ArticleClinical Medicine Insights. Cardiology2019
Impact of Cine Frame Selection on Quantitative Coronary Angiography Results.
Article in Clinical Medicine Insights. Cardiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Inter- and intra-core laboratory variability in the quantitative coronary angiography analysis for drug-eluting stent treatment and follow up.Therapeutic advances in cardiovascular diseaseTrial
- Deep learning-based treatment decision support framework for multi-vessel coronary artery disease using integrated coronary angiography and clinical data.BMC medical informatics and decision making · 2026Article
- The current state of artificial intelligence-based invasive coronary angiography image analysis: a systematic review.European heart journal. Digital health · 2026Review
- Artificial Intelligence Powered Real-Time Coronary Stenosis Recognition and Quantification in Angiography.Journal of imaging informatics in medicine · 2026Article
- Benchmarking Photon-Counting Computed Tomography Angiography Against Invasive Assessment of Coronary Stenosis: Implications for Severely Calcified Coronaries.JACC. Cardiovascular imaging · 2025Article
- Stent visualization methods to guide percutaneous coronary interventions and assess long-term patency.World journal of cardiology · 2021Review
- Clinical expert consensus document on quantitative coronary angiography from the Japanese Association of Cardiovascular Intervention and Therapeutics.Cardiovascular intervention and therapeutics · 2020Article
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4 authors.
Funding
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Abstract
We evaluated intra- and interobserver variability of quantitative coronary angiography (QCA) due to cine frame selection for 9 coronary stenoses. The projection was selected in advance. Cine frames were selected by 2 blinded experts (blind frame QCA) followed by assignment by supervisor (pre-selected frame QCA). Each expert analyzed 18 frames twice with a 3-month interval. A total of 72 measurements by 2 experts were used for intra- and interobserver variability analysis in calibration factor (CF), minimal lumen diameter (MLD), percent diameter stenosis (%DS), interpolated reference diameter (Int R), and lesion length (LL). Accuracy, precision, and coefficient of variation (CV) were calculated based on 2 measurements. For interobserver variability, intraclass correlation coefficient (ICC) was evaluated. Regarding intraobserver variability, precision (CV) was 0.0026 (1.45), 0.220 (25.1), 0.282 (11.0), 7.626 (11.8), and 4.042 (28.7) for blind frame QCA and 0.0044 (2.46), 0.094 (11.2), 0.225 (8.6), 3.924 (5.9), and 1.941 (12.1) for pre-selected frame QCA and regarding interobserver variability, precision (CV) was 0.0037 (2.09), 0.271 (31.8), 0.307 (11.9), 10.10 (15.4), and 5.121 (39.5) for blind frame QCA and 0.0050 (2.82), 0.098 (11.4), 0.246 (9.5), 5.253 (8.0), and 2.857 (19.0) for pre-selected frame QCA in CF, MLD, Int R, %DS, and LL, respectively. Intraclass correlation coefficient of Int R was almost perfect in blind and pre-selected frame QCA. Intraclass correlation coefficient of MLD, %DS, and LL were substantial/lower by blind frame QCA and improved to almost perfect by pre-selected frame QCA. Blind cine film selection might affect intra- and interobserver variability, especially in MLD and LL. In the multiple linear regression analysis, blind frame QCA was selected as an explanatory factor of QCA variability in MLD, %DS, and LL. The error range due to frame selection must be taken into consideration in clinical use.
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