The radiographic quantitation of aortic valve calcification: implications for assessing bioprosthetic valve calcification<i>in vitro</i>
Bibliographic record
Abstract
Calcification of natural aortic and bioprosthetic heart valves is a poorly understood phenomenon that results in valvular obstruction and tissue failure. We describe a non-destructive quantitative computed microtomographic (QCT) technique for determining both calcium content and local calcium distribution within explanted valves. As a reference standard, a dual-energy x-ray absorptiometry (DEXA) system with an accuracy demonstrated to be within 1% of the true calcium mass of test material was used to obtain the total calcium content of 24 human aortic valve cusps recovered at autopsy from patients aged 51-80 years. These cusps were then scanned using our unique volume QCT scanner, with multiple x-ray projections acquired by rotating the explanted tissue through a single axis of rotation. A three-dimensional cross-sectional map was reconstructed for each cusp. Voxel size was 0.003 mm3 and a calibration phantom was used to calculate calcium content. The minimum detection limit for calcium mass was 1 mg within the whole cusp. The DEXA and QCT scans were compared with respect to total calcium content, which ranged from 0 to 15 mg. An excellent correlation between the two independent techniques was demonstrated with an r2 value of 0.94 (p < 0.001). Non-destructive microtomographic CT scanning provided excellent volumetric density measurements, with quantitative 3D images permitting an assessment of any individual area of the cusp for calcium content and spatial distribution. This new approach to valve tissue analysis allows for subsequent histologic assessment.
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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 | 0.002 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".