Percutaneous Coronary Interventions: Intravascular Imaging and Assessment of Intracoronary Haemodynamics

Chernyak, A. A.; Dzeshka, Mikhail S.; Snezhitskiy, V. A.; Yanushka, A. V.; Maksimchik, A. V.

doi:10.25298/2221-8785-2020-18-5-513-522

Journal GrSMU

2020

DOI: 10.25298/2221-8785-2020-18-5-513-522

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Percutaneous Coronary Interventions: Intravascular Imaging and Assessment of Intracoronary Haemodynamics

A. A. Chernyak¹,

Mikhail S. Dzeshka²,

V. A. Snezhitskiy³

et al.

Abstract: Conventional coronary angiography does not provide thorough information about the structure of atherosclerotic lesions and severity of vascular stenosis. Since their introduction in past decades, optical coherence tomography and intravascular ultrasound have demonstrated high diagnostic yield in patients with coronary heart disease, translated into improved clinical outcomes. The fractional flow reserve and instantaneous wave-free ratio have emerged as reliable criteria for assessment of hemodynamically signif… Show more

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Cited by 2 publications

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Prospects for using machine learning to improve coronary angiography

Trusov,

Vildanova,

Zagitova

et al. 2024

HERALD of North-Western State Medical University named after I.

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Cardiovascular diseases pose the main threat to the population health of the Russian Federation and rank the first among the causes of death. Coronary heart disease has the highest standardized mortality rates among the population of the Russian Federation. Comprehensive diagnosis of coronary artery disease includes assessment of coronary atherosclerosis using both non-invasive methods, such as multispiral computed tomography of the coronary arteries, and invasive ones, including coronary angiography, and sometimes intravascular imaging. First two methods are the two most important diagnostic methods for coronary heart disease. The widespread use of medical technologies based on artificial intelligence in recent years has led to the emergence of new diagnostic and therapeutic opportunities. Artificial intelligence has bridged the gap between massive datasets and useful information by processing and analyzing important data at an unprecedented rate. The review identifies five potential cases with machine learning having significant prospects in the field of coronary angiography: improving quality and effectiveness, determining plaque characteristics, assessing hemodynamics, predicting disease outcomes and diagnosing non-atherosclerotic lesions of the coronary arteries. While machine learning has transformative potential in the field of coronary angiogram analysis, careful consideration of limitations, including data exchange protocols and interpretability of models is essential to fully exploit its potential and ensure optimal diagnosis and treatment of patients.

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Prospects for using machine learning to improve coronary angiography

Trusov,

Vildanova,

Zagitova

et al. 2024

HERALD of North-Western State Medical University named after I.

View full text Add to dashboard Cite

show abstract

The role of intravascular methods of examination of coronary arteries in the selection of patients with diffuse and multivessel lesions for myocardial revascularization

Максимкин

Bolivogu

Faybushevich

et al. 2021

Innovacionnaâ medicina Kubani

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Objective Assessment of the role of intravascular imaging methods in choosing the surgical strategy of myocardial revascularization.Material and Methods The study included 62 patients with diffuse and multivessel coronary artery disease, who underwent percutaneous coronary infervention (PCI) using intravascular imaging methods. Measurement of fractional flow reserve (FFR) in diffusely altered arteries was performed under conditions of maximum hyperemia, sequentially between stenoses, using the sensor, starting from the distal segment. Initially, the most distal hemodynamically significant stenosis was stented. Then, a repeated measurement of FFR was performed, and the issue of the need for stenting of other stenoses was solved. The results of stenting, as well as determination of the area of stent implantation were carried out by the method of optical coherence tomography (OCT).Results After FFR measurement the number of arteries with hemodynamically significant stenoses decreased by 24.7% (from 93 to 70). It was also noted that in patients with two-vessel lesions, the average number of such stenoses decreased from 2.95 ± 0.65 to 1.82 ± 0.88, and in patients with three-vessel lesions – from 2.96 ± 0.6 to 2.24 ± 0.76 respectively (p = 0.0024). Complete (functionally adequate according to FFR measurements) myocardial revascularization was achieved in 88.7% of patients. The second-generation drug eluting stents were implanted in 82 (47.1%) patients, and the third generation stents – in 92 (52.9%) patients. At the same time, the success rate of recanalization of occlusions was 100%. Overall, optimal stent implantation was achieved in all patients. Major cardiovascular complications were observed in 1 (1.6%) patient, which required additional interventions.Conclusion Complex use of intravascular imaging methods (OCT and FFR measurements) allows a differentiated approach to the assessment of each stenosis of the affected artery in patients with diffuse and multivessel coronary lesions, to achieve a high frequency of complete myocardial revascularization, as well as to reduce the number of unnecessary interventions and intraoperative complications.

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Percutaneous Coronary Interventions: Intravascular Imaging and Assessment of Intracoronary Haemodynamics

Cited by 2 publications

References 32 publications

Prospects for using machine learning to improve coronary angiography

Prospects for using machine learning to improve coronary angiography

The role of intravascular methods of examination of coronary arteries in the selection of patients with diffuse and multivessel lesions for myocardial revascularization

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