Comparison of Medic and 3d Dess with Routine MRI to Assess the Diagnostic Efficacy in Symptomatic Temporomandibular Disorders – A Cross Sectional Observational Study

Comparison of Medic and 3d Dess with Routine MRI to Assess the Diagnostic Efficacy in Symptomatic Temporomandibular Disorders – A Cross Sectional Observational Study | 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 Article Comparison of Medic and 3d Dess with Routine MRI to Assess the Diagnostic Efficacy in Symptomatic Temporomandibular Disorders – A Cross Sectional Observational Study ELAKYA RAMESH, ANURADHA GANESAN, JEEVITHA GAUTHAMAN, KRITHIKA CHANDRASEKAR LAKSHMI, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6541464/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 29 Sep, 2025 Read the published version in Scientific Reports → Version 1 posted 13 You are reading this latest preprint version Abstract Background: Temporomandibular disorders (TMDs) affect the orofacial region, particularly the temporomandibular joint (TMJ). This study evaluated early intra-articular disc changes in symptomatic TMD patients using various MRI sequences, comparing the diagnostic efficacy of MEDIC and 3D DESS with routine MRI. Materials and Methods: A total of 108 TMJs from symptomatic patients were assessed. All underwent routine MRI, MEDIC, and 3D DESS sequences. Three radiologists qualitatively and quantitatively evaluated images using Likert’s scale. Statistical analysis was performed with SPSS, and inter-observer variability assessed via Fleiss' kappa (κ). Results: MRI revealed 41.7% disc displacement with reduction, 19.4% without reduction, and 38.9% normal. MEDIC provided superior visualization of joint fluid and bone marrow changes, followed by PD-FSE and DESS. Signal intensity ratios were highest in PD-FSE, followed by MEDIC and DESS. Inter-observer reliability showed perfect agreement. Conclusion: While PD-FSE offers excellent contrast, it may miss early degenerative changes. Adding MEDIC improves detection of joint effusions and bone marrow abnormalities, enhancing early diagnosis and clinical decision-making for TMDs. Health sciences/Diseases Health sciences/Health care Health sciences/Medical research Magnetic resonance imaging Diagnostic accuracy Temporomandibular joint Early Detection Diagnostic Accuracy Image quality Signal intensity ratio Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION The temporomandibular joint (TMJ) exists as a connection that binds the lower jaw and the temporal bone in the craniofacial complex to permit essential jaw functions. [1] Proprioception of the joint is influenced by multiple factors, such as the capsule, the muscles of mastication, receptors of skin and periodontal ligaments. [2] A class of degenerative musculoskeletal diseases known as temporomandibular joint disorders is distinguished by morphological and functional complications. [3] It encompasses dysfunction of the related muscles and anomalies of the intra-articular discal location and/or structure. [4] There are several different causes that contribute to the etiology of TMD, including both physical and psychological ones. [5] It primarily affects individuals aged 20–40, making it a significant concern for young adults. Early diagnosis is vital to prevent chronic pain, joint damage, and functional issues. Prolonged TMD may hinder educational, social, and occupational development. The DC/TMD is the preferred and reliable tool for diagnosing and classifying TMD. [6] Various imaging methods—CT, CBCT, MRI, ultrasonography, and traditional radiography—are used to assess the temporomandibular joint (TMJ). MRI is the most effective non-invasive tool for visualizing TMJ soft tissues. Early diagnosis of TMD includes monitoring symptoms and joint effusion. [7] The MRI reveals early signs of TMJ dysfunction by showing disc deformity together with joint effusion and retro discal tissue deformity and anterior or posterior band thickening. [8] Proton-density (PD), T1-weighted, and T2-weighted images are most commonly used scanning sequences. [9] However, MRI has limitations, including high costs and the need for specialized facilities. It is contraindicated in patients with claustrophobia, pacemakers, metallic heart valves, ferromagnetic foreign bodies, and during pregnancy. [10] The Proton Density Fast Spin Echo (PD FSE) MRI sequence is preferred in musculoskeletal imaging for its sharp soft tissue contrast, especially of the condyle and surrounding muscles. It offers high SIR and excellent resolution for evaluating cartilage, ligaments, tendons, and bones, aiding accurate diagnosis. [11] The Siemens 2D spoiled gradient echo multi-echo sequence MEDIC ("Multi-Echo Data Image Combination") incorporates a magnetization transfer saturation pulse, enhancing the visualization of structures such as the condyle and surrounding muscles. [12] MEDIC’s high spatial resolution enables detailed assessment of the bony architecture of the condyle, clearly delineating it from adjacent soft tissues. [13] The Siemens 3D DESS sequence offers improved contrast resolution between fluid and cartilage in the synovial joint. [14] With this gap in literature, this study assessed the diagnostic accuracy and clinical relevance ofthese advanced sequences in symptomatic patients. And compared the effectiveness of MEDIC and 3D DESS sequences with routine MRI in detecting early degenerative changes, disc displacements, joint effusion, and other structural abnormalities in symptomatic temporomandibular disorders (TMDs). MATERIALS AND METHODS This cross-sectional observational study was conducted at the Department of Oral Medicine and Radiology, SRM Dental College, Chennai, from April 2023 to December 2024. Ethical approval was obtained (SRMDC/IRB/2022/MDS/NO. 901), and the study adhered to the Declaration of Helsinki. Participants were recruited voluntarily based on inclusion criteria. The study was registered with the Clinical Trial Registry of India (CTRI/2025/03/082074). Simple random sampling was used to select participants. Using G*Power (v3.0), the required sample size was estimated at 108 TMJs, divided equally into three groups (36 each): Group A (PD-FSE), Group B (MEDIC), and Group C (3D-DESS). All MRI scans were obtained from patients at the Oral Medicine and Radiology outpatient department, SRM Dental College, Chennai. Participants aged 18–40 years of both genders, diagnosed with TMD based on RDC criteria (arthralgia: ICD-9 524.62; ICD-10 M26.62), and presenting with relevant symptoms such as joint pain, clicking, jaw deviation, limited opening, and preauricular pain were included upon informed consent. Individuals who were pregnant or lactating, had contraindications to MRI (such as pacemakers, metal implants, or claustrophobia), presented with physical or mental disabilities, weighed over 150 kg, or had a history of TMD, arthritis, trauma, or significant TMJ swelling and pain requiring treatment were excluded from the study A comprehensive case history and clinical assessment were conducted for all participants, and data were documented in a proforma. Participants underwent routine MRI with MEDIC and 3D DESS sequences in a supine position using a 3 Tesla Siemens scanner. Imaging was performed with a 32-channel head and neck coil, with scan parameters provided in Table 1 . The field of view was set at 5cm x 5cm. MRI images of the bilateral TMJs were acquired in axial, coronal, and sagittal planes, with adjustments made for the open & closed mouth position. Images were evaluated by an experienced medical radiologist and two oral radiologists. Three MRI sequences (PD-FSE, MEDIC, and 3D DESS) were combined with two oblique sagittal positions (closed and open mouth) for analysis, as shown in Fig. 1 and Fig. 2 . Table 1 Acquisition parameters of the applied MRI sequences Imaging Technique PD-FSE MEDIC 3D DESS TR (ms) 3400 31.0 15.20 TE (ms) 34 17.0 5.25 FOV (mm × mm) 150 × 150 150 × 150 130 × 130 Slice Thickness (mm) 2.0 0.76 0.85 Flip Angle (°) 150 8 25 Bandwidth (Hz/Px) 240 181 250 The qualitative assessment of MRI: We qualitatively assessed articular disc morphology, including configuration (biplanar, biconcave, biconvex, hemiconvex, thickened posterior band), disc position, joint fluid, and bone marrow characteristics. Disc displacement was classified according to Tasaki et al. [15] and Murakami et al. [16] , while joint effusion was evaluated based on Larheim et al.'s criteria- four categories of fluid accumulation observed, ranging from minimal to significant. [17] Bone marrow abnormalities, including edema and osteonecrosis, were classified using Larheim et al. 's guidelines- based on the presence of edema or osteonecrosis. [18] The quantitative assessment of MRI: Signal intensity ratio (SIR) changes were evaluated to assess the relationship between tissue signal alterations and clinical outcomes (Fig. 3 ). Image quality (IQ) was rated on a 4-point Likert scale, with two radiologists independently scoring each sequence: 1 = inadequate, 2 = suboptimal, 3 = sufficient, and 4 = optimal as described by Markus Kopp et al., The assessment focused on disc morphology, disc position, and osseous joint morphology as shown in Fig. 3 . [19] STATISTICAL ANALYSIS: Statistical analysis was performed using SPSS (Version 26.0) and JASP software. Non-parametric methods were used, with descriptive statistics expressed as median and interquartile range (IQR). The Kruskal-Wallis test compared signal intensity ratios across MRI sequences for MCBM, AB, and LP, followed by Dunn post hoc tests for pairwise comparisons. The Chi-square test assessed categorical variables and image quality, while Fleiss' Kappa evaluated interobserver reliability. The significance level was set at α = 0.05. RESULTS This study assessed the effectiveness of different MRI sequences in evaluating TMJ structures, focusing on disc position, morphology, joint fluid, bone marrow, condyle, lateral pterygoid muscle and associated pathological changes. It also provide insights into the variations in image quality, diagnostic accuracy, and structural differences observed across MRI sequences. Table 2: Frequency distribution characteristics with grouping based on MRI based diagnosis. Groups based on MRI Diagnosis (n) DWR (15) DWOR (7) Normal (14) Age (mean ± SD) 28.26 ± 8.762 27.71 ± 7.181 27.57 ± 6.37 Gender Male 2 (13.33) 0 5 (35.71) Female 13 (86.66) 7 (100) 9 (64.28) Disc configuration Hemiconvex 10 (66.66) 5 (71.42) 0 Thickening of the posterior band 0 2 (28.57) 0 Biconcave 0 0 4 (100) Biplanar 5 (33.33) 0 0 Disc position- Closed Anterior 15 (100) 7 (100) 0 Superior 0 0 14 (100) Disc position- Open Add with reduction 15 (100) 0 0 Add without reduction 0 7 (100) 0 Superior 0 0 14 (100) Groups based on MRI Diagnosis (n) PD - FSE (36) MEDIC (36) 3D DESS (36) Joint fluid (Nil) 17 (47.22) 14 (38.88) 24 (66.66) Joint fluid (Minimum) 11 (30.55) 16 (44.44) 11 (30.55) Joint fluid (Moderate) 8 (22.22) 6 (16.66) 1 (2.77) Bone marrow (Normal) 29 (80.55) 17 (47.22) 34 (94.44) Bone marrow (Edema) 7 (19.44) 19 (52.77) 2 (5.55) Most TMD patients were female, with anterior disc displacement common in DWR and DWOR groups, while normals showed superior disc position and biconcave shape. Hemiconvex disc configuration was frequent in DWR and DWOR groups, whereas normals had no such deformities. PD-FSE showed the highest sensitivity for detecting joint fluid than MEDIC but more than 3D DESS. MEDIC showed the highest sensitivity for detecting bone marrow edema, unlike 3D DESS, which showed mostly normal marrow. Combining MEDIC with PD-FSE may offer improved diagnostic accuracy for detecting early joint fluid and marrow abnormalities as shown in Table 2. Table 3: Inter-Observer Reliability for Image Quality Observation, Joint Fluid, Bone Marrow Quality, and Disc Assessment. (Fliess Kappa is used for interrater reliability assessment) Parameter Groups Fliess kappa 95% CI Lower Upper For image quality observation (Ordinal Likert scale scoring) Condyle PD - FSE 0.928 0.778 1.079 MEDIC 0.963 0.817 1.109 3D DESS 0.969 0.829 1.109 Disc PD - FSE 0.956 0.767 1.144 MEDIC 0.95 0.801 1.098 DESS 0.962 0.821 1.103 Lateral Pterygoid Muscle PD - FSE 0.97 0.833 1.107 MEDIC 1 0.864 1.136 3D DESS 0.941 0.802 1.08 Joint fluid and Bone marrow quality (Nominal scale) Joint fluid PD - FSE 1 0.864 1.136 MEDIC 0.962 0.821 1.103 3D DESS 0.97 0.833 1.107 Bone marrow quality PD - FSE 1 0.864 1.136 MEDIC 0.97 0.833 1.107 3D DESS 0.963 0.817 1.109 Disc configuration 1 0.811 1.189 Disc position- Closed 1 0.878 1.122 Disc position- Open 1 0.878 1.122 The inter-rater reliability, assessed using Fleiss' kappa which indicates strong observer consistency in evaluating TMJ anatomy and image quality across modalities. as shown in table 3. Raincloud plots show that PD-FSE consistently yields higher and more variable signal intensities across MCBM, AB, and LP, indicating greater sensitivity or contrast. In contrast, MEDIC and 3D DESS display lower, more uniform signal intensities, suggesting more consistent but less intense imaging. Overall, PD-FSE offers stronger signals, while MEDIC and DESS provide steadier image profiles as shown in Figure 4. Intergroup comparisons show PD-FSE has significantly higher signal intensities than MEDIC and 3D DESS (p < .001), indicating superior contrast. For MCBM, MEDIC and DESS show no significant difference (p = 0.739), while AB and LP show significant differences across all sequences (p < 0.05). Overall, PD-FSE outperforms in signal strength; MEDIC and DESS vary by structure. MEDIC showed the highest rates of optimal image quality (IQ) in the condyle, disc, and LP muscle, with minimal partly diagnostic ratings. PD-FSE offered a balanced distribution of image quality across regions. 3D DESS had more partly diagnostic images, especially in the condyle and LP muscle, but still achieved notable optimal IQ levels as shown in Figure 5. Table 4: Comparison of Joint Fluid and Bone marrow quality observation Using Different MRI Sequences (PD-FSE, MEDIC, and DESS) *Chi-square test is used for significance testing of association between the groups. P value of ≤0.05 is considered to be significant. Groups JOINT FLUID Value df P Nil Minimum Moderate PD - FSE Count 17 11 8 9.389 4 0.052* % within column 30.9 % 28.94 % 53.33 % MEDIC Count 14 16 6 % within column 25.45 % 42.105 % 40 % DESS Count 24 11 1 % within column 43.63 % 28.947 % 6.66 % Total Count 55 38 15 % within column 100 % 100 % 100 % Groups BONE MARROW QUALITY Value df P Normal EDEMA PD - FSE Count 29 07 22.082 2 < .001* % within column 36.25 % 25.00 % MEDIC Count 17 19 % within column 21.25 % 67.85 % DESS Count 34 2 % within column 42.5 % 7.14 % Total Count 80 28 % within column 100 % 100 % The sensitivity of MRI sequences for joint fluid and bone marrow abnormalities varies. PD-FSE showed the highest sensitivity for detecting "Moderate" joint fluid (53.33%), while MEDIC had a balanced distribution, with more "Minimum" detections (42.11%). DESS had the most "Nil" detections (43.63%). For bone marrow, MEDIC was most sensitive to edema (67.85%), outperforming PD-FSE (25%) and DESS (7.14%). The significant difference in bone marrow detection (p < 0.001) highlights MEDIC's superior performance, while joint fluid detection showed no significant difference (p = 0.052) as shown in Table 4. DISCUSSION A collection of complex, multifactorial conditions that affect the temporomandibular joint (TMJ) and its associated structures are collectively referred to as "temporomandibular joint disorders" (TMJ disorders). [3] The progression or worsening of these signs and symptoms can ultimately restrict or even prevent individuals from carrying out their normal physiological activities. [20] The primary approach to diagnosing TMD involves a clinical examination, often supplemented by radiographic imaging. A common non-invasive and non-ionizing imaging technique for evaluating TMJ-related problems, the ideal method for diagnosing temporomandibular disorders (TMDs) involving soft tissues is magnetic resonance imaging (MRI). [21] To improve detection and clinical decision-making, our study used a variety of MRI sequences to assess early diagnostic alterations in TMD. [22] Moreover, MRI does not expose patients to ionizing radiation or other biological hazards. Additional benefits include its high sensitivity, specificity, and diagnostic accuracy. [23] This study investigates the diagnostic performance of three distinct Magnetic Resonance Imaging (MRI) sequences – Proton Density Fast Spin Echo (PD-FSE), Multiple Echo Data Image Combination (MEDIC), and three-dimensional Dual Echo Steady State (3D DESS) – in the assessment of symptomatic temporomandibular disorders (TMDs). Our research on 108 temporomandibular joints from symptomatic TMD patients provides a comprehensive dataset for analysis, contrasting with a prior study by Aksoy et al. that evaluated 60 joints using advanced MRI sequences. [24] The demographic profile of our study population revealed a mean age of 28.26 ± 8.762 years for the Disc Displacement with Reduction (DWR) group, 27.71 ± 7.181 years for the Disc Displacement Without Reduction (DWOR) group, and 27.57 ± 6.37 years for the Normal group. This younger age range, focusing on patients under 40, suggests that TMDs in our study are not strongly age-dependent, aligning with our research's specific focus. Notably, we observed a significant female predominance in both the DWR (86.66%) and DWOR (100%) groups, while the Normal group exhibited a higher proportion of males (35.71%), hinting at a potential gender-related susceptibility to TMDs. This contrasts with the study by Aksoy et al., which reported a mean age of 38.1 years for females and 32.4 years for males in their TMD patient population. [24] In assessing disc morphology, our findings indicated that the hemiconvex disc shape was most prevalent in the DWR (66.66%) and DWOR (71.42%) groups. Conversely, the Normal group exclusively presented with a biconcave disc shape (100%), highlighting structural disparities between healthy and dysfunctional joints. This contrasts with the findings of Sivakumar et al., who, in their analysis of 52 TMJs, identified biconcave as the most common disc shape (52 TMJs), followed by biplanar, hemiconvex, and folded configurations, suggesting a broader spectrum of morphological variations in their study. Regarding disc position, our study corroborated the observations of Sivakumar et al., noting anterior disc displacement in the closed-mouth state for both DWR and DWOR cases, while the Normal group exhibited a superior disc position. [25] This aligns with Murakami et al.'s study, which suggested that normal discs are predominantly biconcave, and displaced discs often undergo deformation post-displacement, with biconcave discs being prone to folding under condylar pressure due to their thin central portion. [16] The hemiconvex shape observed in our study in the dysfunctional groups may represent an intermediate stage of disc deformation resulting from mechanical stress and degeneration, potentially exacerbated by parafunctional habits like bruxism and clenching, leading to disc thickening and alterations. Our study also compared the efficacy of PD-FSE, MEDIC, and 3D DESS sequences in detecting joint fluid and bone marrow changes, contrasting with Aksoy et al.'s comparison of Fat-Suppressed T2-weighted (FS T2W), Fast Spin Echo T2 (FSE T2), and 3D Fast Imaging Employing Steady-State Acquisition (FIESTA-C) sequences. We found that PD-FSE demonstrated the highest detection rate for moderate joint fluid (53.333%), while 3D DESS exhibited the highest “Nil joint fluid” detection (43.636%), indicating lower sensitivity to fluid. MEDIC showed a balanced distribution, with the highest detection in the minimum fluid category (42.105%). In contrast, Aksoy et al. reported that 3D FIESTA-C and FS T2W were significantly more effective in detecting joint fluid compared to FSE T2W. [24] Regarding bone marrow changes, our study revealed that MEDIC was the most effective sequence, detecting bone marrow edema in 67.857% of cases, signifying its superior sensitivity to pathological alterations. Conversely, 3D DESS showed the highest proportion of normal bone marrow (42.5%) and the lowest edema detection (7.143%), suggesting reduced effectiveness in identifying bone marrow abnormalities. PD-FSE presented a balanced detection, identifying normal bone marrow in 36.25% and edema in 25% of cases. This contrasts with Aksoy et al.'s finding that 3D FIESTA-C and FS T2W had the highest sensitivity for detecting bone marrow changes. The superior performance of MEDIC in detecting bone marrow edema aligns with earlier studies highlighting its high signal-to-noise ratio (SNR), multi-echo acquisition, and improved contrast resolution, facilitating better fat-water separation and enhanced visualization of edema as increased signal intensity on T2-weighted images. Interobserver reliability, assessed using the Fleiss kappa statistic, demonstrated fair to good agreement (κ ≥ 0.61) among the three radiologists for all sequences and parameters evaluated in our study. Notably, PD-FSE showed perfect agreement (κ = 1.000) for joint fluid and bone marrow assessments, while disc configuration and position evaluations also had perfect agreement (κ = 1.000) across all sequences. Image