With the developments of digital medicine, Gd-EOB-DTPA enhanced magnetic resonance imaging, molecular imaging and optical/acoustic multi-modality imaging, the hepatopancreatobiliary surgery have entered the era of precise diagnosis and treatment.Bidimensional pattern of disease diagnosis and treatment is developing toward three-dimensional pattern, which make the diagnosis and treatment more comprehensive and clear.Morphological imaging is gradually developing towards molecular imaging.Ultimately, the goal of truly precise diagnosis and accurate treatment will be achieved.

Objective To explore the effect of LPLD (laparoscopic peritoneal lavage and drainage ) on SAP (severe acute pancreatitis), and to compare its effect with that of non- LPLD (conservative medical management). Methods We collected data from 87 consecutive patients with SAP, from January 2009 to May 2014, including LPLD group (n = 46) and non-LPLD group (n = 41). LPLD was performed in the 1st and 2nd week after the disease onset in LPDP group and other treatment in LPDP group was the same as that in non-LPLD group. Data were comparatively analyzed in two groups about the length of hospital stay, ICU stay, cure rate, incidence of complications and in-hospital mortality. Results In LPLD group, hospital stay, and ICU stay were shorter while cure rate was higher than those in non-LPLD group , and the difference was statistically significant (P < 0.05). In terms of the incidence of complications in two groups, only the incidence of sepsis indicated statistical significance (P < 0.05) and in-hospital mortality did not differ significantly between two groups (P > 0.05). Conclusion Compared with non-LPLD, LPLD is effective in short outcome, which is a promising treatment for SAP.

Objective To evaluate the clinical value of percutaneous transhepaticcholangioscopic lithotomy (PTCSL)combined with rigid cholangioscopy in treatment of recurrent hepatolithiasis. Methods Retrospective analysisof therapeutic result of 54 patientswith postoperative recurrent hepatolithiasisduring January 2012 to January 2015. Twenty eight cases were recruited as the observation group (PTCSL group). Twenty six cases were recruited as the control group (Laparotomy group). Following parameters were observed, operation time, intraoperative blood loss, clearance of stones and postoperative hospital stay. Results The operation time, intraoperative blood loss , clearanceof stones , and the postoperative hospital stay of the PTCSL group werebetter than that of the laparotomy group (P<0.05). The number of patients with postoperative pain of the PTCSL group was significantly lower than in the laparotomygroup (P<0.05). There were no significant differences in other complication rates. There was no difference in terms of stone recurrence , incidence of cholangitis and intrahepatic biliary strictures recurrence ratebetween two groups in follow-up period. Conclusions PTCSL combined with rigid choledochoscopywas a safe and effectivemethod with minimal invasion formanagement of the postoperative recurrent hepatolithiasis. It could got a better resultsin the short-term outcomes.

OBJECTIVETo study the value of three-dimensional (3D) visualization, 3D printing and 3D laparoscopy (3-3D techniques) in the diagnosis and surgical treatment of hepatic tumors.

METHODSFrom November 2013 to January 2015, 22 patients with hepatic tumors admitted in our department underwent abdominal thin-slice CT scanning. The CT images were imported into Medical Image three Dimensional Visualization System (MI-3DVS) for 3D reconstruction. Standard Template Library (STL) files were exported for 3D printing. The hepatic vascular classification and predicted liver resection were performed with the aid of MI-3DVS system. The 3D models were then printed and virtual liver resections were executed accordingly. Based on these preoperative surgical planning data, we performed anatomical hepatectomy using 3D laparoscopy, and the intraoperative blood loss, volume of virtual and actual liver resection and postoperative hospital stay were recorded.

RESULTSAccording to Michels's classifications, 19 patients had type I, 2 had type II, and 1 had type VIII hepatic arteries; based on Cheng classifications, the portal vein was classified into type I in 17 cases, type II in 2 cases, and type III in 2 cases, and type IV in 1 case; according to Nakamura classifications, the right hemiliver hepatic vein was classified into type I in 10 cases, type II in 7 cases, and type III in 5 cases. In the virtual operations, the mean volume of liver resected was 490 ± 228 ml and the mean remnant liver volume was 885 ± 139 ml, with a remnant to functional liver volume ratio of (71 ± 11)%. The 3D printed models stereoscopically displayed the location of the liver tumors and adjacent liver vascular structure clearly. Laparoscopic hepatectomy was performed successfully in 20 patients guided by the 3-3D techniques, and the other 2 patients required convertion to open hepatectomy. The mean operation time was 186 ± 92 min, the intraoperative blood loss was 284 ± 286 ml, the mean actual liver resection volume was 491 ± 192 ml, and the mean postoperative hospital stay of the patients was 8.6 ± 3.7 days.

