Clinical impact of using the deterministic patient dose calculation algorithm Acuros XB for lung stereotactic body radiation therapy
Bibliographic record
Abstract
PURPOSE: To evaluate the clinical impact of using the deterministic dose calculation algorithm, Acuros XB, for early stage lung cancer patients undergoing stereotactic body radiotherapy (SBRT). MATERIAL AND METHODS: Seventy-seven stage I non-small cell lung cancer patients who underwent lung SBRT from 2008 to 2012 at our center were included in this study. All treatment plans originally calculated by the anisotropic analytical algorithm (AAA) were recalculated using the AAA and Acuros XB algorithms with identical monitor units and beam arrangements. The dose, dose distribution, conformality number (CN) and heterogeneity index (HI) of the target were determined for each plan. A paired matched t-test was used to evaluate the difference between the mean dose, the dose distribution, and the CN and HI for the target. The importance of tumor (volume, location), patient (pulmonary functional, body mass index) and treatment (number of SBRT beams) on the dose distributions obtained from the two algorithms was statistically determined using linear regression analyses. RESULTS: The mean target dose was same for both algorithms. Compared to AAA, a small and significant difference in dose distribution in the target was found for the Acuros XB algorithm, resulting in lower conformity (-2.1%, p < 0.0001) and higher heterogeneity (p < 0.0001) of dose. Single logistic regression identified pulmonary function, number of beams and target location as being correlated with the difference of CN between the two calculations. Multivariate analysis indicated that the patient's pulmonary function (p = 0.0296) was the only predictor for the difference in conformality between the two dose calculation algorithms. CONCLUSIONS: In lung SBRT, the patient's pulmonary function is responsible for the difference in target dose distribution between the Acuros XB and AAA algorithms. The Acuros XB algorithm could be used to advantage in patients with compromised pulmonary function based on its accurate modeling of lung tissue in comparison to AAA.
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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 | 0.002 | 0.012 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".