Imaging severity stratification of thoracic disc herniation and its association with neurological dysfunction: a retrospective cohort study

Imaging severity stratification of thoracic disc herniation and its association with neurological dysfunction: a retrospective cohort 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 Research Article Imaging severity stratification of thoracic disc herniation and its association with neurological dysfunction: a retrospective cohort study Kunfeng Song, Daniel Rosenthal, Stephan Dützmann, Alexis Montes Martinez, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8626677/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Purpose To develop a practical imaging severity stratification for thoracic disc herniation (TDH) combining canal occupation ratio and the axial ABC-0/1/2 morphology, and to evaluate associations with neurological dysfunction and postoperative recovery. Methods In a retrospective single-network TDH cohort (1998–2025), canal occupation (%) was measured on axial CT/MRI and axial morphology was classified as ABC-0/1/2. Primary outcomes were preoperative bladder dysfunction and severe myelopathy; secondary outcomes included gait disturbance and recovery. Multivariable logistic regression adjusted for age, sex, calcification, and multilevel disease. Results Of 1129 surgical TDH cases, 536 had complete axial classification and canal measurements. Preoperative gait disturbance occurred in 42.5% and bladder dysfunction in 23.2%. Canal occupation increased from class A to C (38.0% to 47.5%). Each 10% increase in canal occupation was independently associated with bladder dysfunction (OR 1.11, 95% CI 1.01–1.22; p = 0.024), while calcification was associated with severe myelopathy (OR 1.50, 95% CI 1.03–2.19; p = 0.037). The bladder-dysfunction model showed modest discrimination (AUC 0.62). Among patients with baseline deficits and follow-up, recovery occurred in 72.6% (gait) and 83.6% (bladder). Conclusion A combined canal-occupation and ABC-0/1/2 framework provides an interpretable mapping to neurological dysfunction in TDH and may support preoperative risk stratification and counseling. thoracic disc herniation imaging severity spinal canal occupation calcification myelopathy bladder dysfunction Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Symptomatic thoracic disc herniation (TDH) is uncommon but may cause progressive myelopathy with gait impairment and sphincter dysfunction. Clinical decision-making is challenged by heterogeneous radiologic patterns (central vs paracentral, broad-based vs focal), variable calcification, and frequent multilevel degeneration. “Giant” TDH—typically defined as > 40% canal occupation—has been linked to higher rates of myelopathy and intradural extension, and it often requires careful approach planning. [ 1 , 2 , 3 , 4 ] Despite increasing surgical experience with anterior transthoracic, thoracoscopic, retropleural, and posterolateral techniques, preoperative imaging-to-neurology mapping remains insufficiently standardized. Many reports describe canal occupation (or cord compression) but lack a pragmatic morphological framework that is reproducible on routine axial CT/MRI. [ 5 , 6 , 7 , 8 , 9 ] We therefore aimed to (1) implement an axial morphology classification (ABC–0/1/2) aligned to clear anatomic landmarks, (2) quantify canal occupation ratio, and (3) evaluate how these imaging severity metrics associate with baseline neurological dysfunction and postoperative recovery in a long-term retrospective cohort. Methods Study design and setting This retrospective cohort study included consecutive patients undergoing anterior decompression for symptomatic thoracic disc herniation (TDH) between 1998 and 2025 within a single surgical network. We hypothesized that higher canal occupation and more extensive axial ABC-0/1/2 morphology would be independently associated with preoperative neurological dysfunction (bladder dysfunction and severe myelopathy) and lower likelihood of postoperative recovery. Two historical datasets were harmonized into a unified database with standardized variable definitions and coding. Eligibility Adults with symptomatic TDH treated surgically were eligible. For the imaging-severity analysis, inclusion required interpretable preoperative axial CT or MRI allowing morphology classification and canal occupation measurement. Patients lacking key exposure variables or primary outcomes were excluded. Imaging severity measures Canal occupation was measured on axial CT or MRI using a region-of-interest approach and expressed as percentage canal compromise. When both CT and MRI were available, the modality with clearer boundaries was selected; calcification was determined preferentially on CT. Axial morphology was classified using the ABC–0/1/2 system based on two reference lines: posterior vertebral body border and anterior facet border. Extent was defined as A (not exceeding line 1), B (between line 1 and line 2), and C (exceeds line 2). Location was defined as 0 (central), 1 (paramedian/lateralized), and 2 (broad-based). The combined subtype (A0–C2) was used for stratification in analyses.(Fig. 1 ) Reliability assessment To evaluate measurement reliability, two trained raters independently re-assessed a subset of cases. Agreement for axial morphology (extent A/B/C and location 0/1/2) was quantified using Cohen’s kappa and quadratic-weighted kappa. Canal occupation (%) was assessed using intraclass correlation coefficients (ICC, two-way random effects, absolute agreement) and Bland–Altman analysis. Reliability metrics were predefined to ensure reproducibility and consistency of classification. [ 10 , 11 , 12 ] Outcomes Primary outcomes were preoperative bladder dysfunction and severe myelopathy. Severe myelopathy was defined as bladder or bowel dysfunction and/or marked lower extremity motor weakness (Medical Research Council grade ≤ 3). Secondary outcomes included gait disturbance (documented impairment of ambulation) and postoperative recovery of gait/bladder function among patients with baseline deficits and available follow-up. All outcomes were defined according to standardized clinical documentation protocols and established neurological assessment criteria. Missing data and imputation Missing data were handled using multiple imputation by chained equations (MICE) under a missing-at-random assumption. Predictive mean matching was applied for continuous