Multiparametric quantitative structural and functional cardiac MRI in orthotopic heart transplant recipients with cardiac allograft vasculopathy
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Updated: Jul 3, 2026
In Vivo Quantitative Assessment of Myocardial Structure, Function, Perfusion and Viability Using Cardiac Micro-computed Tomography
Published on: February 16, 2016
Sandra Quinn1, Roberto Sarnari2, Andrew Zbihley2
1Department of Radiology, Northwestern University Feinberg School of Medicine, 737 N Michigan Ave, Suite 1600, Chicago, IL, 60611, USA. sandra.quinn.eire@gmail.com.
Insights
Multiparametric cardiac magnetic resonance (CMR) can detect cardiac allograft vasculopathy (CAV) in heart transplant patients. This non-invasive approach combines imaging and strain analysis to predict CAV status.
Area of Science:
- Cardiology
- Radiology
- Transplant Medicine
Background:
- Cardiac allograft vasculopathy (CAV) is a major cause of long-term graft dysfunction and failure after orthotopic heart transplantation (OHT).
- Early detection of mild-to-moderate CAV is crucial for timely intervention and improved patient outcomes.
- Current diagnostic methods may be invasive or lack sensitivity for early-stage disease.
Purpose of the Study:
- To evaluate the efficacy of multiparametric quantitative cardiac magnetic resonance (CMR) in detecting mild-to-moderate CAV in OHT recipients.
- To identify CMR-derived parameters that can serve as non-invasive biomarkers for CAV status.
Main Methods:
- Retrospective analysis of 51 OHT patients who underwent multiparametric CMR (CINE, T1/T2 mapping, ECV, feature-tracking strain).
- Comparison of CMR parameters between CAV-negative (CAV0) and CAV-positive (CAV1-CAV2) groups.
- Logistic regression analysis to determine predictors of CAV status and assess diagnostic performance.
Main Results:
- CAV-positive patients exhibited higher myocardial T2 and extracellular volume fraction (ECV) compared to CAV-negative patients.
- Attenuated radial and circumferential peak systolic strain rates, and diastolic strain rates were observed in CAV-positive patients.
- A predictive model combining ECV, peak systolic strain rates, and longitudinal diastolic strain rate achieved an AUC of 0.85 ± 0.06 for distinguishing CAV status.
Conclusions:
- Multiparametric quantitative CMR, integrating tissue characterization (ECV, T2) and myocardial strain analysis, can effectively detect mild-to-moderate CAV post-OHT.
- This non-invasive imaging approach shows significant potential for predicting CAV status in heart transplant recipients.
- The combination of functional and tissue parameters offers a promising tool for risk stratification and management of CAV.
Abstract:
The aim of this study was to verify if multiparametric quantitative CMR can detect mild-to-moderate cardiac allograft vasculopathy (CAV) in patients post-orthotopic heart transplant (OHT). 51 patients (age = 50.0 ± 13.6 years, 29% female) post-OHT 0-6 years (mean 3.2 ± 1.5 years) who underwent CMR from 2011 to 2019 were retrospectively included. Multiparametric CMR included CINE imaging covering the left ventricle (LV), pre- and post-contrast T1 mapping, and T2 mapping, extracellular volume fraction (ECV) calculation, and 2D-feature tracking strain. CAV0 ('CAV negative') patient variables were compared with CAV1-CAV2 ('CAV positive') variables. Logistic regression was used to determine predictors of CAV status. Myocardial T2 was higher in CAV positive compared with CAV negative patients (54.5 ± 7.7 ms vs. 50.2 ± 3.3 ms, p < 0.05), as was ECV (31.3 ± 5.3% vs. 27.4 ± 4.1%, p < 0.05). Radial and circumferential peak systolic strain rates were attenuated in CAV positive vs. CAV negative patients (radial: 1.4 ± 0.4 s-1 vs. 1.8 ± 0.3 s-1, circumferential: -0.9 ± 0.2 s-1 vs. -1.1 ± 0.1 s-1, p < 0.05),as well as circumferential and longitudinal peak diastolic strain rates (0.7 ± 0.7 s-1 vs. 1.0 ± 0.5 s-1, and 0.8 ± 0.3 s-1 vs. 0.9 ± 0.3 s-1, p < 0.05, respectively). CAV positive vs. negative status correlated with ECV (rho 0.41, P < 0.01), T2 (rho 0.29, p < 0.05), radial and circumferential peak systolic strain rate (rho - 0.48, P < 0.01 and rho 0.47, p < 0.001, respectively), and circumferential and longitudinal peak diastolic strain rates (rho - 0.34, p < 0.05 and rho - 0.35, p < 0.01, respectively). Logistic regression revealed that a model including ECV, peak radial and circumferential systolic strain rates and longitudinal diastolic strain rate was significant for distinguishing CAV positive vs. negative status with a receiver operator characteristic area under curve of 0.85 ± 0.06 (CI 0.73-0.97), p < 0.005. A model combining functional (strain) and tissue parameters (ECV) was predictive of CAV status, indicating the potential of multiparametric CMR for non-invasive prediction of CAV status in OHT recipients.
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