CONCLUSIONSThe 3-3D technique can facilitate the evaluation of preoperative risk and critical anatomical structures and navigate the surgical procedure in real time in anatomical hepatectomy for hepatic tumors.

Blood Loss, Surgical ; Hepatectomy ; Hepatic Artery ; anatomy & histology ; Hepatic Veins ; anatomy & histology ; Humans ; Imaging, Three-Dimensional ; Laparoscopy ; Liver Neoplasms ; diagnosis ; surgery ; Portal Vein ; Printing, Three-Dimensional ; Tomography, X-Ray Computed

Objective To study the value of three-dimensional (3D) visualization, 3D printing and 3D laparoscopy (3-3D techniques) in the diagnosis and surgical treatment of hepatic tumors. Methods From November 2013 to January 2015, 22 patients with hepatic tumors admitted in our department underwent abdominal thin-slice CT scanning. The CT images were imported into Medical Image three Dimensional Visualization System (MI-3DVS) for 3D reconstruction. Standard Template Library (STL) files were exported for 3D printing. The hepatic vascular classification and predicted liver resection were performed with the aid of MI-3DVS system. The 3D models were then printed and virtual liver resections were executed accordingly. Based on these preoperative surgical planning data, we performed anatomical hepatectomy using 3D laparoscopy, and the intraoperative blood loss, volume of virtual and actual liver resection and postoperative hospital stay were recorded. Results According to Michels's classifications, 19 patients had type I, 2 had type II, and 1 had type VIII hepatic arteries;based on Cheng classifications, the portal vein was classified into type I in 17 cases, type II in 2 cases, and type III in 2 cases, and type IV in 1 case;according to Nakamura classifications, the right hemiliver hepatic vein was classified into type I in 10 cases, type II in 7 cases, and type III in 5 cases. In the virtual operations, the mean volume of liver resected was 490±228 ml and the mean remnant liver volume was 885 ± 139 ml, with a remnant to functional liver volume ratio of (71 ± 11)%. The 3D printed models stereoscopically displayed the location of the liver tumors and adjacent liver vascular structure clearly. Laparoscopic hepatectomy was performed successfully in 20 patients guided by the 3-3D techniques, and the other 2 patients required convertion to open hepatectomy. The mean operation time was 186±92 min, the intraoperative blood loss was 284±286 ml, the mean actual liver resection volume was 491±192 ml, and the mean postoperative hospital stay of the patients was 8.6±3.7 days. Conclusions The 3-3D technique can facilitate the evaluation of preoperative risk and critical anatomical structures and navigate the surgical procedure in real time in anatomical hepatectomy for hepatic tumors.

Objective To study the value of three-dimensional (3D) visualization, 3D printing and 3D laparoscopy (3-3D techniques) in the diagnosis and surgical treatment of hepatic tumors. Methods From November 2013 to January 2015, 22 patients with hepatic tumors admitted in our department underwent abdominal thin-slice CT scanning. The CT images were imported into Medical Image three Dimensional Visualization System (MI-3DVS) for 3D reconstruction. Standard Template Library (STL) files were exported for 3D printing. The hepatic vascular classification and predicted liver resection were performed with the aid of MI-3DVS system. The 3D models were then printed and virtual liver resections were executed accordingly. Based on these preoperative surgical planning data, we performed anatomical hepatectomy using 3D laparoscopy, and the intraoperative blood loss, volume of virtual and actual liver resection and postoperative hospital stay were recorded. Results According to Michels's classifications, 19 patients had type I, 2 had type II, and 1 had type VIII hepatic arteries;based on Cheng classifications, the portal vein was classified into type I in 17 cases, type II in 2 cases, and type III in 2 cases, and type IV in 1 case;according to Nakamura classifications, the right hemiliver hepatic vein was classified into type I in 10 cases, type II in 7 cases, and type III in 5 cases. In the virtual operations, the mean volume of liver resected was 490±228 ml and the mean remnant liver volume was 885 ± 139 ml, with a remnant to functional liver volume ratio of (71 ± 11)%. The 3D printed models stereoscopically displayed the location of the liver tumors and adjacent liver vascular structure clearly. Laparoscopic hepatectomy was performed successfully in 20 patients guided by the 3-3D techniques, and the other 2 patients required convertion to open hepatectomy. The mean operation time was 186±92 min, the intraoperative blood loss was 284±286 ml, the mean actual liver resection volume was 491±192 ml, and the mean postoperative hospital stay of the patients was 8.6±3.7 days. Conclusions The 3-3D technique can facilitate the evaluation of preoperative risk and critical anatomical structures and navigate the surgical procedure in real time in anatomical hepatectomy for hepatic tumors.

