Clinical and Radiological Characteristics in Multiple Sclerosis Patients with Large Cavitary Lesions
Bibliographic record
Abstract
BACKGROUND: Large cavitary lesions are not typical for multiple sclerosis (MS). Cavitary white matter changes may be seen in megalencephalic leukoencephalopathy with subcortical cysts, Alexander disease, mitochondrial leukoencephalopathies, vanishing white matter disease, leukoencephalopathy with calcifications and cysts, cytomegalovirus infection, and cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy. OBJECTIVE: To analyze clinical and radiological characteristics in MS patients with large cavitary lesions. METHODS: We studied MS patients with large cavitary brain lesions. Patient characteristics, disease onset/duration/subtype, expanded disability status scale (EDSS), mini mental state (MMS), corpus callosum lesions, history of segmental myelitis, CSF oligoclonal bands (OCB), visual evoked potentials (VEP), vanishing white matter disease genetic analysis, and characteristics of the cavitary lesions were analyzed. RESULTS: Nine patients were analyzed, 1 man and 8 women. Mean age of disease onset was 38.5 years. Mean disease duration was 9 years. Three patients had initial relapsing-remitting MS and 6 patients had primary-progressive MS. Mean EDSS was 4.5. Mean MMS was 20/30. Segmental myelitis was present in 6 cases. OCB were found in 6 patients. VEP was performed in 6 patients, and pathological in all but one. Vanishing white matter disease genetic analysis was performed and negative in 5 patients. Inferior corpus callosum lesions were seen in all patients with available sagittal FLAIR sequences. Cavitary lesions were strictly supratentorial, and located inside the diffuse leukoencephalopathy, with often a posterior predominance. CONCLUSION: MS patients with large cavitary lesions seem to represent an MS subgroup, predominantly women, with relatively late disease onset, predominantly primary-progressive type, relatively high EDSS scores, and severe cognitive dysfunction.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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".