Three‐dimensional ultrasound system for guided breast brachytherapy
Bibliographic record
Abstract
Breast-conserving surgery combined with subsequent radiation therapy is a standard procedure in breast cancer treatment. The disadvantage of whole-breast beam irradiation is that it requires 20-25 treatment days, which is inconvenient for patients with limited mobility or who reside far from the treatment center. However, interstitial high-dose-rate (HDR) brachytherapy is an irradiation method requiring only 5 treatment days and that delivers a lower radiation dose to the surrounding healthy tissue. It involves delivering radiation through 192Ir seeds placed inside the catheters, which are inserted into the breast. The catheters are attached to a HDR afterloader, which controls the seed placement within the catheters and irradiation times to deliver the proper radiation dose. One disadvantage of using HDR brachytherapy is that it requires performing at least one CT scan during treatment planning. The procedure at our institution involves the use of two CT scans. Performing CT scans requires moving the patient from the brachytherapy suite with catheters inserted in their breasts. One alternative is using three-dimensional ultrasound (3DUS) to image the patient. In this study, the authors developed a 3DUS translation scanning system for use in breast brachytherapy. The new system was validated using CT, the current clinical standard, to image catheters in a breast phantom. Once the CT and 3DUS images were registered, the catheter trajectories were then compared. The results showed that the average angular separation between catheter trajectories was 2.4 degrees, the average maximum trajectory separation was 1.0 mm, and the average mean trajectory separation was found to be 0.7 mm. In this article, the authors present the 3DUS translation scanning system's capabilities as well as its potential to be used as the primary treatment planning imaging modality in breast brachytherapy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".