Objective To observe the clinical effect of percutaneous transhepatic one-step biliary fistulation (PTOBF) and percutaneous transhepatic cholangioscopy (PTCS) in the treatment of hepatolithiasis with hepatobiliary surgery history,and to explore the clinical application value of PTOBF.Methods This is retrospective analysis of 68 patients with hepatolithiasis who were admitted to hepatobiliary surgery in the First Affiliated Hospital of Guangzhou Medical University from November 2009 to October 2017.Among these cases,35 patients in the observation group (group PTOBF) were treated with PTOBF,and 33 patients in the control group (group PTCS) received PTCS treatment.The final clearance rate,the postoperative complications rate,the hospitalization time,the operation times within the course of treatment,the recurrence rate and the residual stenosis rate of the two groups were compared.Results Compared with group PTCS,the clearance rate was significantly higher in group PTOBF(82.9％ vs 54.6％,P＜0.05),while the postoperative complications rate between the two groups are similar (14.3 ％ vs 30.3 ％,P＞ 0.05);Besides,the hospitalization time(12.3±5.3 d vs 17.4±7.0 d,P＜0.05),the operation times within the course of treatment (2.2±1.3 vs 2.8±1.0,P＜0.05) and the recurrence rate(17.4％ vs 39.4％,P＜0.05) of group PTOBF were obviously lower.Conclusions PTOBF is a safe and feasible treatment for hepatolithiasis with hepatobiliary surgery history.Compared with PTCS,it has the advantages of short hospitalization time,fewer operations and better recovery.

Objective:To investigate the application value of augmented reality navigation combined with indocyanine green(ICG) fluorescence imaging technology in laparoscopic anatomical segment 8 liver resection.Methods:Clinical and pathological data from 8 patients with hepatocellular carcinoma located in segment 8 of the liver admitted to the First Department of Hepatobiliary Surgery,Zhujiang Hospital,Southern Medical University from October 2021 to October 2022 were collected restrospectively. Among them,there were 5 males and 3 females,aged between 40 and 72 years. During the operation,the self-developed laparoscopic augmented reality surgical navigation system was used to integrate the three-dimensional liver model with the laparoscopic scene,and ICG fluorescence imaging technology was used to guide the anatomical liver resection of segment 8. The predicted liver resection volume and actual liver resection volume,related surgical indicators and postoperative complications were analyzed.Results:Among the 8 patients, 4 underwent laparoscopic anatomical segment 8 liver resection,1 underwent laparoscopic anatomical ventral subsegment of segment 8 liver resection,2 underwent laparoscopic anatomical ventral subsegment combined with medial subsegment of segment 8 liver resection, and 1 underwent laparoscopic anatomical dorsal subsegment of segment 8 liver resection. All operations were completed under the guidance of augmented reality navigation combined with ICG fluorescence imaging,without conversion to open surgery. The operation time was (276.3±54.8)minutes(range:200 to 360 minutes). Intraoperative blood loss was (75.0±35.4)ml(range:50 to 150 ml). No blood transfusion was performed during the operation. The length of postoperative hospital stay was (7.6±0.8)days(range:7 to 9 days). There were no deaths or postoperative complications such as bleeding or biliary fistula during the perioperative period.Conclusion:Augmented reality navigation combined with ICG fluorescence imaging technology can guide the implementation of laparoscopic anatomical segment 8 liver resection.

