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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
Multiparametric quantitative structural and functional cardiac MRI in orthotopic heart transplant recipients with
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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