摘要
回顾性分析了2004-08/2005-09解放军总医院神经外科应用Dexotroscope计划系统进行术前模拟的30例患者的资料,其中基底动脉瘤2例,大脑后动脉瘤1例,眼动脉瘤3例,大脑中☆动脉瘤2例,大脑前动脉瘤1例,寰枕畸形7例,脑膜瘤4例,神经鞘瘤5例,深部胶质瘤5例。将所有患者术前CT,MRI扫描的原始资料直接输入Dexotroscope计划系统的工作站,进行重建、模拟、分割等处理,并模拟手术全过程。结果手术中所见病变与周边神经、血管、颅骨的关系与手术前模拟完全符合;动脉瘤夹闭时间从2004-01/07未使用模拟系统前的(37.60±13.43)min降低为(23.51±7.62)min,齿状突磨除时间从模拟前的81min缩短至50min左右;术后3个月Karnofsky评分达88.7分,无死亡病例。提示应用Dexotroscope计划系统进行术前模拟可以制定精确而详细的手术计划,提前了解手术的难易程度,缩短手术时间。
The data of 30 patients simulated before surgery were analyzed using Dextroscope operation planning system in Department of Neurosurgery, General Hospital of Chinese PLA between August 2004 and September 2005, including 2 patients with basilar artery aneurysm, 1 with posterior cerebral artery aneurysm, 3 with ophthalmic aneurysm, 2 with middle cerebral artery aneurysms, 1 with anterior cerebral artery aneurysm, 7 atlas-occipital malformation, 4 meningioma, 5 schwannomas, and 5 deep gliomas. The primary CT and MRI data of 30 patients were input to the workstation of Dextroscope system for 3D reconstruction, reunion, segmentation and simulation the entire process of the operation. The relationship of the cranial nerves, vessels and skull base bone with lesions during operations were similar with that of the preoperative simulation on the workstation. The time of clipping aneurysms was reduced from (37.60±13.43) minutes to (23.51±7.62) minutes following application of Dextroscope system, and time of resections of odontoid processes was shortened from 81 minutes to 50 minutes. The ratios of complications were decreased and the patients' Karnofsky scales were 88.7 scores 3 months after operation. Dextroscope operation planning system can help doctors to analyze the patients' image data on a 3-D view and video outlook. The system can raise a precise and detailed operation plan before operation based on the simulation of the operation process, to well know the difficulty and shorten operation duration.
出处
《中国组织工程研究与临床康复》
CAS
CSCD
北大核心
2009年第4期789-792,共4页
Journal of Clinical Rehabilitative Tissue Engineering Research