Precise hepatectomy in the intelligent digital era

Impact of three-dimensional reconstruction visualization technology on short-term and long-term outcomes after hepatectomy in patients with hepatocellular carcinoma: a propensity-score-matched and inverse probability of treatment-weighted multicenter study

BACKGROUND

Three-dimensional reconstruction visualization technology (3D-RVT) is an important tool in the preoperative assessment of patients undergoing liver resection. However, it is not clear whether this technique can improve short-term and long-term outcomes in patients with hepatocellular carcinoma (HCC) compared with two-dimensional (2D) imaging.

METHOD

A total of 3402 patients from five centers were consecutively enrolled from January 2016 to December 2020, and grouped based on the use of 3D-RVT or 2D imaging for preoperative assessment. Baseline characteristics were balanced using propensity score matching (PSM, 1:1) and stabilized inverse probability of treatment-weighting (IPTW) to reduce potential selection bias. The perioperative outcomes, long-term overall survival (OS), and recurrence-free survival (RFS) were compared between the two groups. Cox-regression analysis was used to identify the risk factors associated with RFS.

RESULTS

A total of 1681 patients underwent 3D-RVT assessment before hepatectomy (3D group), while 1721 patients used 2D assessment (2D group). The PSM cohort included 892 patient pairs. In the IPTW cohort, there were 1608.3 patients in the 3D group and 1777.9 patients in the 2D group. In both cohorts, the 3D group had shorter operation times, lower morbidity and liver failure rates, as well as shorter postoperative hospital stays. The 3D group had more margins ≥10 mm and better RFS than the 2D group. The presence of tumors with a diameter ≥5 cm, intraoperative blood transfusion and multiple tumors were identified as independent risk factors for RFS, while 3D assessment and anatomical resection were independent protective factors.

CONCLUSION

In this multicenter study, perioperative outcomes and RFS of HCC patients following 3D-RVT assessment were significantly different from those following 2D imaging assessment. Thus, 3D-RVT may be a feasible alternative assessment method before hepatectomy for these patients.

Utilization of 3D printing technology in hepatopancreatobiliary surgery

The technology of three-dimensional (3D) printing emerged in the late 1970s and has since undergone considerable development to find numerous applications in mechanical engineering, industrial design, and biomedicine. In biomedical science, several studies have initially found that 3D printing technology can play an important role in the treatment of diseases in hepatopancreatobiliary surgery. For example, 3D printing technology has been applied to create detailed anatomical models of disease organs for preoperative personalized surgical strategies, surgical simulation, intraoperative navigation, medical training, and patient education. Moreover, cancer models have been created using 3D printing technology for the research and selection of chemotherapy drugs. With the aim to clarify the development and application of 3D printing technology in hepatopancreatobiliary surgery, we introduce seven common types of 3D printing technology and review the status of research and application of 3D printing technology in the field of hepatopancreatobiliary surgery.

The Role of Colour Segmented Fluorescence (CSF) Mode and Same-day Administration of Low-dose Indocyanine Green in Liver Surgery: Our Initial Experience : Indocyanine Green Fluorescence Guided Resection of Liver Tumours

Indocyanine green (ICG) fluorescence image guidance (I-FIGS) is increasingly used in liver surgery. Several regimens have been described regarding the optimum timing and dose of administration. This study presents our early experience with utilising monochromatic Colour Segmented Fluorescence (CSF)-mode and same-day administration of low-dose-ICG in the resection of liver tumours. Between November 2020 and March 2022, I-FIGS was used in 15 patients with suspected liver tumours. ICG was administered intravenously at 0.02 to 0.05 mg/kg dose 2-3 h before surgery. ICG camera was switched to CSF-grey-scale mode to visualise the tumour and to avoid the interference of the green background liver. Using the SPY-CSF mode, the image was scaled to near-infra-red (NIR) fluorescence intensity to accurately identify the tumours and resection margins. Fifteen patients (eight males) with a median age of 71 years (range: 36-86) underwent I-FIGS. Of these, 67% underwent laparoscopic liver surgery, 78% had non-anatomical resections, and 33% underwent redo liver surgery. The mean tumour size was 40.6 mm (SD+/-41 mm). The median number of tumours was two (1-7). All colorectal liver metastases (CRLM) had a signet ring appearance. Hepatocellular carcinomas (HCC) showed partial fluorescence. Tumours were well/moderately differentiated, with CRLM in 86% and HCC in two patients. The R0 resection rate was 72%. In our experience, low-dose-ICG administered at least 2-3 h before surgery can identify liver tumours and their margins in CSF-grey-scale mode. Further research is needed to evaluate its role in reducing R1 resection rates and surgical outcomes.

