Key result
The integration of artificial intelligence in multimodality imaging presents a promising avenue to overcome intrinsic limitations in evaluating right ventricular morphology and function.
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Why the study?
Conventional cardiovascular imaging modalities have intrinsic limitations for evaluating right ventricular morphology and function, highlighting the need to integrate artificial intelligence into multimodality imaging.
Artificial intelligence presents a promising avenue to overcome intrinsic limitations of conventional cardiovascular imaging modalities in evaluating right ventricular morphology and function.
AI may enhance RV assessment via automated multimodality imaging; leaves open prospective validation before clinical use.
The crucial pathophysiological and prognostic roles of the right ventricle in various diseases have been well-established. Nonetheless, conventional cardiovascular imaging modalities are frequently associated with intrinsic limitations when evaluating right ventricular (RV) morphology and function. The integration of artificial intelligence (AI) in multimodality imaging presents a promising avenue to circumvent these obstacles, paving the way for future fully automated imaging paradigms. This review aimed to address the current challenges faced by clinicians and researchers in integrating RV imaging and AI technology, to provide a comprehensive overview of the current applications of AI in RV imaging, and to offer insights into future directions, opportunities, and potential challenges in this rapidly advancing field.
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Qin et al. (2024) conducted a review in Right ventricular evaluation. Artificial intelligence in multimodality imaging vs. Conventional cardiovascular imaging modalities was evaluated. The integration of artificial intelligence in multimodality imaging presents a promising avenue to overcome intrinsic limitations in evaluating right ventricular morphology and function.
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