variables, logistic regression for binary variables, and multinomial regression for categorical variables. Twenty imputations were generated with a fixed random seed, and estimates were pooled using Rubin’s rules. Sensitivity analyses included complete-case models and alternative imputation specifications (e.g., m = 50). [ 13 , 14 ] Statistical analysis Continuous variables were summarized as mean ± SD or median (IQR), and categorical variables as counts (%). Between-group comparisons used t-tests or Wilcoxon rank-sum tests for continuous variables and chi-square or Fisher’s exact tests for categorical variables. Multivariable logistic regression was performed to estimate adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Canal occupation was scaled per 10% increase and age per 10 years. Model diagnostics included assessment of multicollinearity, linearity of continuous predictors, and influence statistics. Discrimination was evaluated using the area under the receiver operating characteristic curve (AUC), and calibration was assessed with calibration plots and Brier score. Bootstrap resampling (500 iterations) was used for internal validation. [ 15 , 16 , 17 , 18 , 19 ] Reporting The study followed the STROBE statement for observational studies. [ 20 ] Results Cohort characteristics. The imaging subcohort comprised 536 patients. Mean canal occupation was 40.6%±22.6%. Preoperative prevalence was 42.5% for gait disturbance, 23.2% for bladder dysfunction, and 32.1% for severe myelopathy. Baseline characteristics stratified by axial extent class (A/B/C) are shown in Table 1. Table 1. Baseline characteristics of the imaging subcohort stratified by axial extent class (A/B/C) Variable Class A (n=206) Class B (n=236) Class C (n=94) Age, years 47.4 ± 12.7 50.5 ± 11.9 55.6 ± 12.8 Female sex 120 (58.3%) 152 (64.4%) 66 (70.2%) Calcified disc 48 (23.3%) 77 (32.6%) 72 (76.6%) Multilevel disease 85 (41.3%) 81 (34.3%) 17 (18.1%) Canal occupation, % 38.0 ± 22.3 40.1 ± 23.1 47.5 ± 20.7 Gait disturbance (preop) 76 (36.9%) 99 (41.9%) 52 (55.3%) Bladder dysfunction (preop) 44 (21.4%) 50 (21.2%) 30 (31.9%) Severe myelopathy (preop) 59 (28.6%) 71 (30.1%) 42 (44.7%) Notes: Baseline demographic, radiological, and neurological characteristics of patients included in the imaging-defined thoracic disc herniation subcohort, stratified by axial extent class (A/B/C). Continuous variables are presented as mean ± SD and categorical variables as n (%). Measurement reliability. Across 201 paired observations, the axial ABC-0/1/2 classification showed excellent reproducibility, with an overall agreement of 91.54% (95% CI 86.87-94.65). Agreement for the ABC component (A/B/C) was almost perfect (Cohen’s kappa=0.884, 95% CI 0.825-0.943), and agreement for the ordinal 0/1/2 grade was almost perfect (linear weighted kappa=0.972, 95% CI 0.941-1.000; quadratic weighted kappa=0.978, 95% CI 0.952-1.000). Canal occupation measurement also showed excellent agreement (ICC(2,1)=0.94, 95% CI 0.88-0.98; n=108), with Bland-Altman bias -1.10 percentage points and limits of agreement -8.39 to 6.18. Reliability results are summarized in Table 2. Table 2. Measurement reliability of axial ABC–0/1/2 classification and canal occupation (%) Measure Paired observations (n) Statistic Estimate (95% CI) Subtype (A0–C2) 201 Overall agreement 91.54% (86.87–94.65) Extent (A/B/C) 201 Cohen’s kappa 0.884 (0.825–0.943) Severity grade (0/1/2) 201 Linear-weighted κ 0.972 (0.941–1.000) Severity grade (0/1/2) 201 Quadratic-weighted κ 0.978 (0.952–1.000) Canal occupation (%) 108 ICC(2,1) 0.94 (0.88–0.98) Bland–Altman bias (canal occupation) 108 Mean difference −1.10% (limits −8.39 to 6.18) Abbreviations: ICC, intraclass correlation coefficient; κ, kappa. Notes: Overall agreement is the proportion of identical subtype ratings (A0–C2) between two independent raters; 95% CI for agreement was calculated using the Wilson method. Cohen’s kappa was used for nominal agreement on extent (A/B/C). Linear- and quadratic-weighted κ were used for ordinal agreement on severity grade (0/1/2). Canal occupation (%) reliability was assessed using ICC(2,1) (two-way random effects, absolute agreement). Bland–Altman bias is reported as mean difference with limits of agreement. Imaging severity distribution. Canal occupation increased with axial extent class (A: 38.0%, B: 40.1%, C: 47.5%; Fig.2). Severe myelopathy prevalence rose from 28.6% in class A to 44.7% in class C (Fig.3). Association between imaging severity and neurological dysfunction. In pooled multivariable logistic regression after multiple imputation (m=20), canal occupation (per 10% increase) was associated with higher odds of preoperative bladder dysfunction (OR 1.11, 95% CI 1.01–1.22; p=0.024). Calcification was associated with severe myelopathy (OR 1.50, 95% CI 1.03–2.19; p=0.037). Full regression results are presented in Table 3, with odds ratios illustrated in Fig.4. Table 3. Multivariable logistic regression for neurological outcomes Outcome Predictor OR (95% CI) p value Preoperative bladder dysfunction Canal occupation (per 10%) 1.11 (1.01–1.22) 0.024 Calcified disc 1.35 (0.89–2.06) 0.156 Multilevel disease 0.82 (0.53–1.27) 0.373 Age (per 10 years) 1.17 (0.99–1.38) 0.063 Male sex 0.78 (0.50–1.20) 0.258 Severe myelopathy Canal occupation (per 10%) 1.08 (1.00–1.18) 0.061 Calcified disc 1.50 (1.03–2.19) 0.037 Multilevel disease 0.77 (0.52–1.15) 0.199 Age (per 10 years) 1.13 (0.98–1.32) 0.100 Male sex 0.81 (0.55–1.19) 0.281 Multivariable logistic regression models evaluating the association between imaging severity parameters and preoperative neurological dysfunction. Odds ratios (ORs) are adjusted for age, sex, calcification status, and multilevel disease. Model performance and diagnostics Model discrimination for preoperative bladder dysfunction was modest (AUC 0.62; Fig.5), with bootstrap internal validation (500 resamples) yielding a 95% percentile interval of 0.58–0.68. Additional model diagnostics, including calibration, are provided in the Supplementary Materials (Supplementary Figs. S1–S3). Postoperative recovery Among patients with baseline deficits and available follow-up, gait recovery occurred in 72.6% and bladder recovery in 83.6%. Supplementary Materials Additional analyses and extended diagnostics are provided in the Supplementary Materials. Reliability plots and detailed agreement statistics are shown in Supplementary Figs. S1–S2. Model calibration is presented in Supplementary