Thoracic aortic aneurysms (TAAs) predispose patients to sudden death due to aortic rupture or dissection. Despite advances in surgical management and medical treatment, nearly 40% of patients die before reaching a hospital ? highlighting the importance of more effective risk stratification to prevent sudden death. Current risk stratification is based on noninvasive imaging to regularly assess aortic size, the criterion used to guide timing of prophylactic surgical repair. However, we know that size alone does not fully capture the underlying causes of TAA complications. For example, among patients with genetically-mediated TAAs (the leading cause of TAAs), up to 60% of dissections occur in aortic segments with diameters below the conventional threshold for surgery. Until we identify new risk factors for aortic instability, patients will continue to suffer life-threatening complications not predicted by aortic size alone. This knowledge gap will be addressed in the applicant's proposal. In his career development proposal, based on his robust pilot data, the applicant hypothesizes that increased aortic wall inflammation and abnormal aortic biomechanics lead to faster aortic growth, a metric for aortic instability. The detection of these pathological processes is not possible with the currently used anatomic-based imaging approaches, but rather requires application of molecular and functional imaging techniques, such as positron emission tomography (PET) and magnetic resonance imaging (MRI). To establish the impact of inflammation on aortic growth, he innovatively proposes to use inflammatory radiotracers to detect aortic wall inflammation as a high-risk marker. He then proposes to study the impact of aortic stiffness, a validated biomechanical parameter, as another high- risk marker that results in rapid aortic growth. Finally, he proposes to evaluate whether stiffness and inflammation are inter-related, and whether the combination improves prediction of aortic growth. This novel study approach takes advantage of an institutional infrastructure that includes state-of-the-art hybrid PET-MR scanner that allow for simultaneous assessment of aortic anatomy and function. In addition, he will leverage the strength of his institution as a leading recruitment site for the NIH/NHLBI- sponsored GenTAC registry, and recruit participants with Marfan Syndrome, a prototype TAA disorder. The completion of the proposed project will help us understand the association between inflammation and biomechanics with aortic instability. The findings from this proposal have the potential to accelerate diagnosis, refine prognosis, and guide optimal treatment to prevent aortic complications. These findings may lead to a paradigm-shift in our approach to TAA monitoring and change in existing management guidelines with resultant reduction in mortality.
Thoracic aortic aneurysms (TAAs) predispose patients to sudden death due to aortic rupture or dissection. Despite advances in surgical management and medical treatment, nearly 40% of patients die even before reaching a hospital ? highlighting the public health importance of more effective risk stratification to prevent sudden death. Current risk stratification uses serial noninvasive imaging to regularly assess aortic size. However, aortic size alone poorly predicts TAA complications. The goals of this proposal are to identify new risk factors for TAA complications and to foster the development of a clinical-investigator who will devote his career to pursuing research in the optimal diagnosis and management of TAAs and its deadly complications.
|Singh, Parmanand; Narula, Jagat (2018) Molecular Characterization of High-Risk Aortic Aneurysms: Imaging Beyond Anatomy. J Am Coll Cardiol 71:524-526|
|Salata, Brian M; Singh, Parmanand (2017) Role of Cardiac PET in Clinical Practice. Curr Treat Options Cardiovasc Med 19:93|