Key result
Advanced multimodality imaging and AI refine AS subtype classification to inform individualized intervention strategies.
Why the study?
Standard transthoracic echocardiography relies on flow-dependent parameters that can lead to inconsistent grading in aortic stenosis, creating a need for advanced and multimodality imaging approaches.
Answers are grounded in this paper and cite their sources.
Multimodality imaging, including advanced echocardiography, CT, CMR, and emerging technologies, is essential for accurate diagnosis, risk stratification, and procedural planning in aortic stenosis.
Aortic stenosis (AS) is the most common degenerative valvular disease in elderly patients and is linked to high morbidity and mortality. Accurate diagnosis and risk stratification are critical for effective management. Transthoracic echocardiography is the standard diagnostic tool, but its reliance on flow-dependent parameters can lead to inconsistent grading, especially in low-flow, low-gradient, or normal-flow, low-gradient AS. Advanced echocardiographic methods, such as 3D imaging, stress echocardiography, and Doppler indices, such as the mean gradient-to-effective orifice area ratio, improve the evaluation of AS severity and assist in clinical decision-making. Computed tomography provides a flow-independent evaluation of AS. It uses noncontrast calcium scoring with sex-specific thresholds, along with contrast-enhanced angiography, for detailed anatomical assessment. These modalities are essential for procedural planning, particularly for transcatheter aortic valve replacement. Cardiac magnetic resonance (CMR) provides additional prognostic information. It quantifies myocardial remodeling and fibrosis, which are associated with outcomes and recovery potential. Emerging technologies are expanding diagnostic capabilities in AS. Examples include 18F-sodium fluoride positron emission tomography for detecting microcalcification, artificial intelligence-based ECG and echocardiography for early diagnosis, and 4D flow CMR. Integration of echocardiography, computed tomography, CMR, and emerging positron emission tomography and artificial intelligence-based approaches can help address diagnostic uncertainty. This integration helps refine AS subtype classification and inform individualized intervention strategies.
No takes yet. Share an insight, caveat, or question.
Itani et al. (2026) conducted a review in Aortic stenosis. Advanced imaging modalities (echocardiography, CT, CMR, PET, AI) was evaluated. Integration of advanced imaging modalities, including echocardiography, CT, CMR, PET, and AI, refines aortic stenosis subtype classification and informs individualized intervention strategies.
Synapse has enriched 10 related papers. Consider them for comparative context: