Energy modulated electron therapy using a few leaf electron collimator in combination with IMRT and 3D‐CRT: Monte Carlo‐based planning and dosimetric evaluation
Bibliographic record
Abstract
Energy modulated electron therapy (EMET) based on Monte Carlo dose calculation is a promising technique that enhances the treatment planning and delivery of superficially located tumors. This study investigated the application of EMET using a novel few-leaf electron collimator (FLEC) in head and neck and breast sites in comparison with three-dimensional conventional radiation therapy (3D-CRT) and intensity modulated radiation therapy (IMRT) techniques. Treatment planning was performed for two parotid cases and one breast case. Four plans were compared for each case: 3D-CRT, IMRT, 3D-CRT in conjunction with EMET (EMET-CRT), and IMRT in conjunction with EMET (EMET-IMRT), all of which were performed and calculated with Monte Carlo techniques. For all patients, dose volume histograms (DVHs) were obtained for all organs of interest and the DVHs were used as a means of comparing the plans. Homogeneity and conformity of dose distributions were calculated, as well as a sparing index that compares the effect of the low isodose lines. In addition, the whole-body dose equivalent (WBDE) was estimated for each plan. Adding EMET delivered with the FLEC to 3D-CRT improves sparing of normal tissues. For the two head and neck cases, the mean dose to the contralateral parotid and brain stem was reduced relative to IMRT by 43% and 84%, and by 57% and 71%, respectively. Improved normal tissue sparing was quantified as an increase in sparing index of 47% and 30% for the head and neck and the breast cases, respectively. Adding EMET to either 3D-CRT or IMRT results in preservation of target conformity and dose homogeneity. When adding EMET to the treatment plan, the WBDE was reduced by between 6% and 19% for 3D-CRT and by between 21% and 33% for IMRT, while WBDE for EMET-CRT was reduced by up to 72% when compared with IMRT. FLEC offers a practical means of delivering modulated electron therapy. Although adding EMET delivered using the FLEC results in perturbation of target conformity when compared to IMRT, it significantly improves normal tissue sparing while offering enhanced target conformity to the 3D-CRT planning. The addition of EMET systematically leads to a reduction in WBDE especially when compared with IMRT.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".