Dissection and/or rupture of ascending thoracic aortic aneurysms (aTAA) are catastrophic emergencies with 40% pre-hospital mortality, and operative mortality as high as 25%. Clinical guidelines recommend elective surgical repair based primarily on aTAA size, as well as growth, symptoms, and bicuspid or connective tissue pathologies. However, significant proportion of type A dissection patients presented with aortas under specified size limits for repair. Our long-term goal is to modernize clinical aTAA decision-making using patient-specific biomechanics, fluid dynamics, and clinical profiles to predict rupture/dissection and risk-stratify patients for earlier surgical repair. The rationale is that aTA rupture/dissection is a mechanical failure occurring when wall stress exceeds wall strength. Guidelines use diameter as a surrogate for wall stress based on LaPlace's Law. We hypothesize that fluid structure interaction (FSI) analyses of aTAA wall stress is a better predictor of true wall stress and therefore better predict adverse clinical events than diameter. True wall stress, unfortunately, cannot be measured directly in vivo but requires ex vivo aTAA specimens, where patient-specific 3D zero- pressure geometry, wall thickness, residual stress, and material properties can be measured with very high resolution. Prior aTAA computational models have made numerous assumptions using generalized wall thickness, literature-based material properties, and often ignored zero-stress geometry-all of which substantially change simulation results. The Achilles heel of aTAA models to date is that none have been validated casting doubts on their accuracy and clinical utility. We propose a prospective study to compare the effectiveness of FSI vs. diameter-based approaches in predicting true wall stress in surgical aTAA patients.
Aims are: 1) Develop and validate in vivo patient-specific FSI in aTAA patients undergoing repair with the gold standard, ex vivo patient-specific aTAA from surgical specimen controls; 2) Demonstrate superiority of in vivo FSI over diameter in predicting true wall stress; 3 Quantify aTAA wall material strength from aTAA specimens and elucidate its relationship to regional aTAA wall stress. Develop empirical model to noninvasively predict in vivo wall strength; 4) Compare aortic wall stress and material properties between normal subjects and surgical aTAA patients. Define high-risk profiles using wall stress, fluid shear stress and turbulence, and clinical risk factors. We propose to first improve accuracy of in vivo aTAA FSI using 4-D flow cardiac magnetic resonance imaging (CMR) with Cine Displacement Encoding with Simulated Echos (DENSE) to determine wall material properties, wall thickness, and zero-stress geometry. We will validate in vivo models with surgical aTAA specimens and correlate aTAA failure strength with stress. Our development of high risk profiles using advanced CMR techniques to determine wall stress and fluid shear stress coupled with clinical risk factors may be used in the future to prospectively follow and predict growth and complications in all aTAA patients

Public Health Relevance

Aortic aneurysm, a swelling of the aorta, can rupture or the layers of its wall can tear apart, namely dissect, and as such, aortic aneurysm is the 15th leading cause of death in people over age 55. Though surgery is currently performed when aneurysms of the ascending thoracic aorta reach specified size limits, unfortunately, rupture/dissection still occur in significant numbers of patients below those size guidelines with no means to predict which patients are at greater risk at this time. This proposal will study patients undergoing surgical repair of ascending thoracic aortic aneurysms to determine how well computational models based on noninvasive imaging can predict aneurysm mechanical behavior in the hopes of eventually identifying and treating high risk patients with small aneurysms before they rupture or die.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL119857-04
Application #
9490418
Study Section
Bioengineering, Technology and Surgical Sciences Study Section (BTSS)
Program Officer
Lee, Albert
Project Start
2015-04-01
Project End
2019-03-31
Budget Start
2018-04-01
Budget End
2019-03-31
Support Year
4
Fiscal Year
2018
Total Cost
Indirect Cost
Name
Northern California Institute Research & Education
Department
Type
DUNS #
613338789
City
San Francisco
State
CA
Country
United States
Zip Code
94121
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