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多模影像技术在解剖性肝切除手术导航中应用价值研究
引用本文:张 鹏,祝 文,方驰华,何松盛,曾思略,文 赛,张 可.多模影像技术在解剖性肝切除手术导航中应用价值研究[J].中国实用外科杂志,2019,39(5):480-486.
作者姓名:张 鹏  祝 文  方驰华  何松盛  曾思略  文 赛  张 可
作者单位:1南方医科大学珠江医院肝胆一科 广东省数字医学临床工程技术研究中心,广东广州510282;2成都中创五联科技有限公司,四川成都610041
基金项目:"十三五"国家重点研发计划数字诊疗装备研发重点专项(No.2016YFC0106500);"十二五"国家高技术研究发展计划(863计划)(2012AA021105);"十一五"国家高技术研究发展计划(863计划)(2006AA02Z346);国家自然科学基金重大科研仪器研制项目(No.81627805);NSFC-广东联合基金项目(No.U1401254);广州市科技计划项目(No.201604020144);广东省科技计划项目(No.2017ZC0110;2016A020220013)
摘    要:目的研究三维可视化(3DV)、吲哚菁绿荧光融合影像(FIGFI)、虚拟现实(VR)技术等多模影像技术在解剖性肝切除手术导航的应用价值。方法选择2016年1月至2018年6月间南方医科大学珠江医院肝胆外科64例肝脏肿瘤病人临床资料。采用MI-3DVS对薄层CT图像数据进行个体化的肝脏、肝内脉管和肿瘤三维重建,并将三维重建模型导入VR开发引擎中转化为VR模型,指导术前规划和决策;术中使用荧光成像仪对肝脏、肿瘤进行侦测,并联合3DV和VR技术导航肝切除手术。结果 MI-3DVS三维重建的64例病人肝脏、肿瘤及肝内脉管等结构清晰;通过头戴式显示器及安装了捕捉手和手指运动的传感器的操纵手柄融入一个3D-VR环境,更立体直观地显示前期3DV模型的沉浸感、空间感和立体感;FIGFI可进行肿瘤边界界定、肝切缘的界定、微小肝癌和肝切缘残留病灶的侦测。64例病人中,肝左外叶切除4例,肝左叶切除16例,肝右前叶切除5例,肝右后叶切除5例,肝右叶切除17例,肝中叶切除术5例,肝段切除11例(5段3例、6段6例、7段1例、8段1例),尾状叶切除1例。实际手术过程与术前手术规划一致。术后均未出现腹腔出血、胆漏、肝功能衰竭等严重并发症,围手术期无死亡病例。结论多模影像技术在术前精确影像评估和术中导航解剖性、功能性、根治性肝切除手术具有重要应用价值。

关 键 词:肝切除  三维成像  吲哚菁绿  虚拟现实

Application of multimode imaging technology in real time navigation in anatomical liver resections
Affiliation:(The First Department,of Hapatobiliary Surgery,Zhujiang Hospital,Southern Medical University,Guangdong Provincial Clinical and Engineering Center of Digital Medicine,Guangzhou 510282,China)
Abstract:Application of multimode imaging technology in real time navigation in anatomical liver resections  ZHANG Peng*, ZHU Wen, FANG Chi-hua, et al.*The First Department of Hapatobiliary Surgery, Zhujiang Hospital, Southern Medical University; Guangdong Provincial Clinical and Engineering Center of Digital Medicine,Guangzhou 510282,China
Corresponding author: FANG Chi-hua, E-mail:fangch_dr@163.com
Abstract Objective To explore the value of three dimensional (3D) visualization combined with indocyanine green (ICG) fluorescent imaging and virtual reality (VR) technique in real-time navigation in anatomical liver resections. Methods Data of 64 patients with liver neoplasms were collected from January 2016 to June 2018 in Hapatobiliary Surgery, Zhujiang Hospital,Southern Medical University. Pre-operative 64-slice CT or 256-slice CT examination was performed. Thin-slice CT image data were imported into MI-3DVS to perform 3D reconstruction of liver, intrahepatic vessels and tumors. The 3D reconstruction model was then imported into a VR development engine to transform into a VR model, so as to instruct preoperative planning and decision-making; intraoperative Pinpoint fluorescence imager was used to detect liver and tumor, and 3DV and VR techniques were combined to assist the hepatectomy.During the period of this research,no perioperative death was obtained. Results Sixty-four patients with MI-3DVS 3D reconstruction showed clear liver, tumor, and intrahepatic vascular structures. The manipulator with a head-mounted display and a sensor for capturing hand and finger movement was integrated into a 3D-VR environment to visualize the immersion, spatial and stereoscopic sensation of the pre-3DV model. FIGFI could be used to define the tumor boundary and the hepatic margin, as well as to detect the small liver cancer and the residual lesion of the liver margin. In the group of 64 patients, left lateral lobe resection was performed in 4 cases, left hepatectomy in 16 cases, right anterior resection of the liver in 5 cases, right hepatic resection in 5 cases, right lobe resection in 17 cases, middle hepatectomy in 5 cases and hepatic segmentectomy in 11 cases (5 segments, 3 cases, 6 segments, 6 cases, 7 segments, 1 case, 8 segments, 1 case) and caudate lobectomy in 1 case. The actual operation procedure was consistent with the preoperative planning. No severe complications such as intraperitoneal hemorrhage, bile leakage, liver failure, death occurred after operation. Conclusion Multimode imaging technique has important application value in preoperative accurate imaging diagnosis and intraoperative anatomic, functional and radical hepatectomy.
Keywords:hepatectomy  three-dimensional imaging  indocyanine green  virtual reality  
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