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Subramanian V, Keshvani N, Segar MW, Kondamudi NJ, Chandra A, Maddineni B, Matulevicius SA, Michos ED, Lima JAC, Berry JD, Pandey A. Association of global longitudinal strain by feature tracking cardiac magnetic resonance imaging with adverse outcomes among community-dwelling adults without cardiovascular disease: The Dallas Heart Study. Eur J Heart Fail 2024; 26:208-215. [PMID: 38345558 DOI: 10.1002/ejhf.3158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Revised: 12/20/2023] [Accepted: 01/19/2024] [Indexed: 03/27/2024] Open
Abstract
AIM Left ventricular (LV) global longitudinal strain (GLS) may detect subtle abnormalities in myocardial contractility among individuals with normal LV ejection fraction (LVEF). However, the prognostic implications of GLS among healthy, community-dwelling adults is not well-established. METHODS AND RESULTS Overall, 2234 community-dwelling adults (56% women, 47% Black) with LVEF ≥50% without a history of cardiovascular disease (CVD) from the Dallas Heart Study who underwent cardiac magnetic resonance (CMR) with GLS assessed by feature tracking CMR (FT-CMR) were included. The association of GLS with the risk of incident major adverse cardiovascular events (MACE; composite of incident myocardial infarction, incident heart failure [HF], hospitalization for atrial fibrillation, coronary revascularization, and all-cause death), and incident HF or death were assessed with adjusted Cox proportional hazards models. A total of 309 participants (13.8%) had MACE during a median follow-up duration of 17 years. Participants with the worst GLS (Q4) were more likely male and of the Black race with a history of tobacco use and diabetes with lower LVEF, higher LV end-diastolic volume, and higher LV mass index. Cumulative incidence of MACE was higher among participants with worse (Q4 vs. Q1) GLS (20.4% vs. 9.0%). In multivariable-adjusted Cox models that included clinical characteristics, cardiac biomarkers and baseline LVEF, worse GLS (Q4 vs. Q1) was associated with a significantly higher risk of MACE (hazard ratio [HR] 1.55, 95% confidence interval [CI] 1.07-2.24, p = 0.02) and incident HF or death (HR 1.57, 95% CI 1.03-2.38, p = 0.04). CONCLUSIONS Impaired LV GLS assessed by FT-CMR among adults free of cardiovascular disease is associated with a higher risk of incident MACE and incident HF or death independent of cardiovascular risk factors, cardiac biomarkers and LVEF.
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Affiliation(s)
- Vinayak Subramanian
- Division of Cardiology, Department of Medicine, UT Southwestern Medical Center, Dallas, TX, USA
- Parkland Health and Hospital System, Dallas, TX, USA
| | - Neil Keshvani
- Division of Cardiology, Department of Medicine, UT Southwestern Medical Center, Dallas, TX, USA
- Parkland Health and Hospital System, Dallas, TX, USA
| | - Matthew W Segar
- Division of Cardiology, Texas Heart Institute, Houston, TX, USA
| | - Nitin J Kondamudi
- Division of Cardiology, Department of Medicine, UT Southwestern Medical Center, Dallas, TX, USA
- Parkland Health and Hospital System, Dallas, TX, USA
| | - Alvin Chandra
- Division of Cardiology, Department of Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Bhumika Maddineni
- Division of Cardiology, Department of Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Susan A Matulevicius
- Division of Cardiology, Department of Medicine, UT Southwestern Medical Center, Dallas, TX, USA
| | - Erin D Michos
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Joao A C Lima
- Division of Cardiology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jarett D Berry
- Department of Medicine, UT Health Science Center at Tyler, Tyler, TX, USA
| | - Ambarish Pandey
- Division of Cardiology, Department of Medicine, UT Southwestern Medical Center, Dallas, TX, USA
- Parkland Health and Hospital System, Dallas, TX, USA
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Weberling LD, Albert D, Ochs A, Ochs M, Siry D, Salatzki J, Giannitsis E, Frey N, Riffel J, André F. Layer-specific fast strain-encoded cardiac magnetic resonance imaging aids in the identification and discrimination of acute myocardial injury: a prospective proof-of-concept study. J Cardiovasc Magn Reson 2024; 26:101001. [PMID: 38244931 PMCID: PMC11211227 DOI: 10.1016/j.jocmr.2024.101001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 01/11/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Acute myocardial injury is a common diagnosis in the emergency department and differential diagnoses are numerous. Cardiac magnetic resonance (CMR) strain sequences, such as fast strain ENCoded (fSENC), are early predictors of myocardial function loss. This study assessed the potential diagnostic and prognostic benefits of a layer-specific approach. METHODS For this prospective study, patients in the emergency department fulfilling rule-in criteria for non-ST-elevation myocardial infarction (NSTEMI) received an ultra-fast fSENC CMR. Volunteers without cardiac diseases (controls) were recruited for comparison. Measurements were performed in a single heartbeat acquisition to measure global longitudinal strain (GLS) and segmental longitudinal strain and dysfunctional segments. The GLS was measured in two layers and a difference (GLSdifference = GLSepicardial - GLSendocardial) was calculated. The performance of those