Safety and efficacy of precision hepatectomy in the treatment of primary liver cancer

BACKGROUND

The aim of this study was to investigate the safety and efficacy of precision hepatectomy in the treatment of primary liver cancer.

METHODS

An randomized controlled trial of 98 patients with primary liver cancer admitted to our hospital from February 2020 to February 2021 were analyzed for the study, and they were divided into 49 cases each in the control group (conventional hepatectomy) and the study group (precision hepatectomy) according to the different surgical methods. The surgical condition, complications and follow-up results of the two groups were counted, and the liver function and immune function of the two groups were observed before and 1 week after surgery.

RESULTS

The operation time, intraoperative bleeding, hospitalization time and anal venting time in the study group were less than those in the control group (P < 0.05). One week after surgery, AST, TBiL, ALT and ALB levels decreased, with in the study group significantly higher than those in the control group (P < 0.05); CD4+, CD3 + and CD4+/CD8 + levels were significantly higher in the study group (P < 0.05). The incidence of complications in the study group was significantly lower than that in the control group (P < 0.05). After 2 years of follow-up, the recurrence rate and mortality rate of the study group were lower than those of the control group (P < 0.05); the difference was not statistically significant when comparing the metastasis rate between the two groups (P > 0.05).

CONCLUSION

Precision hepatectomy can effectively treat primary liver cancer with high safety and could be promoted in clinical practice.

Efficacy evaluation and prognostic risk factors analysis of precise hepatectomy in the treatment of intermediate and advanced hepatocellular carcinoma

BACKGROUND

To investigate the efficacy of precise hepatectomy in the treatment of patients with intermediate and advanced hepatocellular carcinoma and analyze the risk factors affecting prognosis.

METHODS

Totally 104 patients with intermediate and advanced hepatocellular carcinoma from January 2018 to January 2019 were enrolled in this retrospective analysis. Of these, four patients lost to follow-up. Logistic regression was conducted to explore the odds ratio (OR) and 95% confidence interval (CI).

RESULTS

Compared with the control group, the precise hepatectomy decreased intraoperative blood loss (331.2928.91 to 203.29 ± 29.34 ml), operation time (198.29 ± 19.38 to 150.28 ± 18.27 min), perioperative blood transfusion volume (376.22 ± 25.93 to 228.29 ± 22.19 ml) (all P < 0.001). Logistic regression analysis of study group showed that hepatitis B infection (OR  = 1.746; 95% CI, 1.068-2.976), P  =  0.021, Child-Pugh classification (OR  =  2.319; 95% CI, 1.428-3.213), P < 0.001, Eastern Cooperative Oncology Group (ECOG) score (OR  =  2.287; 95% CI, 1.098-3.876; P  =  0.013) and Barcelona-Clinic Liver Cancer (BCLC) staging (OR = 2.029; 95% CI, 1.086-3.671; P = 0.022) were independent risk factors for prognosis of the precise hepatectomy.

CONCLUSION

Hepatitis B virus infection, Child-Pugh grade, ECOG score and BCLC staging grade were the independent risk factors affecting the prognosis of precise hepatectomy.

Liver surgery for colorectal metastasis: New paths and new goals with the help of artificial intelligence

Colorectal cancer is one of the most common neoplasia with an high risk to metastatic spread. Improving medical and surgical treatment is moving along with improving the precision of diagnosis and patient's assessment, the latter two aided more and more with the use of artificial intelligence (AI). The management of colorectal liver metastasis is multidisciplinary, and surgery is the main option. After the diagnosis, a surgical assessment of the patient is fundamental. Reaching a R0 resection with a proper remnant liver volume can be done using new techniques involving also artificial intelligence. Considering the recent application of artificial intelligence as a valid substitute for liver biopsy in chronic liver diseases, several authors tried to apply similar techniques to pre-operative imaging of liver metastasis. Radiomics showed good results in identifying structural changes in a unhealthy liver and in evaluating the prognosis after a liver resection. Recently deep learning has been successfully applied in estimating the remnant liver volume before surgery. Moreover AI techniques can help surgeons to perform an early diagnosis of neoplastic relapse or a better differentiation between a colorectal metastasis and a benign lesion. AI could be applied also in the histopathological diagnostic tool. Although AI implementation is still partially automatized, it appears faster and more precise than the usual diagnostic tools and, in the short future, could become the new gold standard in liver surgery.

