Coronary computed tomography angiography to guide percutaneous coronary intervention: Expert opinion from a SCAI/SCCT roundtable
Bibliographic record
Abstract
Coronary computed tomography angiography (CCTA) has emerged as an important tool for planning percutaneous coronary intervention (PCI). While it has traditionally been employed for diagnostic purposes, increasing evidence and real-world experience suggest that CCTA can be used for the pre-procedural planning of PCI and inform patient triage, shared decision-making, case complexity, and resource use. This approach mirrors how computed tomography angiography is routinely used to plan structural interventions. To address these emerging opportunities, the Society for Cardiovascular Angiography & Interventions (SCAI) and the Society of Cardiovascular Computed Tomography (SCCT) organized a multidisciplinary, expert scientific roundtable on the use of CCTA for guiding PCI. The goal of this document is to provide a state-of-the-art overview of CCTA-guided PCI, focused on practical applications and key coronary lesion subsets, define unmet needs and barriers, and outline future directions.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".