Application of 3-dimensional visualization and image fusion technology in liver cancer with portal vein tumor thrombus surgery

Author:

Tan Yong1,Zhu Jian Yong2,Li Jing3,Wu Li Ming1,Ouyang Zaixing1,Liu Wen Ying1,Song Hao1,Huang Cong Yun1ORCID

Affiliation:

1. Department of Hepatobiliary Surgery, Yuebei People’s Hospital, Shaoguan, P.R. China

2. Senior Department of Hepato-Pancreato-Biliary Surgery, the First Medical Center of PLA General Hospital, Beijing, P.R. China

3. Department of Pathology, Yuebei People’s Hospital, Shaoguan, P.R. China.

Abstract

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.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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