FFR<sub>CT</sub> for Complex Coronary Artery Disease Treatment Planning: New Opportunities
Bibliographic record
Abstract
Coronary computed tomography (CT) is well established for the assessment of symptomatic patients with suspected but not yet confirmed coronary artery disease with high diagnostic accuracy and risk prediction. Until recently, coronary computed tomography angiography (CTA) has played a limited role in the management of complex coronary artery disease (CAD) and in planning revascularisation strategies. With the advent of FFR CT , enabling anatomy and physiology with a single study and the ability to adjudicate lesion specific pressure loss, the potential of combined coronary CT angiography (CCTA) and fractional flow reserve (FFR) computed from non-invasive CT angiography (FFR CT ) to inform treatment decision-making and help guide revascularisation has been recognised. In this review, we highlight the evolving role of FFR CT in the management of complex CAD; the opportunities, the data and the unanswered questions.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".