Abstract #1392

Optimization and evaluation of multi-compartment diffusion MRI using the spherical mean technique for practical multiple sclerosis imaging

Sean P Devan^1,2, Xiaoyu Jiang^1,3, Francesca Bagnato⁴, and Junzhong Xu^1,3,5,6

¹Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN, United States, ²Chemical and Physical Biology Program, Vanderbilt University, Nashville, TN, United States, ³Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States, ⁴Neuroimaging Unit/Neuroimmunology Division, Department of Neurology, Vanderbilt University Medical Center, Nashville, TN, United States, ⁵Department of Biomedical Engineering, Vanderbilt University, Nashville, TN, United States, ⁶Department of Physics and Astronomy, Vanderbilt University, Nashville, TN, United States

Multi-compartment diffusion imaging using the spherical mean technique (SMT) is a recently developed method that provides more specific information for probing axonal properties in e.g., multiple sclerosis (MS) patients. However, the accuracy and precision of SMT have not been comprehensively investigated to date. We used Cramér-Rao Lower Bound (CRLB) analysis and MS patient data to optimize an SMT acquisition protocol for practical MS imaging. Second, we used computer simulations to comprehensively evaluate the accuracy and precision of SMT for reporting axonal information under various pathologic conditions. The results support better implementation and interpretation of SMT imaging for MS patients.

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