 (12.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e30 (37.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e37 (45.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwoR-AL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e75\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4 (5.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e13 (17.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e11 (14.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e23 (30.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e24 (32.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwoR-AM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e68\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2 (2.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3 (4.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e8 (11.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e16 (23.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e39 (57.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are n (%) within each group. Grade I includes biconcave and concave-shaped discs; Grade II, mildly folded discs; Grade III, shortened folded discs; Grade IV, severely deformed discs. Abbreviations: NDP, normal disc position; ADDwR, anterior disc displacement with reduction; ADDwoR, anterior disc displacement without reduction; A, anterior; AL, anterolateral; AM, anteromedial.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCondylar imaging features distribution by disc\u0026ndash;condyle group, n (%). Group sizes are provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eCondylar position\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003eCondylar morphology grade\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eCondylar bone status grade\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConcentric\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePosterior\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAnterior\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eBeak-shaped\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eShortened\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eDegenerative\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eDestruction\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNDP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e78 (58.6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (31.6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (9.8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e133 (100.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e125 (94.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e8 (6.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0 (0.0)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwR-A\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e4 (4.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e80 (94.1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1 (1.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e84 (98.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e1 (1.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e78 (91.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e7 (8.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwR-AL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e9 (14.1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e54 (84.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1 (1.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e64 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e59 (92.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e5 (7.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwR-AM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e14 (22.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e42 (67.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e6 (9.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e62 (100.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e56 (90.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e6 (9.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e0 (0.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwoR-A\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e16 (19.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e44 (54.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e21 (25.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e63 (77.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e9 (11.1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e9 (11.1)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e38 (46.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e31 (38.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e12 (14.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwoR-AL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e19 (25.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e37 (49.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e19 (25.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e55 (73.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e14 (18.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e6 (8.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e39 (52.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e35 (46.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e1 (1.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwoR-AM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e21 (30.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e33 (48.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e14 (20.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e48 (70.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e16 (23.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e4 (5.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e35 (51.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e28 (41.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c10\"\u003e \u003cp\u003e\u003cb\u003e5 (7.4)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eValues are n (%) within each group. Abbreviations: NDP, normal disc position; ADDwR, anterior disc displacement with reduction; ADDwoR, anterior disc displacement without reduction; A, anterior; AL, anterolateral; AM, anteromedial.\u003c/p\u003e \u003cp\u003e4. HCA across groups\u003c/p\u003e\u003cp\u003eHCA differed across disc-condyle groups (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e and Fig.\u0026nbsp;5). Descriptive post hoc comparisons suggested similar HCA values among NDP, ADDwR-A, and ADDwR-AL; higher values in ADDwR-AM, ADDwoR-A, and ADDwoR-AL; and the highest values in ADDwoR-AM. When stratified by reduction status, HCA showed a graded increase from NDP to ADDwR and ADDwoR.