Fig. S3. Extended baseline characteristics, regression outputs, missing data summaries, sensitivity analyses, and diagnostic tables are available in Supplementary Tables S1–S11 Discussion Principal findings This study proposes a pragmatic imaging severity framework for TDH that integrates a quantitative canal occupation ratio with a reproducible axial morphological classification (ABC–0/1/2). In a long-term cohort, higher canal occupation was associated with bladder dysfunction and more severe myelopathy, while calcification signaled a higher-risk neurological presentation. Interpretation and clinical implications Sphincter dysfunction is an urgent clinical red flag in TDH. The observed association between canal occupation and bladder dysfunction supports using quantitative canal compromise (especially when approaching or exceeding the “giant” threshold) for risk communication and surgical prioritization. Morphological context matters: the ABC–0/1/2 system captures ventral canal encroachment and distribution, which can complement continuous measurement and may be incorporated into an “imaging-to-neurology” mapping chart for multidisciplinary decision-making. Comparison with literature Prior work on giant and calcified thoracic disc herniation (TDH) consistently links marked canal compromise with myelopathy and a higher likelihood of complex pathology such as intradural extension, thereby increasing the technical demands of anterior transthoracic or thoracoscopic strategies. Hott et al. defined “giant” TDH as occupying >40% of the spinal canal and reported that these lesions commonly present with myelopathy and require meticulous surgical planning to avoid neurological deterioration [3]. In a dedicated series of calcified giant TDH, Quraishi et al. reported substantial canal encroachment and highlighted the operative complexity and complication profile associated with anterior approaches for calcified fragments adherent to the dura [21]. Roelz et al. further demonstrated that increasing lesion size correlates with intradural extension in giant central TDH, reinforcing the need for stratified preoperative risk communication beyond a binary “calcified vs. non-calcified” description [22]. Contemporary reviews emphasize that giant calcified herniations are among the main drivers of myelopathy, intradural extension, and postoperative complications, and they underscore the approach-dependent morbidity of transthoracic routes and the learning-curve burden of thoracoscopic techniques [23]. Large thoracoscopic cohorts have shown that thoracoscopic discectomy can achieve favorable outcomes in selected TDH, yet central/calcified lesions remain technically demanding and require careful patient selection and surgeon experience [2,6,7,23,24]. Building on this body of evidence, our axial ABC–0/1/2 stratification provides an explicit, clinically intuitive morphological framework that complements canal-occupation metrics and better standardizes communication of ventral encroachment pattern and extent in high-risk TDH. Strengths and limitations Strengths include a large historical cohort and consistent imaging-derived variables. Limitations include the retrospective design, potential heterogeneity in imaging acquisition across decades, and incomplete postoperative imaging metrics due to near-complete decompression in most cases. Neurological outcomes were captured in routine clinical documentation rather than standardized mJOA/ASIA for all cases; future prospective validation is warranted. Future directions We plan external validation and integration of additional imaging biomarkers (e.g., intramedullary T2 hyperintensity, HU-based calcification quantification) to improve predictive performance and to link imaging severity directly to approach selection and complication risk in subsequent manuscripts.[25,26] Conclusions A combined imaging severity stratification based on canal occupation ratio and axial ABC–0/1/2 morphology provides an interpretable mapping to neurological dysfunction in thoracic disc herniation. Canal occupation most strongly relates to bladder dysfunction, and calcification is associated with severe myelopathy. This framework can support preoperative counseling and may serve as a cornerstone for a broader “approach selection + risk warning” decision model. Statements and Declarations Ethics approval: This study was approved by the Ethics Committee of the State Medical Association of Hesse, Germany. Consent to participate: The study was conducted in accordance with applicable local regulations and institutional policies for retrospective research. Consent for publication: Not applicable. Availability of data and materials: De-identified data supporting the findings of this study are available from the corresponding author upon reasonable request and with appropriate institutional approvals. Competing interests: The authors declare no competing interests. Funding: This work was supported by the Henan Provincial Medical Science and Technology Research Project of China (No. LHGJ20250253) and the Henan Charity Federation Daojian Fund Major Project (No. szsyky24001; No. szsyky24021). Authors' contributions: All authors contributed to study conception and design. 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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-8626677","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":591630696,"identity":"02ceaa38-2cef-43f4-bda2-dd9cffd9e112","order_by":0,"name":"Kunfeng Song","email":"","orcid":"","institution":"Hochtaunus-Kliniken gGmbH","correspondingAuthor":false,"prefix":"","firstName":"Kunfeng","middleName":"","lastName":"Song","suffix":""},{"id":591630698,"identity":"6c10cf24-7d68-43fa-ad30-f21e54939adf","order_by":1,"name":"Daniel Rosenthal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABDUlEQVRIie3PsUrEMBjA8UggLmm7Jgi9V4gEquVepkGoy+ni0qlWDnqD9AFc9BUqQnGsfFCX6Kzcootzi4uCgpEuDq13bg75L8mQX5IPIZvtP1b3S4Q2cc36PUXoCeFVREQIk6gnhH7fsBahYj3iLgHa7vrj0JvTbpkkqb8zKW5aNZsib3EaDRF+H8f8TIsjBs5VqDXIMHf3mKr2EdN35RARmgbYyYXKwKn4SV6rsjE/VBUgwQ7GiHz9NOQC6Ish6bEh8m0FEVsbhpRAiSE4Eg0Nfn2FaxLzIpfqEogMMw3bZTMLds0sdGwWV2No33Nfnd/Onx+zJJ0I0PKhq6a+tygGyXj0b8dtNpvN9rMvQrFmbEO7/bIAAAAASUVORK5CYII=","orcid":"","institution":"Hochtaunus-Kliniken gGmbH","correspondingAuthor":true,"prefix":"","firstName":"Daniel","middleName":"","lastName":"Rosenthal","suffix":""},{"id":591630699,"identity":"5022ef66-ebba-4e42-a910-af6c2287985f","order_by":2,"name":"Stephan