strain features was compared to standard care (physical examination, cardiac biomarkers, electrocardiogram). According to the final diagnosis after discharge, patients were divided into groups and followed up for 2 years. RESULTS A total of 114 participants, including 50 controls, were included. The 64 patients (51 male) were divided into a NSTEMI (25), myocarditis (16), and other myocardial injury group (23). GLS served as a potent predictor of myocardial injury (area under the curve (AUC) 91.8%). The GLSdifference provided an excellent diagnostic performance to identify a NSTEMI (AUC 83.2%), further improved by including dysfunctional segments (AUC 87.5%, p = 0.01). An optimal test was achieved by adding fSENC to standard care (AUC 95.5%, sensitivity 96.0%, specificity 86.5%, p = 0.03). No death occurred in 2 years for patients with normal GLS and ≤5 dysfunctional segments, while three patients died that showed abnormal GLS or >5 dysfunctional segments. CONCLUSIONS Layer-specific strain is a potential new marker with high diagnostic performance in the identification and differentiation of acute myocardial injuries.
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Affiliation(s)
- Lukas D Weberling
- Department of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, Heidelberg, Germany; DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany.
| | - David Albert
- Department of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, Heidelberg, Germany
| | - Andreas Ochs
- Department of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, Heidelberg, Germany; DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
| | - Marco Ochs
- Department of Cardiology, Angiology, Frankfurt University Hospital, Frankfurt am Main, Germany; Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Deborah Siry
- Department of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, Heidelberg, Germany
| | - Janek Salatzki
- Department of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, Heidelberg, Germany; DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
| | - Evangelos Giannitsis
- Department of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, Heidelberg, Germany; DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
| | - Norbert Frey
- Department of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, Heidelberg, Germany; DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
| | - Johannes Riffel
- Department of Cardiology and Angiology, Robert-Bosch-Hospital, Stuttgart, Germany
| | - Florian André
- Department of Cardiology, Angiology and Pneumology, Heidelberg University Hospital, Heidelberg, Germany; DZHK (German Centre for Cardiovascular Research), Heidelberg, Germany
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Korosoglou G, Sagris M, André F, Steen H, Montenbruck M, Frey N, Kelle S. Systematic review and meta-analysis for the value of cardiac magnetic resonance strain to predict cardiac outcomes. Sci Rep 2024; 14:1094. [PMID: 38212323 PMCID: PMC10784294 DOI: 10.1038/s41598-023-50835-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Accepted: 12/26/2023] [Indexed: 01/13/2024] Open
Abstract
Cardiac magnetic resonance (CMR) is the gold standard for the diagnostic classification and risk stratification in most patients with cardiac disorders. The aim of the present study was to investigate the ability of Strain-encoded MR (SENC) for the prediction of major adverse cardiovascular events (MACE). A systematic review and meta-analysis was performed according to the PRISMA Guidelines, including patients with or without cardiovascular disease and asymptomatic individuals. Myocardial strain by HARP were used as pulse sequences in 1.5 T scanners. Published literature in MEDLINE (PubMed) and Cochrane's databases were explored before February 2023 for studies assessing the clinical utility of myocardial strain by Harmonic Phase Magnetic Resonance Imaging (HARP), Strain-encoded MR (SENC) or fast-SENC. In total, 8 clinical trials (4 studies conducted in asymptomatic individuals and 4 in patients with suspected or known cardiac disease) were included in this systematic review, while 3 studies were used for our meta-analysis, based on individual patient level data. Kaplan-Meier analysis and Cox proportional hazard models were used, testing the ability of myocardial strain by HARP and SENC/fast-SENC for the prediction of MACE. Strain enabled risk stratification in asymptomatic individuals, predicting MACE and the development of incident heart failure. Of 1332 patients who underwent clinically indicated CMR, including SENC or fast-SENC acquisitions, 19 patients died, 28 experienced non-fatal infarctions, 52 underwent coronary revascularization and 86 were hospitalized due to heart failure during median 22.4 (17.2-28.5) months of follow-up. SENC/fast-SENC, predicted both all-cause mortality and MACE with high accuracy (HR = 3.0, 95% CI = 1.2-7.6, p = 0.02 and HR = 4.1, 95% CI = 3.0-5.5, respectively, p < 0.001). Using hierarchical Cox-proportional hazard regression models, SENC/fast-SENC exhibited incremental value to clinical data and conventional CMR parameters. Reduced myocardial strain predicts of all-cause mortality and cardiac outcomes in symptomatic patients with a wide range of ischemic or non-ischemic cardiac diseases, whereas in asymptomatic individuals, reduced strain was a precursor of incident heart failure.
