Opportunistic Identification of Coronary Artery Calcium and Valve/Vascular Calcifications on Chest X-Ray: Improvements With Single-ExposureDual-Energy Imaging
Bibliographic record
Abstract
Purpose: To evaluate whether single-exposure, dual-energy chest X-ray (DEX) improves visualization of coronary artery calcium (CAC) and valve/vascular calcifications compared to conventional X-ray. Materials and Methods: Sixty-one bone-marrow transplant patients (22- 79 years; median 61; IQR 15; w/m, 24/37), underwent single-exposure dual-energy X-ray (Reveal 35C, KA imaging) in pa and lateral projection, followed by a standard-of-care chest CT. Two DEX pairs (pa/lateral) were calculated: a composite image (COMP) and a bone image with soft-tissue subtraction (BI). The COMP pair was reviewed by 2 chest radiologists, assessing the presence/absence of CAC and valve/vascular calcifications on a confidence scale from −2 (confidently not present) to 2 (confidently present). Subsequently, the BI pair was revealed, and readers reevaluated both pairs (COMP and BI) jointly using the identical scale. CTCAC scores were categorized according to the CAC-DRS (0-3) and served as standard of reference, valve/vascular calcifications were categorized on CT as present or absent. Results: For detecting CAC on DEX in any CAC-DRS category (1-3), in category 2-3, in category 3, and for valve/vascular calcifications, the ROC-AUC (combined for both readers) for COMP images was 0.74 (CI: 0.64-0.84), 0.81 (CI: 0.68-0.94), 0.84 (CI: 0.69-0.98), and 0.90 (CI: 0.83-0.99), and for the BI images 0.91 (CI: 0.83-0.98), 0.94 (CI: 0.86- 1.00), 0.89 (CI: 0.77-1.00), and 0.98 (CI: 0.96-1.00), with P = .0003, P = .044, P = .42, and P = .55, respectively. The Intraclass-Correlation-Coefficient (ICC) for CAC on COMP/BI was 0.973/0.954, and for valve/vascular calcifications 0.971/0.965. Conclusion: Single-exposure, dual-energy acquisition improves diagnostic confidence for coronary artery calcium and valve/vascular calcification identification on chest X-rays.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".