NI-67 * THE ROLE OF FLAIR VOLUME AS A PROGNOSTICATING FACTOR IN PATIENTS WITH GLIOBLASTOMA
Bibliographic record
Abstract
BACKGROUND: Volumetric analysis on T1-weighted post-gadolinium (T1-PG) magnetic resonance imaging (MRI) sequence is central in managing patients with glioblastoma. It is unclear how the contrast enhancing tumor volume relates to abnormal findings in other MRI sequences such as fluid attenuated inversion recovery (FLAIR) and whether additional prognosticating information can be derived from these supplementary radiographic techniques. OBJECTIVES: To determine the relationship between volumetric measurements (T1-PG, FLAIR) and survival in patients with newly diagnosed GBM using rapid volumetric measurement (MacDonald ellipsoid method) for estimation of tumor volume. We will also compare the accuracy of rapid volumetric measurement to a manual tracing method for determination of tumor volume. METHODS: Tumor volumes of 30 patients (10 females, mean age 63 years) with diagnosis of glioblastoma were retrospectively measured using pre-operative MRI. Enhancing tumor volume on the T1-PG sequence was calculated using both a manual tracing method and the MacDonald ellipsoid method while volume of abnormal signal intensity on the FLAIR sequence was measured using the MacDonald ellipsoid method. The relationship between volumetric analyses and duration of survival were examined. RESULTS: Mean volume of enhancing tumors in the T1-PG sequence was 43.93 cm3 and 48.30 cm3 (manual and MacDonald ellipsoid method respectively), while mean volume of abnormal signal intensity in the FLAIR sequence was 147.60 cm3. There was moderate correlation between the T1-PG and FLAIR volumes (r= 0.65). Average duration of survival from surgery was 341 days. Neither tumor volume measurements correlated with duration of survival. CONCLUSIONS: Rapid measurement of tumor volume is a reasonable and accurate estimate of manually traced tumor volumes. Both T1-PG and FLAIR alone do not correlate with survival in this small group of patients.
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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 | 0.003 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".