Water‐silicone separated volumetric MR acquisition for rapid assessment of breast implants
Bibliographic record
Abstract
PURPOSE: To develop a robust T(2) -weighted volumetric imaging technique with uniform water-silicone separation and simultaneous fat suppression for rapid assessment of breast implants in a single acquisition. MATERIALS AND METHODS: A three-dimensional (3D) fast spin echo sequence that uses variable refocusing flip angles was combined with a three-point chemical-shift technique (IDEAL) and short tau inversion recovery (STIR). Phase shifts of -π/6, +π/2, and +7π/6 between water and silicone were used for IDEAL processing. For comparison, two-dimensional images using 2D-FSE-IDEAL with STIR were also acquired in axial, coronal, and sagittal orientations. RESULTS: Near-isotropic (true spatial resolution-0.9 × 1.3 × 2.0 mm(3) ) volumetric breast images with uniform water-silicone separation and simultaneous fat suppression were acquired successfully in clinically feasible scan times (7:00-10:00 min). The 2D images were acquired with the same in-plane resolution (0.9 × 1.3 mm(2) ), but the slice thickness was increased to 6 mm with a slice gap of 1 mm for complete coverage of the implants in a reasonable scan time, which varied between 18:00 and 22:30 min. CONCLUSION: The single volumetric acquisition with uniform water and silicone separation enables images to be reformatted into any orientation. This allows comprehensive assessment of breast implant integrity in less than 10 min of total examination time.
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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 | 0.001 | 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".