quality assessments were highly consistent, with κ values ranging from 0.928 to 0.969. This contrasts with Aksoy et al.'s study, which found that 3D FIESTA-C and FS T2W sequences exhibited the highest interobserver agreement for detecting joint fluid and bone marrow changes, while FSE T2W showed lower agreement in these aspects but the greatest agreement for identifying anterior disc displacement without reduction. Quantitatively, our analysis of signal intensity ratios (SIR) in the mandibular condyle bone marrow (MCBM), anterior band of disc (AB), and lateral pterygoid muscle (LP) revealed that PD-FSE yielded the highest mean values, with significant differences observed across PD-FSE, MEDIC, and 3D DESS. This contrasts with Aksoy et al.'s study, which found that the SIRs of FS-T2 and 3D FIESTA-C were substantially better than those of FSE-T2, with no discernible difference between FS-T2 and 3D FIESTA-C. [24] Our findings suggest that PD-FSE's superior feature separation and noise reduction capabilities contribute to higher SIR values in the assessed TMJ structures compared to MEDIC and 3D DESS. While MEDIC excels in reducing metal artifacts and enhancing soft tissue contrast, it may experience signal averaging that reduces fine structural details. DESS, known for high-resolution cartilage imaging, may exhibit lower SIR in mixed tissue regions due to partial volume effects. Our study, being the first to compare the image quality of MEDIC with PD-FSE and 3D DESS sequences using a 4-point Likert scale based on comprehensive reporting from three radiologists, found that MEDIC achieved the highest proportion of Optimal Image Quality (IQ) for the condyle (37.879%), disc (41.791%), and lateral pterygoid muscle (39.344%). Conversely, 3D DESS had the highest proportion of Partly Diagnostic IQ, indicating lower overall image quality. This contrasts with Kopp et al.'s study, which compared 0.55 T and 1.5 T MRI systems and found superior IQ for disc and osseous joint morphology at 1.5 T, and Manoliu et al.'s (2015) study, which recommended 3.0 T imaging over 1.5 T for TMJ evaluation due to increased SNR and enhanced visibility of anatomical structures. [19,26] Our inclusion of 3 T MRI imaging aligns with this recommendation. According to a study by Meera et al., the clinical pain score and the FLAIR MR signal intensity ratios are significantly correlated. [27] Our study demonstrates that while PD-FSE is most efficient for quantitative analysis due to its highest SIR values, MEDIC exhibits superior image quality for detecting bone marrow edema and joint fluid, crucial for identifying early degenerative changes in TMDs. 3D DESS, although showing the least sensitivity to pathological changes, may provide valuable additional structural information. The fair to good interobserver agreement across all sequences underscores the reliability of our findings. Based on these results, we recommend incorporating the MEDIC sequence alongside PD-FSE in standard MRI protocols for a more comprehensive and precise diagnosis of TMDs, ultimately improving patient management and clinical outcomes. Limitations Our study's relatively small sample size and single-center design may limit the generalizability of the findings. The qualitative nature of some assessments introduces potential subjectivity. The exclusion of asymptomatic individuals restricts our ability to detect subclinical TMD. Additionally, incorporating MEDIC into routine protocols may increase imaging costs. Future Perspectives Future research should address these limitations through multicenter studies, longitudinal assessments, and the integration of artificial intelligence to enhance objectivity and diagnostic precision. CONCLUSION Combining MEDIC with conventional PD-FSE MRI enhances diagnostic accuracy in evaluating TMDs by improving visualization of joint effusions and bone marrow changes. This integrated approach allows earlier detection of structural abnormalities, supports better clinical decisions, and may lead to improved outcomes. Further research is needed to validate its role in refining diagnostic protocols for TMD management. Declarations FINANCIAL SUPPORT Nil CONFLICT OF INTEREST There is no conflict of interest DATA AVAILABILITY STATEMENT: The data that support the findings of this study are available on request from the author Dr. Elakya Ramesh ( [email protected] ). ETHICAL CONSENT AND INSTITUTIONAL REVIEW BOARD STATEMENT Ethical approval for this study was obtained from the institutional ethics committee. (IRB approval number - SRMDC/IRB/2022/MDS/NO. 901. Author Contribution Elakya Ramesh: Conceptualization, methodology, data analysis, manuscript writing, and project administration.Anuradha Ganesan: Data collection, investigation, and critical revision of the manuscript.Jeevitha Gauthaman: Statistical analysis, visualization, and interpretation of results.Krithika Chandrasekar Lakshmi: Supervision, funding acquisition, and final approval of the manuscript.Saravanan Kannan: reviewed the manuscript. References Bender ME, Lipin RB, Goudy SL. Development of the Pediatric Temporomandibular Joint. Oral Maxillofac Surg Clin North Am. 2018 Feb;30(1):1-9. Bravetti P, Membre H, El Haddioui A, Gérard H, Fyard JP, Mahler P, Gaudy JF. Histological study of the human temporo-mandibular joint and its surrounding muscles. Surg Radiol Anat. 2004 Oct;26(5):371-8. Zarb GA, Carlsson GE. Temporomandibular disorders: osteoarthritis. J Orofac Pain. 1999;13:295–306. Tanaka E, Detamore MS, Mercuri LG. 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Aksoy S, Orhan K. Comparison of T2 Weighted, Fat‐Suppressed T2 Weighted, and Three‐Dimensional (3D) Fast Imaging Employing Steady‐State Acquisition (FIESTA‐C) Sequences in the Temporomandibular Joint (TMJ) Evaluation. BioMed Research International. 2021;2021(1):6032559. Sivakumar A, Ganesan A, Lakshmi KC, Aniyan Y, Kannan S. Evaluation of the Articular Disc Using the Magnetic Resonance Cartigram in Asymptomatic and Symptomatic Temporomandibular Disorders. Indian Journal of Radiology and Imaging. 2025 Jan;35(01):050-8. Manoliu A, Spinner G, Wyss M, Erni S, Ettlin DA, Nanz D, Ulbrich EJ, Gallo LM, Andreisek G. Quantitative and qualitative comparison of MR imaging of the temporomandibular joint at 1.5 and 3.0 T using an optimized high-resolution protocol. Dentomaxillofacial Radiology. 2016 Jan 1;45(1):20150240. Meera R, Kannan A, Krithika C L, Aniyan K Y. Correlation between clinical pain in temporomandibular disorders and signal intensity of the retrodiscal tissue using fluid attenuation inversion recovery MRI: a cross sectional study. Matrix. 2022;8(01):20–25. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 29 Sep, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Accepted 11 Jul, 2025 Reviews received at journal 10 Jul, 2025 Reviews received at journal 10 Jul, 2025 Reviewers agreed at journal 06 Jul, 2025 Reviewers agreed at journal 04 Jun, 2025 Reviewers agreed at journal 04 Jun, 2025 Reviews received at journal 17 May, 2025 Reviewers agreed at journal 17 May, 2025 Reviewers invited by journal 14 May, 2025 Editor assigned by journal 14 May, 2025 Editor invited by journal 13 May, 2025 Submission checks completed at journal 13 May, 2025 First submitted to journal 27 Apr, 2025 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-6541464","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":458003207,"identity":"70e1c10b-1edc-41bc-a3ad-6184cc07ad42","order_by":0,"name":"ELAKYA RAMESH","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIie2OMQrCQBBFJwSsAmlXQu4wkMJGzFWyCLG1tAwIayOWouAhcoQvW9gEPUAaQbAOpBV0IZ3IRjuLfTDDL/6DT+Rw/CU+9IPHJngFdb8LFgYSwTzvyvhOCRIEje4yqL9PYQSG4Es62upl29A4LuGrq00ZbrIMzLU81FIJUJ6U8FZsU7giIOM6E5FUZpiWRlHCpqSVVwB8To2ybEDPfoUDn44Fw9tFsjDD0K+IakCaeCqNokTF02Sve5RwHbYtPSZm2OzWLBaTeHNa3a3K+05z/g99h8PhcHzmBap7T111KqNRAAAAAElFTkSuQmCC","orcid":"","institution":"SRM DENTAL COLLEGE, RAMAPURAM, CHENNAI , TAMIL NADU","correspondingAuthor":true,"prefix":"","firstName":"ELAKYA","middleName":"","lastName":"RAMESH","suffix":""},{"id":458003212,"identity":"e42eb836-14e3-4f89-9014-ddd5e36f2abc","order_by":1,"name":"ANURADHA GANESAN","email":"","orcid":"","institution":"SRM DENTAL COLLEGE, RAMAPURAM, CHENNAI , TAMIL NADU","correspondingAuthor":false,"prefix":"","firstName":"ANURADHA","middleName":"","lastName":"GANESAN","suffix":""},{"id":458003213,"identity":"4f22e37f-6f12-4417-abb3-6a94c196a001","order_by":2,"name":"JEEVITHA GAUTHAMAN","email":"","orcid":"","institution":"SRM DENTAL COLLEGE, RAMAPURAM, CHENNAI , TAMIL NADU","correspondingAuthor":false,"prefix":"","firstName":"JEEVITHA","middleName":"","lastName":"GAUTHAMAN","suffix":""},{"id":458003214,"identity":"45d67632-5a90-4cee-ba14-abc44f708c50","order_by":3,"name":"KRITHIKA CHANDRASEKAR LAKSHMI","email":"","orcid":"","institution":"SRM DENTAL COLLEGE, RAMAPURAM, CHENNAI , TAMIL NADU","correspondingAuthor":false,"prefix":"","firstName":"KRITHIKA","middleName":"CHANDRASEKAR","lastName":"LAKSHMI","suffix":""},{"id":458003215,"identity":"d6e6eea6-d512-4e7a-ac44-3ab305ccae00","order_by":4,"name":"SARAVANAN KANNAN","email":"","orcid":"","institution":"DEPARTMENT OF RADIOLOGY IN SARAVANA IMAGING AND RESEARCH CENTRE, NANDANAM, CHENNAI, TAMIL NADU","correspondingAuthor":false,"prefix":"","firstName":"SARAVANAN","middleName":"","lastName":"KANNAN","suffix":""}],"badges":[],"createdAt":"2025-04-27 15:53:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6541464/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6541464/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-025-11650-2","type":"published","date":"2025-09-29T15:57:25+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":83109250,"identity":"1173a470-73c8-4809-8109-9abb4bcbce16","added_by":"auto","created_at":"2025-05-20 06:54:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":388548,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA) PD-FSE Oblique sagittal-Open mouth B) MEDIC Oblique sagittal -Open mouth C) 3D DESS Oblique sagittal-Open mouth\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-6541464/v1/c7ad6225d20e6ea239e95e14.png"},{"id":83109251,"identity":"36439ed2-028b-47cd-9084-0a48aa1444cb","added_by":"auto","created_at":"2025-05-20 06:54:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":266615,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eA) PD-FSE Oblique sagittal- closed mouth B) MEDIC Oblique sagittal -closed mouth C) 3D DESS Oblique sagittal-closed mouth\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-6541464/v1/b1b46345b3a33178fbad16c8.png"},{"id":83108234,"identity":"a8869222-de4c-4352-8676-e66602f421ce","added_by":"auto","created_at":"2025-05-20 06:46:55","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":363861,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSelection of ROIs in three different MRI sequences. MCBM: mandibular condyle bone marrow; AB: anterior band of disc; LP: Lateral pterygoid muscle. A) PD-FSE Oblique sagittal- closed mouth B) MEDIC Oblique sagittal -closed mouth C) 3D DESS Oblique sagittal-closed mouth\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-6541464/v1/e0593e80154e4be9cc1dadef.png"},{"id":83108236,"identity":"b690c0d9-622b-4395-82c8-1cbc7b551bcd","added_by":"auto","created_at":"2025-05-20 06:46:55","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":70730,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of SIR values in the ROI (MCBM, AB and LP) Among Different MRI Sequences (PD-FSE, MEDIC, and 3D DESS) Using a Raincloud Plot.