Dosimetric uncertainties of three‐dimensional dose reconstruction from two‐dimensional data in a multi‐institutional study
Bibliographic record
Abstract
Inconsistencies in the treatment planning process leading to dosimetric uncertainties may affect conclusions drawn from interinstitutional radiation oncology clinical trials. The purpose of this study was to assess the dosimetric uncertainties resulting from the process of reconstructing three-dimensional dose distributions from two-dimensional treatment plan information provided by participating institutions in a randomized clinical trial. This study was based on American College of Radiology Protocol #427, Locally Advanced Multi-Modality Protocol; a multi-institutional phase II randomized study involving radiation therapy for patients with inoperable non-small cell lung cancer. Several sources of dosimetric uncertainty were identified and analyzed, including image quality of hard-copy computed tomography (CT) images, slice spacing of CT scans, treatment position, interpretations of target volumes by radiation oncologists, the contouring of normal anatomic structures, and the use of common beam models for all dose calculations. Each source of uncertainty was investigated using a set of plans, with the ideal characteristics of digital images with 3-mm axial slice spacing and a flat couch, consisting of eight cases from Vanderbilt University Medical Center with electronically transferred CT data. The target volume DVH values were dependent on the additional uncertainty introduced by differences in delineation of the target volumes by the participating radiation oncologists. The DVH values for the lungs and heart were dependent on image quality and treatment position. Esophagus DVH values were not dependent on any of the sources of uncertainty. None of the structure DVH values were dependent on slice thickness or variations in the contouring of normal anatomic structures. Reconstruction of three-dimensional dose distributions from two-dimensional treatment plan information may be useful in cases for which digital CT data is not available or for historical data review. However, dosimetric accuracy will depend on image quality of the treatment planning CT data and consistency in the delineation of tumor volumes.
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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 | 0.120 | 0.204 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".