PS1 -131 Dosimetric Feasibility of the Hybrid Magnetic Resonance Imaging (MRI)-LINAC System for Brain Metastases
Bibliographic record
Abstract
We aimed to investigate the feasibility of delivering stereotactic radiosurgery (SRS) or hypofractionated stereotactic radiotherapy with the hybrid MRI-LINAC (MRL) system for patients with single brain metastases, and to characterize the dosimetric impact at tissue-air interfaces resulting from the electron return effect (ERE). Material/Methods: 24 patients treated for intact single brain metastases were selected for analysis. Three optimized radiotherapy plans with the same prescribed dose were generated for each case: 1) standard noncoplanar volumetric modulated arc therapy (VMAT), 2) coplanar step-and-shoot intensity modulated radiotherapy (IMRT) on the MRL in the absence (MRL_B=0), and 3) in the presence of the transverse magnetic field (MRL_B=1.5). The plans were evaluated using cumulative dose-volume histograms (DVHs) and by calculation of Paddick conformity index (PCI), V100%, V12Gy minus gross tumor volume (V12Gy – GTV), and V2Gy. The dosimetric impact of ERE to the skin and air cavities was quantified using a 5 mm rim of tissue around tissue-air boundaries. Results: All plans met the objectives with respective to target coverage and OAR constraints. Differences between all investigated dosimetric parameters significantly favored the VMAT plans as compared to the MRL_B=0 and MRL_B=1.5 plans, except for V2Gy. The VMAT plans showed a higher mean (±standard deviation) PCI compared to the MRL_B=0 and MRL_B=1.5 plans (0.85±0.08 vs. 0.79±0.09 vs. 0.78±0.11). In the presence of the magnetic field, ERE resulted in a statistically significant but small increase in mean dose and D2cc in the skin (0.08 Gy, p < 0.0001 and 0.66 Gy, p < 0.0001, respectively) and around air cavities (0.07 Gy, p = 0.0092 and 0.25 Gy, p = 0.0004, respectively). Conclusions: Stereotactic radiation to single brain metastases is feasible using the MRL Monaco treatment planning system; however, in its current iteration, application to small targets deserve careful consideration given the technical limitations resulting in less favorable plan quality compared to that of a noncoplanar standard VMAT technique. The dosimetric impact of ERE at tissue-air boundaries is minor and does not compromise target conformity or dose gradient.
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 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 | 0.008 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.003 | 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; both teacher heads agree on what is shown here.
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".