Shindoh Junichi, Satou Shoichi, Aoki Taku, Kawaguchi Yoshikuni, Beck Yoshifumi, Sugawara Yasuhiko, Hasegawa Kiyoshi, Kokudo Norihiro
Department of Surgery, University of Tokyo, Tokyo, Japan.
Hepatogastroenterology. 2012 Mar-Apr;59(114):511-4. doi: 10.5754/hge11454.
BACKGROUND/AIMS: To establish an objective and precise vascular naming method to explore the segmental anatomy of the liver with major anomalies using three dimensional (3D) simulations.
Two algorithms, "Alternative vascular visualization method" (Algorithm A) and "Cholecystic axis based definition" (Algorithm B), were devised. Twenty livers with typical anatomy and four anomalous cases were screened by six masked physicians using a blinded protocol.
After confirming the feasibility in subjects with a typical anatomy, the accuracies of the algorithms were tested in anomalous cases. Using conventional 3D screening, the accuracies of the portal and hepatic venous definitions were 40.6% and 61.1%, respectively. However, after the introduction of the presently reported algorithms, these results improved to 83.4% and 83.4%, respectively, for Algorithm A, and 88.5% and 83.3%, respectively, for Algorithm B. In particular, the accuracy was further improved to nearly 100% when the naming process was started from the larger side of the liver in Algorithm A.
The present study confirmed that Algorithm A enables the precise vascular definitions when the process is started from the larger side of the liver. This method may be a useful tool for anatomic exploration of liver with major anomalies.
背景/目的：建立一种客观、精确的血管命名方法，利用三维（3D）模拟探索存在主要异常情况的肝脏的节段性解剖结构。
设计了两种算法，即“交替血管可视化方法”（算法A）和“基于胆囊轴的定义”（算法B）。6名盲法医生采用盲法方案对20例具有典型解剖结构的肝脏和4例异常病例进行筛查。
在确认算法在具有典型解剖结构的受试者中的可行性后，在异常病例中测试算法的准确性。采用传统的3D筛查，门静脉和肝静脉定义的准确率分别为40.6%和61.1%。然而，在引入本报告的算法后，算法A的这些结果分别提高到83.4%和83.4%，算法B的结果分别提高到88.5%和83.3%。特别是，在算法A中从肝脏较大侧开始命名过程时，准确率进一步提高到近100%。
本研究证实，算法A在从肝脏较大侧开始命名过程时能够实现精确的血管定义。该方法可能是探索存在主要异常情况的肝脏解剖结构的有用工具。
