An in-depth Monte Carlo study of lateral electron disequilibrium for small fields in ultra-low density lung: implications for modern radiation therapy
Bibliographic record
Abstract
Modern radiation therapy techniques such as intensity-modulated radiation therapy (IMRT) and stereotactic body radiation therapy (SBRT) use tightly conformed megavoltage x-ray fields to irradiate a tumour within lung tissue. For these conditions, lateral electron disequilibrium (LED) may occur, which systematically perturbs the dose distribution within tumour and nearby lung tissues. The goal of this work is to determine the combination of beam and lung density parameters that cause significant LED within and near the tumour. The Monte Carlo code DOSXYZnrc (National Research Council of Canada, Ottawa, ON) was used to simulate four 20 × 20 × 25 cm(3) water-lung-water slab phantoms, which contained lung tissue only, or one of three different centrally located small tumours (sizes: 1 × 1 × 1, 3 × 3 × 3, 5 × 5 × 5 cm(3)). Dose calculations were performed using combinations of six beam energies (Co-60 up to 18 MV), five field sizes (1 × 1 cm(2) up to 15 × 15 cm(2)), and 12 lung densities (0.001 g cm(-3) up to 1 g cm(-3)) for a total of 1440 simulations. We developed the relative depth-dose factor (RDDF), which can be used to characterize the extent of LED (RDDF <1.0). For RDDF <0.7 severe LED occurred, and both lung and tumour dose were drastically reduced. For example, a 6 MV (3 × 3 cm(2)) field was used to irradiate a 1 cm(3) tumour embedded in lung with ultra-low density of 0.001 g cm(-3) (RDDF = 0.2). Dose in up-stream lung and tumour centre were reduced by as much as 80% with respect to the water density calculation. These reductions were worse for smaller tumours irradiated with high energy beams, small field sizes, and low lung density. In conclusion, SBRT trials based on dose calculations in homogeneous tissue are misleading as they do not reflect the actual dosimetric effects due to LED. Future clinical trials should only use dose calculation engines that can account for electron scatter, with special attention given to patients with low lung density (i.e. emphysema). In cases where tissue inhomogeneity corrections are applied, the nature of the correction used may be inadequate in predicting the correct level of LED. In either case, the dose to the tumour is not the prescribed dose and clinical response data are uncertain. The new information from this study can be used by radiation oncologists who wish to perform advanced radiation therapy techniques while avoiding the deleterious predictable dosimetric effects of LED.
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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 | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".