\u003c/p\u003e \u003cp\u003eWhen HCA was categorized as 0\u0026ndash;9 degrees, 10\u0026ndash;30 degrees, and \u0026gt;\u0026thinsp;30 degrees, the distribution also differed across groups (chi-square test, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001; descriptive only). NDP was concentrated mainly in the 10\u0026ndash;30 degree range, whereas the proportion of HCA\u0026thinsp;\u0026gt;\u0026thinsp;30 degrees increased across displaced groups and was highest in ADDwoR-AM (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). These unadjusted patterns were further examined in patient-clustered multivariable GEE models that accounted for within-patient bilateral correlation.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMean HCA and categorical distribution by disc\u0026ndash;condyle group, n (%). Group sizes are provided in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHCA, mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD (\u0026deg;)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0\u0026ndash;9\u0026deg;, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10\u0026ndash;30\u0026deg;, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;30\u0026deg;, n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNDP\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e18.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (9.8)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e119 (89.5)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.8)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eADDwR-A\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.0\u0026thinsp;\u0026plusmn;\u0026thinsp;8.2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (10.6)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68 (80.0)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (9.4)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwR-AL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e18.1\u0026thinsp;\u0026plusmn;\u0026thinsp;8.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e7 (10.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e52 (81.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e5 (7.8)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwR-AM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e26.2\u0026thinsp;\u0026plusmn;\u0026thinsp;9.8\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2 (3.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e39 (62.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e21 (33.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwoR-A\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e27.4\u0026thinsp;\u0026plusmn;\u0026thinsp;10.9\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4 (4.9)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e49 (60.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e28 (34.6)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwoR-AL\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e25.4\u0026thinsp;\u0026plusmn;\u0026thinsp;12.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e6 (8.0)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e44 (58.7)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e25 (33.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eADDwoR-AM\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e34.3\u0026thinsp;\u0026plusmn;\u0026thinsp;12.0\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e1 (1.5)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e26 (38.2)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e41 (60.3)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e Values are n (%) within each group unless otherwise indicated. Abbreviations: HCA, horizontal condylar angle; SD, standard deviation; NDP, normal disc position; ADDwR, anterior disc displacement with reduction; ADDwoR, anterior disc displacement without reduction; A, anterior; AL, anterolateral; AM, anteromedial.\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 5. Raincloud plot of HCA across the seven disc-condyle groups.\u003c/b\u003e \u003c/p\u003e \u003cp\u003eRaincloud plots show the distribution of HCA across the seven MRI-based disc-condyle groups. The half-violin indicates distribution density, dots represent individual TMJ sides, and the overlaid boxplot summarizes the distribution. Abbreviations: NDP, normal disc position; ADDwR, anterior disc displacement with reduction; ADDwoR, anterior disc displacement without reduction; A, anterior; AL, anterolateral; AM, anteromedial.\u003c/p\u003e \u003cp\u003e5. Univariable and multivariable GEE logistic regression and ROC analysis\u003c/p\u003e \u003cp\u003ePatient-clustered univariable and multivariable GEE logistic regression models are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. In the ADD analysis, univariable GEE showed significant associations for HCA, posterior condylar position, and condylar bone status grade. In the multivariable ADD model, HCA, posterior condylar position, and condylar bone status grade remained independently associated with ADD, whereas anterior condylar position was not statistically significant. Condylar morphology grade and disc deformation grade were not included because the NDP group showed no variability for these variables.\u003c/p\u003e \u003cp\u003eIn the ADDwoR analysis, univariable GEE showed significant associations for HCA, condylar position, condylar morphology grade, condylar bone status grade, and disc deformation grade. In the multivariable ADDwoR model, higher disc deformation grade, condylar morphology grade, and condylar bone status grade remained independently associated with ADDwoR. Relative to concentric position, anterior condylar position was independently associated with ADDwoR, whereas posterior condylar position was not statistically significant after adjustment. HCA showed a positive trend but did not remain independently associated in the multivariable model.\u003c/p\u003e \u003cp\u003eROC curves based on model-derived individual probabilities are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e. The apparent AUCs were 0.833 (95% CI, 0.783\u0026ndash;0.880) for the ADD model and 0.923 (95% CI, 0.895\u0026ndash;0.948) for the ADDwoR model, indicating good in-sample discrimination for both contrasts, particularly for ADDwoR. In sensitivity analyses additionally adjusting for age and sex, neither covariate was statistically significant, and the effect estimates for the main imaging variables were materially unchanged. Given the cross-sectional design, these ROC results reflect discrimination of current disc-condyle status rather than prediction of future progression or outcomes.