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Detection and Grading of Coronary Allograft Vasculopathy in Post Transplanted Heart Recipients Using Magnetic Resonance Imaging

Student thesis: Doctoral ThesisDoctor of Philosophy

6 Late gadolinium enhancement (LGE) CMRI showed not only that coronary magnetic resonance angiography (CMRA) is more sensitive than conventional angiography in detecting epicardial disease but also that the degree of enhancement correlates with IVUS Based on these results CMRI could be used as a standard screening tool in patients after heart transplantation. Patients with coronary vessel wall involvement can be identified noninvasively and radiation free using CMRA. IVUS can be reserved for patients with high suspicion of CAV and may be obsolete in the future for risk stratification. Chapter 4: Alternative parameters for CAV assessment are presented in chapter four looking at wall motion abnormalities and strain defined by CMRI, using a newly available software, previously validated in congenital heart disease and other cardiac conditions. Using feature-tracking-derived CMRI, wall motion abnormalities (WMA) were identified not only in all the patients who had angiographic disease but also in 9 additional patients. Our results correlated with both mean coronary artery stenosis on IVUS and graft survival on follow up. This pilot study demonstrates that wall motion abnormalities assessed with MRI allows discrimination between patients who have coronary involvement and those who do not. Accordingly, invasive investigations can be restricted to patients at risk defined by CMRI. Chapter 5: Chapter five provides an overall discussion of the major findings of the thesis and proposes a multi-parametric CMRI sequence approach as well as a diagnostic algorithm that can safely and easily be applied to the paediatric transplant cohort in order to detect CAV earlier and non-invasively aiming towards improved outcomes in patients after heart transplantation.
Original languageEnglish
Awarding Institution
Supervisors/Advisors
  • Gerald Greil (Supervisor)
  • Michael Burch (External person) (Supervisor)
Award date2019

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