Presenting Author:

Alex Hanna

Principal Investigator:

Andrew Arai

Department:

Medicine

Keywords:

Diagnosis, Cardiac, Allograft, Vasculopathy, CAV, Heart, Transplant, Patients,Pixelated, Stress, Perfusion, Analysis, Ma... [Read full text] Diagnosis, Cardiac, Allograft, Vasculopathy, CAV, Heart, Transplant, Patients,Pixelated, Stress, Perfusion, Analysis, Magnetic, Resonance, imaging, mri, cmr, mr, aif, arterial, input, function, ekg, angiography, coronary, [Shorten text]

Location:

Ryan Family Atrium, Robert H. Lurie Medical Research Center

C36 - Clinical

Detecting CAV in heart transplant patients using stress perfusion MRI

Background: Cardiac Allograft Vasculopathy (CAV) is a major cause of morbidity and mortality in heart transplant patients. CAV accounts for 17% of deaths within three years of transplant and is detectable by angiography in 50% of patients within ten years of transplant. Angiography and intravascular ultrasound are currently the gold standards for detecting CAV, but repeated invasive procedures present significant risks to patients. Stress perfusion cardiac magnetic resonance imaging has previously been used to diagnosis ischemic heart disease and in studies on CAV. This study seeks to improve the sensitivity and specificity of CMR in diagnosing CAV by using a new state-of-art pixel-wise analysis. Methods: The cohort includes patients with an age range of 18 to 89 years old who were being evaluated at NMH for post-transplant rejection as part of standard of care. Coronary angiography and stress perfusion CMR studies were previously performed to evaluate CAV. The time between angiography and CMR ranged from under six months to two years with an average time of one year between studies. 44 subjects out of 49 were identified as having possibly quantifiable CMR perfusion studies, and the quality of the arterial input function (AIF), as imaged by either a dual sensitivity method or a dual bolus injection protocol, was evaluated. 19 cases had complete AIF sequences, none had the dual bolus injection. These cases were analyzed with custom software (see parameters in Figure 1). The remaining 17 cases were analyzed for problems with the AIF and re-run through the CMR analyzer with varying parameters described in Figure 1. ROIs were then manually drawn on good quality PQ maps. Results: Out of 20 potential cases with the dual sensitivity AIF sequences, only 2 cases had good perfusion maps that were usable. 7 cases were excluded during quality assurance steps due to a clipped AIF or image acquisition starting mid-perfusion. 11 cases may be usable after further processing and correcting for issues such as inaccurate gating with the EKG. Discovering these issues led to improved guidelines for CMR imaging at NMH, including recommendations to have patients breathe freely during stress and rest perfusion imaging. Conclusions: Overall, this study set out to solve a question about the diagnosis of CAV, but evolved into a quality improvement project for quantitative stress perfusion CMR imaging at NMH. Future steps for this project include correcting for missed heart beats due to EKG gating issues by using heart rates measured by nurses during image acquisition, and communicating CMR recommendations to Lurie Children’s Hospital.