Abstract #0046

Fully Automated Inline 4D Flow MRI Visualization and Flow Analysis

Ning Jin¹, Haben Berhane^2,3, Rachel Davids¹, Katherine Binzel^4,5, Juliet Varghese⁶, Justin Baraboo^2,3, Xiaoming Bi¹, Kelvin Chow⁷, and Michael Markl^2,3

¹Siemens Medical Solutions USA, Inc., Malvern, PA, United States, ²Department of Biomedical Engineering, Northwestern University, Evanston, IL, United States, ³Department of Radiology, Northwestern Medicine, Chicago, IL, United States, ⁴Dorothy M. Davis Heart & Lung Research Institute, The Ohio State University, Columbus, OH, United States, ⁵Department of Radiology, The Ohio State University, Columbus, OH, United States, ⁶Department of Biomedical Engineering, The Ohio State University, Columbus, OH, United States, ⁷Cardiovascular MR R&D, Siemens Healthcare Ltd, Calgary, AB, Canada

Synopsis

Keywords: Flow, Flow, Automated, inline, post-processing, 4D Flow

Motivation: The widespread clinical adoption of 4D Flow remains challenging due to the need for extensive, time-consuming offline manual post-processing.

Goal(s): This study developed an innovative automated framework to fully integrate 4D Flow analysis directly on the MRI scanner.

Approach: This framework integrates automated background phase correction, vessel segmentation, blood flow pattern visualization, as well as quantification of blood flow and pulse wave velocity.

Results: The framework was tested on data from patients and volunteers, achieving comparable accuracy to commercial analysis software, while significantly reducing processing time. Analysis results were available for immediate review on the MRI console and saved for clinical use.

Impact: This automated inline 4D Flow MRI framework simplifies 4D Flow post-processing and provides immediate results from hemodynamic analysis on the scanner. It provides the potential to increase the accessibility of 4D flow and improve its translation into routine clinical practice.

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