Energy‐dependent <scp>OAR</scp> sparing and dose conformity for total marrow irradiation of obese patients
Bibliographic record
Abstract
Abstract Purpose To investigate the effect on target coverage and organs at risk sparing by using 10 versus 6 MV for VMAT total marrow irradiation of obese patients. Methods and Materials Twenty‐six total marrow irradiation, TMI, treatment plans delivered between December 2014 and June 2017 were reviewed and 10 were chosen for replanning based on patient characteristics and plan metrics. Beam geometry and isocenter placement were conserved, energy was changed from 6 to 10 MV and plans were reoptimized. Resulting dose distributions were compared to original plans to evaluate any potential advantage of choosing one energy over the other. Results Target coverage and total monitor units were consistent between the 6 and 10 MV plans when averaged over all ten patients. Improvement in the conformity index (−11.0%, P = 0.009) when using 10 MV was statistically significant compared to the 6 MV plans. Volumes of normal tissue receiving 50%, 75%, and 90% Rx all decreased for the 10 MV plans compared to the original 6 MV plans. The mean dose to individual OARs decreased significantly for all investigated structures except for the lenses, oral cavity, and genitalia. The largest decreases in Dmean were found for the rectum (22.4%, P = 0.004) and bladder (18.1%, P = 0.005). The three highest priorities for sparing during plan optimization (lungs, liver, and heart), showed decreases of 7.6%, 16.1%, and 13.0%. Conclusions Use of a higher energy 10 MV beam provided similar dose to target while achieving increased OAR and normal tissue sparing for the patients reviewed in this study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".