Chengjun Yao1, Yixun Liu2, Jianhua Yao2, Dongxiao Zhuang1, Jinsong Wu3, Zhiyong Qin1, Ying Mao1, Liangfu Zhou4. 1. Glioma Surgery Division, Neurological Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, PR China. 2. Radiology and Imaging Sciences, National Institutes of Health, PR China. 3. Glioma Surgery Division, Neurological Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, PR China. Electronic address: wjsongc@126.com. 4. Glioma Surgery Division, Neurological Surgery Department, Huashan Hospital, Shanghai Medical College, Fudan University, PR China. Electronic address: lfzhouc@126.com.
Abstract
BACKGROUND: Preoperatively acquired diffusion tensor image (DTI) and blood oxygen level dependent (BOLD) have been proved to be effective in providing more anatomical and functional information; however, the brain deformation induced by brain shift and tumor resection severely impairs the correspondence between the image space and the patient space in image-guided neurosurgery. METHOD: To address the brain deformation, we developed a hybrid non-rigid registration method to register high-field preoperative MRI with low-field intra-operative MRI in order to recover the deformation induced by brain shift and tumor resection. The registered DTI and BOLD are fused with low-field intra-operative MRI for image-guided neurosurgery. RESULTS: The proposed hybrid registration method was evaluated by comparing the landmarks predicted by the hybrid registration method with the landmarks identified in the low-field intra-operative MRI for 10 patients. The prediction error of the hybrid method is 1.92±0.54 mm, and the compensation accuracy is 74.3±5.0%. Compared to the landmarks far from the resection region, those near the resection region demonstrated a higher compensation accuracy (P-value=.003) although these landmarks had larger initial displacements. CONCLUSIONS: The proposed hybrid registration method is able to bring preoperatively acquired BOLD and DTI into the operating room and compensate for the deformation to augment low-field intra-operative MRI with rich anatomical and functional information.
BACKGROUND: Preoperatively acquired diffusion tensor image (DTI) and blood oxygen level dependent (BOLD) have been proved to be effective in providing more anatomical and functional information; however, the brain deformation induced by brain shift and tumor resection severely impairs the correspondence between the image space and the patient space in image-guided neurosurgery. METHOD: To address the brain deformation, we developed a hybrid non-rigid registration method to register high-field preoperative MRI with low-field intra-operative MRI in order to recover the deformation induced by brain shift and tumor resection. The registered DTI and BOLD are fused with low-field intra-operative MRI for image-guided neurosurgery. RESULTS: The proposed hybrid registration method was evaluated by comparing the landmarks predicted by the hybrid registration method with the landmarks identified in the low-field intra-operative MRI for 10 patients. The prediction error of the hybrid method is 1.92±0.54 mm, and the compensation accuracy is 74.3±5.0%. Compared to the landmarks far from the resection region, those near the resection region demonstrated a higher compensation accuracy (P-value=.003) although these landmarks had larger initial displacements. CONCLUSIONS: The proposed hybrid registration method is able to bring preoperatively acquired BOLD and DTI into the operating room and compensate for the deformation to augment low-field intra-operative MRI with rich anatomical and functional information.