\u003c/p\u003e \u003cp\u003eIn univariate ROC analysis, HCA showed moderate discrimination for both ADD and ADDwoR, with AUCs of 0.688 (95% CI, 0.631\u0026ndash;0.741) and 0.684 (95% CI, 0.629\u0026ndash;0.736), respectively (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e6\u003c/span\u003e). The Youden index-based reference cutoffs were 26\u0026deg; for ADD and 28\u0026deg; for ADDwoR. These findings indicate that HCA alone is insufficient for precise classification but may still provide supportive discriminatory information as a quantitative imaging marker, and is therefore better interpreted as a complementary imaging indicator rather than a standalone diagnostic threshold.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e(A) ADD: AUC\u0026thinsp;=\u0026thinsp;0.688 for HCA alone and 0.833 for the multivariable GEE model. (B) ADDwoR: AUC\u0026thinsp;=\u0026thinsp;0.684 for HCA alone and 0.923 for the multivariable GEE model. Model-based ROC curves were constructed from individual predicted probabilities and reflect discrimination of current disc-condyle status in this cross-sectional dataset.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient-clustered univariable and multivariable GEE logistic regression models for ADD and ADDwoR\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePredictor\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eADD univariable OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eADD multivariable OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eADDwoR univariable OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eADDwoR multivariable OR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHCA (per 1\u0026deg; increase)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.06 (1.04\u0026ndash;1.08)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.07 (1.04\u0026ndash;1.09)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.07 (1.05\u0026ndash;1.09)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.03 (1.00\u0026ndash;1.05)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.072\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCondylar position: posterior vs concentric\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3.49 (2.26\u0026ndash;5.38)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.57 (2.80\u0026ndash;7.46)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32 (0.19\u0026ndash;0.56)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.67 (0.27\u0026ndash;1.68)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.397\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCondylar position: anterior vs concentric\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e1.88 (0.99\u0026ndash;3.59)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.056\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e1.56 (0.74\u0026ndash;3.31)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e0.245\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e3.28 (1.39\u0026ndash;7.73)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.007\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3.38 (1.11\u0026ndash;10.34)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.033\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCondylar bone status grade (per 1-grade increase)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e3.15 (1.97\u0026ndash;5.04)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e3.40 (1.86\u0026ndash;6.22)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e9.08 (5.37\u0026ndash;15.37)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e4.38 (2.46\u0026ndash;7.79)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCondylar morphology grade (per 1-grade increase)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e30.78 (3.71\u0026ndash;255.22)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e8.98 (2.36\u0026ndash;34.21)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDisc deformation grade (4-level, per 1-grade increase)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003e\u0026mdash;\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e4.18 (3.19\u0026ndash;5.49)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e3.87 (2.89\u0026ndash;5.19)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eOR, odds ratio; CI, confidence interval; HCA, horizontal condylar angle; NDP, normal disc position. \u0026ldquo;Concentric\u0026rdquo; denotes the reference category for condylar position. \u0026ldquo;\u0026mdash;\u0026rdquo; indicates not estimable or not included. In the ADD analyses, condylar morphology grade and disc deformation grade were not estimable and were therefore not included, because the NDP reference group showed no variability for these variables (all Grade I / normal pattern).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, using a relatively large TMJ MRI dataset, we applied a seven-type disc-condyle classification integrating sagittal reduction status and coronal displacement direction and characterized disc morphology, disc deformation grade, condylar position, condylar morphology grade, condylar bone status grade, and HCA across these groups. Overall, MRI findings showed a graded structural distribution across the disc-condyle categories, with more severe disc deformation, shifts in condylar positional composition, more frequent abnormal condylar morphology and osseous change, and higher HCA values in the displaced groups, particularly in the nonreducing subtypes. This pattern is consistent with the recognized natural history of TMJ disc displacement and with prior longitudinal MRI observations, although the present cross-sectional study was not designed to establish temporal progression. In patient-clustered multivariable GEE analyses accounting for bilateral correlation, HCA, posterior condylar position, and condylar bone status grade remained independently associated with ADD. In contrast, disc deformation grade, condylar morphology grade, condylar bone status grade, and anterior condylar position were independently associated with ADDwoR, whereas HCA showed a positive trend but did not retain independent significance after adjustment. Collectively, these findings support a multidimensional MRI-based characterization of ADD and ADDwoR, in which disc displacement is typically accompanied by co-occurring changes in disc morphology, condylar position, condylar morphology, osseous status, and HCA rather than being interpreted on the basis of any single isolated imaging finding [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e With respect to disc morphology and disc deformation, ADDwR was predominantly characterized by Grade I morphology, with Grade II as the second most common category, suggesting that disc architecture was relatively