RADT-53. IMPACT OF SMALLER CLINICAL TARGET VOLUME EXPANSIONS FOR THE RADIATION TREATMENT OF NEWLY DIAGNOSED GLIOBLASTOMA
Bibliographic record
Abstract
Abstract BACKGROUND With advances in image-guidance, there has been interest in smaller clinical target volume (CTV) expansions for radiation therapy planning in glioblastoma. We reviewed the impact of varying CTV expansion margins on patterns of recurrence in two patient cohorts. METHODS 412 consecutive adult glioblastoma patients treated with chemoradiation at a single institution and were included in the analysis with available pre-radiation and first recurrence imaging. A separate prospectively collected imaging cohort of 22 patients (NCT04188535) was used for validation. Multiple CTV expansions (0-2cm) were applied to the pre-radiation segmentation of enhancing tumor(GTVgad) and T2/FLAIR abnormality(GTVflair). CTVs were cropped to brain. We focus on an approach generously incorporating T2/FLAIR abnormality (Approach 1: CTV1 = [GTVgad+1.5cm] + [GTVflair+1.5cm]) and a more focal approach prioritizing enhancing disease (Approach 2: CTV2 = [GTVgad+1.5cm] + [GTVflair]). RESULTS The retrospective cohort included 412 patients with a median age of 60.1 (range 21.0-94.0), 46% patients underwent gross total resection, 43% KPS> 90, and 39% were MGMT promoter methylated. On multivariable analysis, CTV volume was associated with OS(p<0.01). With a more comprehensive approach (Approach 1), CTV1 was median 269.9cc (range 56.2cc-907.7cc), and the epicenter of recurrent tumor was covered in 93% of cases. With Approach 2, the CTV2 was median 154.0cc (range 37.5cc-475.2cc), and the epicenter of recurrent tumor was covered in 90% of cases. Given comparable patterns of in-field failure with both approaches, we evaluated coverage of subsequent progressive disease in a validation cohort with the more focal approach (Approach 2), and CTV2 covered the epicenter of recurrent tumor in all 22 (100%) cases with a median CTV 175.4cc (range 71.9cc-316.2cc). CONCLUSION Smaller CTV margins significantly decrease integral brain radiation dose without a significantly increased risk of out-of-field failure. Target delineation approaches utilizing smaller CTV expansions in conjunction with advanced imaging may meaningfully decrease treatment-related toxicity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".