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Affiliation(s)
- Grigorios Korosoglou
- Departments of Cardiology, Vascular Medicine and Pneumology, GRN Academic Teaching Hospital Weinheim, Roentgenstrasse 1, 69469, Weinheim, Germany.
- Cardiac Imaging Center Weinheim, Hector Foundations, Weinheim, Germany.
| | - Marios Sagris
- Hippokration General Hospital, National and Kapodistrian University of Athens, School of Medicine, Athens, Greece
| | - Florian André
- Departments of Cardiology, Angiology and Pneumology, Heidelberg University, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | - Henning Steen
- Departments of Cardiology, Angiology and Pneumology, Heidelberg University, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | | | - Norbert Frey
- Departments of Cardiology, Angiology and Pneumology, Heidelberg University, Heidelberg, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Heidelberg/Mannheim, Heidelberg, Germany
| | - Sebastian Kelle
- Department of Cardiology, Angiology and Intensive Care Medicine, Deutsches Herzzentrum der Charité, Berlin, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Berlin, Berlin, Germany
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Pezel T, Toupin S, Hovasse T, Champagne S, Unterseeh T, Chitiboi T, Sharma P, Sanguineti F, Garot P, Garot J. A fully automated stress regional strain score as a prognostic marker of cardiovascular events in patients with normal CMR. Front Cardiovasc Med 2024; 10:1334553. [PMID: 38259308 PMCID: PMC10800929 DOI: 10.3389/fcvm.2023.1334553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 12/21/2023] [Indexed: 01/24/2024] Open
Affiliation(s)
- Théo Pezel
- Department of Cardiology, University Hospital of Lariboisiere, Université Paris-Cité, (Assistance Publique des Hôpitaux de Paris, AP-HP), Paris, France
- Inserm MASCOT-UMRS 942, Department of Data Science, University Hospital of Lariboisiere, Paris, France
- Department of Radiology, University Hospital of Lariboisiere, Université Paris-Cité, (Assistance Publique des Hôpitaux de Paris, AP-HP), Paris, France
- Cardiovascular Magnetic Resonance Laboratory, Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France
- MIRACL.ai laboratory, Multimodality Imaging for Research and Analysis Core Laboratory-Artificial Intelligence, Department of Data Science, Machine Learning and Artificial Intelligence in Health, University Hospital of Lariboisiere (AP-HP), Paris, France
| | - Solenn Toupin
- Siemens Healthcare France, Scientific Partnerships, Saint-Denis, France
| | - Thomas Hovasse
- Cardiovascular Magnetic Resonance Laboratory, Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France
| | - Stéphane Champagne
- Cardiovascular Magnetic Resonance Laboratory, Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France
| | - Thierry Unterseeh
- Cardiovascular Magnetic Resonance Laboratory, Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France
| | - Teodora Chitiboi
- Siemens Healthcare GmbH, Department of CMR, Hamburg, Deutschland
| | - Puneet Sharma
- Digital Technologies and Innovation, Siemens Healthineers, Princeton, NJ, United States
| | - Francesca Sanguineti
- Cardiovascular Magnetic Resonance Laboratory, Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France
| | - Philippe Garot
- Cardiovascular Magnetic Resonance Laboratory, Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France
| | - Jérôme Garot
- Cardiovascular Magnetic Resonance Laboratory, Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Privé Jacques Cartier, Ramsay Santé, Massy, France
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Pezel T, Garot P, Toupin S, Hovasse T, Sanguineti F, Champagne S, Morisset S, Chitiboi T, Jacob AJ, Sharma P, Unterseeh T, Garot J. Prognostic impact of artificial intelligence-based fully automated global circumferential strain in patients undergoing stress CMR. Eur Heart J Cardiovasc Imaging 2023; 24:1269-1279. [PMID: 37159403 DOI: 10.1093/ehjci/jead100] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 03/11/2023] [Accepted: 04/24/2023] [Indexed: 05/11/2023] Open