\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6541464/v1/681677d6dea6717855d787b0.jpeg"},{"id":83108239,"identity":"0827af55-6fb1-480b-8828-5c4ed3b6d032","added_by":"auto","created_at":"2025-05-20 06:46:55","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":56718,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of Image Quality (IQ) Across Different MRI Sequences (PD-FSE, MEDIC, and DESS) for Condyle, Disc, and Lateral Pterygoid Muscle\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6541464/v1/e663d98bd28a92e67527866d.jpg"},{"id":92883744,"identity":"80a90677-9b2d-48c0-bfc6-74c9fc34c886","added_by":"auto","created_at":"2025-10-06 16:08:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3362293,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6541464/v1/b4a12670-11c1-4b1b-bc91-16e124cd1f03.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eComparison of Medic and 3d Dess with Routine MRI to Assess the Diagnostic Efficacy in Symptomatic Temporomandibular Disorders – A Cross Sectional Observational Study\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eThe temporomandibular joint (TMJ) exists as a connection that binds the lower jaw and the temporal bone in the craniofacial complex to permit essential jaw functions. \u003csup\u003e[1]\u003c/sup\u003e Proprioception of the joint is influenced by multiple factors, such as the capsule, the muscles of mastication, receptors of skin and periodontal ligaments.\u003csup\u003e[2]\u003c/sup\u003e A class of degenerative musculoskeletal diseases known as temporomandibular joint disorders is distinguished by morphological and functional complications.\u003csup\u003e[3]\u003c/sup\u003e It encompasses dysfunction of the related muscles and anomalies of the intra-articular discal location and/or structure.\u003csup\u003e[4]\u003c/sup\u003e There are several different causes that contribute to the etiology of TMD, including both physical and psychological ones.\u003csup\u003e[5]\u003c/sup\u003e It primarily affects individuals aged 20\u0026ndash;40, making it a significant concern for young adults. Early diagnosis is vital to prevent chronic pain, joint damage, and functional issues. Prolonged TMD may hinder educational, social, and occupational development. The DC/TMD is the preferred and reliable tool for diagnosing and classifying TMD.\u003csup\u003e[6]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eVarious imaging methods\u0026mdash;CT, CBCT, MRI, ultrasonography, and traditional radiography\u0026mdash;are used to assess the temporomandibular joint (TMJ). MRI is the most effective non-invasive tool for visualizing TMJ soft tissues. Early diagnosis of TMD includes monitoring symptoms and joint effusion.\u003csup\u003e[7]\u003c/sup\u003e The MRI reveals early signs of TMJ dysfunction by showing disc deformity together with joint effusion and retro discal tissue deformity and anterior or posterior band thickening.\u003csup\u003e[8]\u003c/sup\u003e Proton-density (PD), T1-weighted, and T2-weighted images are most commonly used scanning sequences.\u003csup\u003e[9]\u003c/sup\u003e However, MRI has limitations, including high costs and the need for specialized facilities. It is contraindicated in patients with claustrophobia, pacemakers, metallic heart valves, ferromagnetic foreign bodies, and during pregnancy.\u003csup\u003e[10]\u003c/sup\u003e The Proton Density Fast Spin Echo (PD FSE) MRI sequence is preferred in musculoskeletal imaging for its sharp soft tissue contrast, especially of the condyle and surrounding muscles. It offers high SIR and excellent resolution for evaluating cartilage, ligaments, tendons, and bones, aiding accurate diagnosis.\u003csup\u003e[11]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe Siemens 2D spoiled gradient echo multi-echo sequence MEDIC (\"Multi-Echo Data Image Combination\") incorporates a magnetization transfer saturation pulse, enhancing the visualization of structures such as the condyle and surrounding muscles.\u003csup\u003e[12]\u003c/sup\u003e MEDIC\u0026rsquo;s high spatial resolution enables detailed assessment of the bony architecture of the condyle, clearly delineating it from adjacent soft tissues.\u003csup\u003e[13]\u003c/sup\u003e The Siemens 3D DESS sequence offers improved contrast resolution between fluid and cartilage in the synovial joint.\u003csup\u003e[14]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eWith this gap in literature, this study assessed the diagnostic accuracy and clinical relevance ofthese advanced sequences in symptomatic patients. And compared the effectiveness of MEDIC and 3D DESS sequences with routine MRI in detecting early degenerative changes, disc displacements, joint effusion, and other structural abnormalities in symptomatic temporomandibular disorders (TMDs).\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003e This cross-sectional observational study was conducted at the Department of Oral Medicine and Radiology, SRM Dental College, Chennai, from April 2023 to December 2024. Ethical approval was obtained (SRMDC/IRB/2022/MDS/NO. 901), and the study adhered to the Declaration of Helsinki. Participants were recruited voluntarily based on inclusion criteria. The study was registered with the Clinical Trial Registry of India (CTRI/2025/03/082074).\u003c/p\u003e \u003cp\u003eSimple random sampling was used to select participants. Using G*Power (v3.0), the required sample size was estimated at 108 TMJs, divided equally into three groups (36 each): Group A (PD-FSE), Group B (MEDIC), and Group C (3D-DESS). All MRI scans were obtained from patients at the Oral Medicine and Radiology outpatient department, SRM Dental College, Chennai.\u003c/p\u003e \u003cp\u003e Participants aged 18\u0026ndash;40 years of both genders, diagnosed with TMD based on RDC criteria (arthralgia: ICD-9 524.62; ICD-10 M26.62), and presenting with relevant symptoms such as joint pain, clicking, jaw deviation, limited opening, and preauricular pain were included upon informed consent. Individuals who were pregnant or lactating, had contraindications to MRI (such as pacemakers, metal implants, or claustrophobia), presented with physical or mental disabilities, weighed over 150 kg, or had a history of TMD, arthritis, trauma, or significant TMJ swelling and pain requiring treatment were excluded from the study\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eA comprehensive case history and clinical assessment were conducted for all participants, and data were documented in a proforma. Participants underwent routine MRI with MEDIC and 3D DESS sequences in a supine position using a 3 Tesla Siemens scanner. Imaging was performed with a 32-channel head and neck coil, with scan parameters provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The field of view was set at 5cm x 5cm. MRI images of the bilateral TMJs were acquired in axial, coronal, and sagittal planes, with adjustments made for the open \u0026amp; closed mouth position. Images were evaluated by an experienced medical radiologist and two oral radiologists. Three MRI sequences (PD-FSE, MEDIC, and 3D DESS) were combined with two oblique sagittal positions (closed and open mouth) for analysis, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cb\u003eand\u003c/b\u003e Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\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\u003eAcquisition parameters of the applied MRI sequences\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImaging Technique\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePD-FSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMEDIC\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3D DESS\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTR (ms)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3400\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTE (ms)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFOV (mm \u0026times; mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150 \u0026times; 150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e150 \u0026times; 150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e130 \u0026times; 130\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSlice Thickness (mm)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFlip Angle (\u0026deg;)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBandwidth (Hz/Px)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e181\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e250\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eThe qualitative assessment of MRI:\u003c/h2\u003e \u003cp\u003eWe qualitatively assessed articular disc morphology, including configuration (biplanar, biconcave, biconvex, hemiconvex, thickened posterior band), disc position, joint fluid, and bone marrow characteristics. Disc displacement was classified according to Tasaki et al.\u003csup\u003e[15]\u003c/sup\u003e and Murakami et al.\u003csup\u003e[16]\u003c/sup\u003e, while joint effusion was evaluated based on Larheim et al.'s criteria- four categories of fluid accumulation observed, ranging from minimal to significant.\u003csup\u003e[17]\u003c/sup\u003e Bone marrow abnormalities, including edema and osteonecrosis, were classified using Larheim et al. 's guidelines- based on the presence of edema or osteonecrosis.