Dützmann","email":"","orcid":"","institution":"Hochtaunus-Kliniken gGmbH","correspondingAuthor":false,"prefix":"","firstName":"Stephan","middleName":"","lastName":"Dützmann","suffix":""},{"id":591630702,"identity":"5b148996-2981-4fed-aa7a-59ea703112ed","order_by":3,"name":"Alexis Montes Martinez","email":"","orcid":"","institution":"Hochtaunus-Kliniken gGmbH","correspondingAuthor":false,"prefix":"","firstName":"Alexis","middleName":"Montes","lastName":"Martinez","suffix":""},{"id":591630703,"identity":"eb201236-c7e8-49a9-82bf-6b44da2797b2","order_by":4,"name":"Zizhuo Jin","email":"","orcid":"","institution":"Hochtaunus-Kliniken gGmbH","correspondingAuthor":false,"prefix":"","firstName":"Zizhuo","middleName":"","lastName":"Jin","suffix":""}],"badges":[],"createdAt":"2026-01-17 14:38:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8626677/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8626677/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102991910,"identity":"38336e17-74e6-4208-bc49-81c771a28efa","added_by":"auto","created_at":"2026-02-19 11:35:45","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":325012,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAxial ABC–0/1/2 classification protocol and canal occupation measurement \u003c/strong\u003eThe ABC component describes axial extent (A/B/C), and the 0/1/2 component grades increasing ventral canal compromise; the combined subtype (A0–C2) was used for stratified analyses. Abbreviations: CT, computed tomography; MRI, magnetic resonance imaging; TDH, thoracic disc herniation\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8626677/v1/590e7da76a6ad17638f58392.png"},{"id":102991911,"identity":"f308d92f-33de-4144-9f1e-150fb0cadc1f","added_by":"auto","created_at":"2026-02-19 11:35:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":42582,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCanal occupation (%) by axial extent class (A/B/C). \u003c/strong\u003eBox plots show the median (center line), interquartile range (box), and whiskers with outliers. TDH, thoracic disc herniation\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8626677/v1/c2f2d0a1fd825d4e91d1b219.png"},{"id":102991912,"identity":"d72533af-bfb7-4d1a-970f-a65faa606c34","added_by":"auto","created_at":"2026-02-19 11:35:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":56724,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdjusted probability of bladder dysfunction across canal occupation (%). \u003c/strong\u003eThe solid line depicts model-based predicted probability with the shaded band indicating 95% confidence intervals. CI, confidence interval\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8626677/v1/dd9f585ab3cb457b3de57b54.png"},{"id":102991913,"identity":"a65f08de-c85d-4daa-9b62-342bccc43520","added_by":"auto","created_at":"2026-02-19 11:35:45","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":63869,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMultivariable associations with bladder dysfunction and severe myelopathy. \u003c/strong\u003eAdjusted odds ratios are shown on a logarithmic scale with 95% confidence intervals; the vertical dashed line indicates OR=1. CI, confidence interval; OR, odds ratio\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8626677/v1/bdc44592e940be34b8f6a65d.png"},{"id":102991914,"identity":"fc48e7b5-eb98-4a12-bcae-2c3700738067","added_by":"auto","created_at":"2026-02-19 11:35:45","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":110983,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eReceiver operating characteristic curve for the multivariable prediction model. \u003c/strong\u003eThe area under the curve is shown in the panel (AUC=0.62). AUC, area under the curve; ROC, receiver operating characteristic\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8626677/v1/377e7c245cf30f0df529b53e.png"},{"id":102991919,"identity":"03b2d92a-19d1-47ed-9a4c-72800e469d25","added_by":"auto","created_at":"2026-02-19 11:35:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1477372,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8626677/v1/f73f826c-2f37-4b75-abb5-70671034a29d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Imaging severity stratification of thoracic disc herniation and its association with neurological dysfunction: a retrospective cohort study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSymptomatic thoracic disc herniation (TDH) is uncommon but may cause progressive myelopathy with gait impairment and sphincter dysfunction. Clinical decision-making is challenged by heterogeneous radiologic patterns (central vs paracentral, broad-based vs focal), variable calcification, and frequent multilevel degeneration. \u0026ldquo;Giant\u0026rdquo; TDH\u0026mdash;typically defined as \u0026gt;\u0026thinsp;40% canal occupation\u0026mdash;has been linked to higher rates of myelopathy and intradural extension, and it often requires careful approach planning. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eDespite increasing surgical experience with anterior transthoracic, thoracoscopic, retropleural, and posterolateral techniques, preoperative imaging-to-neurology mapping remains insufficiently standardized. Many reports describe canal occupation (or cord compression) but lack a pragmatic morphological framework that is reproducible on routine axial CT/MRI. [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/p\u003e \u003cp\u003eWe therefore aimed to (1) implement an axial morphology classification (ABC\u0026ndash;0/1/2) aligned to clear anatomic landmarks, (2) quantify canal occupation ratio, and (3) evaluate how these imaging severity metrics associate with baseline neurological dysfunction and postoperative recovery in a long-term retrospective cohort.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy design and setting\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study included consecutive patients undergoing anterior decompression for symptomatic thoracic disc herniation (TDH) between 1998 and 2025 within a single surgical network. We hypothesized that higher canal occupation and more extensive axial ABC-0/1/2 morphology would be independently associated with preoperative neurological dysfunction (bladder dysfunction and severe myelopathy) and lower likelihood of postoperative recovery. Two historical datasets were harmonized into a unified database with standardized variable definitions and coding.