better preserved in the reducing groups. By contrast, the ADDwoR groups were dominated by Grade III and Grade IV morphology, indicating a greater burden of structural disc abnormality in the nonreducing groups. This distribution is consistent with prior longitudinal MRI evidence showing that nonreducing joints tend to exhibit more severe disc shortening and deformation than reducing joints [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Although the grading scheme used in the present study was defined independently on the basis of the current dataset and analytic objectives, the overall morphologic distribution was broadly comparable to that described by Hu et al., with relatively preserved configurations predominating in ADDwR and shortened folded or more severely deformed discs more common in ADDwoR [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The articular disc has been described as a fibrous, viscoelastic structure that supports normal force distribution [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Repetitive abnormal loading and altered disc-condyle mechanics may progressively disturb this normal stress distribution, leading to folding, shortening, and loss of the normal biconcave configuration. More severe deformation may also be associated with a lower likelihood of disc recapture, which may partly contribute to the predominance of higher-grade deformation in the nonreducing groups. Notably, Grade IV morphology was more frequent in ADDwR-AL and ADDwR-AM than in ADDwR-A, and ADDwoR-AM showed the highest proportion overall. These findings suggest that displacement with a mediolateral component, particularly nonreducing anteromedial displacement, may represent a more complex form of disc-condyle derangement. The proposed seven-type framework may also help refine MRI-based structural stratification by capturing subtype-specific patterns of co-occurring structural abnormalities beyond a binary reducing/nonreducing classification. Given the cross-sectional design, however, this interpretation remains hypothesis-generating and should be tested in studies incorporating three-dimensional quantitative assessment and longitudinal follow-up.\u003c/p\u003e \u003cp\u003eRegarding condylar features, the NDP group most commonly showed a concentric condylar position with largely normal condylar morphology and osseous status. In the ADDwR groups, posterior condylar position was more frequent, whereas in ADDwoR the relative proportions of concentric and anterior positions increased compared with ADDwR. This distribution is broadly consistent with prior reports and with Chen et al., who found significant associations of disc position and morphology with condylar position and bone morphology, although disc displacement did not invariably lead to condylar osseous change [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. It is also in line with Li and Zhang, who reported posterior condylar position and abnormal condylar morphology as significant correlates of symptomatic TMJs [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Moreover, degenerative change and severe destruction were more prevalent in ADDwoR, together with higher proportions of shortened and beak-shaped condyles. This pattern is likewise consistent with prior evidence linking disc displacement, particularly ADDwoR, to condylar erosion and other advanced osseous abnormalities [\u003cspan additionalcitationids=\"CR16 CR17 CR18 CR19\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the present study, HCA measurement showed good reliability, which provides important support for its use as a quantitative imaging marker. This is noteworthy because formal reliability assessment has been lacking in much of the previous literature on HCA. HCA also differed across the disc-condyle groups and showed an overall increase from NDP to ADDwR and ADDwoR. In the categorical analyses, NDP clustered mainly within the 10\u0026ndash;30 degree range, whereas the proportion of HCA\u0026thinsp;\u0026gt;\u0026thinsp;30 degrees increased across displaced groups. These findings are broadly consistent with prior reports showing that higher HCA values are more frequently observed in joints with disc displacement and osseous abnormality [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. More recent axial MRI work has likewise shown that angular changes of the condyle and related structures can be demonstrated in association with anterior disc displacement, further supporting the relevance of axial angular metrics in TMJ internal derangement [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. One possible explanation is that altered disc-condyle mechanics in displaced joints may be accompanied by rotational reorientation of the condyle, which is reflected by an increased HCA. Beyond this overall gradient, our data further suggest that the increase in HCA is not uniformly distributed across all displaced joints. Rather, subtypes with anteromedial displacement tended to show both higher mean HCA values and a higher proportion of HCA\u0026thinsp;\u0026gt;\u0026thinsp;30 degrees, particularly ADDwoR-AM. This pattern may indicate greater structural complexity in joints with a medial displacement component. A possible explanation is that, because the medial aspect of the glenoid fossa provides relatively limited space, a medially displaced disc may occupy part of the medial joint compartment and mechanically displace the condyle, resulting in rotational reorientation and a larger HCA. Given the retrospective cross-sectional design, however, this interpretation remains hypothesis-generating.\u003c/p\u003e \u003cp\u003eOur patient-clustered GEE analyses further clarify how these MRI features contribute across different levels of disc-condyle derangement. In univariable analyses, HCA, condylar position, condylar morphology grade, condylar bone status grade, and disc deformation grade all showed discriminatory information when considered individually. After joint modeling, however, the pattern differed between the two modeled contrasts. In the ADD contrast, posterior condylar position, HCA, and condylar bone status grade remained the principal independent imaging correlates after adjustment, with posterior condylar position showing a particularly strong association (OR, 4.57) and condylar bone status grade also contributing substantially (OR, 3.40 per grade increase). This pattern suggests that, at the broader level of distinguishing normal joints from joints with disc displacement, the most informative MRI features are those reflecting overall disc-condyle imbalance, including altered condylar positional composition, increasing condylar rotational