Heart Transplantation

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

247 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-11-19

Study Completion Date

2030-01-31

Brief Summary

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Heart transplantation (HTx) is a well-established life-saving procedure but is associated with severe complications. Regular monitoring of heart transplant recipients is thus important for the early detection of these complications. Current standard clinical tests, however, rely on frequent invasive procedures including endomyocardial biopsies (EMB) and catheter angiography (Cath). In addition, these standard tests are limited by sampling error, the diffuse nature of HTx complications, and high health care utilization cost, estimated at \>$150,000 per year per patient in the US. To address these limitations, our group has developed a non-invasive multiparametric cardiac MRI, which can quantify abnormal changes in heart tissue and function. Our efforts during the initial period of this study (NIH funded 2014-2019) have focused on the two major complications of HTx: 1) acute cardiac rejection (ACR), the leading cause of death in the first year after heart transplant; and 2) cardiac allograft vasculopathy (CAV), the greatest risk factor for 5-year mortality beyond the first year after heart transplantation. For these major compilation, our previous cardiac MRI studies have identified new non-invasive cardiac MRI measures that can detect abnormalities of heart tissue and function. In addition, the data was able to show that heart donor and recipient mismatch (age, sex, height, weight, etc.) can cause changes in tissue and function of the transplanted heart.

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Detailed Description

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Aim 1:

To develop dedicated multiparametric cardiac MRI protocols that account for wide range body sizes and patient physiology (e.g., heart rates, breathing patterns) of heart transplant recipients, critical for the wide age range in HTx from pediatric to adult. Second, to facilitate clinical translation and multi-site portability of the often time-consuming data analysis methodology, the development of artificial intelligence (AI) deep learning concepts to enable automated cardiac MRI analysis across large cohorts. The hypothesis to be tested will verify that automated AI analysis can detect altered cardiac MRI metrics with improved efficiency and reduced inter-rater variability

Aim 2:

Comprehensive cardiac MRI measures will be evaluated for the identification of complications after heart transplantation (ACR, CAV) in children. The anticipated enrollment of n=80 (20 per year) pediatric HTx patients (\<21 years) in years 2-5 at Lurie Children's Hospital. Inclusion criteria include a clinically indicated routine cardiac MRI for HTx graft surveillance. The hypothesis to be tested is that cardiac MRI measures can inform pediatric donor selection by providing important new data on the impact of donor-recipient mismatch (e.g. age, sex, heart size, etc.) on changes in tissue and function of the transplanted heart.

Aim 3:

The slow progression of complications in heart transplant recipients requires a long-term (\>5-year) follow-up study to determine the diagnostic value of cardiac MRI for the detection of patient outcomes. Cardiac MRI data will be collected at long-term (\>5-year) follow-up in 80 HTx recipients who have already received their baseline cardiac MRI during the initial NIH-funded study period (2014-2019). will study the diagnostic value of cardiac MRI to improve the monitoring of heart transplant recipients for the major complications of acute cardiac rejection (ACR) and cardiac allograft vasculopathy (CAV). The anticipated follow-up enrollment of a total of 80 HTx patients during years 2-5 with a minimum of 5-year follow-up (20 HTx patients/year returning for HTx surveillance, baseline MRI scan was performed during the initial funding period. To clarify, our aim isn't to perfectly match donor-recipient but rather to study the clinical implications of mismatch and to help define the threshold for "too much" mismatch. In other words, today the human body may sometimes not accept a heart if the mismatch will be too great, this is sometimes hard to do and literature is scarce, especially in terms of functional rather than anatomic implications. The goal of the study could better inform these decisions.

Conditions

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Transplant, Heart Magnetic Resonance Imaging

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Study Groups

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Aim#1 Development

Developing dedicated multiparametric cardiac MRI protocols that account for a wide range of body sizes and patient physiology (e.g., heart rates, breathing patterns) of heart transplant recipients, is critical for the wide age range in HTx from pediatric to adult. Second, to facilitate clinical translation and multi-site portability of the often time-consuming data analysis. Methodology, to be employed and developed artificial intelligence (AI) deep learning concepts to enable automated cardiac MRI analysis across large cohorts. The hypothesis to be tested is that automated AI analysis can detect altered cardiac MRI metrics with improved efficiency and reduced inter-rater variability