Diagnostic Accuracy of Centrally Restricted Diffusion in the Differentiation of Treatment-Related Necrosis from Tumor Recurrence in High-Grade Gliomas
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Centrally restricted diffusion has been demonstrated in recurrent high-grade gliomas treated with bevacizumab. Our purpose was to assess the accuracy of centrally restricted diffusion in the diagnosis of radiation necrosis in high-grade gliomas not treated with bevacizumab. MATERIALS AND METHODS: In this prospective study, we enrolled patients with high-grade gliomas who developed a new ring-enhancing necrotic lesion and who underwent re-resection. The presence of a centrally restricted diffusion within the ring-enhancing lesion was assessed visually on diffusion trace images and by ADC measurements on 3T preoperative diffusion tensor examination. The percentage of tumor recurrence and radiation necrosis in each surgical specimen was defined histopathologically. The association between centrally restricted diffusion and radiation necrosis was assessed using the Fisher exact test. Differences in ADC and the ADC ratio between the groups were assessed via the Mann-Whitney U test, and receiver operating characteristic curve analysis was performed. RESULTS: Seventeen patients had re-resected ring-enhancing lesions: 8 cases of radiation necrosis and 9 cases of tumor recurrence. There was significant association between centrally restricted diffusion by visual assessment and radiation necrosis (P = .015) with a sensitivity of 75% and a specificity of 88.9%, a positive predictive value 85.7%, and a negative predictive value of 80% for the diagnosis of radiation necrosis. There was a statistically significant difference in the ADC and ADC ratio between radiation necrosis and tumor recurrence (P = .027). CONCLUSIONS: The presence of centrally restricted diffusion in a new ring-enhancing lesion might indicate radiation necrosis rather than tumor recurrence in high-grade gliomas previously treated with standard chemoradiation without bevacizumab.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".