Comprehensive dosimetric planning comparison for early‐stage, non‐small cell lung cancer with SABR: fixed‐beam IMRT versus VMAT versus TomoTherapy
Bibliographic record
Abstract
Volumetric-modulated arc therapy (VMAT) is emerging as a leading technology in treating early-stage, non-small cell lung cancer (NSCLC) with stereotactic ablative radiotherapy (SABR). However, two other modalities capable of deliver-ing intensity-modulated radiation therapy (IMRT) include fixed-beam and helical TomoTherapy (HT). This study aims to provide an extensive dosimetric compari-son among these various IMRT techniques for treating early-stage NSCLC with SABR. Ten early-stage NSCLC patients were retrospectively optimized using three fixed-beam techniques via nine to eleven beams (high and low modulation step-and-shoot (SS), and sliding window (SW)), two VMAT techniques via two partial arcs (SmartArc (SA) and RapidArc (RA)), and three HT techniques via three different fan beam widths (1 cm, 2.5 cm, and 5 cm) for 80 plans total. Fixed-beam and VMAT plans were generated using flattening filter-free beams. SS and SA, HT treatment plans, and SW and RA were optimized using Pinnacle v9.1, Tomoplan v.3.1.1, and Eclipse (Acuros XB v11.3 algorithm), respectively. Dose-volume histogram statistics, dose conformality, and treatment delivery efficiency were analyzed. VMAT treatment plans achieved significantly lower values for contralat-eral lung V5Gy (p ≤ 0.05) compared to the HT plans, and significantly lower mean lung dose (p < 0.006) compared to HT 5 cm treatment plans. In the comparison between the VMAT techniques, a significant reduction in the total monitor units (p = 0.05) was found in the SA plans, while a significant decrease was observed in the dose falloff parameter, D2cm, (p = 0.05), for the RA treatments. The maximum cord dose was significantly reduced (p = 0.017) in grouped RA&SA plans com-pared to SS. Estimated treatment time was significantly higher for HT and fixed-beam plans compared to RA&SA (p < 0.001). Although, a significant difference was not observed in the RA vs. SA (p = 0.393). RA&SA outperformed HT in all parameters measured. Despite an increase in dose to the heart and bronchus, this study demonstrates that VMAT is dosimetrically advantageous in treating early-stage NSCLC with SABR compared to fixed-beam, while providing significantly shorter treatment times.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".