Wallerian degeneration of the corticospinal tract following multimodal high-grade glioma treatment: a case series and recommendations for radiotherapy planning
Bibliographic record
Abstract
Introduction: Wallerian Degeneration of the Corticospinal Tract (WDCT) is a scarcely reported complication of multimodal treatment for high-grade gliomas, which, despite its potential clinical impact, may lead to severe motor dysfunction and impair quality of life. Methodology: This retrospective case series describes 13 adult patients with high-grade gliomas treated between 2018 and 2023 who developed imaging findings consistent with WDCT after receiving multimodal treatment. Clinical and radiological data were collected from medical records; a standardized imaging follow-up or functional scoring system was not applied. Tractography was retrospectively available for two cases, enabling its incorporation into radiotherapy planning system for CST precise delineation and corresponding dose estimation. Results: WDCT was identified in 13 out of 192 high-grade glioma patients (6.8%). Diagnosis was based on T2/FLAIR hyperintensity along the ipsilateral CST with compatible clinical symptoms. Three cases developed WDCT after reirradiation, and seven (53.8%) had received bevacizumab prior to diagnosis: two during disease progression, two for the treatment of radionecrosis, and three as prophylaxis. Clinical symptomatology was detailed to 11 patients, 72.7% presented with hemiparesis, and 36.4% had seizures. In two cases, retrospective dose-volume analysis revealed CST mean doses ranging from 25.81 Gy to 42.83 Gy. Conclusions: This retrospective series highlights WDCT as a potentially underrecognized complication in glioma patients undergoing multimodal treatment. While etiology is likely multifactorial, radiotherapy may play a contributing role. CST delineation, when tractography is available, may support individualized treatment planning, enable better assessment of dose exposure, and help identify patients at higher risk of motor decline. Further prospective studies are warranted to define dose thresholds and assess functional outcomes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".