A systematic review on deep learning-enabled coronary CT angiography for plaque and stenosis quantification and cardiac risk prediction.

Journal: European journal of radiology open
Published Date: May 2, 2025

Abstract

BACKGROUND: Coronary artery disease (CAD) is a major worldwide health concern, contributing significantly to the global burden of cardiovascular diseases (CVDs). According to the 2023 World Health Organization (WHO) report, CVDs account for approximately 17.9 million deaths annually. This emphasizies the need for advanced diagnostic tools such as coronary computed tomography angiography (CCTA). The incorporation of deep learning (DL) technologies could significantly improve CCTA analysis by automating the quantification of plaque and stenosis, thus enhancing the precision of cardiac risk assessments. A recent meta-analysis highlights the evolving role of CCTA in patient management, showing that CCTA-guided diagnosis and management reduced adverse cardiac events and improved event-free survival in patients with stable and acute coronary syndromes.

Authors

  • Priyal Shrivastava
    Department of Radio-Diagnosis, Jawaharlal Nehru Medical College Wardha, Datta Meghe Institute of Higher Education and Research (DU), Sawangi (Meghe), Wardha, India.
  • Shivali Kashikar
    Department of Radio-Diagnosis, Jawaharlal Nehru Medical College Wardha, Datta Meghe Institute of Higher Education and Research (DU), Sawangi (Meghe), Wardha, India.
  • P H Parihar
    Department of Radio-Diagnosis, Jawaharlal Nehru Medical College Wardha, Datta Meghe Institute of Higher Education and Research (DU), Sawangi (Meghe), Wardha, India.
  • Pachyanti Kasat
    Department of Radio-Diagnosis, Jawaharlal Nehru Medical College Wardha, Datta Meghe Institute of Higher Education and Research (DU), Sawangi (Meghe), Wardha, India.
  • Paritosh Bhangale
    Department of Radio-Diagnosis, Jawaharlal Nehru Medical College Wardha, Datta Meghe Institute of Higher Education and Research (DU), Sawangi (Meghe), Wardha, India.
  • Prakher Shrivastava
    Jawaharlal Nehru Medical College Wardha, Datta Meghe Institute of Higher Education and Research (DU), Sawangi (Meghe), Wardha, India.

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