naa a22 4500 510807216 CHVBK 20180411083424.0 cr unu---uuuuu 180411e20131101xx s 000 0 eng 10.1007/s11548-013-0843-5 doi (NATIONALLICENCE)springer-10.1007/s11548-013-0843-5 Cerebrovascular segmentation and planning of depth electrode insertion for epilepsy surgery [Elektronische Daten] [Xiaofei Du, Hui Ding, Wenjing Zhou, Guangming Zhang, Guangzhi Wang] Purpose : Depth electrodes are inserted in the brain to locate the epileptogenic zone without craniotomy, but there is risk of surgical hemorrhage. Preoperative planning is required to mitigate this risk. A preoperative imaging, segmentation and three dimensional (3D) visualization procedure was developed to provide neurosurgeons with cortical and vascular anatomy information for surgical planning and neuronavigation. Methods : Cerebral vascular imaging was performed with phase-contrast magnetic resonance angiography (PC-MRA). Fuzzy c-means was performed to extract brain parenchyma from the PC-MRA images. A multi-scale vessel enhancement filter and thresholding process were combined to segment the vasculature and suppress background noise in the PC-MRA images. Finally, 3D visualization of the vasculature and cortical structures was implemented using volume rendering. Results : Quantitative and qualitative validation of the vascular segmentation method were done. Using manual vascular segmentation as the gold standard, our method produced a satisfactory result: sensitivity was as high as 90% at a specificity level of 95%. Moreover, comparing the 3D visualizations of the vasculature and cortical structure for 4 patients with their respective intraoperative craniotomy photographs showed high levels of similarity. Conclusion : A new automated segmentation and visualization procedure provides sufficient and accurate cortical and vascular anatomy information compared to intraoperative photographs. This method has potential to assist neurosurgeons with planning and neuronavigation for depth electrode insertion with avoidance of cerebral hemorrhage. CARS, 2013 Cerebrovascular segmentation nationallicence Vessel imaging nationallicence Depth electrode insertion nationallicence Image-guided neurosurgery nationallicence 3D visualization nationallicence Du Xiaofei Department of Biomedical Engineering, School of Medicine, Tsinghua University, Room C249, 100084, Beijing, China aut Ding Hui Department of Biomedical Engineering, School of Medicine, Tsinghua University, Room C249, 100084, Beijing, China aut Zhou Wenjing Tsinghua University Yuquan Hospital, No. 5, Shijingshan Road, Shijingshan District, 100049, Beijing, China aut Zhang Guangming Tsinghua University Yuquan Hospital, No. 5, Shijingshan Road, Shijingshan District, 100049, Beijing, China aut Wang Guangzhi Department of Biomedical Engineering, School of Medicine, Tsinghua University, Room C249, 100084, Beijing, China aut International Journal of Computer Assisted Radiology and Surgery Springer Berlin Heidelberg 8/6(2013-11-01), 905-916 1861-6410 8:6<905 2013 8 11548 https://doi.org/10.1007/s11548-013-0843-5 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11548-013-0843-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Du Xiaofei Department of Biomedical Engineering, School of Medicine, Tsinghua University, Room C249, 100084, Beijing, China aut NATIONALLICENCE 700 1- Ding Hui Department of Biomedical Engineering, School of Medicine, Tsinghua University, Room C249, 100084, Beijing, China aut NATIONALLICENCE 700 1- Zhou Wenjing Tsinghua University Yuquan Hospital, No. 5, Shijingshan Road, Shijingshan District, 100049, Beijing, China aut NATIONALLICENCE 700 1- Zhang Guangming Tsinghua University Yuquan Hospital, No. 5, Shijingshan Road, Shijingshan District, 100049, Beijing, China aut NATIONALLICENCE 700 1- Wang Guangzhi Department of Biomedical Engineering, School of Medicine, Tsinghua University, Room C249, 100084, Beijing, China aut NATIONALLICENCE 773 0- International Journal of Computer Assisted Radiology and Surgery Springer Berlin Heidelberg 8/6(2013-11-01), 905-916 1861-6410 8:6<905 2013 8 11548 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer