Three-dimensional thoracic aorta principal strain analysis from routine ECG-gated computerized tomography: feasibility in patients undergoing transcatheter aortic valve replacement
Bibliographic record
Abstract
BACKGROUND: Functional impairment of the aorta is a recognized complication of aortic and aortic valve disease. Aortic strain measurement provides effective quantification of mechanical aortic function, and 3-dimenional (3D) approaches may be desirable for serial evaluation. Computerized tomographic angiography (CTA) is routinely performed for various clinical indications, and offers the unique potential to study 3D aortic deformation. We sought to investigate the feasibility of performing 3D aortic strain analysis in a candidate population of patients undergoing transcatheter aortic valve replacement (TAVR). METHODS: Twenty-one patients with severe aortic valve stenosis (AS) referred for TAVR underwent ECG-gated CTA and echocardiography. CTA images were analyzed using a 3D feature-tracking based technique to construct a dynamic aortic mesh model to perform peak principal strain amplitude (PPSA) analysis. Segmental strain values were correlated against clinical, hemodynamic and echocardiographic variables. Reproducibility analysis was performed. RESULTS: and mean AS pressure gradient (MG) 44±11 mmHg. CTA-based 3D PPSA analysis was feasible in all subjects. Mean PPSA values for the global thoracic aorta, ascending aorta, aortic arch and descending aorta segments were 6.5±3.0, 10.2±6.0, 6.1±2.9 and 3.3±1.7%, respectively. 3D PSSA values demonstrated significantly more impairment with measures of worsening AS severity, including AVA and MG for the global thoracic aorta and ascending segment (p<0.001 for all). 3D PSSA was independently associated with AVA by multivariable modelling. Coefficients of variation for intra- and inter-observer variability were 5.8 and 7.2%, respectively. CONCLUSIONS: Three-dimensional aortic PPSA analysis is clinically feasible from routine ECG-gated CTA. Appropriate reductions in PSSA were identified with increasing AS hemodynamic severity. Expanded study of 3D aortic PSSA for patients with various forms of aortic disease is warranted.
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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) | 0.001 | 0.012 |
| 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 | 0.000 |
| 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".