Abstract #1444

Relaxation-normalized fast diffusion kurtosis imaging for semi-automatic segmentation of acute stroke lesion

Iris Yuwen Zhou¹, Yingkun Guo^1,2, Yu Wang³, Emiri Mandeville⁴, Suk-Tak Chan¹, Mark Vangel¹, Eng H Lo⁴, Xunming Ji³, and Phillip Zhe Sun¹

¹Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States, ²Department of Radiology, Key Laboratory of Obstetric & Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, China, People's Republic of, ³Cerebrovascular Diseases Research Institute, Xuanwu Hospital of Capital Medical University, Beijing, China, People's Republic of, ⁴Neuroprotection Research Laboratory, Department of Radiology and Neurology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States

Kurtosis augments DWI for defining irreversible ischemic injury. However, long acquisition time of conventional DKI limits its use in the acute stroke setting. Moreover, the complexity of cerebral structure/composition makes kurtosis map heterogeneous, limiting the specificity of kurtosis hyperintensity to acute ischemia. With strongest correlation found between mean kurtosis and R1, we proposed the relaxation-normalized fast DKI approach to mitigate the kurtosis heterogeneity in normal brain with substantially reduced scan time. We further demonstrated that this approach enabled semi-automatic lesion segmentation and enhanced stratification of the heterogeneous DWI lesion, aiding the translation of fast DKI to the acute stroke setting.

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