alignment, and associated osseous abnormality. By contrast, in the ADDwoR contrast, disc deformation grade, condylar morphology grade, condylar bone status grade, and anterior condylar position remained independently associated after adjustment, whereas HCA showed a positive trend but no longer retained independent significance (P\u0026thinsp;=\u0026thinsp;0.072). This difference suggests that the distinction between reducing and nonreducing displacement is characterized less by generalized imbalance and more by direct structural deterioration of the disc-condyle complex, particularly worsening disc deformation, condylar remodeling, and osseous change. This overall pattern is broadly consistent with the recent semiquantitative MRI study by Liao et al. [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], in which nonreducing joints also showed more advanced structural abnormalities. However, their multivariable analysis identified fold-curved disc configuration, displacement degree, and joint effusion grade as independent correlates of ADDwoR [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], whereas the independently associated features in our study were not identical. This difference may partly reflect differences in analytic framework, because the present study applied a seven-type disc-condyle classification incorporating both reduction status and coronal displacement direction, thereby permitting a more granular comparison of co-occurring structural changes than binary ADDwR/ADDwoR models alone [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe relationship between the univariable and multivariable findings is also informative. The loss of independent significance of HCA in the ADDwoR multivariable model does not indicate that HCA is uninformative; rather, it suggests that part of the information captured by HCA overlaps with that conveyed more directly by disc deformation, condylar morphology, condylar bone status, and condylar position when these variables are considered jointly. The ROC findings support this interpretation. HCA alone showed only moderate discrimination for both ADD and ADDwoR (AUCs, 0.688 and 0.684, respectively), whereas the final multivariable models achieved substantially higher AUCs (0.833 and 0.923, respectively), particularly for ADDwoR. Accordingly, HCA is unlikely to serve as a standalone diagnostic threshold, but it still provides useful quantitative structural information within a broader MRI-based assessment. Conversely, the stronger discrimination of the multivariable models indicates that current disc-condyle status is better characterized by the combined MRI pattern of disc deformation, condylar position, condylar morphology, osseous change, and HCA than by any single isolated imaging feature. Given the retrospective cross-sectional design, these findings should be interpreted as reflecting discrimination of current disc-condyle status rather than prediction of future progression or outcomes.\u003c/p\u003e \u003cp\u003eOur findings may also have ancillary practical implications in routine TMJ imaging assessment. Many patients presenting to TMJ clinics have already undergone CBCT before MRI is considered. In the present study, condylar position, morphology, and osseous status showed generally good agreement between CBCT and MRI, suggesting that these condylar features can be assessed with reasonable consistency across the two modalities. Because our patient-clustered GEE analyses identified condylar structural features as relevant correlates of both ADD and ADDwoR, and because prior studies have likewise linked condylar abnormalities to disc displacement and more advanced internal derangement [\u003cspan additionalcitationids=\"CR16 CR17 CR18\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], CBCT-derived condylar findings may provide useful preliminary information when considering whether further TMJ MRI is warranted. This interpretation is also broadly consistent with recent CBCT-based studies [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] and recent 3T MRI evidence [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. However, this secondary analysis was not designed as a formal modality-comparison or triage study, and such information should therefore be regarded as complementary rather than a substitute for MRI, because MRI remains necessary for direct assessment of disc position, reduction status, and disc morphology [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSeveral limitations should be acknowledged. First, this was a single-center retrospective cross-sectional study. Although patient-clustered GEE models were used to account for bilateral within-patient correlation, the temporal sequence and causal direction among disc displacement, HCA, disc deformation, condylar remodeling, and osseous change cannot be determined. This is particularly relevant because prior MRI and semiquantitative studies, including longitudinal or follow-up observations, suggest that disc deformation and associated structural abnormalities may evolve over time rather than remain static [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In addition, the NDP group was derived from a clinically referred MRI cohort rather than from an asymptomatic healthy control population; therefore, the findings should be interpreted as contrasts within a clinical imaging population rather than as direct comparisons with the general population. Second, although the proposed classification framework improves clinical applicability and permits more granular stratification of disc-condyle derangement, it remains subject to the spatial resolution of routine MRI, oblique-plane prescription, slice thickness, and reader judgment, and some within-subtype heterogeneity in accompanying structural features may therefore remain. Third, the ROC-derived cutoffs from this single-center sample, including the Youden index-based reference thresholds for HCA, should not be interpreted as universal diagnostic thresholds. In addition, HCA measurement may be influenced by head positioning, axial slice selection, and planning variability, underscoring the need for further standardization of acquisition and measurement procedures before broader clinical application [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFuture work should validate this classification framework and the multivariable models in multicenter prospective cohorts and should further determine, through longitudinal follow-up, whether HCA and other MRI features have value not only for discrimination of current disc-condyle status but also for risk stratification of ADD onset and transition from reducing to nonreducing displacement states [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Incorporation of more granular quantitative imaging features, including three-dimensional or surface-based descriptors of condylar morphology, disc shape, joint geometry, and broader MRI-based structural features, may further refine structural characterization beyond the semiquantitative variables used here [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Together with external validation, model recalibration, and assessment of clinical utility, such work will help define the appropriate clinical role of HCA thresholds and integrated MRI-based models in TMJ imaging.