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEligibility\u003c/h3\u003e\n\u003cp\u003eAdults with symptomatic TDH treated surgically were eligible. For the imaging-severity analysis, inclusion required interpretable preoperative axial CT or MRI allowing morphology classification and canal occupation measurement. Patients lacking key exposure variables or primary outcomes were excluded.\u003c/p\u003e\n\u003ch3\u003eImaging severity measures\u003c/h3\u003e\n\u003cp\u003eCanal occupation was measured on axial CT or MRI using a region-of-interest approach and expressed as percentage canal compromise. When both CT and MRI were available, the modality with clearer boundaries was selected; calcification was determined preferentially on CT. Axial morphology was classified using the ABC\u0026ndash;0/1/2 system based on two reference lines: posterior vertebral body border and anterior facet border. Extent was defined as A (not exceeding line 1), B (between line 1 and line 2), and C (exceeds line 2). Location was defined as 0 (central), 1 (paramedian/lateralized), and 2 (broad-based). The combined subtype (A0\u0026ndash;C2) was used for stratification in analyses.(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e)\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eReliability assessment\u003c/h3\u003e\n\u003cp\u003eTo evaluate measurement reliability, two trained raters independently re-assessed a subset of cases. Agreement for axial morphology (extent A/B/C and location 0/1/2) was quantified using Cohen\u0026rsquo;s kappa and quadratic-weighted kappa. Canal occupation (%) was assessed using intraclass correlation coefficients (ICC, two-way random effects, absolute agreement) and Bland\u0026ndash;Altman analysis. Reliability metrics were predefined to ensure reproducibility and consistency of classification. [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003ePrimary outcomes were preoperative bladder dysfunction and severe myelopathy. Severe myelopathy was defined as bladder or bowel dysfunction and/or marked lower extremity motor weakness (Medical Research Council grade\u0026thinsp;\u0026le;\u0026thinsp;3). Secondary outcomes included gait disturbance (documented impairment of ambulation) and postoperative recovery of gait/bladder function among patients with baseline deficits and available follow-up. All outcomes were defined according to standardized clinical documentation protocols and established neurological assessment criteria.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eMissing data and imputation\u003c/h2\u003e \u003cp\u003eMissing data were handled using multiple imputation by chained equations (MICE) under a missing-at-random assumption. Predictive mean matching was applied for continuous variables, logistic regression for binary variables, and multinomial regression for categorical variables. Twenty imputations were generated with a fixed random seed, and estimates were pooled using Rubin\u0026rsquo;s rules. Sensitivity analyses included complete-case models and alternative imputation specifications (e.g., m\u0026thinsp;=\u0026thinsp;50). [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eContinuous variables were summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD or median (IQR), and categorical variables as counts (%). Between-group comparisons used t-tests or Wilcoxon rank-sum tests for continuous variables and chi-square or Fisher\u0026rsquo;s exact tests for categorical variables. Multivariable logistic regression was performed to estimate adjusted odds ratios (ORs) with 95% confidence intervals (CIs). Canal occupation was scaled per 10% increase and age per 10 years. Model diagnostics included assessment of multicollinearity, linearity of continuous predictors, and influence statistics. Discrimination was evaluated using the area under the receiver operating characteristic curve (AUC), and calibration was assessed with calibration plots and Brier score. Bootstrap resampling (500 iterations) was used for internal validation. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eReporting\u003c/h3\u003e\n\u003cp\u003eThe study followed the STROBE statement for observational studies. [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eCohort characteristics. The imaging subcohort comprised 536 patients. Mean canal occupation was 40.6%\u0026plusmn;22.6%. Preoperative prevalence was 42.5% for gait disturbance, 23.2% for bladder dysfunction, and 32.1% for severe myelopathy. Baseline characteristics stratified by axial extent class (A/B/C) are shown in Table 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Baseline characteristics of the imaging subcohort\u003c/strong\u003e \u003cstrong\u003estratified by axial extent class (A/B/C)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eClass A (n=206)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eClass B (n=236)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eClass C (n=94)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eAge, years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e47.4 \u0026plusmn; 12.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e50.5 \u0026plusmn; 11.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e55.6 \u0026plusmn; 12.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eFemale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e120 (58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e152 (64.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e66 (70.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eCalcified disc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e48 (23.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e77 (32.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e72 (76.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eMultilevel disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e85 (41.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e81 (34.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e17 (18.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eCanal occupation, %\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e38.0 \u0026plusmn; 22.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e40.1 \u0026plusmn; 23.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e47.5 \u0026plusmn; 20.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eGait disturbance (preop)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e76 (36.