Artificial intelligence and imaging: Opportunities in cardio-oncology

American Heart Journal Plus

Lili Zhang¹  Sherry-Ann Brown²  Marielle Scherrer-Crosbie³  Nausheen Akhter⁴  Nidhi Madan⁵  Abhinav Sharma⁶  Noelle C. Garster⁶  Feixiong Cheng⁷  Avirup Guha⁸  Julliette Lucas⁹  Ethan Wen⁹  Imeh Ndiokho⁹  Abdulaziz Hamid⁹  Patrick Collier^1,10 

[1]Cardio-Oncology Program, Division of Cardiology, Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USA

[2]Cardio-Oncology Program, Division of Cardiovascular Medicine, Medical College of Wisconsin, Milwaukee, WI, USA

[3]Division of Cardiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USA

[4]Division of Cardiology, Northwestern University, Chicago, IL, USA

[5]Division of Cardiology, Rush University Medical Center, Chicago, IL, USA

[6]Division of Cardiovascular Medicine, Medical College of Wisconsin, Milwaukee, WI, USA

[7]Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USA

[8]Harrington Heart and Vascular Institute, Cleveland, OH, USA

[9]Medical College of Wisconsin, Milwaukee, WI, USA

[10]Robert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH, USA

关键词: Imaging;    Cardio-oncology;    Cancer;    Cardiac tumors;    Artificial intelligence;    Echocardiography;   

DOI  :  

来源: DOAJ

【 摘 要 】

Cardiovascular disease is a leading cause of death in cancer survivors. It is critical to apply new predictive and early diagnostic methods in this population, as this can potentially inform cardiovascular treatment and surveillance decision-making. We discuss the application of artificial intelligence (AI) technologies to cardiovascular imaging in cardio-oncology, with a particular emphasis on prevention and targeted treatment of a variety of cardiovascular conditions in cancer patients. Recently, the use of AI-augmented cardiac imaging in cardio-oncology is gaining traction. A large proportion of cardio-oncology patients are screened and followed using left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS), currently obtained using echocardiography. This use will continue to increase with new cardiotoxic cancer treatments. AI is being tested to increase precision, throughput, and accuracy of LVEF and GLS, guide point-of-care image acquisition, and integrate imaging and clinical data to optimize the prediction and detection of cardiac dysfunction. The application of AI to cardiovascular magnetic resonance imaging (CMR), computed tomography (CT; especially coronary artery calcium or CAC scans), single proton emission computed tomography (SPECT) and positron emission tomography (PET) imaging acquisition is also in early stages of analysis for prediction and assessment of cardiac tumors and cardiovascular adverse events in patients treated for childhood or adult cancer. The opportunities for application of AI in cardio-oncology imaging are promising, and if availed, will improve clinical practice and benefit patient care.

【 授权许可】

Unknown