\u003csup\u003e[18]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe quantitative assessment of MRI:\u003c/h3\u003e\n\u003cp\u003eSignal intensity ratio (SIR) changes were evaluated to assess the relationship between tissue signal alterations and clinical outcomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Image quality (IQ) was rated on a 4-point Likert scale, with two radiologists independently scoring each sequence: 1\u0026thinsp;=\u0026thinsp;inadequate, 2\u0026thinsp;=\u0026thinsp;suboptimal, 3\u0026thinsp;=\u0026thinsp;sufficient, and 4\u0026thinsp;=\u0026thinsp;optimal as described by Markus Kopp et al., The assessment focused on disc morphology, disc position, and osseous joint morphology as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003csup\u003e[19]\u003c/sup\u003e\u003c/p\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSTATISTICAL ANALYSIS:\u003c/h2\u003e \u003cp\u003eStatistical analysis was performed using SPSS (Version 26.0) and JASP software. Non-parametric methods were used, with descriptive statistics expressed as median and interquartile range (IQR). The Kruskal-Wallis test compared signal intensity ratios across MRI sequences for MCBM, AB, and LP, followed by Dunn post hoc tests for pairwise comparisons. The Chi-square test assessed categorical variables and image quality, while Fleiss' Kappa evaluated interobserver reliability. The significance level was set at α\u0026thinsp;=\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThis study assessed the effectiveness of different MRI sequences in evaluating TMJ structures, focusing on disc position, morphology, joint fluid, bone marrow, condyle, lateral pterygoid muscle and associated pathological changes. It also provide insights into the variations in image quality, diagnostic accuracy, and structural differences observed across MRI sequences.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Frequency distribution characteristics with grouping based on MRI based diagnosis.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"105%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups based on MRI Diagnosis (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDWR (15)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDWOR (7)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal (14)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (mean \u0026plusmn; SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.26 \u0026plusmn; 8.762\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.71 \u0026plusmn; 7.181\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e27.57 \u0026plusmn; 6.37\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGender\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 (13.33)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (35.71)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e13 (86.66)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9 (64.28)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisc configuration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHemiconvex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e10 (66.66)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (71.42)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eThickening of the posterior band\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 (28.57)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiconcave\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBiplanar\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e5 (33.33)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisc position- Closed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAnterior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuperior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisc position- Open\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdd with reduction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdd without reduction\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSuperior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14 (100)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups based on MRI Diagnosis (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD - FSE (36)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEDIC (36)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3D DESS (36)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint fluid\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(Nil)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17 (47.22)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14 (38.88)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24 (66.66)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint fluid\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(Minimum)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11 (30.55)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16 (44.44)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11 (30.55)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint fluid\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;(Moderate)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8 (22.22)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6 (16.66)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1 (2.77)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBone marrow (Normal)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e29 (80.55)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17 (47.22)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e34 (94.44)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 42px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBone marrow (Edema)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7 (19.44)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 19px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e19 (52.77)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2 (5.55)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMost TMD patients were female, with anterior disc displacement common in DWR and DWOR groups, while normals showed superior disc position and biconcave shape. Hemiconvex disc configuration was frequent in DWR and DWOR groups, whereas normals had no such deformities. PD-FSE showed the highest sensitivity for detecting joint fluid than MEDIC but more than 3D DESS. MEDIC showed the highest sensitivity for detecting bone marrow edema, unlike 3D DESS, which showed mostly normal marrow. Combining MEDIC with PD-FSE may offer improved diagnostic accuracy for detecting early joint fluid and marrow abnormalities as shown in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Inter-Observer Reliability for Image Quality Observation, Joint Fluid, Bone Marrow Quality, and Disc Assessment. (Fliess Kappa is used for interrater reliability assessment)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"564\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParameter\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFliess kappa\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 129px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLower\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUpper\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 564px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eFor image quality observation (Ordinal Likert scale scoring)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCondyle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD - FSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.928\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.778\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.079\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEDIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.963\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.817\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.109\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3D DESS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.969\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.829\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.109\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisc\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD - FSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.956\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.767\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.144\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEDIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.95\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.801\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.098\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDESS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.821\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.103\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLateral Pterygoid Muscle\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD - FSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.97\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.833\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.107\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEDIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.864\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.136\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3D DESS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.941\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.802\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.08\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 564px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint fluid and Bone marrow quality (Nominal scale)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJoint fluid\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD - FSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.864\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.136\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEDIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.962\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.821\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.103\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3D DESS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.97\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.833\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.107\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"3\" valign=\"top\" style=\"width: 200px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBone marrow quality\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD - FSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.864\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.136\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEDIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.97\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.833\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.107\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 134px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e3D DESS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.963\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.817\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.109\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 334px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisc configuration\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.811\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.189\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 334px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisc position- Closed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.878\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.122\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 334px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisc position- Open\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 100px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.878\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1.122\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe inter-rater reliability, assessed using Fleiss\u0026apos; kappa which indicates strong observer consistency in evaluating TMJ anatomy and image quality across modalities. as shown in table 3.