Evaluation of tattoo reliability in breast cancer re-irradiation
Bibliographic record
Abstract
Background Tattoos help guide field placement in breast re-irradiation. This study evaluates the stability of medial tattoos in patients with prior breast radiotherapy (RT) to determine their reliability as surface markers. Materials and methods We retrospectively identified patients who had breast/chest wall re-irradiation between January 2022 and December 2023 (RT 2 ) and prior breast RT (RT 1 ) at our institution. Planning CTs for both RT courses were registered using rigid image registration. The medial tattoo, sternum, and internal perforating branches of the internal thoracic vessels were contoured on both CT 1 and CT 2 , and POIs were placed at the respective centers to assess shifts and 3D distances reported as target registration errors (TRE). Results Eighteen patients were included, average sternum 3D TRE was 0.8 mm(SD0.8), within CT voxel thickness. The average medial tattoo 3D TRE was 9.2 mm(SD5.4). Significantly greater 3D TRE was observed in patients whose arm positions varied between scans (Same: 4.7 mm vs Different: 10.9 mm, p = 0.002). The largest 3D TRE was 22.1 mm, observed in a patient who had a mastectomy before RT 2 . The average vessels 3D TRE was 4.1 mm (SD2.3) and impacted by arm position (Different = 4.4 mm vs Same = 2.9 mm, p = 0.009). Conclusion Relying solely on previous medial tattoos as indicators of the previous RT field border can be inaccurate due to arm positioning and surgical procedure changes that impact surface anatomy over time. Reproducing the patient's original setup and arm positioning is essential to reducing registration errors in breast re-irradiation. If varying arm positions are unavoidable, internal thoracic perforator vessels may provide more robust registration.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 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".