Murray law-based quantitative flow ratio for assessment of left main bifurcation derived from a single fluoroscopic angiographic view as compared to FFRCT
Bibliographic record
Abstract
Abstract Background In patients with complex CAD, the presence of left main (LM) disease is an important prognostic factor in assessing the risk balance between PCI and CABG. Functional assessment has become standard of care to evaluate the significance of coronary stenosis and to justify the performance of PCI in the contemporary practice. FFRCT is a well-established method based on 3D reconstruction of coronary artery derived from CCTA. The Murray law-based quantitative flow reserve (μQFR) is a novel computational method of invasive angiography relying on a single angiographic view that takes into account side branches diameters to compute fractal flow division. The aim of the current analysis is to evaluate in patients with complex CAD the feasibility of μQFR in LM bifurcation and its diagnostic concordance with FFRCT. The impact of the optimal viewing angle defined by CCTA on the physiological assessment of the LM bifurcation using a single angiographic view was also evaluated. Methods In 299 consecutive patients with 3-vessel disease with or without LM coronary artery disease, up to 3 analyzable fluoroscopic projections per patient were analysed with μQFR retrospectively. FFRCT and μQFR were measured at 3 fiducial landmark points: i) point of LM bifurcation (POB); ii) proximal LAD 10 mm distal to POB; ii) proximal LCX 10 mm distal to POB. CCTA-based “optimal viewing angle” of LM bifurcation are computed by creating a 3-point closed spline involving the LM, LAD, and LCX at 5mm from the POB and subsequently by reconstructing the “en face” fluoroscopic viewing angle of the spline. The en face viewing angle provides an optimal assessment of the bifurcation geometry [1]. In terms of Rx gantry angulation, the closest angiographic projection to the optimal viewing angle derived from CCTA was defined as the “best fluoroscopic projection” for each patient. Results In 299 patients, 793 projections were analysed with μQFR and compared to FFRCT. Single view μQFR was analyzable in 100%. Correlation and agreement between μQFR and FFRCT for 793 projections in 299 patients are shown in Figure 1A, 2A. The Spearman's correlation coefficient showed moderate correlations at POB (r=0.481, p<0.001) and LCX (r=0.584, p<0.001), and strong correlation at LAD (r=0.642, p<0.001). Correlation and agreement between μQFR and FFRCT for best projections from each patient are shown in Figure 1B, 2B. Correlations were improved in the best projections with the following Spearman's correlation coefficient: at POB (r=0.522, p<0.001), LCX (r=0.622, p<0.001), and LAD (r=0.695, p<0.001). Conclusion Computation of μQFR from a single angiographic view has a high feasibility. Tailored optimal fluoroscopic view is essential for the physiological assessment of the LM bifurcation using a single angiographic view. Evaluation of diagnostic accuracy of μQFR warrants further analysis of the LMCAD after prospective planning of the optimal fluoroscopic view based on the selection of the best CCTA 3D view. Funding Acknowledgement Type of funding sources: None.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".