Abstract #0742

4D flow MRI of splanchnic vasculature for diagnosis of severe portal hypertension and prediction of outcomes

Octavia Bane^1,2, Amine Geahchan¹, Daniel Stocker³, Ghadi Abboud¹, Paul Kennedy¹, Himanshu Sharma¹, Stefanie Hectors¹, Swan Thung⁴, Ning Jin⁵, Aaron Fischman¹, Michael Markl⁶, Scott Reeder⁷, Thomas Schiano⁸, and Bachir Taouli^1,2

¹Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States, ²BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States, ³Radiology, University Hospital Zurich, Zurich, Switzerland, ⁴Pathology, Icahn School of Medicine at Mount Sinai, New York, NY, United States, ⁵Siemens Healthineers, Solon, OH, United States, ⁶Biomedical Engineering, Northwestern University, Chicago, IL, United States, ⁷University of Wisconsin, Madison, WI, United States, ⁸Recanati-Miller Transplantation Institute, Icahn School of Medicine at Mount Sinai, New York, NY, United States

Synopsis

Keywords: Velocity/Flow, Flow, portal hypertension, 4D flow MRI, liver decompensation

Motivation: Non-invasive detection of severe portal hypertension [PH; hepatic venous pressure gradient (HVPG)≥12 mmHg] is important to prevent decompensation and death in patients with chronic liver disease.

Goal(s): We assess the diagnostic performance of hemodynamic parameters measured with 4D flow MRI in the splanchnic vasculature for diagnosis of severe PH and prediction of liver decompensation.

Approach: In our prospective, single-center study, 56 patients with chronic liver disease had 4D flow MRI within a month of invasive HVPG measurement.

Results: Splanchnic hemodynamic measurements by 4D flow MRI identified patients with severe portal hypertension with excellent diagnostic performance, and predicted liver decompensation with good diagnostic performance.

Impact: 4D flow MRI diagnoses severe portal hypertension with excellent performance, and predicts hepatic decompensation with equivalent performance to HVPG, making it suitable for integration into surveillance MRI protocols for patients with liver cirrhosis.

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