3D Reconstruction Methods Purporting 3D Visualization and Volume Estimation of Brain Tumors

This work proposes the Crust algorithm for 3D reconstruction of brain tumor, an effective mechanism in the visualization of tumors for presurgical planning, radiation dose calculation. Despite the promising performance of Crust algorithm in reconstruction of Stanford models, it has not yet been considered in 3D reconstruction of brain tumor. Validation of the results is done using the comparison of the 3D models from two cutting edge techniques namely the Marching Cube and the Alpha shape algorithm. The obtained result shows that Crust algorithm provides the brain tumor model with an average quality of triangle meshes ranging from 0.85 to 0.95. Concerning the visual realism, the quality of Crust algorithm models is higher on comparison to the other models. Precision of tumor volume measurement by convex hull method is analysed by repeatability and reproducibility. The standard deviations of repeatability were between 2.03 % and 3.97 %. The experimental results show that Linear Crust algorithm produces high quality meshes with average quality of equilateral triangles close to 1.

Does application of indocyanine green fluorescence imaging enhance clinical outcomes in liver resection? A meta-analysis

BACKGROUND

Indocyanine green fluorescence imaging technology has been widely used in liver resection. However, there has been a lack of strong evidence on whether application of indocyanine green fluorescence imaging enhances clinical outcomes in liver resection. This meta-analysis was performed to compare the latest clinical results of indocyanine green fluorescence imaging-guided hepatectomy (FIGH) and conventional hepatectomy (CH) in liver diseases.

METHODS

Relevant clinical studies were retrieved from PubMed, Embase, Cochrane Library, Medline and the Web of Science databases until June 21, 2021. Stata14.0 software was adopted in meta-analysis, in which the pooled effect size was calculated by the random-effects model or the fixed-effects model. Meta-regression and subgroup analysis were used to explore sources of heterogeneity. The publication bias was ascertained by egger's test and begg's test. The trim and fill method was used to adjust the occurrence of publication bias.

RESULTS

Overall twelve studies comprising 931 patients were included. Compared to the CH group, the FIGH group has lower complications (weighted mean difference [WMD] = 0.5238; 95% CI = 0.351-0.780; P = 0.001), shorter hospital stays (WMD = -1.857; 95% CI = -2.806--0.908; P = 0.000). Six of the studies indicated that no perioperative mortality occurred in either group. In overall analysis, there was no statistical difference in the estimated blood loss between the two groups (WMD = -42.509; 95% CI = -87.842 -2.825; P = 0.066), while in subgroup analysis of only literature from Japan or published between 2018 and 2019 years showed the consistent results above (WMD = 5.613; 95% CI = -45.101-56.328; P = 0.828. WMD = 5.582; 95% CI = -34.597-45.762; P = 0.785). No significant differences were found in operative time, blood transfusion rate, R0 resection, 1-year recurrence rate, 2-year-recurrence rate and the 1-year overall survival rate (P > 0.05).

CONCLUSION

This meta-analysis showed that during the liver resection operation, application of indocyanine green fluorescence imaging is a feasible and safe method in the treatment of liver diseases, which enhances some clinical outcomes, such as lower complications and shorter hospital stays.

Two novel online nomograms for predicting the survival of individual patients undergoing partial hepatectomy for huge hepatocellular carcinoma

BACKGROUND

A method for predicting prognosis of patients who undergo partial hepatectomy for huge hepatocellular carcinoma (HHCC, diameter ≥10 cm) is currently lacking. This study aimed to establish two online nomograms to predict the overall survival (OS) and disease-free survival (DFS) for patients undergoing resection for HHCC.

METHODS

The clinicopathologic characteristics and follow-up information of patients who underwent partial hepatectomy for HHCC at two medical centers were reviewed. Using a training cohort, a Cox model was used to identify the predictors of survival. Two dynamic nomograms for OS and DFS were developed and validated based on the data.

RESULTS

Eight and nine independent factors derived from the multivariate analysis of the training cohort were screened and incorporated into the nomograms for OS and DFS, respectively. In the training cohort, the nomogram achieved concordance indices (C-indices) of 0.745 and 0.738 in predicting the OS and DFS, respectively. These results were supported by external validation (C-indices: 0.822 for OS and 0.827 for DFS). Further, the calibration curves of the endpoints showed a favorable agreement between the nomograms' assessments and actual observations.

CONCLUSIONS

The two web-based nomograms demonstrated optimal predictive performance for patients undergoing partial hepatectomy for HHCC. This provides a practical method for a personalized prognosis based on an individual's underlying risk factors.