COMPARATIVE EFFECTIVENESS OF PET AND SPECT MPI FOR PREDICTING RISK IN PATIENTS WITH CARDIOMETABOLIC DISEASE.

PET myocardial perfusion imaging cardiovascular outcomes chronic kidney disease diabetes obesity

Journal

Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
ISSN: 1532-6551
Titre abrégé: J Nucl Cardiol
Pays: United States
ID NLM: 9423534

Informations de publication

Date de publication:
10 Jul 2024
Historique:
received: 09 02 2024
revised: 23 06 2024
accepted: 01 07 2024
medline: 13 7 2024
pubmed: 13 7 2024
entrez: 12 7 2024
Statut: aheadofprint

Résumé

The epidemiology of coronary artery disease (CAD) has shifted, with increasing prevalence of cardiometabolic disease and decreasing findings of obstructive CAD on myocardial perfusion imaging (MPI). Coronary microvascular dysfunction (CMD), defined as impaired myocardial flow reserve (MFR) by positron emission tomography (PET), has emerged as a key mediator of risk. We aimed to assess whether PET MFR provides additive value for risk stratification of cardiometabolic disease patients compared with single-photon emission computed tomography (SPECT) MPI. We retrospectively followed patients referred for PET, exercise SPECT, or pharmacologic SPECT MPI with cardiometabolic disease (obesity, diabetes, or chronic kidney disease) and without known CAD. We compared rates and hazards of composite MACE (annualized cardiac mortality or acute myocardial infarction) among propensity-matched PET and SPECT patients using Poisson and Cox regression. Normal SPECT was defined as a total perfusion deficit (TPD) <5% reflecting the absence of obstructive CAD. Normal PET was defined as TPD <5% plus MFR ≥2.0. Among 21,544 patients referred from 2006-2020, cardiometabolic disease was highly prevalent (PET: 2308 [67%], SPECT: 9984 [55%]) and higher among patients referred to PET (p <0.001). Obstructive CAD findings (TPD >5%) were uncommon (PET: 21% and SPECT 11%). Conversely, impaired MFR on PET (<2.0) was common (62%). In propensity-matched analysis over a median 6.4-year follow-up, normal PET identified low-risk (0.9%/year MACE) patients, and abnormal PET identified high-risk (4.2%/year MACE) patients with cardiometabolic disease; conversely, those with normal pharmacologic SPECT remained moderate-risk (1.6%/year, p<0.001 compared to normal PET). Cardiometabolic disease is common among patients referred for MPI and is associated with heterogenous level of risk. Compared with pharmacologic SPECT, PET with MFR can detect nonobstructive CAD including CMD and can more accurately discriminate low-risk from higher-risk individuals.

Sections du résumé

BACKGROUND BACKGROUND
The epidemiology of coronary artery disease (CAD) has shifted, with increasing prevalence of cardiometabolic disease and decreasing findings of obstructive CAD on myocardial perfusion imaging (MPI). Coronary microvascular dysfunction (CMD), defined as impaired myocardial flow reserve (MFR) by positron emission tomography (PET), has emerged as a key mediator of risk. We aimed to assess whether PET MFR provides additive value for risk stratification of cardiometabolic disease patients compared with single-photon emission computed tomography (SPECT) MPI.
METHODS METHODS
We retrospectively followed patients referred for PET, exercise SPECT, or pharmacologic SPECT MPI with cardiometabolic disease (obesity, diabetes, or chronic kidney disease) and without known CAD. We compared rates and hazards of composite MACE (annualized cardiac mortality or acute myocardial infarction) among propensity-matched PET and SPECT patients using Poisson and Cox regression. Normal SPECT was defined as a total perfusion deficit (TPD) <5% reflecting the absence of obstructive CAD. Normal PET was defined as TPD <5% plus MFR ≥2.0.
RESULTS RESULTS
Among 21,544 patients referred from 2006-2020, cardiometabolic disease was highly prevalent (PET: 2308 [67%], SPECT: 9984 [55%]) and higher among patients referred to PET (p <0.001). Obstructive CAD findings (TPD >5%) were uncommon (PET: 21% and SPECT 11%). Conversely, impaired MFR on PET (<2.0) was common (62%). In propensity-matched analysis over a median 6.4-year follow-up, normal PET identified low-risk (0.9%/year MACE) patients, and abnormal PET identified high-risk (4.2%/year MACE) patients with cardiometabolic disease; conversely, those with normal pharmacologic SPECT remained moderate-risk (1.6%/year, p<0.001 compared to normal PET).
CONCLUSIONS CONCLUSIONS
Cardiometabolic disease is common among patients referred for MPI and is associated with heterogenous level of risk. Compared with pharmacologic SPECT, PET with MFR can detect nonobstructive CAD including CMD and can more accurately discriminate low-risk from higher-risk individuals.

Identifiants

pubmed: 38996910
pii: S1071-3581(24)00584-1
doi: 10.1016/j.nuclcard.2024.101908
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

101908

Informations de copyright

Copyright © 2024 American Society of Nuclear Cardiology. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest ☒ The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Sanjay Divakaran reports a relationship with Kinevant Sciences that includes: consulting or advisory. Brittany N. Weber reports a relationship with Novo Nordisk that includes: consulting or advisory. Brittany N Weber reports a relationship with Kiniksa Pharmaceuticals that includes: consulting or advisory. Brittany N. Weber reports a relationship with Horizon Therapeutics that includes: consulting or advisory. Jen Brown reports a relationship with Bayer that includes: consulting or advisory. Ron Blankstein reports a relationship with Amgen Inc that includes: funding grants. Ron Blankstein reports a relationship with Novartis Inc that includes: funding grants. Sharmila Dorbala reports a relationship with Pfizer that includes: funding grants. Sharmila Dorbala reports a relationship with Attralus that includes: funding grants. Sharmila Dorbala reports a relationship with GE Healthcare that includes: funding grants. Sharmila Dorbala reports a relationship with Siemens that includes: funding grants. Sharmila Dorbala reports a relationship with Philips that includes: funding grants. Sharmila Dorbala reports a relationship with Novo Nordisk that includes: consulting or advisory. Sharmila Dorbala reports a relationship with Pfizer that includes: consulting or advisory. Marcelo Di Carli reports a relationship with Gilead Sciences that includes: funding grants. Marcelo Di Carli reports a relationship with Sun Pharmaceuticals that includes: funding grants. Marcelo Di Carli reports a relationship with Amgen that includes:. Marcelo Di Carli reports a relationship with Sanofi that includes: consulting or advisory. Marcelo Di Carli reports a relationship with MedTrace Pharma that includes: consulting or advisory. Marcelo Di Carli reports a relationship with Valo Health that includes: consulting or advisory. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Daniel M Huck (DM)

Cardiovascular Imaging Program, Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. Electronic address: dhuck@bwh.harvard.edu.

Sanjay Divakaran (S)

Cardiovascular Imaging Program, Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Brittany Weber (B)

Cardiovascular Imaging Program, Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Jenifer M Brown (JM)

Cardiovascular Imaging Program, Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Diana Lopez (D)

Cardiovascular Imaging Program, Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Ana Carolina do A H Souza (ACDAH)

Cardiovascular Imaging Program, Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Jon Hainer (J)

Cardiovascular Imaging Program, Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Ron Blankstein (R)

Cardiovascular Imaging Program, Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Sharmila Dorbala (S)

Cardiovascular Imaging Program, Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Marcelo Di Carli (M)

Cardiovascular Imaging Program, Departments of Medicine and Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.

Classifications MeSH