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e99 (41.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e52 (55.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eBladder dysfunction (preop)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e44 (21.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e50 (21.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e30 (31.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003eSevere myelopathy (preop)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e59 (28.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e71 (30.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 144px;\"\u003e\n \u003cp\u003e42 (44.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNotes: Baseline demographic, radiological, and neurological characteristics of patients included in the imaging-defined thoracic disc herniation subcohort, stratified by axial extent class (A/B/C). Continuous variables are presented as mean \u0026plusmn; SD and categorical variables as n (%).\u003c/p\u003e\n\u003cp\u003eMeasurement reliability. Across 201 paired observations, the axial ABC-0/1/2 classification showed excellent reproducibility, with an overall agreement of 91.54% (95% CI 86.87-94.65). Agreement for the ABC component (A/B/C) was almost perfect (Cohen\u0026rsquo;s kappa=0.884, 95% CI 0.825-0.943), and agreement for the ordinal 0/1/2 grade was almost perfect (linear weighted kappa=0.972, 95% CI 0.941-1.000; quadratic weighted kappa=0.978, 95% CI 0.952-1.000). Canal occupation measurement also showed excellent agreement (ICC(2,1)=0.94, 95% CI 0.88-0.98; n=108), with Bland-Altman bias -1.10 percentage points and limits of agreement -8.39 to 6.18. Reliability results are summarized in Table 2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Measurement reliability of axial ABC\u0026ndash;0/1/2 classification and canal occupation (%)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeasure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePaired observations (n)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStatistic\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEstimate (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eSubtype (A0\u0026ndash;C2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eOverall agreement\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e91.54% (86.87\u0026ndash;94.65)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eExtent (A/B/C)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCohen\u0026rsquo;s kappa\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.884 (0.825\u0026ndash;0.943)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eSeverity grade (0/1/2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eLinear-weighted \u0026kappa;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.972 (0.941\u0026ndash;1.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eSeverity grade (0/1/2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eQuadratic-weighted \u0026kappa;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.978 (0.952\u0026ndash;1.000)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCanal occupation (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eICC(2,1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.94 (0.88\u0026ndash;0.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eBland\u0026ndash;Altman bias (canal occupation)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e108\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eMean difference\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026minus;1.10% (limits \u0026minus;8.39 to 6.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eAbbreviations: ICC, intraclass correlation coefficient; \u0026kappa;, kappa.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNotes: Overall agreement is the proportion of identical subtype ratings (A0\u0026ndash;C2) between two independent raters; 95% CI for agreement was calculated using the Wilson method. Cohen\u0026rsquo;s kappa was used for nominal agreement on extent (A/B/C). Linear- and quadratic-weighted \u0026kappa; were used for ordinal agreement on severity grade (0/1/2). Canal occupation (%) reliability was assessed using ICC(2,1) (two-way random effects, absolute agreement). Bland\u0026ndash;Altman bias is reported as mean difference with limits of agreement.\u003c/p\u003e\n\u003cp\u003eImaging severity distribution. Canal occupation increased with axial extent class (A: 38.0%, B: 40.1%, C: 47.5%; Fig.2). Severe myelopathy prevalence rose from 28.6% in class A to 44.7% in class C (Fig.3).\u003c/p\u003e\n\u003cp\u003eAssociation between imaging severity and neurological dysfunction. In pooled multivariable logistic regression after multiple imputation (m=20), canal occupation (per 10% increase) was associated with higher odds of preoperative bladder dysfunction (OR 1.11, 95% CI 1.01\u0026ndash;1.22; p=0.024). Calcification was associated with severe myelopathy (OR 1.50, 95% CI 1.03\u0026ndash;2.19; p=0.037). Full regression results are presented in Table 3, with odds ratios illustrated in Fig.4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Multivariable logistic regression for neurological outcomes\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eOutcome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003ePredictor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eOR (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003ep value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003ePreoperative bladder dysfunction\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCanal occupation (per 10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.11 (1.01\u0026ndash;1.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCalcified disc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.35 (0.89\u0026ndash;2.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.156\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eMultilevel disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.82 (0.53\u0026ndash;1.27)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.373\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eAge (per 10 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.17 (0.99\u0026ndash;1.38)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eMale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.78 (0.50\u0026ndash;1.