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Abstract #2151

Gradient performance-constrained optimization of OGSE time-dependent diffusion MRI for tissue microstructure imaging

Ante Zhu1, Sanghee Cho1, Muhan Shao1, Yousef Mazaheri2, Charles R.G. Guttmann3, H. Douglas Morris4,5, J. Kevin DeMarco4, Maggie Fung6, Jennifer A. McNab7, Raymond Huang3, Oguz Akin2, and Thomas K.F. Foo1
1Technology & Innovation Center, GE HealthCare, Niskayuna, NY, United States, 2Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States, 3Brigham and Women’s Hospital, Boston, MA, United States, 4Walter Reed National Military Medical Center, Bethesda, MD, United States, 5Uniformed Services University, Bethesda, MA, United States, 6MR Clinical Solutions, GE HealthCare, New York, NY, United States, 7Stanford University, Stanford, CA, United States

Synopsis

Keywords: Diffusion Acquisition, Diffusion Acquisition

Motivation: OGSE diffusion MRI (OGSE-dMRI) has been shown to differentiate tumor cellular density and thus improve tumor grading and post-treatment evaluation. Imaging protocol to maximize the differentiation is desired.

Goal(s): A framework to optimize OGSE-dMRI protocol.

Approach: Maximum b-values at different OGSE frequencies and echo times were generated based on gradient performance. ADC(f)/ADC(0 Hz) estimated from a tumor signal model was calculated. Receiver operating characteristic of differentiating cellular density was analyzed and the optimized protocol was obtained at maximum area-under-the-curve.

Results: Higher area-under-the-curve was achieved at high OGSE frequency, high b-value, and short echo time using high-performance gradient MRI system.

Impact: Radiologists, MR physicists, and engineers who need optimized imaging protocol of OGSE time-dependent diffusion MRI to assess tumor microstructure and improve clinical diagnosis of tumor grading and evaluation of treatment effectiveness.

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Keywords