Automated Quantitative Nuclear Cardiology Methods

Manish Motwani; Daniel S Berman; Guido Germano; Piotr Slomka

doi:10.1016/j.ccl.2015.08.003

Automated Quantitative Nuclear Cardiology Methods

Cardiol Clin. 2016 Feb;34(1):47-57. doi: 10.1016/j.ccl.2015.08.003. Epub 2015 Oct 20.

Authors

Manish Motwani¹, Daniel S Berman², Guido Germano², Piotr Slomka³

Affiliations

¹ Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA.
² Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA; David Geffen School of Medicine at UCLA, Los Angeles, CA, USA.
³ Departments of Imaging and Medicine, Cedars-Sinai Medical Center, 8700 Beverly Boulevard, Los Angeles, CA 90048, USA; David Geffen School of Medicine at UCLA, Los Angeles, CA, USA. Electronic address: piotr.slomka@cshs.org.

Abstract

Quantitative analysis of SPECT and PET has become a major part of nuclear cardiology practice. Current software tools can automatically segment the left ventricle, quantify function, establish myocardial perfusion maps, and estimate global and local measures of stress/rest perfusion, all with minimal user input. State-of-the-art automated techniques have been shown to offer high diagnostic accuracy for detecting coronary artery disease, as well as predict prognostic outcomes. This article briefly reviews these techniques, highlights several challenges, and discusses the latest developments.

Keywords: Automated quantitation; Ischemia; Left ventricular ejection fraction; Myocardial function; Myocardial perfusion; PET; SPECT; Total perfusion deficit.

Publication types

Review

MeSH terms

Humans
Myocardial Perfusion Imaging*
Positron-Emission Tomography
Predictive Value of Tests
Reproducibility of Results
Tomography, Emission-Computed, Single-Photon*

Grants and funding

R01 HL089765/HL/NHLBI NIH HHS/United States