Variations of lung density and geometry on inhomogeneity correction algorithms: A Monte Carlo dosimetric evaluation
Bibliographic record
Abstract
This work contributed the following new information to the study of inhomogeneity correction algorithm: (1) Evaluation of lung dose calculation methods as a function of lung relative electron density (rhoe,lung) and treatment geometry and (2) comparison of doses calculated using the collapsed cone convolution (CCC) and adaptive convolution (AC) in lung using the Monte Carlo (MC) simulation with the EGSnrc-based code. The variations of rhoe,lung and geometry such as the position and dimension of the lung were studied with different photon beam energies and field sizes. Three groups of inhomogeneous lung phantoms, namely, "slab," "column," and "cube," with different positions, volumes, and shapes of lung in water as well as clinical computed tomography lung images were used. The rhoe,lung in each group of phantoms vary from 0.05 to 0.7. 6 and 18 MV photon beams with small (4 x 4 cm2) and medium (10 x 10 cm2) field sizes produced by a Varian 21 EX linear accelerator were used. This study reveals that doses in the inhomogeneous lung calculated by the CCC match well with those by AC within +/- 1%, indicating that the AC, with an advantage of shorter computing times (three to four times shorter than CCC), is a good substitute for CCC. Comparing the CCC and AC to MC in general, significant dose deviations are found when the rhoe,lung is < or =0.3. The degree of deviation depends on the photon beam energy and field size and is relatively large when high-energy photon beams with small fields are used. For penumbra widths (20%-80%), the CCC and AC agree well with MC for the slab and cube phantoms with the lung volumes at the central beam axis (CAX). However, deviations (>2 mm) occur in the column phantoms, with two lung volumes separated by a unit density column along the CAX in the middle using the 18 MV beam with 4 x 4 cm2 field for rhoe,lung < or =0.1. This study provides new dosimetric data to evaluate the impact of the variations of rhoe,lung and geometry on dose calculations in inhomogeneous media using CCC and AC.
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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".