应用放射造影术进行肝脏数字化及其管道三维重建的研究及意义

目的探索应用放射造影术进行数字化虚拟肝脏及其管道三维可视化重建研究。方法采用4例新鲜肝脏标本进行聚乙烯醇-氧化铋造影填充剂管道灌注,经64层螺旋CT无间断连续扫描后,获得肝脏断层图像数据集加以数字化处理,利用Mimics10.01、3D-Doctor、Amkira4.1等电脑软件,构建数字化虚拟肝脏模型及其管道三维可视化重建,并对其各管道进行图像质量评估。结果①4例标本灌注全部满意,管道连续、饱满圆滑、无伪影,构建的数字化肝脏可视模型,其形态逼真,能随意旋转、放大和缩小;肝内管道系统的空间结构与外形的三维关系显示清晰,将肝脏外形与内部管道透明成像显示,可进行虚拟肝切实验;②肝内管道显影清晰,肝静脉显示级数为11.7±0.81,门静脉显示级数为11.8±0.76,胆管显示级数为10.1±0.98,肝动脉显示级数为10.2±0.98;管道三维重建图像质量平均优秀率依次为:96.21%、97.05%、97.63%、97.82%;肝内管道图像平均优秀率为97.18%。结论应用放射造影术,结合螺旋CT扫描可获得精确完整的肝脏数据资料,构建出理想的数字化虚拟肝脏及管道模型,图像质量高、空间立体感强烈,可进行临床术前虚拟肝切实验及数字化网络教学应用。

Liver digitization and 3D visualization reconstruction of hepatic duct with contrast radiography

Objective To explore the liver digitization and 3D visualization reconstruction of hepatic duct with contrast radiography.Methods A total of 4 samples of fresh liver were selected and perfused with polyvinyl alcohol-bismuth oxide.After continual scanning by 64 slice spiral CT,data of liver segment were collected and digtized.With Mimics10.01,3D-Doctor,Amkira4.1software,the reconstruction was carried out and all the images were evaluated.Results All samples had satisfactory perfussion,with contiual duct,full and smooth shape,and shadow-free.The digital models were lifelike,and can be rotated and zoomed at will.The spatial construction of inner duct and outer 3D appearance were clear,showing transparent imaging which could be used in virtual heaptic resection.Besides,all inner hepatic ducts had clear development,with series of hepatic vein was 11.7±0.81,portal vein was 11.8±0.76,bile duct was 10.1±0.98,and hepatic artery was 10.2±0.98.The excellent and good rate of reconstruction images were 96.21%,97.05%,97.63%,97.82%,respectively,with the average rate was 97.18%.Conclusion Radiography combined with CT scanning are helpful in obtaining accurate and complete hepatic data,and reconstructing ideal digitized virtual models of liver and ducts.What's more,the imagings were of high quality and strong 3D sense,and can be applied in virtual experiment of liver resection and digitized network teaching.