Quantitative Computed Tomography Angiography for the Evaluation of Valvular Fibrocalcific Volume in Aortic Stenosis
Bibliographic record
Abstract
BACKGROUND: Aortic stenosis (AS) is characterized by calcification and fibrosis. The ability to quantify these processes simultaneously has been limited with previous imaging methods. OBJECTIVES: The purpose of this study was to evaluate the aortic valve fibrocalcific volume by computed tomography (CT) angiography in patients with AS, in particular, to assess its reproducibility, association with histology and disease severity, and ability to predict/track progression. METHODS: In 136 patients with AS, fibrocalcific volume was calculated on CT angiograms at baseline and after 1 year. CT attenuation distributions were analyzed using Gaussian-mixture-modeling to derive thresholds for tissue types enabling the quantification of calcific, noncalcific, and fibrocalcific volumes. Scan-rescan reproducibility was assessed and validation provided against histology and in an external cohort. RESULTS: Fibrocalcific volume measurements took 5.8 ± 1.0 min/scan, demonstrating good correlation with ex vivo valve weight (r = 0.51; P < 0.001) and excellent scan-rescan reproducibility (mean difference -1%, limits of agreement -4.5% to 2.8%). Baseline fibrocalcific volumes correlated with mean gradient on echocardiography in both male and female participants (rho = 0.64 and 0.69, respectively; both P < 0.001) and in the external validation cohort (n = 66, rho = 0.58; P < 0.001). The relationship was driven principally by calcific volume in men and fibrotic volume in women. After 1 year, fibrocalcific volume increased by 17% and correlated with progression in mean gradient (rho = 0.32; P = 0.003). Baseline fibrocalcific volume was the strongest predictor of subsequent mean gradient progression, with a particularly strong association in female patients (rho = 0.75; P < 0.001). CONCLUSIONS: The aortic valve fibrocalcific volume provides an anatomic assessment of AS severity that can track disease progression precisely. It correlates with disease severity and hemodynamic progression in both male and female patients.
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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 | 0.009 |
| Bibliometrics | 0.001 | 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".