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Artificial intelligence assisted precise and rapid diagnosis of 'heart disease'
Published Time:
2025-03-01
Author:
Source:
China Medical News
Summary
The application of AI medical imaging software in CCTA can achieve image quality improvement and automatic calculation. Traditional methods such as increasing radiation dose and applying iterative reconstruction functions can reduce noise to a certain extent, while when AI is applied to CCTA image reconstruction, DL (deep learning) models can be used to reduce noise, improve image quality, and avoid the potential harm of high radiation levels. Before performing CCTA examination, it is usually necessary to obtain coronary artery calcification score (CACS) through plain CT scan. AI models can directly achieve automatic calculation of CACS through CCTA, optimizing the CCTA process and reducing radiation. Meanwhile, when CCTA detects and evaluates calcified plaques, AI assistance can significantly shorten the time required. In terms of measuring coronary artery stenosis, clinical evaluation mainly adopts the visual diameter method. Based on the percentage of reduction in the diameter of the narrowed lesion compared to its normal diameter at the proximal and distal ends, it is classified according to the Coronary Disease Imaging Reporting and Data System (CAD-RADS) grading standards. Among them, fractional flow reserve (FFR) is an indicator for evaluating coronary blood flow, which requires percutaneous intervention angiography to obtain. And AI technology can perform 3D reconstruction through AI algorithms, combined with fluid dynamics simulation calculations to obtain corresponding values.
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