Yuancheng Jiang1, Xiao Han2, Jinchao Wang2, Sisi Li3, Ke Wang4, Yandong Liu5, Wei Liang5, Wen Jiang5, and Hua Guo3
1Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Department of spine surgery, Beijing Jishuitan Hospital, Beijing, China, 3Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 4Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States, 5Department of Radiology, Beijing Jishuitan Hospital, Beijing, China
1Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 2Department of spine surgery, Beijing Jishuitan Hospital, Beijing, China, 3Center for Biomedical Imaging Research, Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing, China, 4Electrical Engineering and Computer Sciences, University of California, Berkeley, Berkeley, CA, United States, 5Department of Radiology, Beijing Jishuitan Hospital, Beijing, China
We find that study for metrics in different ROIs is necessary. By designing a multi-parameter model, we aim to propose a comprehensive imaging index that correlates well with mJOA.
Fig.
2 Calculated DTI and MTR metrics for
the non-compressed slice (No. 1) and the compressed slice (No. 2).
Fig.
3 Spearman
correlation between mJOA and FA (left), mJOA, and MTR (middle). Both 2 metrics
are extracted from DC at C2 level. The direct correlation between FA and MTR is also significant (right).