\u003c/p\u003e\n\u003cp\u003eRaincloud plots show that PD-FSE consistently yields higher and more variable signal intensities across MCBM, AB, and LP, indicating greater sensitivity or contrast. In contrast, MEDIC and 3D DESS display lower, more uniform signal intensities, suggesting more consistent but less intense imaging. Overall, PD-FSE offers stronger signals, while MEDIC and DESS provide steadier image profiles as shown in \u003cstrong\u003eFigure 4.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIntergroup comparisons show PD-FSE has significantly higher signal intensities than MEDIC and 3D DESS (p \u0026lt; .001), indicating superior contrast. For MCBM, MEDIC and DESS show no significant difference (p = 0.739), while AB and LP show significant differences across all sequences (p \u0026lt; 0.05).\u003cbr\u003e\u0026nbsp;Overall, PD-FSE outperforms in signal strength; MEDIC and DESS vary by structure.\u003c/p\u003e\n\u003cp\u003eMEDIC showed the highest rates of optimal image quality (IQ) in the condyle, disc, and LP muscle, with minimal partly diagnostic ratings. PD-FSE offered a balanced distribution of image quality across regions. 3D DESS had more partly diagnostic images, especially in the condyle and LP muscle, but still achieved notable optimal IQ levels as shown in \u003cstrong\u003eFigure 5.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Comparison of Joint Fluid and Bone marrow quality observation Using Different MRI Sequences (PD-FSE, MEDIC, and DESS) *Chi-square test is used for significance testing of association between the groups. P value of \u0026le;0.05 is considered to be significant.\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eJOINT FLUID\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNil\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMinimum\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eModerate\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD - FSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCount\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e8\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e9.389\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.052*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% within column\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e30.9\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.94\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e53.33\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEDIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCount\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e14\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e16\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% within column\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.45\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e42.105\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e40\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDESS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCount\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e24\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e11\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% within column\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e43.63\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28.947\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e6.66\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCount\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e55\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e38\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e15\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% within column\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" rowspan=\"2\" valign=\"top\" style=\"width: 34px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eGroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 39px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBONE MARROW QUALITY\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eValue\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cstrong\u003edf\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNormal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEDEMA\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePD - FSE\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCount\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e29\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e07\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 10px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e22.082\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 5px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 9px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026nbsp;.001*\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% within column\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e36.25\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e25.00\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMEDIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCount\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e17\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e19\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% within column\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e21.25\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e67.85\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDESS\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCount\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e34\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% within column\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e42.5\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e7.14\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" style=\"width: 13px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCount\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e80\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e28\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e% within column\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 18px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 20px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e100\u0026thinsp;%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 95px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 148px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 84px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 49px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 99px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 75px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 38px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd style=\"width: 71px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eThe sensitivity of MRI sequences for joint fluid and bone marrow abnormalities varies. PD-FSE showed the highest sensitivity for detecting \u0026quot;Moderate\u0026quot; joint fluid (53.33%), while MEDIC had a balanced distribution, with more \u0026quot;Minimum\u0026quot; detections (42.11%). DESS had the most \u0026quot;Nil\u0026quot; detections (43.63%). For bone marrow, MEDIC was most sensitive to edema (67.85%), outperforming PD-FSE (25%) and DESS (7.14%). The significant difference in bone marrow detection (p \u0026lt; 0.001) highlights MEDIC\u0026apos;s superior performance, while joint fluid detection showed no significant difference (p = 0.052) as shown in Table 4.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eA collection of complex, multifactorial conditions that affect the temporomandibular joint (TMJ) and its associated structures are collectively referred to as \"temporomandibular joint disorders\" (TMJ disorders).\u003csup\u003e[3]\u003c/sup\u003e The progression or worsening of these signs and symptoms can ultimately restrict or even prevent individuals from carrying out their normal physiological activities.\u003csup\u003e[20]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe primary approach to diagnosing TMD involves a clinical examination, often supplemented by radiographic imaging. A common non-invasive and non-ionizing imaging technique for evaluating TMJ-related problems, the ideal method for diagnosing temporomandibular disorders (TMDs) involving soft tissues is magnetic resonance imaging (MRI).\u003csup\u003e[21]\u003c/sup\u003e To improve detection and clinical decision-making, our study used a variety of MRI sequences to assess early diagnostic alterations in TMD.\u003csup\u003e[22]\u003c/sup\u003e Moreover, MRI does not expose patients to ionizing radiation or other biological hazards. Additional benefits include its high sensitivity, specificity, and diagnostic accuracy.\u003csup\u003e[23]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThis study investigates the diagnostic performance of three distinct Magnetic Resonance Imaging (MRI) sequences \u0026ndash; Proton Density Fast Spin Echo (PD-FSE), Multiple Echo Data Image Combination (MEDIC), and three-dimensional Dual Echo Steady State (3D DESS) \u0026ndash; in the assessment of symptomatic temporomandibular disorders (TMDs). Our research on 108 temporomandibular joints from symptomatic TMD patients provides a comprehensive dataset for analysis, contrasting with a prior study by Aksoy et al. that evaluated 60 joints using advanced MRI sequences.