Impact of Cine Frame Selection on Quantitative Coronary Angiography Results

Ito, Shigenori; Kinoshita, Kanako; Endo, Akiko; Nakamura, Masato

doi:10.1177/1179546819838232

Cited by 4 publications

(5 citation statements)

References 15 publications

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“…One of the major coronary angiography drawbacks is its two-dimensional luminogram of a three-dimensional structure, as well as vessel overlap and foreshortening during acquisition. Furthermore, QCA is influenced by the frame selection, vessel movement, end-diastolic phase and calibration[ 49 , 50 ].…”

Section: Quantitative Coronary Analysismentioning

confidence: 99%

Stent visualization methods to guide percutaneous coronary interventions and assess long-term patency

Ghafari¹,

Carlier²

2021

WJC

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Evaluation of acute percutaneous coronary intervention (PCI) results and long-term follow-up remains challenging with ongoing stent designs. Several imaging tools have been developed to assess native vessel atherosclerosis and stent expansion, improving overall PCI results and reducing adverse cardiac events. Quantitative coronary analysis has played a crucial role in quantifying the extent of coronary artery disease and stent results. Digital stent enhancement methods have been well validated and improved stent strut visualization. Intravascular imaging remains the gold standard in PCI guidance but adds costs and time to the procedure. With a recent shift towards non-invasive imaging assessment and coronary computed tomography angiography imaging have shown promising results. We hereby review novel stent visualization techniques used to guide PCI and assess stent patency in the modern PCI era.

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Section: Quantitative Coronary Analysismentioning

confidence: 99%

Stent visualization methods to guide percutaneous coronary interventions and assess long-term patency

Ghafari¹,

Carlier²

2021

WJC

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“…The difference in LL could be due to projection selection and cine frame selections. 4,18 Because the difference in LL was detected also between intra-core lab analysis, these results might be due to each expert, rather than to the core lab. Cardiac construction may cause vessel flexion, which leads to change in LL.…”

Section: Variability In Initial Data Between the Two Core Labsmentioning

confidence: 91%

“…Our recent study showed the influence of cine frame selection on the QCA results under blind cine frame selection. 4 The target lesions included complex type B2 and type C lesions (58.2%), which could be the potential source of variance between experts. These features might have yielded differences between our study and previous studies that also evaluated inter- core lab variability.…”

Section: Strength Of This Qca Variability Studymentioning

confidence: 99%

“…1 Beyond angiographic metrics, recently developed angiography-derived fractional flow reserve (FFR) may be a useful tool for diagnosing ischemia-producing lesions in patients with non-complex coronary artery disease. 1,2 Meanwhile, although QCA metrics such as acute gain and late lumen loss proved to be instrumental in assessing new technologies, it is true that there are still multiple factors that affect QCA results, including guide catheter size, 3 contrast injection into the vessel, cine projection selection, number of cine projections, cine frame selection, 4 and decision of reference vessel segment. During the QCA process, manual processes cannot be completely eliminated.…”

Section: Introductionmentioning

confidence: 99%

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Inter- and intra-core laboratory variability in the quantitative coronary angiography analysis for drug-eluting stent treatment and follow up

Ito

Kinoshita²,

Endo³

et al. 2020

Therapeutic Advances in Cardiovascular Disease

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Aim: To evaluate inter-core laboratory variability of quantitative coronary angiography (QCA) parameters in comparison with intra-core laboratory variability in a randomized controlled trial evaluating drug-eluting stents. Methods: A total of 50 patients with 62 coronary lesions were analyzed by four analysis experts belonging to an Angiographic Core Laboratory (ACL: 1 expert) and a Cardiovascular Imaging Core Laboratory (CICL: 3 experts). QCA was based on the same standard operating procedure, but selections of projection and cine frames were at the discretion of each analyst. Inter- and intra-core laboratory variabilities were evaluated by accuracy, precision, Bland Altman analysis, and coefficient of variation. Results: Pre-MLD (minimal lumen diameter) was significantly smaller in results from ACL than those from all CICL experts. Number of analyzed projections did not affect pre-MLD results. Acute gain was larger in ACL than in CICL2. No significant difference was observed in late loss and loss index between inter-core laboratories. Agreement between core labs in the Bland-Altman analysis for each QCA parameter was as follows (mean difference, 95% limits of agreement): pre-MLD (–0.32, –0.74 to 0.10), stent MLD (0.08, –0.28 to 0.44), acute gain (0.22, –0.44 to 0.88), and late loss (–0.07, –0.69 to 0.55). Agreement between analysts in CICL (mean difference, 95% limits of agreement) was: pre MLD (–0.03, –0.37 to 0.31), stent MLD (0.15, –0.15 to 0.45), acute gain (0.05, –0.45 to 0.55), and late loss (0.04, –0.52 to 0.60). The widest limits of agreement among three analyses were shown in both analyses. Width of limited agreement in the intra-core laboratory analysis tended to be smaller than the inter-core laboratory analysis with these parameters. Coefficient of variation tended to be larger in lesion length (LL), acute gain, late loss, and loss index in inter- and in intra- core laboratory comparisons. Conclusion: Inter-core laboratory QCA variability in late loss and loss index analysis could be similar to intra-core laboratory variability, but more strict alignment between core laboratories would be necessary for initial procedural data analysis.

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“…In clinical practice, QCA data can be influenced by the frame selection [47]. In the selection of the target frame, the analyst should (1) minimize vessel movement, (2) select the contrast-filled vessels in the end-diastolic phase, and (3) appropriately include the calibration device when the isocenter calibration is not applicable.…”

Section: Tips For Obtaining Optimal Qca Datamentioning

confidence: 99%

Clinical expert consensus document on quantitative coronary angiography from the Japanese Association of Cardiovascular Intervention and Therapeutics

Suzuki

Asano

Nakazawa

et al. 2020

Cardiovasc Interv and Ther

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Impact of Cine Frame Selection on Quantitative Coronary Angiography Results

Cited by 4 publications

References 15 publications

Stent visualization methods to guide percutaneous coronary interventions and assess long-term patency

Stent visualization methods to guide percutaneous coronary interventions and assess long-term patency

Inter- and intra-core laboratory variability in the quantitative coronary angiography analysis for drug-eluting stent treatment and follow up

Clinical expert consensus document on quantitative coronary angiography from the Japanese Association of Cardiovascular Intervention and Therapeutics

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