More than 2100 heart transplants are performed per year in the United States alone, and for patients receiving a heart transplant, cardiac allograft vasculopathy (CAV) is the leading cause of death. There is currently no non-invasive means to detect CAV at is earliest, most treatable stage. CAV is a unique disease that is characterized by diffuse concentric stenosis first of the microvasculature and then the coronary arteries that can lead to ischemia and small stellate infarcts. Because heart transplant patients lack innervation of the heart, they do not experience the chest pain usually associated with infarct allowing CAV to progress un- noticed. For this reason, screening diagnostic measures are particularly important in heart transplant patients. Currently, CAV is detected in its advanced stages with Xray-angiography or Intravasular Ultrasound (IVUS), but these are invasive procedures, and because they assess the coronary arteries instead of the microvasculature, CAV can often go undetected. We propose the development of two new MRI tools to assess changes in myocardial function that reflect early onset CAV: quantitative perfusion and quantitative blood volume. In the proposed work, we will develop these new sequences in healthy volunteers, validate them, and then apply them to the intended population of transplant recipients.
One complication after heart transplant surgery is a diffuse narrowing of vessels within the transplanted heart. This disease is called Cardiac Allograft Vasculopathy (CAV), and it is one of the leading causes of death for patients that receive heart transplants. There is an unmet need to for earlier diagnosis of CAV so that it can be treated before it progresses. The goal of this project is to develop and validate a method to detect CAV in its earliest stages using non-invasive imaging.
|Lin, Chen; Lee, Jungwha; Chatterjee, Neil et al. (2017) Predicting Domain-Specific Health-Related Quality of Life Using Acute Infarct Volume. Stroke 48:1925-1931|
|Chatterjee, Neil R; Ansari, Sameer A; Vakil, Parmede et al. (2015) Automated analysis of perfusion weighted MRI using asymmetry in vascular territories. Magn Reson Imaging 33:618-23|
|Bane, Octavia; Lee, Daniel C; Benefield, Brandon C et al. (2014) Leakage and water exchange characterization of gadofosveset in the myocardium. Magn Reson Imaging 32:224-35|