Abstract
AIMS To determine whether fully automated artificial intelligence-based global circumferential strain (GCS) assessed during vasodilator stress cardiovascular (CV) magnetic resonance (CMR) can provide incremental prognostic value. METHODS AND RESULTS Between 2016 and 2018, a longitudinal study included all consecutive patients with abnormal stress CMR defined by the presence of inducible ischaemia and/or late gadolinium enhancement. Control subjects with normal stress CMR were selected using a propensity score-matching. Stress-GCS was assessed using a fully automatic machine-learning algorithm based on featured-tracking imaging from short-axis cine images. The primary outcome was the occurrence of major adverse clinical events (MACE) defined as CV mortality or nonfatal myocardial infarction. Cox regressions evaluated the association between stress-GCS and the primary outcome after adjustment for traditional prognosticators. In 2152 patients [66 ± 12 years, 77% men, 1:1 matched patients (1076 with normal and 1076 with abnormal CMR)], stress-GCS was associated with MACE [median follow-up 5.2 (4.8-5.5) years] after adjustment for risk factors in the propensity-matched population [adjusted hazard ratio (HR), 1.12 (95% CI, 1.06-1.18)], and patients with normal CMR [adjusted HR, 1.35 (95% CI, 1.19-1.53), both P < 0.001], but not in patients with abnormal CMR (P = 0.058). In patients with normal CMR, an increased stress-GCS showed the best improvement in model discrimination and reclassification above traditional and stress CMR findings (C-statistic improvement: 0.14; NRI = 0.430; IDI = 0.089, all P < 0.001; LR-test P < 0.001). CONCLUSION Stress-GCS is not a predictor of MACE in patients with ischaemia, but has an incremental prognostic value in those with a normal CMR although the absolute event rate remains low.
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Affiliation(s)
- Théo Pezel
- Institut Cardiovasculaire Paris Sud (ICPS), Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300, Massy, France
- Université de Paris Cité, Department of Cardiology, Hôpital Lariboisière-APHP, Inserm UMRS 942, France
| | - Philippe Garot
- Institut Cardiovasculaire Paris Sud (ICPS), Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300, Massy, France
| | - Solenn Toupin
- Siemens Healthcare France, Scientific partnerships, 93200 Saint-Denis, France
| | - Thomas Hovasse
- Institut Cardiovasculaire Paris Sud (ICPS), Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300, Massy, France
| | - Francesca Sanguineti
- Institut Cardiovasculaire Paris Sud (ICPS), Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300, Massy, France
| | - Stéphane Champagne
- Institut Cardiovasculaire Paris Sud (ICPS), Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300, Massy, France
| | - Stéphane Morisset
- Independent Biostatistician, Université de Paris Cité, Pérouges, France
| | - Teodora Chitiboi
- Siemens Healthineers, Biomedical Engineering, Lindenplatz 2, Germany
| | - Athira J Jacob
- Siemens Healthineers, Digital Technologies and Innovation, 755 College Road East, Princeton NJ 08540, USA
| | - Puneet Sharma
- Siemens Healthineers, Digital Technologies and Innovation, 755 College Road East, Princeton NJ 08540, USA
| | - Thierry Unterseeh
- Institut Cardiovasculaire Paris Sud (ICPS), Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300, Massy, France
| | - Jérôme Garot
- Institut Cardiovasculaire Paris Sud (ICPS), Cardiovascular Magnetic Resonance Laboratory, Hôpital Privé Jacques CARTIER, Ramsay Santé, 6 Avenue du Noyer Lambert, 91300, Massy, France
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