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Use of artificial intelligence in MSCT analysis of coronary arteries

Authors

  • Karimova Pokiza Ulug‘bek qizi

    Student of the 2nd Faculty of General Medicine, Tashkent State Medical University
    Author
  • Matyusupov Hamid Madaminovich

    Scientific Supervisors, Head of the Radiodiagnostics Department at the Republican Specialized Scientific and Practical Medical Center of Oncology and Radiology
    Author
  • Abdurashidov Shoxruhbek Shuxratbek o‘g‘li

    1 Resident of the Medical Radiology Department, Tashkent State Medical University
    Author

Keywords:

coronary arteries, MSCT, artificial intelligence, computed tomography, stenosis, atherosclerosis, diagnostics, prognosis, cardiovascular diseases

Abstract

This article examines the modern capabilities of artificial intelligence (AI) technologies in the analysis of coronary artery multislice computed tomography (MSCT) images. Recent studies show that AI significantly improves the ability to determine the degree of coronary artery stenosis, assess atherosclerotic plaques, and predict cardiovascular complications. The analysis indicates that AI algorithms increase diagnostic accuracy, accelerate physicians‘ workflow, and play an important role in developing individualized treatment strategies

References

1. Dey D, Slomka PJ, Leeson P, et al. Artificial intelligence in coronary CT angiography. J Am Coll Cardiol. 2025;85(4):345–358. https://pubmed.ncbi.nlm.nih.gov/40576859

2. Knuuti J, Bax JJ, Saraste A, et al. Coronary CT angiography evaluation with artificial intelligence for individualized treatment. Nat Rev Cardiol. 2026;23(1):15–28. https://pubmed.ncbi.nlm.nih.gov/40751112/

3. van Rosendael AR, Bax AM, Smit JM, et al. Artificial intelligence in CT angiography for detection of coronary stenosis. Eur Heart J Cardiovasc Imaging. 2025;26(2):210–220. https://pubmed.ncbi.nlm.nih.gov/40234162/

4. Motwani M, Dey D, Berman DS, et al. Machine learning for prediction of major adverse cardiovascular events using coronary CT angiography. JACC Cardiovasc Imaging. 2025;18(3):400–412. https://pubmed.ncbi.nlm.nih.gov/39389811/

5. Commandeur F, Goeller M, Razipour A, et al. Prognostic value of coronary CTA-based artificial intelligence plaque quantification. Radiology. 2025;305(1):98–107. https://pubmed.ncbi.nlm.nih.gov/41075372/

6. Lin A, Kolossváry M, Motwani M, et al. AI-enabled coronary plaque analysis and prediction of acute coronary syndrome. Eur Heart J. 2026;47(3):300–312. https://pubmed.ncbi.nlm.nih.gov/41346196/

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Published

2026-05-12