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Published on: July 8, 2021
Transparent, Reproducible Text-Based Phenotyping of Lumbar Intervertebral Disc Degeneration from 500 Consecutive MRI
Ahmed Ibrahim Haidar1, Mohammed Emam2,3, Abdulwahab Ali Aljubran4
1MRI Unit, Radiology Department, Imam Abdulrahman Al Faisal Hospital, First Health Cluster, Riyadh 14723, Saudi Arabia.
Abstract:
Background/Objectives: To characterize the degenerative vocabulary of 500 consecutive lumbar MRI reports using a transparent, reproducible text extraction pipeline; to quantify which descriptors distinguish included from excluded reports and which factors predict text-derived severity; and to specify a reproducible image analysis pipeline whose formal validation against radiologist Pfirrmann grading is defined as the next step. Methods: We analyzed 500 lumbar MRI reports (386 patients; December 2018-November 2025), extracting morphological and severity keywords, segmental levels (L1-L2 to L5-S1), Modic mentions, and a custom text-derived ordinal severity (0-3). Keyword prevalence differences were tested with the Fisher exact test under Benjamini-Hochberg false discovery rate control, with 95% confidence intervals (CIs) for all odds ratios (ORs) and risk differences; predictors of severity were examined by ordinal logistic regression. Robustness to within-patient clustering was assessed with patient-clustered robust estimation and one-report-per-patient analyses. A MATLAB pipeline derived per-disc candidate imaging features (predicted Pfirrmann grade, normalized disc height, T2 signal index, quality control) across 316 studies. Results: In total, 385/500 reports (77.0%) met the inclusion criteria. The structured morphological keyword field was missing in 49.4% of records, varying by year (58.6% in 2020, 68.7% in 2023, 41.9% in 2024, 33.5% in 2025), indicating systematic reporting drift. Bulge was the dominant descriptor (53.8%); L4-L5 and L5-S1 dominated level mentions. After correction, bulge (OR 6.70, 95% CI 3.86-11.65), mild (5.08, 2.39-10.78), dehydration (9.82, 2.36-40.87) and central (8.63, 2.07-36.01) were enriched among the included reports. All four remained significant in clustering-aware sensitivity analyses. Older age independently predicted higher severity (OR 1.36 per 10 years, 95% CI 1.19-1.56). The image pipeline produced per-disc candidate biomarkers across 316 studies. Conclusions: Free-text lumbar MRI reports encode a recognizable but heterogeneous degenerative vocabulary, sufficient for cohort construction yet inconsistent for quantitative grading; the text-derived severity is a noisy proxy. The reproducible image analysis pipeline yields candidate biomarkers whose formal validation against an adjudicated radiologist Pfirrmann reference standard is the explicit, pre-specified next step.
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