Comparing preoperative imaging modalities in patient selection for breast intraoperative radiotherapy
Bibliographic record
Abstract
BACKGROUND: This study evaluated the relative accuracy of mammography, ultrasound, and magnetic resonance imaging (MRI) in predicting the tumor size of early stage breast tumors in preoperative selection of patients for intraoperative radiotherapy (IORT). METHODS: We identified 156 patients with clinical T1/T2, N0 breast cancer who underwent IORT. Clinical, pathologic, and radiation data were collected. The preoperative tumor size obtained by imaging was compared with tumor pathological size. RESULTS: The median patient age was 66. The mean tumor size at excision was 1.05 cm (0.1-3.0 cm). Out of the 156 patients, 98 had a reported, nonzero tumor size by mammography, 131 by ultrasound, and 76 by MRI. The mean difference between imaging and the tumor size was +0.062 ± 0.54 cm for mammography, -0.11 ± 0.43 cm for ultrasound, and +0.33 ± 0.55 cm for MRI, with positive values indicating an overestimate of the tumor size. MRI produced more overestimates of tumor size of at least 0.5 cm than mammography or ultrasound in a paired analysis of patients who received both modalities. CONCLUSIONS: Accuracy of imaging modalities in determining tumor size can influence patients' eligibility for IORT. Mammography and ultrasound showed acceptable accuracy in predicting size. MRI overestimated tumor size and may inappropriately exclude patients from IORT. We would discourage ruling out candidates for IORT on the basis of large size by MRI alone.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".