Axillary Lymph Node Coverage in Breast Cancer Patients Treated with Adjuvant Radiation Using High Tangent Fields Technique: A Single Institution’s Experience
Bibliographic record
Abstract
Background: The high tangent field (HTF) technique is used to provide radiation coverage of the inferior axillary nodal levels for breast cancer patients when the lower axilla is at risk for micrometastatic disease. Despite its use in clinical practice, there is concern about whether HTF provide sufficient coverage of level I and II axillary nodal regions. The purpose of this study is to quantify and evaluate the coverage of HTF at our institution. Methods: Patients diagnosed with early invasive breast carcinoma (pT1-2 pN0-1a) who received HTF radiation between January 1st, 2012 and December 31st, 2016 were retrospectively reviewed. Level I and II axillary nodal regions were contoured on each patient’s simulation CT. Dosimetric parameters were re-calculated to evaluate coverage. Statistical analysis was conducted using Mann-Whitney-U method. Results: Thirty-seven patients with low-risk breast adenocarcinoma were included. For level I and II, the mean V90% was 94.63% ± 7.60% and 73.33% ± 21.83% respectively. Twenty-nine patients received adequate V90% coverage of level I and had a mean level II V90% of 76% ± 18.71% while eight patients who did not receive adequate V90% level I coverage had a mean level II V90% of 63.64% ± 30.22%. The median level II V90% of patients receiving adequate and inadequate level I V90% was 77.74% and 71.11% respectively; the difference was not statistically significant (P = 0.33). Conclusion: HTF provides adequate coverage for level I nodes, but inadequate coverage for level II. Contouring nodal volumes may assist field placement and improve nodal volume coverage.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".