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.258\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eSevere myelopathy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCanal occupation (per 10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.08 (1.00\u0026ndash;1.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eCalcified disc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.50 (1.03\u0026ndash;2.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eMultilevel disease\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.77 (0.52\u0026ndash;1.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eAge (per 10 years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e1.13 (0.98\u0026ndash;1.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003eMale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.81 (0.55\u0026ndash;1.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 144px;\"\u003e\n \u003cp\u003e0.281\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMultivariable logistic regression models evaluating the association between imaging severity parameters and preoperative neurological dysfunction. Odds ratios (ORs) are adjusted for age, sex, calcification status, and multilevel disease.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u003cstrong\u003eModel performance and diagnostics\u003cbr\u003e\u003c/strong\u003eModel discrimination for preoperative bladder dysfunction was modest (AUC 0.62; Fig.5), with bootstrap internal validation (500 resamples) yielding a 95% percentile interval of 0.58\u0026ndash;0.68. Additional model diagnostics, including calibration, are provided in the Supplementary Materials (Supplementary Figs. S1\u0026ndash;S3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePostoperative recovery\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAmong patients with baseline deficits and available follow-up, gait recovery occurred in 72.6% and bladder recovery in 83.6%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAdditional analyses and extended diagnostics are provided in the Supplementary Materials. Reliability plots and detailed agreement statistics are shown in Supplementary Figs. S1\u0026ndash;S2. Model calibration is presented in Supplementary Fig. S3. Extended baseline characteristics, regression outputs, missing data summaries, sensitivity analyses, and diagnostic tables are available in Supplementary Tables S1\u0026ndash;S11\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e\u003cstrong\u003ePrincipal findings\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This study proposes a pragmatic imaging severity framework for TDH that integrates a quantitative canal occupation ratio with a reproducible axial morphological classification (ABC–0/1/2). In a long-term cohort, higher canal occupation was associated with bladder dysfunction and more severe myelopathy, while calcification signaled a higher-risk neurological presentation.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Interpretation and clinical implications\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Sphincter dysfunction is an urgent clinical red flag in TDH. The observed association between canal occupation and bladder dysfunction supports using quantitative canal compromise (especially when approaching or exceeding the “giant” threshold) for risk communication and surgical prioritization. Morphological context matters: the ABC–0/1/2 system captures ventral canal encroachment and distribution, which can complement continuous measurement and may be incorporated into an “imaging-to-neurology” mapping chart for multidisciplinary decision-making.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComparison with literature\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Prior work on giant and calcified thoracic disc herniation (TDH) consistently links marked canal compromise with myelopathy and a higher likelihood of complex pathology such as intradural extension, thereby increasing the technical demands of anterior transthoracic or thoracoscopic strategies. Hott et al. defined “giant” TDH as occupying \u0026gt;40% of the spinal canal and reported that these lesions commonly present with myelopathy and require meticulous surgical planning to avoid neurological deterioration [3]. In a dedicated series of calcified giant TDH, Quraishi et al. reported substantial canal encroachment and highlighted the operative complexity and complication profile associated with anterior approaches for calcified fragments adherent to the dura [21]. Roelz et al. further demonstrated that increasing lesion size correlates with intradural extension in giant central TDH, reinforcing the need for stratified preoperative risk communication beyond a binary “calcified vs. non-calcified” description [22]. Contemporary reviews emphasize that giant calcified herniations are among the main drivers of myelopathy, intradural extension, and postoperative complications, and they underscore the approach-dependent morbidity of transthoracic routes and the learning-curve burden of thoracoscopic techniques [23]. Large thoracoscopic cohorts have shown that thoracoscopic discectomy can achieve favorable outcomes in selected TDH, yet central/calcified lesions remain technically demanding and require careful patient selection and surgeon experience [2,6,7,23,24]. Building on this body of evidence, our axial ABC–0/1/2 stratification provides an explicit, clinically intuitive morphological framework that complements canal-occupation metrics and better standardizes communication of ventral encroachment pattern and extent in high-risk TDH.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStrengths and limitations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Strengths include a large historical cohort and consistent imaging-derived variables. Limitations include the retrospective design, potential heterogeneity in imaging acquisition across decades, and incomplete postoperative imaging metrics due to near-complete decompression in most cases. Neurological outcomes were captured in routine clinical documentation rather than standardized mJOA/ASIA for all cases; future prospective validation is warranted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFuture directions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;We plan external validation and integration of additional imaging biomarkers (e.g., intramedullary T2 hyperintensity, HU-based calcification quantification) to improve predictive performance and to link imaging severity directly to approach selection and complication risk in subsequent manuscripts.