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Abstract #1718

2D (b-M1) Data Sampling and Blood Velocity Standard Deviation Distribution Fitting for Repeatable Tri-exponential IVIM Quantification

Gregory Simchick1,2, Ruiqi Geng1,2, and Diego Hernando1,2
1Radiology, University of Wisconsin-Madison, Madison, WI, United States, 2Medical Physics, University of Wisconsin-Madison, Madison, WI, United States


There is growing evidence of tri-exponential IVIM-DWI signal behavior in the liver. However, tri-exponential estimates often suffer from the instability associated with separating three decaying signal components sampled along a single dimension (i.e., b-value). In this work, standard monopolar and noise-optimized 2D (b-M1) data sampling schemes were acquired. From each acquisition, tri-exponential ROI-based fitting and a blood velocity standard deviation distribution (BVD) fitting method were performed. The estimated tri-exponential parameters were compared across acquisitions and fitting methods. Repeatable tri-exponential IVIM estimates were obtained using the 2D data sampling combined with BVD fitting. A new, physical tri-exponential model is also proposed.

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