New approaches for assessing coronary changes in multi-layer spiral computed tomography

Currently, multi-slice computed tomography (MSCT) coronary angiography is a leader in the diagnosis of coronary artery disease in patients with non-ST elevation acute coronary syndrome of low or moderate risk. High coronary calcium score (CCS) obtained by MSCT indicate a high probability of obstructive coronary artery disease. In the presented case of an 83-year-old patient with unstable angina, the CCS was 1394, and hemodynamically significant stenoses were detected. However, according to selective coronary angiography, no hemodynamically significant coronary lesions were found. High CCS suggests poor image quality in MSCT coronary angiography. High CCS is detected in most people over 70 years of age. Obviously, in this patient, a high CCS is mainly determined by age. Most studies on CCS did not include patients over 80 years of age. When deciding whether to perform MSCT coronary angiography, it is necessary to take into account the individual characteristics of a particular patient, which may affect the interpretation of results.

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High calcium score in an 83-year-old patient with non-ST elevation acute coronary syndrome and nonobstructive coronary artery disease: a case report

Kuznetsova

Sukhinina

Benyan

et al. 2022

Russ J Cardiol

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Comparability of cardiovascular risk assessment according to the SCORE and the coronary artery calcium score (Agatston score)

Safaryan,

Vygodin,

Nebieridze

et al. 2023

Cardiovasc Ther Prev

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Aim. To determine whether the Systematic Coronary Risk Evaluation (SCORE) level corresponds to the coronary artery calcium (CAC) score (Agatston score).Material and methods. The study included 212 people aged 40-65 years (mean age, 56,5±7,9 years). The number of men and women was 54 (25,5%) and 158 (74,5%), respectively.Results. According to the SCORE, the groups were distributed as follows: 62 (29,2%) — low risk, 128 (60,4%) — moderate risk, 16 (7,5%) — high risk, 6 (2,8%) — very high risk. The average SCORE level for the general group was 2,5±2,4%. According to the Agatston score, the groups were distributed as follows: minimal risk (0-10) — 142 (67%) people, low risk (11-100) — 42 (19,8%) people, moderate risk (101-400) — 17 (8%) people, high risk (≥401) — 7 (3,3%) people. Inconsistencies for all categories of cardiovascular risk were revealed between SCORE and Agatston score.Conclusion. The identified inconsistencies in the distribution of risk groups in accordance with the SCORE and Agatston score indicate that the SCORE scale is insufficiently informative. Multislice computed tomography coronary angiography with CAC calculation is additionally recommended, which will allow determining patient management and deciding on therapy. A comparative analysis of CAC score and the SCORE scale can help optimize, first of all, drug therapy for patients with hypertension and lipid metabolism disorders.

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Use of artificial intelligence in the diagnosis of arterial calcification

Trusov,

Chupakhina,

Nurkaeva

et al. 2024

Digital Diagnostics

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Justification. The incidence of diseases of the circulatory system of the population of the Russian Federation has been steadily increasing over the past two decades, increasing 2,047 times from 2000 to 2019. The process of vascular calcification implies the deposition of calcium salts in the artery wall, leading to remodeling of the vascular wall. Radiation research methods are the gold standard for the diagnosis of vascular calcification. However, due to the need for medical professionals to process a large amount of data for a certain period of time, the number of diagnostic errors inevitably increases, as well as the efficiency of work decreases. The active development and introduction of artificial intelligence (AI) into clinical practice has opened up opportunities for specialists to solve these problems. The purpose of the study. To analyze the domestic and foreign literature devoted to the use of AI in the diagnosis of various types of vascular calcification, as well as to summarize the prognostic value of vascular calcification and evaluate aspects that prevent the diagnosis of vascular calcification without the use of AI. Material and methods. The authors searched for publications in the electronic databases PubMed, Web of Science, Google Scholar and eLibrary. The search was carried out using the following keywords: "artificial intelligence", "machine learning", "vascular calcification", "artificial intelligence", "machine learning", "vascular calcification". The search was carried out in the time interval from the moment of the foundation of the corresponding database until July 2023. Conclusion. AI has proven itself well in the diagnosis of vascular calcification. In addition to improving accuracy and efficiency, the ability to detail surpasses the capabilities of the manual diagnostic method. AI has reached a level that allows doctors to help instrumental diagnostics in the automatic detection of vascular calcification. AI capabilities can contribute to the effective development of radiology in the future.

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New approaches for assessing coronary changes in multi-layer spiral computed tomography

Cited by 5 publications

References 24 publications

High calcium score in an 83-year-old patient with non-ST elevation acute coronary syndrome and nonobstructive coronary artery disease: a case report

High calcium score in an 83-year-old patient with non-ST elevation acute coronary syndrome and nonobstructive coronary artery disease: a case report

Comparability of cardiovascular risk assessment according to the SCORE and the coronary artery calcium score (Agatston score)

Use of artificial intelligence in the diagnosis of arterial calcification

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