Linking In Vivo Hemodynamics with Outcomes in Type B Aortic Dissection Using 4D Flow MRI

PI: Bradley Allen, MD, MS, assistant professor of Radiology in the Division of Cardiovascular and Thoracic Imaging

Type B aortic dissection (TBAD) risk-stratification is increasingly relevant in the era of thoracic endovascular aortic repair (TEVAR), as outcomes and costs can differ significantly depending on treatment choice and timing. In addition to clinical and social/demographic risk factors, morphologic imaging biomarkers such as aorta diameter, entry tear size or locations, and false lumen (FL) thrombus have been used to predict which patients are at risk of adverse aorta-related outcomes (AARO). However, these morphologic parameters only indirectly reflect the underlying hemodynamic drivers (e.g. flow, stasis, and pressure) that lead to AARO. Our group has shown that 4D flow MRI in TBAD can measure flow and regurgitation at entry tears (ET) and quantify true lumen (TL) and FL flow, peak velocity, stasis, and kinetic energy (KE). Our pilot studies provide strong evidence for the role of these hemodynamic markers for TBAD AARO prediction, but available data is limited by low patient numbers, heterogenous cohorts, and variable outcome measures.  

Additionally, we have identified the following key barriers to clinical translation of 4D flow in TBAD: 1) image acquisition and analysis is inefficient and not fully validated for accuracy and reproducibility; 2) it remains unclear which hemodynamic parameters best predict AARO; 3) it is uncertain if MRA can be used for TEVAR planning (CTA is clinical standard). The goal of the current proposal is to systematically address these limitations by building on promising developments already underway in our group to test our central hypothesis: in vivo TBAD hemodynamics improve predication of patients at high-risk of AARO relative to current standard-of-care clinical, social/demographic, and morphologic biomarkers. First, we will use state-of-the-art MRI acceleration and reconstruction techniques to develop and test a dedicated, clinically translatable rapid, dual-VENC TBAD MRI protocol (Aim 1). We will also perform baseline and one year follow-up 4D flow MRI in n=100 acute TBAD patients to determine how hemodynamics compare to other biomarkers for risk-stratification and AARO prediction (Aim 2). Finally, we will fine tune our existing AI-based 4D flow analysis tools to create an efficient TBAD hemodynamic quantification pipeline for clinical translation (Aim 3). Insights from this study will improve our understanding of the role of hemodynamics in TBAD pathophysiology and provide new clinical biomarkers for risk assessment. 

Read more about this project.