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Abstract #3078

Application of Automatic Subregion Segmentation in Perfusion Evaluation of Hippocampal Sclerosis based on Arterial Spin Labeling

Yan Mengnan1, Wang Yi Ting1, Li Jian1, Zhang Yan Ling1, Li Jin Qin1, Tian Bo1, Chen Bing1, and Xiong Yu Hui2
1Radiology, General Hospital of Ningxia Medical University, Yinchuan, China, 2MR Research, GE HealthCare MR Research, Beijing, China, Beijing, China

Synopsis

Keywords: Epilepsy, Arterial spin labelling, Automatic Subregion Segmentation

Motivation: Evaluating the hippocampal volume and perfusion level is important in the diagnosis of hippocampal sclerosis (HS). However, further observation at the subregion level is difficult.

Goal(s): To investigate the alterations in hippocampal subregion volume and blood flow in HS patients with an automatic segmentation procedure.

Approach: T1-MPRAGE and 3D-pCASL images were automatically segmented to quantify the hippocampal subregion volume and blood flow. The diagnostic performance of these subregion quantitative metrics in HS were statistically analyzed.

Results: The volume (VCA1) and blood flow (CBFCA1) of CA1 region are independent factors in diagnosing HS. The combination of VCA1 and CBFCA1 has the highest diagnostic performance.

Impact: The combination of automatic segmentation and arterial spin labeling offers a quantitative imaging foundation for diagnosing hippocampal sclerosis at the subregion level. This scheme can also be applied to other MR techniques to improve the diagnostic effectiveness in hippocampal research.

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