Bettina Baeßler, Sandy Engelhardt, Amar Hekalo, Anja Hennemuth, Markus Hüllebrand, Ann Laube, Clemens Scherer, Malte Tölle, Tobias Wech
{"title":"Perfect Match: Radiomics and Artificial Intelligence in Cardiac Imaging.","authors":"Bettina Baeßler, Sandy Engelhardt, Amar Hekalo, Anja Hennemuth, Markus Hüllebrand, Ann Laube, Clemens Scherer, Malte Tölle, Tobias Wech","doi":"10.1161/CIRCIMAGING.123.015490","DOIUrl":null,"url":null,"abstract":"<p><p>Cardiovascular diseases remain a significant health burden, with imaging modalities like echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging playing a crucial role in diagnosis and prognosis. However, the inherent heterogeneity of these diseases poses challenges, necessitating advanced analytical methods like radiomics and artificial intelligence. Radiomics extracts quantitative features from medical images, capturing intricate patterns and subtle variations that may elude visual inspection. Artificial intelligence techniques, including deep learning, can analyze these features to generate knowledge, define novel imaging biomarkers, and support diagnostic decision-making and outcome prediction. Radiomics and artificial intelligence thus hold promise for significantly enhancing diagnostic and prognostic capabilities in cardiac imaging, paving the way for more personalized and effective patient care. This review explores the synergies between radiomics and artificial intelligence in cardiac imaging, following the radiomics workflow and introducing concepts from both domains. Potential clinical applications, challenges, and limitations are discussed, along with solutions to overcome them.</p>","PeriodicalId":10202,"journal":{"name":"Circulation: Cardiovascular Imaging","volume":null,"pages":null},"PeriodicalIF":6.5000,"publicationDate":"2024-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Circulation: Cardiovascular Imaging","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1161/CIRCIMAGING.123.015490","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/6/18 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Cardiovascular diseases remain a significant health burden, with imaging modalities like echocardiography, cardiac computed tomography, and cardiac magnetic resonance imaging playing a crucial role in diagnosis and prognosis. However, the inherent heterogeneity of these diseases poses challenges, necessitating advanced analytical methods like radiomics and artificial intelligence. Radiomics extracts quantitative features from medical images, capturing intricate patterns and subtle variations that may elude visual inspection. Artificial intelligence techniques, including deep learning, can analyze these features to generate knowledge, define novel imaging biomarkers, and support diagnostic decision-making and outcome prediction. Radiomics and artificial intelligence thus hold promise for significantly enhancing diagnostic and prognostic capabilities in cardiac imaging, paving the way for more personalized and effective patient care. This review explores the synergies between radiomics and artificial intelligence in cardiac imaging, following the radiomics workflow and introducing concepts from both domains. Potential clinical applications, challenges, and limitations are discussed, along with solutions to overcome them.
期刊介绍:
Circulation: Cardiovascular Imaging, an American Heart Association journal, publishes high-quality, patient-centric articles focusing on observational studies, clinical trials, and advances in applied (translational) research. The journal features innovative, multimodality approaches to the diagnosis and risk stratification of cardiovascular disease. Modalities covered include echocardiography, cardiac computed tomography, cardiac magnetic resonance imaging and spectroscopy, magnetic resonance angiography, cardiac positron emission tomography, noninvasive assessment of vascular and endothelial function, radionuclide imaging, molecular imaging, and others.
Article types considered by Circulation: Cardiovascular Imaging include Original Research, Research Letters, Advances in Cardiovascular Imaging, Clinical Implications of Molecular Imaging Research, How to Use Imaging, Translating Novel Imaging Technologies into Clinical Applications, and Cardiovascular Images.