\u003csup\u003e[24]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThe demographic profile of our study population revealed a mean age of 28.26\u0026thinsp;\u0026plusmn;\u0026thinsp;8.762 years for the Disc Displacement with Reduction (DWR) group, 27.71\u0026thinsp;\u0026plusmn;\u0026thinsp;7.181 years for the Disc Displacement Without Reduction (DWOR) group, and 27.57\u0026thinsp;\u0026plusmn;\u0026thinsp;6.37 years for the Normal group. This younger age range, focusing on patients under 40, suggests that TMDs in our study are not strongly age-dependent, aligning with our research's specific focus. Notably, we observed a significant female predominance in both the DWR (86.66%) and DWOR (100%) groups, while the Normal group exhibited a higher proportion of males (35.71%), hinting at a potential gender-related susceptibility to TMDs. This contrasts with the study by Aksoy et al., which reported a mean age of 38.1 years for females and 32.4 years for males in their TMD patient population.\u003csup\u003e[24]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn assessing disc morphology, our findings indicated that the hemiconvex disc shape was most prevalent in the DWR (66.66%) and DWOR (71.42%) groups. Conversely, the Normal group exclusively presented with a biconcave disc shape (100%), highlighting structural disparities between healthy and dysfunctional joints. This contrasts with the findings of Sivakumar et al., who, in their analysis of 52 TMJs, identified biconcave as the most common disc shape (52 TMJs), followed by biplanar, hemiconvex, and folded configurations, suggesting a broader spectrum of morphological variations in their study. Regarding disc position, our study corroborated the observations of Sivakumar et al., noting anterior disc displacement in the closed-mouth state for both DWR and DWOR cases, while the Normal group exhibited a superior disc position.\u003csup\u003e[25]\u003c/sup\u003e This aligns with Murakami et al.'s study, which suggested that normal discs are predominantly biconcave, and displaced discs often undergo deformation post-displacement, with biconcave discs being prone to folding under condylar pressure due to their thin central portion.\u003csup\u003e[16]\u003c/sup\u003e The hemiconvex shape observed in our study in the dysfunctional groups may represent an intermediate stage of disc deformation resulting from mechanical stress and degeneration, potentially exacerbated by parafunctional habits like bruxism and clenching, leading to disc thickening and alterations.\u003c/p\u003e \u003cp\u003eOur study also compared the efficacy of PD-FSE, MEDIC, and 3D DESS sequences in detecting joint fluid and bone marrow changes, contrasting with Aksoy et al.'s comparison of Fat-Suppressed T2-weighted (FS T2W), Fast Spin Echo T2 (FSE T2), and 3D Fast Imaging Employing Steady-State Acquisition (FIESTA-C) sequences. We found that PD-FSE demonstrated the highest detection rate for moderate joint fluid (53.333%), while 3D DESS exhibited the highest \u0026ldquo;Nil joint fluid\u0026rdquo; detection (43.636%), indicating lower sensitivity to fluid. MEDIC showed a balanced distribution, with the highest detection in the minimum fluid category (42.105%). In contrast, Aksoy et al. reported that 3D FIESTA-C and FS T2W were significantly more effective in detecting joint fluid compared to FSE T2W.\u003csup\u003e[24]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eRegarding bone marrow changes, our study revealed that MEDIC was the most effective sequence, detecting bone marrow edema in 67.857% of cases, signifying its superior sensitivity to pathological alterations. Conversely, 3D DESS showed the highest proportion of normal bone marrow (42.5%) and the lowest edema detection (7.143%), suggesting reduced effectiveness in identifying bone marrow abnormalities. PD-FSE presented a balanced detection, identifying normal bone marrow in 36.25% and edema in 25% of cases. This contrasts with Aksoy et al.'s finding that 3D FIESTA-C and FS T2W had the highest sensitivity for detecting bone marrow changes. The superior performance of MEDIC in detecting bone marrow edema aligns with earlier studies highlighting its high signal-to-noise ratio (SNR), multi-echo acquisition, and improved contrast resolution, facilitating better fat-water separation and enhanced visualization of edema as increased signal intensity on T2-weighted images.\u003c/p\u003e \u003cp\u003e Interobserver reliability, assessed using the Fleiss kappa statistic, demonstrated fair to good agreement (κ\u0026thinsp;\u0026ge;\u0026thinsp;0.61) among the three radiologists for all sequences and parameters evaluated in our study.\u003c/p\u003e \u003cp\u003e Notably, PD-FSE showed perfect agreement (κ\u0026thinsp;=\u0026thinsp;1.000) for joint fluid and bone marrow assessments, while disc configuration and position evaluations also had perfect agreement (κ\u0026thinsp;=\u0026thinsp;1.000) across all sequences. Image quality assessments were highly consistent, with κ values ranging from 0.928 to 0.969. This contrasts with Aksoy et al.'s study, which found that 3D FIESTA-C and FS T2W sequences exhibited the highest interobserver agreement for detecting joint fluid and bone marrow changes, while FSE T2W showed lower agreement in these aspects but the greatest agreement for identifying anterior disc displacement without reduction.\u003c/p\u003e \u003cp\u003eQuantitatively, our analysis of signal intensity ratios (SIR) in the mandibular condyle bone marrow (MCBM), anterior band of disc (AB), and lateral pterygoid muscle (LP) revealed that PD-FSE yielded the highest mean values, with significant differences observed across PD-FSE, MEDIC, and 3D DESS. This contrasts with Aksoy et al.'s study, which found that the SIRs of FS-T2 and 3D FIESTA-C were substantially better than those of FSE-T2, with no discernible difference between FS-T2 and 3D FIESTA-C. \u003csup\u003e[24]\u003c/sup\u003e Our findings suggest that PD-FSE's superior feature separation and noise reduction capabilities contribute to higher SIR values in the assessed TMJ structures compared to MEDIC and 3D DESS. While MEDIC excels in reducing metal artifacts and enhancing soft tissue contrast, it may experience signal averaging that reduces fine structural details. DESS, known for high-resolution cartilage imaging, may exhibit lower SIR in mixed tissue regions due to partial volume effects.\u003c/p\u003e \u003cp\u003eOur study, being the first to compare the image quality of MEDIC with PD-FSE and 3D DESS sequences using a 4-point Likert scale based on comprehensive reporting from three radiologists, found that MEDIC achieved the highest proportion of Optimal Image Quality (IQ) for the condyle (37.879%), disc (41.791%), and lateral pterygoid muscle (39.344%). Conversely, 3D DESS had the highest proportion of Partly Diagnostic IQ, indicating lower overall image quality. This contrasts with Kopp et al.'s study, which compared 0.55 T and 1.5 T MRI systems and found superior IQ for disc and osseous joint morphology at 1.5 T, and Manoliu et al.'s (2015) study, which recommended 3.0 T imaging over 1.5 T for TMJ evaluation due to increased SNR and enhanced visibility of anatomical structures.\u003csup\u003e[19,26]\u003c/sup\u003e Our inclusion of 3 T MRI imaging aligns with this recommendation. According to a study by Meera et al., the clinical pain score and the FLAIR MR signal intensity ratios are significantly correlated.\u003csup\u003e[27]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eOur study demonstrates that while PD-FSE is most efficient for quantitative analysis due to its highest SIR values, MEDIC exhibits superior image quality for detecting bone marrow edema and joint fluid, crucial for identifying early degenerative changes in TMDs. 3D DESS, although showing the least sensitivity to pathological changes, may provide valuable additional structural information. The fair to good interobserver agreement across all sequences underscores the reliability of our findings. Based on these results, we recommend incorporating the MEDIC sequence alongside PD-FSE in standard MRI protocols for a more comprehensive and precise diagnosis of TMDs, ultimately improving patient management and clinical outcomes.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eLimitations\u003c/strong\u003e \u003cp\u003eOur study's relatively small sample size and single-center design may limit the generalizability of the findings. The qualitative nature of some assessments introduces potential subjectivity. The exclusion of asymptomatic individuals restricts our ability to detect subclinical TMD. Additionally, incorporating MEDIC into routine protocols may increase imaging costs.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eFuture Perspectives\u003c/strong\u003e \u003cp\u003eFuture research should address these limitations through multicenter studies, longitudinal assessments, and the integration of artificial intelligence to enhance objectivity and diagnostic precision.\u003c/p\u003e \u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eCombining MEDIC with conventional PD-FSE MRI enhances diagnostic accuracy in evaluating TMDs by improving visualization of joint effusions and bone marrow changes. This integrated approach allows earlier detection of structural abnormalities, supports better clinical decisions, and may lead to improved outcomes. Further research is needed to validate its role in refining diagnostic protocols for TMD management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFINANCIAL SUPPORT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNil\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCONFLICT OF INTEREST\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no conflict of interest\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDATA AVAILABILITY STATEMENT:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available on request from the author\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eDr. Elakya Ramesh ([email protected]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eETHICAL CONSENT AND INSTITUTIONAL REVIEW BOARD STATEMENT\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for this study was obtained from the institutional ethics committee. (IRB approval number - SRMDC/IRB/2022/MDS/NO. 901.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eElakya Ramesh: Conceptualization, methodology, data analysis, manuscript writing, and project administration.Anuradha Ganesan: Data collection, investigation, and critical revision of the manuscript.Jeevitha Gauthaman: Statistical analysis, visualization, and interpretation of results.Krithika Chandrasekar Lakshmi: Supervision, funding acquisition, and final approval of the manuscript.Saravanan Kannan: reviewed the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eBender ME, Lipin RB, Goudy SL. Development of the Pediatric Temporomandibular Joint. Oral Maxillofac Surg Clin North Am. 2018 Feb;30(1):1-9.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eBravetti P, Membre H, El Haddioui A, G\u0026eacute;rard H, Fyard JP, Mahler P, Gaudy JF. Histological study of the human temporo-mandibular joint and its surrounding muscles. Surg Radiol Anat.\u0026nbsp;2004 Oct;26(5):371-8.\u003c/li\u003e\n \u003cli\u003e\u0026nbsp;Zarb GA, Carlsson GE. Temporomandibular disorders: osteoarthritis. \u003cem\u003eJ Orofac Pain.\u0026nbsp;\u003c/em\u003e1999;13:295\u0026ndash;306.\u003c/li\u003e\n \u003cli\u003eTanaka E, Detamore MS, Mercuri LG. Degenerative disorders of the temporomandibular joint: etiology, diagnosis, and treatment. \u003cem\u003eJ Dent Res.\u0026nbsp;\u003c/em\u003e2008;87:296\u0026ndash;307.\u003c/li\u003e\n \u003cli\u003eRollman G.B., Gillespie J.M. The role of psychosocial factors in temporomandibular disorders. \u003cem\u003eCurr. Rev. Pain.\u0026nbsp;\u003c/em\u003e2000;4:71\u0026ndash;81. doi:\u0026nbsp;10.1007/s11916-000-0012-8.\u003c/li\u003e\n \u003cli\u003eTalmaceanu D, Lenghel LM, Bolog N, Hedesiu M, Buduru S, Rotar H, Baciut M, Baciut G. Imaging modalities for temporomandibular joint disorders: an update. Clujul Med. 2018 Jul;91(3):280-287. doi: 10.15386/cjmed-970. Epub 2018 Jul 31. PMID: 30093805; PMCID: PMC6082607.\u003c/li\u003e\n \u003cli\u003eBaba IA, Najmuddin M, Shah AF, Yousuf A. TMJ Imaging: A review. \u003cem\u003eInternational Journal of Contemporary Medical Research.\u0026nbsp;\u003c/em\u003e2016;3(8):2253\u0026ndash;2256.\u003c/li\u003e\n \u003cli\u003eTomas X, Pomes J, Berenguer J, Quinto L, Nicolau C, Mercader JM, et al. MR imaging of temporomandibular joint dysfunction: a pictorial review. \u003cem\u003eRadiographics.\u0026nbsp;\u003c/em\u003e2006;26(3):765\u0026ndash;781.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eSal\u0026eacute; H, Bryndahl F, Isberg A. Temporomandibular joints in asymptomatic and symptomatic nonpatient volunteers: a prospective 15-year follow-up clinical and MR imaging study. \u003cem\u003eRadiology.\u0026nbsp;\u003c/em\u003e2013;267:183\u0026ndash;194.\u003c/li\u003e\n \u003cli\u003eGarcia MD, Machado KF, Mascarenhas MH. Resson\u0026acirc;ncia magn\u0026eacute;tica e tomografia computadorizada da articula\u0026ccedil;\u0026atilde;o temporomandibular: al\u0026eacute;m da disfun\u0026ccedil;\u0026atilde;o. Radiologia Brasileira. 2008;41:337-42.\u003c/li\u003e\n \u003cli\u003ePass B, Robinson P, Hodgson R, Grainger AJ. Can a single isotropic 3D fast spin echo sequence replace three-plane standard proton density fat-saturated knee MRI at 1.5 T?. The British journal of radiology. 2015 Aug 1;88(1052):20150189. \u0026nbsp;\u003c/li\u003e\n \u003cli\u003eFUJINAGA Y., YOSHIOKA H., SAKAI T., SAKAI Y., et al.: Quantitative measurement of femoral condyle cartilage in the knee by MRI: Validation study by multireaders. J. Magn. Reson. Imaging, 39: 972-977, 2014.\u003c/li\u003e\n \u003cli\u003eHeld P, Dorenbeck U, Seitz J, Frund R, Albrich H. MRI of the abnormal cervical spinal cord using 2D spoiled gradient echo multiecho sequence (MEDIC) with magnetization transfer saturation pulse. A T2* weighted feasibility study. J Neuroradiol 2003;30:83-90.\u003c/li\u003e\n \u003cli\u003eWen D, Zhou X, Hou B, Zhang Q, Raithel E, Wang Y, Wu G, Li X. 3D-DESS MRI with CAIPIRINHA two-and fourfold acceleration for quantitatively assessing knee cartilage morphology. Skeletal Radiology. 2024 Aug;53(8):1481-94.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eTasaki MM, Westesson PL, Isberg AM, et al . Classification and prevalence of temporomandibular joint disk displacement in pat ients and symptom-f ree volunteers. Am J OrthodDentofacial Orthop1996; 109:249\u0026ndash;62\u003c/li\u003e\n \u003cli\u003eMurakami S, Takahashi A, Nishiyama H, et al . Magnetic resonance evaluation of the temporomandibular joint disc position and configuration. Dentomaxillofac Radiol 1993;22:205\u0026ndash;07\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eLarheim TA, Westesson PL, Sano T. MR grading of temporomandibular joint fluid: association with disc displacement categories, condyle marrow abnormalities and pain. Int J Oral Maxi l lofac Surg 2001; 30:104\u0026ndash;12\u003c/li\u003e\n \u003cli\u003eLarheim TA, Westesson PL, Hicks DG, et al . Osteonecrosis of the temporomandibular joint : correlat ion of magnetic resonance imaging and histology. J Oral Maxillofac Surg 1999; 57:888 \u0026ndash;98, discussion 899\u003c/li\u003e\n \u003cli\u003eKopp M, Wiesmueller M, Buchbender M, Kesting M, Nagel AM, May MS, Uder M, Roemer FW, Heiss R. MRI of temporomandibular joint disorders: a comparative study of 0.55 T and 1.5 T MRI. Investigative Radiology. 2024 Mar 1;59(3):223-9.\u003c/li\u003e\n \u003cli\u003eLi DTS, Leung YY. Temporomandibular disorders: current con-cepts and controversies in diagnosis and management. Diagnostics.2021;11(3):459. doi:10.3390/diagnostics11030459\u003c/li\u003e\n \u003cli\u003eMenezes MS, Bussadori SK, Fernandes KPS, Biasotto-Gonzalez DA. Correlation between headache and temporomandibular joint dysfunction. Fisioter Pesq. 2008;15: 183\u0026ndash;187.\u003c/li\u003e\n \u003cli\u003eManfredini, D., Bucci, M.B., Nardini, L.G., 2007. The diagnostic process for temporomandibular disorders. Stomatologija 9 (2), 35\u0026ndash;39.\u0026nbsp;\u003c/li\u003e\n \u003cli\u003eMichelle A, Wessely F, Martin Y. Magnetic resonance imaging of the temporomandibular joint. Clin Chiropractic 2008;11:37\u0026ndash;44.\u003c/li\u003e\n \u003cli\u003eAksoy S, Orhan K. Comparison of T2 Weighted, Fat‐Suppressed T2 Weighted, and Three‐Dimensional (3D) Fast Imaging Employing Steady‐State Acquisition (FIESTA‐C) Sequences in the Temporomandibular Joint (TMJ) Evaluation. BioMed Research International. 2021;2021(1):6032559.\u003c/li\u003e\n \u003cli\u003eSivakumar A, Ganesan A, Lakshmi KC, Aniyan Y, Kannan S. Evaluation of the Articular Disc Using the Magnetic Resonance Cartigram in Asymptomatic and Symptomatic Temporomandibular Disorders. Indian Journal of Radiology and Imaging. 2025 Jan;35(01):050-8.\u003c/li\u003e\n \u003cli\u003eManoliu A, Spinner G, Wyss M, Erni S, Ettlin DA, Nanz D, Ulbrich EJ, Gallo LM, Andreisek G. Quantitative and qualitative comparison of MR imaging of the temporomandibular joint at 1.5 and 3.0 T using an optimized high-resolution protocol. Dentomaxillofacial Radiology. 2016 Jan 1;45(1):20150240.\u003c/li\u003e\n \u003cli\u003eMeera R, Kannan A, Krithika C L, Aniyan K Y. Correlation between clinical pain in temporomandibular disorders and signal intensity of the retrodiscal tissue using fluid attenuation inversion recovery MRI: a cross sectional study. Matrix. 2022;8(01):20\u0026ndash;25.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Magnetic resonance imaging, Diagnostic accuracy, Temporomandibular joint, Early Detection, Diagnostic Accuracy, Image quality, Signal intensity ratio","lastPublishedDoi":"10.21203/rs.3.rs-6541464/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6541464/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eTemporomandibular disorders (TMDs) affect the orofacial region, particularly the temporomandibular joint (TMJ). This study evaluated early intra-articular disc changes in symptomatic TMD patients using various MRI sequences, comparing the diagnostic efficacy of MEDIC and 3D DESS with routine MRI.\u003c/p\u003e\u003ch2\u003eMaterials and Methods:\u003c/h2\u003e \u003cp\u003eA total of 108 TMJs from symptomatic patients were assessed. All underwent routine MRI, MEDIC, and 3D DESS sequences. Three radiologists qualitatively and quantitatively evaluated images using Likert\u0026rsquo;s scale. Statistical analysis was performed with SPSS, and inter-observer variability assessed via Fleiss' kappa (κ).\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eMRI revealed 41.7% disc displacement with reduction, 19.4% without reduction, and 38.9% normal. MEDIC provided superior visualization of joint fluid and bone marrow changes, followed by PD-FSE and DESS. Signal intensity ratios were highest in PD-FSE, followed by MEDIC and DESS. Inter-observer reliability showed perfect agreement.\u003c/p\u003e\u003ch2\u003eConclusion:\u003c/h2\u003e \u003cp\u003eWhile PD-FSE offers excellent contrast, it may miss early degenerative changes. Adding MEDIC improves detection of joint effusions and bone marrow abnormalities, enhancing early diagnosis and clinical decision-making for TMDs.\u003c/p\u003e","manuscriptTitle":"Comparison of Medic and 3d Dess with Routine MRI to Assess the Diagnostic Efficacy in Symptomatic Temporomandibular Disorders – A Cross Sectional Observational Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-20 06:46:50","doi":"10.21203/rs.3.rs-6541464/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Accepted","date":"2025-07-11T07:19:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-11T03:20:50+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-10T12:01:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"68702283220824262291589189953935904539","date":"2025-07-06T18:12:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"166359167302280765672828159083326923976","date":"2025-06-04T19:15:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"137619546463241694399024845626022643818","date":"2025-06-04T18:16:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-17T12:48:51+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"244034685796523140596337052223772984971","date":"2025-05-17T12:32:37+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-05-14T19:44:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-14T16:10:34+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-14T03:11:41+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-13T06:26:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-27T15:49:24+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"66f71e85-0eb4-4910-8577-5196994c5fbd","owner":[],"postedDate":"May 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":48702531,"name":"Health sciences/Diseases"},{"id":48702532,"name":"Health sciences/Health care"},{"id":48702533,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2025-10-06T16:01:52+00:00","versionOfRecord":{"articleIdentity":"rs-6541464","link":"https://doi.org/10.1038/s41598-025-11650-2","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-09-29 15:57:25","publishedOnDateReadable":"September 29th, 2025"},"versionCreatedAt":"2025-05-20 06:46:50","video":"","vorDoi":"10.1038/s41598-025-11650-2","vorDoiUrl":"https://doi.org/10.1038/s41598-025-11650-2","workflowStages":[]},"version":"v1","identity":"rs-6541464","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6541464","identity":"rs-6541464","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}