Artificial intelligence and imaging: Opportunities in cardio-oncology
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 intellige...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-03-01
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| Series: | American Heart Journal Plus |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S266660222200043X |
| _version_ | 1811252657029906432 |
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| author | Nidhi Madan Julliette Lucas Nausheen Akhter Patrick Collier Feixiong Cheng Avirup Guha Lili Zhang Abhinav Sharma Abdulaziz Hamid Imeh Ndiokho Ethan Wen Noelle C. Garster Marielle Scherrer-Crosbie Sherry-Ann Brown |
| author_facet | Nidhi Madan Julliette Lucas Nausheen Akhter Patrick Collier Feixiong Cheng Avirup Guha Lili Zhang Abhinav Sharma Abdulaziz Hamid Imeh Ndiokho Ethan Wen Noelle C. Garster Marielle Scherrer-Crosbie Sherry-Ann Brown |
| author_sort | Nidhi Madan |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-12T16:37:53Z |
| format | Article |
| id | doaj.art-b6e59096997a42f1a753a9473446bdfe |
| institution | Directory Open Access Journal |
| issn | 2666-6022 |
| language | English |
| last_indexed | 2024-04-12T16:37:53Z |
| publishDate | 2022-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | American Heart Journal Plus |
| spelling | doaj.art-b6e59096997a42f1a753a9473446bdfe2022-12-22T03:24:55ZengElsevierAmerican Heart Journal Plus2666-60222022-03-0115100126Artificial intelligence and imaging: Opportunities in cardio-oncologyNidhi Madan0Julliette Lucas1Nausheen Akhter2Patrick Collier3Feixiong Cheng4Avirup Guha5Lili Zhang6Abhinav Sharma7Abdulaziz Hamid8Imeh Ndiokho9Ethan Wen10Noelle C. Garster11Marielle Scherrer-Crosbie12Sherry-Ann Brown13Division of Cardiology, Rush University Medical Center, Chicago, IL, USAMedical College of Wisconsin, Milwaukee, WI, USADivision of Cardiology, Northwestern University, Chicago, IL, USARobert and Suzanne Tomsich Department of Cardiovascular Medicine, Sydell and Arnold Miller Family Heart and Vascular Institute, Cleveland Clinic, Cleveland, OH, USAGenomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, OH, USAHarrington Heart and Vascular Institute, Cleveland, OH, USACardio-Oncology Program, Division of Cardiology, Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, NY, USADivision of Cardiovascular Medicine, Medical College of Wisconsin, Milwaukee, WI, USAMedical College of Wisconsin, Milwaukee, WI, USAMedical College of Wisconsin, Milwaukee, WI, USAMedical College of Wisconsin, Milwaukee, WI, USADivision of Cardiovascular Medicine, Medical College of Wisconsin, Milwaukee, WI, USADivision of Cardiology, Hospital of the University of Pennsylvania, Philadelphia, PA, USACardio-Oncology Program, Division of Cardiovascular Medicine, Medical College of Wisconsin, Milwaukee, WI, USA; Corresponding author at: Cardio-Oncology Program, Division of Cardiovascular Medicine, Medical College of Wisconsin, 8701 Watertown Plank Road, Milwaukee, WI 53226, USA.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.http://www.sciencedirect.com/science/article/pii/S266660222200043XImagingCardio-oncologyCancerCardiac tumorsArtificial intelligenceEchocardiography |
| spellingShingle | Nidhi Madan Julliette Lucas Nausheen Akhter Patrick Collier Feixiong Cheng Avirup Guha Lili Zhang Abhinav Sharma Abdulaziz Hamid Imeh Ndiokho Ethan Wen Noelle C. Garster Marielle Scherrer-Crosbie Sherry-Ann Brown Artificial intelligence and imaging: Opportunities in cardio-oncology American Heart Journal Plus Imaging Cardio-oncology Cancer Cardiac tumors Artificial intelligence Echocardiography |
| title | Artificial intelligence and imaging: Opportunities in cardio-oncology |
| title_full | Artificial intelligence and imaging: Opportunities in cardio-oncology |
| title_fullStr | Artificial intelligence and imaging: Opportunities in cardio-oncology |
| title_full_unstemmed | Artificial intelligence and imaging: Opportunities in cardio-oncology |
| title_short | Artificial intelligence and imaging: Opportunities in cardio-oncology |
| title_sort | artificial intelligence and imaging opportunities in cardio oncology |
| topic | Imaging Cardio-oncology Cancer Cardiac tumors Artificial intelligence Echocardiography |
| url | http://www.sciencedirect.com/science/article/pii/S266660222200043X |
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