Analysis of left ventricle regional myocardial motion for cardiac radioablation
Bibliographic record
Abstract
PURPOSE: Left ventricle (LV) regional myocardial displacement due to cardiac motion was assessed using cardiovascular magnetic resonance (CMR) cine images to establish region-specific margins for cardiac radioablation treatments. METHODS: CMR breath-hold cine images and LV myocardial tissue contour points were analyzed for 200 subjects, including controls (n = 50) and heart failure (HF) patients with preserved ejection fraction (HFpEF, n = 50), mid-range ejection fraction (HFmrEF, n = 50), and reduced ejection fraction (HFrEF, n = 50). Contour points were divided into segments according to the 17-segment model. For each patient, contour point displacements were determined for the long-axis (all 17 segments) and short-axis (segments 1-12) directions. Mean overall, tangential (longitudinal or circumferential), and normal (radial) displacements were calculated for the 17 segments and for each segment level. RESULTS: The greatest overall motion was observed in the control group-long axis: 4.5 ± 1.2 mm (segment 13 [apical anterior] epicardium) to 13.8 ± 3.0 mm (segment 6 [basal anterolateral] endocardium), short axis: 4.3 ± 0.8 mm (segment 9 [mid inferoseptal] epicardium) to 11.5 ± 2.3 mm (segment 1 [basal anterior] endocardium). HF patients exhibited lesser motion, with the smallest overall displacements observed in the HFrEF group-long axis: 4.3 ± 1.7 mm (segment 13 [apical anterior] epicardium) to 10.6 ± 3.4 mm (segment 6 [basal anterolateral] endocardium), short axis: 3.9 ± 1.3 mm (segment 8 [mid anteroseptal] epicardium) to 7.4 ± 2.8 mm (segment 1 [basal anterior] endocardium). CONCLUSIONS: This analysis provides an estimate of epicardial and endocardial displacement for the 17 segments of the LV for patients with normal and impaired LV function. This reference data can be used to establish treatment planning margin guidelines for cardiac radioablation. Smaller margins may be used for patients with higher degree of impaired heart function, depending on the LV segment.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".