\u003c/p\u003e \u003cp\u003eOverall, TMJ disc displacement was characterized by coordinated abnormalities of disc deformation, condylar position, condylar morphology, condylar bone status, and HCA. The proposed seven-type framework may help refine MRI-based structural stratification by capturing subtype-specific patterns of co-occurring structural abnormalities beyond a binary reducing/nonreducing classification. HCA provides complementary quantitative information, but it is insufficient as a standalone diagnostic threshold.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eTemporomandibular joint disc displacement is characterized by coordinated abnormalities of disc deformation, condylar position, condylar morphology, condylar bone status, and horizontal condylar angle on magnetic resonance imaging. The proposed seven-type disc-condyle classification may support more refined structural stratification than a binary reducing/nonreducing framework alone by capturing subtype-specific patterns of co-occurring abnormalities. Horizontal condylar angle provides complementary quantitative information, but its standalone discriminatory performance is limited and it is better interpreted within an integrated magnetic resonance imaging assessment. These findings are relevant to the imaging-based evaluation of temporomandibular joint internal derangement and may help improve structural interpretation of current disc-condyle status.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanterior disc displacement\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADDwR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanterior disc displacement with reduction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eADDwoR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanterior disc displacement without reduction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanterolateral\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eanteromedial\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAUC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003earea under the curve\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCBCT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econe-beam computed tomography\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003econfidence interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGEE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003egeneralized estimating equation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehorizontal condylar angle\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eICC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eintraclass correlation coefficient\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIQR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einterquartile range\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMRI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emagnetic resonance imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNDP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003enormal disc position\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eodds ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePACS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epicture archiving and communication system\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePDWI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eproton density-weighted imaging\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eROC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ereceiver operating characteristic\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003estandard deviation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTMJ\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etemporomandibular joint\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTMD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etemporomandibular disorder\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eT2WI-FS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eT2-weighted imaging with fat suppression\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThis retrospective cross-sectional study was approved by the Ethics Committee of School \u0026amp; Hospital of Stomatology, Wuhan University (Approval No. WDKQ2026-B04). The requirement for informed consent was waived by the Ethics Committee of School \u0026amp; Hospital of Stomatology, Wuhan University because of the retrospective design and the use of anonymized imaging data. The study was conducted in accordance with the Declaration of Helsinki.\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003cbr\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003eAvailability of data and materials\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study are not publicly available because they contain clinical imaging data derived from human participants and are subject to privacy and ethical restrictions. De-identified data may be available from the corresponding author on reasonable request, subject to approval by the relevant institutional and ethics requirements.\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003eFunding\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003eAuthors\u0026rsquo; contributions\u003c/p\u003e\n\u003cp\u003eH.L. contributed to study design, image evaluation, data collection, and drafting of the manuscript. L.W. contributed to image evaluation and revision of the manuscript. F.W. contributed to data interpretation and revision of the manuscript. B.L. conceived and supervised the study and contributed to study design, data interpretation, and revision of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgements\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003eClinical trial number\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eLarheim TA, Hol C, L\u0026oslash;seth G, Arvidsson LZ. Temporomandibular joint pathologies: pictorial review. Br J Radiol. 2024;97(1153):53\u0026ndash;67. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/bjr/tqad021\u003c/span\u003e\u003cspan address=\"10.1093/bjr/tqad021\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHegab AF, AbdAl Hameed HI, Karam KS. 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Cone-Beam Computed Tomography as a Diagnostic Tool for TMJ Morphological Alterations in Disc Displacement. Int Dent J. 2025;75(5):100908. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.identj.2025.100908\u003c/span\u003e\u003cspan address=\"10.1016/j.identj.2025.100908\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e\u0026Ouml;zel Ş, Tun\u0026ccedil; S, Şenol AU. Association between clinical findings and 3T MRI features in temporomandibular joint disorders. BMC Oral Health. 2025;25(1):921. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12903-025-06283-w\u003c/span\u003e\u003cspan address=\"10.1186/s12903-025-06283-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTang R, Chen W, Xu N, Yuan X, Bai X, Zhang B, et al. Condylar alteration in three subtypes of temporomandibular disorder based on U-HRCT: a cross-sectional study. BMC Oral Health. 2025;25(1):1930. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12903-025-07557-z\u003c/span\u003e\u003cspan address=\"10.1186/s12903-025-07557-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRamesh E, Ganesan A, Gauthaman J, Lakshmi KC, Kannan S. Comparison of medic and 3D DESS with routine MRI to assess the diagnostic efficacy in symptomatic temporomandibular disorders: a cross sectional observational study. Sci Rep. 2025;15(1):33468. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41598-025-11650-2\u003c/span\u003e\u003cspan address=\"10.1038/s41598-025-11650-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Temporomandibular joint, Magnetic resonance imaging, Anterior disc displacement, Disc displacement without reduction, Horizontal condylar angle, Disc-condyle classification","lastPublishedDoi":"10.21203/rs.3.rs-9389404/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9389404/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMRI findings in temporomandibular joint disc displacement are commonly described using individual structural markers, whereas integrated disc-condyle classification frameworks remain limited. This study aimed to characterize magnetic resonance imaging structural features and horizontal condylar angle across a seven-type disc-condyle classification and to evaluate their associations and discriminatory performance for anterior disc displacement and anterior disc displacement without reduction.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis single-center retrospective cross-sectional study included 310 patients, contributing 568 temporomandibular joint sides. Joints were classified as normal disc position, anterior disc displacement with reduction, or anterior disc displacement without reduction, with anterior, anterolateral, and anteromedial subtypes. Disc deformation, condylar position, condylar morphology, condylar bone status, and horizontal condylar angle were assessed. Associations and discrimination were evaluated using patient-clustered generalized estimating equation models and receiver operating characteristic analysis.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eCompared with nondisplaced joints, displaced joints showed greater disc deformation, more frequent condylar abnormalities, and higher horizontal condylar angle values. In multivariable analyses, horizontal condylar angle, posterior condylar position, and condylar bone status were independently associated with anterior disc displacement. Disc deformation grade, condylar morphology grade, condylar bone status, and anterior condylar position were independently associated with anterior disc displacement without reduction. Apparent area under the curve values were 0.833 for anterior disc displacement and 0.923 for anterior disc displacement without reduction, whereas horizontal condylar angle alone showed only moderate discrimination.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eTemporomandibular joint disc displacement is characterized by coordinated abnormalities of disc deformation, condylar position, condylar morphology, condylar bone status, and horizontal condylar angle. The seven-type framework may support more refined magnetic resonance imaging-based structural stratification, whereas horizontal condylar angle is better interpreted as a complementary quantitative marker rather than a standalone diagnostic threshold.\u003c/p\u003e","manuscriptTitle":"TMJ MRI structural features and horizontal condylar angle across a seven-type disc-condyle classification: a retrospective cross-sectional study with patient-clustered GEE and ROC analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-12 14:15:17","doi":"10.21203/rs.3.rs-9389404/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"305017276280971109605921620627713007036","date":"2026-05-19T10:23:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T12:12:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93243925920385847604323595591595838937","date":"2026-05-01T11:54:18+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-01T09:43:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-01T09:34:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-20T05:13:01+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-17T19:20:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Oral Health","date":"2026-04-17T16:43:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-oral-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"ohea","sideBox":"Learn more about [BMC Oral Health](http://bmcoralhealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/ohea/default.aspx","title":"BMC Oral Health","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1bafb519-b351-4783-a46e-e90d018d5d06","owner":[],"postedDate":"May 12th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"305017276280971109605921620627713007036","date":"2026-05-19T10:23:41+00:00","index":36,"fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-05-01T12:12:01+00:00","index":30,"fulltext":""},{"type":"reviewerAgreed","content":"93243925920385847604323595591595838937","date":"2026-05-01T11:54:18+00:00","index":29,"fulltext":""},{"type":"reviewersInvited","content":"6","date":"2026-05-01T09:43:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-05-01T09:34:49+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-12T14:15:18+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-12 14:15:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9389404","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9389404","identity":"rs-9389404","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}