Prognostic Implications of Blunted Feature-Tracking Global Longitudinal Strain During Vasodilator Cardiovascular Magnetic Resonance Stress Imaging.


Journal

JACC. Cardiovascular imaging
ISSN: 1876-7591
Titre abrégé: JACC Cardiovasc Imaging
Pays: United States
ID NLM: 101467978

Informations de publication

Date de publication:
01 2020
Historique:
received: 28 01 2019
revised: 20 02 2019
accepted: 21 02 2019
pubmed: 22 4 2019
medline: 21 7 2020
entrez: 22 4 2019
Statut: ppublish

Résumé

The purpose of this study was to determine the prognostic value of feature-tracking global longitudinal strain (GLS) measured during vasodilator stress cardiac magnetic resonance (CMR) imaging. Prior studies have suggested that blunted myocardial strain during dobutamine stress echocardiography may be associated with adverse prognosis. Recent developments in CMR feature-tracking techniques now allow assessment of strain in clinical practice using standard cine images without specialized pulse sequences or complex post-processing. Whether feature-tracking GLS measured during vasodilator stress provides independent and incremental prognostic data is unclear. Consecutive patients undergoing stress perfusion CMR were prospectively enrolled (n = 535). Feature-tracking stress GLS was measured immediately after regadenoson perfusion. Patients were followed for major adverse cardiac events (MACE): death, nonfatal myocardial infarction, heart failure hospitalization, sustained ventricular tachycardia, and late revascularization. Cox proportional hazards regression modeling was used to examine the association between stress GLS and MACE. The incremental prognostic value of stress GLS was assessed in nested models. Over a median follow-up of 1.5 years, 82 patients experienced MACE. By Kaplan-Meier analysis, patients with stress GLS ≥ median (-19%) had significantly reduced event-free survival compared with those with stress GLS < median (log-rank p < 0.001). Stress GLS was significantly associated with risk of MACE after adjustment for clinical and imaging risk factors including ischemia, ejection fraction, and late gadolinium enhancement (hazard ratio: 1.267; p < 0.001). Addition of stress GLS into a model with clinical and imaging predictors resulted in significant increase in the C-index (from 0.80 to 0.85; p = 0.031) and a continuous net reclassification improvement of 0.898 (95% confidence interval: 0.565 to 1.124). Feature-tracking stress GLS measured during vasodilator stress CMR is an independent predictor of MACE in patients with known or suspected coronary artery disease, incremental to common clinical and imaging risk factors. These findings suggest a role for feature-tracking derived stress GLS in identifying patients at highest risk of adverse events following stress CMR.

Sections du résumé

OBJECTIVES
The purpose of this study was to determine the prognostic value of feature-tracking global longitudinal strain (GLS) measured during vasodilator stress cardiac magnetic resonance (CMR) imaging.
BACKGROUND
Prior studies have suggested that blunted myocardial strain during dobutamine stress echocardiography may be associated with adverse prognosis. Recent developments in CMR feature-tracking techniques now allow assessment of strain in clinical practice using standard cine images without specialized pulse sequences or complex post-processing. Whether feature-tracking GLS measured during vasodilator stress provides independent and incremental prognostic data is unclear.
METHODS
Consecutive patients undergoing stress perfusion CMR were prospectively enrolled (n = 535). Feature-tracking stress GLS was measured immediately after regadenoson perfusion. Patients were followed for major adverse cardiac events (MACE): death, nonfatal myocardial infarction, heart failure hospitalization, sustained ventricular tachycardia, and late revascularization. Cox proportional hazards regression modeling was used to examine the association between stress GLS and MACE. The incremental prognostic value of stress GLS was assessed in nested models.
RESULTS
Over a median follow-up of 1.5 years, 82 patients experienced MACE. By Kaplan-Meier analysis, patients with stress GLS ≥ median (-19%) had significantly reduced event-free survival compared with those with stress GLS < median (log-rank p < 0.001). Stress GLS was significantly associated with risk of MACE after adjustment for clinical and imaging risk factors including ischemia, ejection fraction, and late gadolinium enhancement (hazard ratio: 1.267; p < 0.001). Addition of stress GLS into a model with clinical and imaging predictors resulted in significant increase in the C-index (from 0.80 to 0.85; p = 0.031) and a continuous net reclassification improvement of 0.898 (95% confidence interval: 0.565 to 1.124).
CONCLUSIONS
Feature-tracking stress GLS measured during vasodilator stress CMR is an independent predictor of MACE in patients with known or suspected coronary artery disease, incremental to common clinical and imaging risk factors. These findings suggest a role for feature-tracking derived stress GLS in identifying patients at highest risk of adverse events following stress CMR.

Identifiants

pubmed: 31005520
pii: S1936-878X(19)30226-8
doi: 10.1016/j.jcmg.2019.03.002
pmc: PMC6745296
mid: NIHMS1524418
pii:
doi:

Substances chimiques

Purines 0
Pyrazoles 0
Vasodilator Agents 0
regadenoson 2XLN4Y044H

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

58-65

Subventions

Organisme : NHLBI NIH HHS
ID : K23 HL132011
Pays : United States

Commentaires et corrections

Type : CommentIn

Informations de copyright

Copyright © 2020 American College of Cardiology Foundation. All rights reserved.

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Auteurs

Simone Romano (S)

Department of Medicine, University of Verona, Verona, Italy.

Benjamin Romer (B)

Division of Cardiology, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois.

Kaleigh Evans (K)

Division of Cardiology, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois.

Michael Trybula (M)

Division of Cardiology, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois.

Chetan Shenoy (C)

Division of Cardiology, Department of Medicine, University of Minnesota, Minneapolis, Minnesota.

Raymond Y Kwong (RY)

Division of Cardiology, Department of Medicine, Brigham & Women's Hospital, Harvard Medical School, Boston, Massachusetts.

Afshin Farzaneh-Far (A)

Division of Cardiology, Department of Medicine, University of Illinois at Chicago, Chicago, Illinois; Division of Cardiology, Department of Medicine, Duke University, Durham, North Carolina. Electronic address: afshin@uic.edu.

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Classifications MeSH