A Clinical Tool to Identify Candidates for Stress-First Myocardial Perfusion Imaging

doi:10.1016/j.jcmg.2020.03.022

JACC: Cardiovascular Imaging

Volume 13, Issue 10, October 2020, Pages 2193-2202

https://doi.org/10.1016/j.jcmg.2020.03.022 Get rights and content

Under an Elsevier user license

open archive

Abstract

Objectives

This study sought to develop a clinical model that identifies a lower-risk population for coronary artery disease that could benefit from stress-first myocardial perfusion imaging (MPI) protocols and that can be used at point of care to risk stratify patients.

Background

There is an increasing interest in stress-first and stress-only imaging to reduce patient radiation exposure and improve patient workflow and experience.

Methods

A secondary analysis was conducted on a single-center cohort of patients undergoing single-photon emission computed tomography (SPECT) and positron emission tomography (PET) studies. Normal MPI was defined by the absence of perfusion abnormalities and other ischemic markers and the presence of normal left ventricular wall motion and left ventricular ejection fraction. A model was derived using a cohort of 18,389 consecutive patients who underwent SPECT and was validated in a separate cohort of patients who underwent SPECT (n = 5,819), 1 internal cohort of patients who underwent PET (n=4,631), and 1 external PET cohort (n = 7,028).

Results

Final models were made for men and women and consisted of 9 variables including age, smoking, hypertension, diabetes, dyslipidemia, typical angina, prior percutaneous coronary intervention, prior coronary artery bypass graft, and prior myocardial infarction. Patients with a score ≤1 were stratified as low risk. The model was robust with areas under the curve of 0.684 (95% confidence interval [CI]: 0.674 to 0.694) and 0.681 (95% CI: 0.666 to 0.696) in the derivation cohort, 0.745 (95% CI: 0.728 to 0.762) and 0.701 (95% CI: 0.673 to 0.728) in the SPECT validation cohort, 0.672 (95% CI: 0.649 to 0.696) and 0.686 (95% CI: 0.663 to 0.710) in the internal PET validation cohort, and 0.756 (95% CI: 0.740 to 0.772) and 0.737 (95% CI: 0.716 to 0.757) in the external PET validation cohort in men and women, respectively. Men and women who scored ≤1 had negative likelihood ratios of 0.48 and 0.52, respectively.

Conclusions

A novel model, based on easily obtained clinical variables, is proposed to identify patients with low probability of having abnormal MPI results. This point-of-care tool may be used to identify a population that might qualify for stress-first MPI protocols.

Central Illustration

Key Words

cardiac death

computed tomography

coronary angiography

major adverse cardiac events

myocardial infarction

prognosis

Abbreviations and Acronyms

3-dimensional

ASNC

American Society of Nuclear Cardiology

AUC

area under the curve

BMI

body mass index

CAD

coronary artery disease

confidence interval

CZT

cadmium-zinc-telluride

MPI

myocardial perfusion imaging

OSEM

ordered-subset expectation maximization

PET

positron emission tomography

SPECT

single-photon emission computed tomography

Cited by (0)

: Dr. Wells has received research grants from GE Healthcare and Advance Accelerator Applications. Dr. deKemp has received royalties from rubidium positron emission tomography technologies licensed to Jubilant DraxImage and from positron emission tomography analysis software licensed to INVIA Medical Solutions; and has received research support and honoraria from Jubilant DraxImage and GE Healthcare, Inc. Dr. Beanlands has received support from the Heart and Stroke Foundation of Ontario for service as a career investigator, the University of Ottawa for a Tier 1 Research Chair, and the University of Ottawa Heart Institute for the Vered Chair in Cardiology; and has received research support and honoraria from Lantheus Medical Imaging, Jubilant DraxImage, and GE Healthcare. Dr. Ruddy has received research grant support from GE Healthcare and Advanced Accelerator Applications. Dr. Di Carli has received research grants from Spectrum Dynamics and Gilead Sciences; has institutional research contracts with Xylocor and Alnylam; and has received consulting honoraria from Bayer and Janssen. Dr. Merhige has served as the Associate Medical Director of Cardionavix; and has served as a consultant for Bracco Diagnostics. Dr. Williams has received research support from Biosense Webster, Boehringer Ingelheim, Roche, Gilead, Janssen, Novo Nordisk, and Merck. Dr. Berman has received software royalties from Cedars-Sinai Medical Centre. Dr. Dorbala has received research support from Pfizer and GE Healthcare; has served as a consultant for Pfizer and GE Healthcare. Dr. Chow has held the Saul and Edna Goldfarb Chair in Cardiac Imaging Research; has received research support from TD Bank, CV Diagnostix, Ausculsciences, and Siemens; has received educational support from TeraRecon; and has equity interest in General Electric. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

: The authors attest they are in compliance with human studies committees and animal welfare regulations of the authors’ institutions and Food and Drug Administration guidelines, including patient consent where appropriate. For more information, visit the JACC: Cardiovascular Imaging author instructions page.