Abstract 16524: Cardiac MRI Evaluation of Myocardial Deformation in Repaired Tetralogy of Fallot Provides Insight Into Right Ventricular Mechanics
Bibliographic record
Abstract
Introduction: Pulmonary regurgitation or stenosis after repaired tetralogy of Fallot (TOF) impacts the long-term ventricular mechanics. Our objective was to measure RV myocardial deformation using novel CMR software in repaired TOF. We postulate that RV strain will correlate with cardiac MRI (CMR) volumetric data. Methods: Retrospective study of 55 patients s/p TOF repair compared to 40 normal controls. RV longitudinal strain was measured from the standard 4-chamber view and circumferential strain from the short axis slice apical to the RV outflow tract. Using CMR software developed in-house that utilizes a semi-automatic segmentation program, peak strain was identified. Unpaired t test assessed differences between groups and correlation was performed between strain and volumetric data. Results: The predominant lesion was regurgitation in 48 (regurgitant fraction (RF) 43±2%), stenosis in 10 (peak gradient 32±2 mmHg), and mixed in 4. Longitudinal strain was reduced in TOF compared to controls while circumferential strain was preserved (Table 1). Correlations found reduced strain with increasing volumes and decreasing right ventricular ejection fraction (RVEF) (Table 2). Longitudinal:circumferential ratio (L/C) increased with increasing volumes and decreasing RVEF. No relationship was found between RV strain and RF. Conclusions: The relationships between longitudinal and circumferential strain, and the L/C ratio with RV volumes and RVEF suggest that preservation of circumferential strain is important in maintaining RV systolic function. Measurement of RV deformation may provide insight into the RV’s response to volume or pressure overload in TOF, suggesting we should focus on RV mechanical changes rather than RF when managing these patients.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.006 | 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".