Quantitative clinical nuclear cardiology, part 2: Evolving/emerging applications

被引:0
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作者
Piotr J. Slomka
Jonathan B. Moody
Robert J. H. Miller
Jennifer M. Renaud
Edward P. Ficaro
Ernest V. Garcia
机构
[1] Cedars-Sinai Medical Center,Department of Imaging (Division of Nuclear Medicine), Medicine, and Biomedical Sciences
[2] INVIA Medical Imaging Solutions,Department of Cardiac Sciences
[3] University of Calgary,Division of Cardiology, Department of Internal Medicine
[4] University of Michigan,Department of Radiology and Imaging Sciences
[5] Emory University,undefined
来源
关键词
Nuclear cardiology; myocardial blood flow; quantitation; artificial intelligence; phase analysis;
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摘要
Quantitative analysis has been applied extensively to image processing and interpretation in nuclear cardiology to improve disease diagnosis and risk stratification. This is Part 2 of a two-part continuing medical education article, which will review the potential clinical role for emerging quantitative analysis tools. The article will describe advanced methods for quantifying dyssynchrony, ventricular function and perfusion, and hybrid imaging analysis. This article discusses evolving methods to measure myocardial blood flow with positron emission tomography and single-photon emission computed tomography. Novel quantitative assessments of myocardial viability, microcalcification and in patients with cardiac sarcoidosis and cardiac amyloidosis will also be described. Lastly, we will review the potential role for artificial intelligence to improve image analysis, disease diagnosis, and risk prediction. The potential clinical role for all these novel techniques will be highlighted as well as methods to optimize their implementation.
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页码:115 / 127
页数:12
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