Objective:To investigate the application value of augmented reality navigation combined with indocyanine green(ICG) fluorescence imaging technology in laparoscopic anatomical segment 8 liver resection.Methods:Clinical and pathological data from 8 patients with hepatocellular carcinoma located in segment 8 of the liver admitted to the First Department of Hepatobiliary Surgery,Zhujiang Hospital,Southern Medical University from October 2021 to October 2022 were collected restrospectively. Among them,there were 5 males and 3 females,aged between 40 and 72 years. During the operation,the self-developed laparoscopic augmented reality surgical navigation system was used to integrate the three-dimensional liver model with the laparoscopic scene,and ICG fluorescence imaging technology was used to guide the anatomical liver resection of segment 8. The predicted liver resection volume and actual liver resection volume,related surgical indicators and postoperative complications were analyzed.Results:Among the 8 patients, 4 underwent laparoscopic anatomical segment 8 liver resection,1 underwent laparoscopic anatomical ventral subsegment of segment 8 liver resection,2 underwent laparoscopic anatomical ventral subsegment combined with medial subsegment of segment 8 liver resection, and 1 underwent laparoscopic anatomical dorsal subsegment of segment 8 liver resection. All operations were completed under the guidance of augmented reality navigation combined with ICG fluorescence imaging,without conversion to open surgery. The operation time was (276.3±54.8)minutes(range:200 to 360 minutes). Intraoperative blood loss was (75.0±35.4)ml(range:50 to 150 ml). No blood transfusion was performed during the operation. The length of postoperative hospital stay was (7.6±0.8)days(range:7 to 9 days). There were no deaths or postoperative complications such as bleeding or biliary fistula during the perioperative period.Conclusion:Augmented reality navigation combined with ICG fluorescence imaging technology can guide the implementation of laparoscopic anatomical segment 8 liver resection.

Objective:To investigate the application value of major anatomical structure recognition model of minimally invasive liver resection based on deep learning.Methods:The retrospective and descriptive study was conducted. The 31 surgical videos of laparoscopic left lateral sectionectomy performed in Zhujiang Hospital of Southern Medical University from January 2019 to April 2023 were collected. Video clips containing the surgical procedure of left lateral lobe liver pedicle and left hepatic vein were screened by 2 liver surgeons. After quality control, screening and frame extraction, the major anatomical structures on the images of these clips were annotated. After pre-processing, these images were transported to the DeepLab v3+neural network framework for model training. Observation indicators: (1) video annotation and classification; (2) results of arti-ficial intelligence anatomical recognition model testing. Measurement data with normal distribution were represented as Mean± SD, and count data were described as absolute numbers. Results:(1) Video annotation and classification. A total of 4 130 frames of images were annotated in the 31 surgical videos, including 2 083 frames of annotated images for the left lateral lobe liver pedicle, 1 578 frames of annotated images for the left hepatic vein and 469 frames of annotated images for both the left lateral lobe liver pedicle and left hepatic vein. (2) Results of artificial intelligence anatomical recognition model testing. In four application scenarios (clean scene, bloodstain scene, partially obstruction by instrument scene, and small exposed area scene), the model was able to successfully recognize the left lateral lobe liver pedicle and left hepatic vein, with a recognition speed for anatomical markers >13 frames/s. When performing anatomical recognition on images with only the left lateral lobe liver pedicle, the Dice coefficient, intersection over union, accuracy, sensitivity and specificity of the model were 0.710±0.110, 0.560±0.120, 0.980±0.010, 0.640±0.030, and 0.980±0.010, respectively. The above indicators of the model were 0.670±0.180, 0.530±0.200, 0.980±0.010, 0.600±0.040, and 0.990±0.010 when performing anatomical recognition on images with only the left hepatic vein, and 0.580±0.180, 0.430±0.190, 0.980±0.010, 0.580±0.020, and 0.990±0.010 when per-forming anatomical recognition on images with both the left lateral lobe liver pedicle and left hepatic vein.Conclusion:The major anatomical structure recognition model of minimally invasive liver resection based on deep learning can be applied in identifying liver pedicle and hepatic vein.