[25,26]\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eA combined imaging severity stratification based on canal occupation ratio and axial ABC–0/1/2 morphology provides an interpretable mapping to neurological dysfunction in thoracic disc herniation. Canal occupation most strongly relates to bladder dysfunction, and calcification is associated with severe myelopathy. This framework can support preoperative counseling and may serve as a cornerstone for a broader “approach selection + risk warning” decision model.\u003c/p\u003e"},{"header":"Statements and Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval:\u0026nbsp;\u003c/strong\u003eThis study was approved by the Ethics Committee of the State Medical Association of Hesse, Germany.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate:\u0026nbsp;\u003c/strong\u003eThe study was conducted in accordance with applicable local regulations and institutional policies for retrospective research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication:\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u0026nbsp;\u003c/strong\u003eDe-identified data supporting the findings of this study are available from the corresponding author upon reasonable request and with appropriate institutional approvals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u0026nbsp;\u003c/strong\u003eThis work was supported by the Henan Provincial Medical Science and Technology Research Project of China (No. LHGJ20250253) and the Henan Charity Federation Daojian Fund Major Project (No. szsyky24001; No. szsyky24021).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u0026nbsp;\u003c/strong\u003eAll authors contributed to study conception and design. Material preparation, data collection, and analysis were performed by the study team. All authors commented on previous versions of the manuscript and approved the final manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eKasliwal MK (2024) Evolution and current status of surgical management of thoracic disc herniation - a review. Clin Neurol Neurosurg 236:108055. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.clineuro.2023.108055\u003c/span\u003e\u003cspan address=\"10.1016/j.clineuro.2023.108055\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCourt C, Mansour E, Bouthors C (2018) Thoracic disc herniation: Surgical treatment. 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Eur Spine J 29(7):1717\u0026ndash;1723. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00586-019-06192-x\u003c/span\u003e\u003cspan address=\"10.1007/s00586-019-06192-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"european-spine-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esjo","sideBox":"Learn more about [European Spine Journal](http://link.springer.com/journal/586)","snPcode":"586","submissionUrl":"https://submission.springernature.com/new-submission/586/3","title":"European Spine Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"thoracic disc herniation, imaging severity, spinal canal occupation, calcification, myelopathy, bladder dysfunction","lastPublishedDoi":"10.21203/rs.3.rs-8626677/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8626677/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003ePurpose\u003c/b\u003e\u003c/p\u003e \u003cp\u003eTo develop a practical imaging severity stratification for thoracic disc herniation (TDH) combining canal occupation ratio and the axial ABC-0/1/2 morphology, and to evaluate associations with neurological dysfunction and postoperative recovery.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn a retrospective single-network TDH cohort (1998\u0026ndash;2025), canal occupation (%) was measured on axial CT/MRI and axial morphology was classified as ABC-0/1/2. Primary outcomes were preoperative bladder dysfunction and severe myelopathy; secondary outcomes included gait disturbance and recovery. Multivariable logistic regression adjusted for age, sex, calcification, and multilevel disease.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eOf 1129 surgical TDH cases, 536 had complete axial classification and canal measurements. Preoperative gait disturbance occurred in 42.5% and bladder dysfunction in 23.2%. Canal occupation increased from class A to C (38.0% to 47.5%). Each 10% increase in canal occupation was independently associated with bladder dysfunction (OR 1.11, 95% CI 1.01\u0026ndash;1.22; p\u0026thinsp;=\u0026thinsp;0.024), while calcification was associated with severe myelopathy (OR 1.50, 95% CI 1.03\u0026ndash;2.19; p\u0026thinsp;=\u0026thinsp;0.037). The bladder-dysfunction model showed modest discrimination (AUC 0.62). Among patients with baseline deficits and follow-up, recovery occurred in 72.6% (gait) and 83.6% (bladder).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA combined canal-occupation and ABC-0/1/2 framework provides an interpretable mapping to neurological dysfunction in TDH and may support preoperative risk stratification and counseling.\u003c/p\u003e","manuscriptTitle":"Imaging severity stratification of thoracic disc herniation and its association with neurological dysfunction: a retrospective cohort study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-19 11:35:40","doi":"10.21203/rs.3.rs-8626677/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-02-13T12:51:17+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-01-20T10:51:40+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-20T10:51:31+00:00","index":"","fulltext":""},{"type":"submitted","content":"European Spine Journal","date":"2026-01-17T14:24:12+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"european-spine-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"esjo","sideBox":"Learn more about [European Spine Journal](http://link.springer.com/journal/586)","snPcode":"586","submissionUrl":"https://submission.springernature.com/new-submission/586/3","title":"European Spine Journal","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"d0996d1a-ec14-4858-99de-206c059d1c4c","owner":[],"postedDate":"February 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-02-19T11:35:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-19 11:35:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8626677","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8626677","identity":"rs-8626677","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}