Dedicated Breast CT: Initial Clinical Experience
Bibliographic record
Abstract
PURPOSE: To prospectively and intraindividually compare dedicated breast computed tomographic (CT) images with screen-film mammograms. MATERIALS AND METHODS: All patient studies were performed according to protocols approved by the institutional review board and Radiation Use Committee; informed consent was obtained. A breast CT scanner prototype was used to individually scan uncompressed breasts in 10 healthy volunteers (mean age, 52.1 years) and 69 women with Breast Imaging Reporting and Data System category 4 and 5 lesions (mean age, 54.4 years). In women with lesions, breast CT images were compared with screen-film mammograms by an experienced mammographer and ranked with a continuous scale of 1-10 (score 1, excellent lesion visualization with CT and poor visualization with mammography; score 5.5, equal visualization with both modalities; and score 10, poor visualization with CT and excellent visualization with mammography). A Wilcoxon signed rank procedure was used to test the null hypothesis that ratings were symmetric at about a score of 5.5 for the entire group and for distinguishing microcalcifications versus masses and other findings and benign versus malignant lesions and for effect of breast density on lesion visualization. Women were asked to compare their comfort during CT with that during mammography on a continuous scale of 1-10. With a Wilcoxon signed rank procedure, the null hypothesis that comfort ratings were symmetric about a score of 5.5 (equal comfort with CT and mammography) was tested. RESULTS: Overall, CT was equal to mammography for visualization of breast lesions. Breast CT was significantly better than mammography for visualization of masses (P = .002); mammography outperformed CT for visualization of microcalcifications (P = .006). No significant differences between CT and mammography were seen among benign versus malignant lesions or for effect of breast density on lesion visualization. Subjects found CT significantly more comfortable than mammography (P < .001). CONCLUSION: Some technical challenges remain, but breast CT is promising and may have potential clinical applications.
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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 | 0.008 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".