医学
可视化
肝切除术
门静脉
放射科
肝癌
外科
门静脉栓塞
切除术
癌症
内科学
人工智能
计算机科学
作者
Yong Tan,Jian Zhu,Jing Li,Liming Wu,Zaixing Ouyang,Wen Ying Liu,Hao Song,Cong Yun Huang
出处
期刊:Medicine
[Wolters Kluwer]
日期:2024-07-26
卷期号:103 (30): e38980-e38980
标识
DOI:10.1097/md.0000000000038980
摘要
Liver cancer with portal vein tumor thrombus (PVTT) is a frequent finding and is related to poor prognosis. Surgical resection provides a more promising prognosis in selected patients. The purpose of this study was to explore the application of 3D (3-dimensional) visualization and image fusion technology in liver cancer with PVTT surgery. 12 patients were treated with surgery between March 2019 and August 2022. The preoperative standard liver volume (SLV), estimated future liver remnant (FLR), FLR/SLV, 3D visualization models, PVTT classification, operation programs, surgical results, and prognosis were collected and analyzed. Twelve patients who had complete data of 3D visualization and underwent hemihepatectomy combined with portal vein tumor thrombectomy. The operation plan was formulated by 3D visualization and was highly consistent with the actual surgery. The SLV was 1208.33 ± 63.22 mL, FLR was 734.00 mL and FLR/SLV was 61.62 ± 19.38%. The accuracy of classification of PVTT by 3D visualization was 100%, Cheng type Ⅱa (4 cases), Ⅱb (2 cases), Ⅲa (4 cases), and Ⅲb (2 cases). The 3D visualization model was a perfect fusion with the intraoperative live scene and precise guidance for hepatectomy. No patient was suffering from postoperative liver failure and without procedure‑associated death. 6 patients died of tumor recurrence, and 2 patients died of other reasons. The 12-month cumulative survival rate was 25.9%. 3D visualization and image fusion technology could be used for precise assessment of FLR, classification of PVTT, surgery navigation, and which was helpful in improving the safety of hepatectomy.
科研通智能强力驱动
Strongly Powered by AbleSci AI