Artificial intelligence assists in the precise and rapid diagnosis of "heart conditions."
Release date:
2025-03-01
In recent years, Chinese enterprises have actively invested in research on AI-powered medical imaging software applications in the cardiovascular disease field. Several products have already been approved for market launch, primarily focusing on niche areas such as coronary CT angiography and auxiliary analysis of electrocardiograms.
AI-powered medical imaging software applied to CCTA can enhance image quality and enable automated measurements. Traditional methods have relied on increasing radiation doses or employing iterative reconstruction techniques to reduce noise, but when AI is integrated into CCTA image reconstruction, deep learning (DL) models can effectively minimize noise, improve image clarity, and mitigate the potential risks associated with high radiation exposure. Before undergoing a CCTA examination, patients typically undergo a non-contrast CT scan to obtain the coronary artery calcium score (CACS). Interestingly, AI models can now directly calculate CACS from CCTA images, streamlining the entire CCTA workflow while significantly cutting down on radiation exposure. Moreover, when CCTA is used to detect and assess calcified plaques, AI assistance can markedly shorten the time required for these assessments. In terms of evaluating coronary stenosis, clinicians traditionally rely on visual diameter measurement—assessing the percentage reduction in diameter at the narrowed segment compared to the normal diameters proximally and distally—and categorizing lesions according to the CAD-RADS grading system. Meanwhile, fractional flow reserve (FFR), an essential metric for evaluating coronary blood flow, currently requires invasive angiography via percutaneous intervention to measure accurately. However, AI technology offers a groundbreaking solution by leveraging advanced algorithms to perform 3D reconstructions and, combined with computational fluid dynamics simulations, directly compute FFR values without the need for invasive procedures.
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