Augmented reality technology for preoperative planning and intraoperative navigation during hepatobiliary surgery: A review of current methods

Background: Augmented reality(AR) technology is used to reconstruct three-dimensional(3D) images of hepatic and biliary structures from computed tomography and magnetic resonance imaging data, and to superimpose the virtual images onto a view of the surgical field. In liver surgery, these superimposed virtual images help the surgeon to visualize intrahepatic structures and therefore, to operate precisely and to improve clinical outcomes.Data Sources: The keywords "augmented reality", "liver", "laparoscopic" and "hepatectomy" were used for searching publications in the Pub Med database. The primary source of literatures was from peer-reviewed journals up to December 2016. Additional articles were identified by manual search of references found in the key articles.Results: In general, AR technology mainly includes 3D reconstruction, display, registration as well as tracking techniques and has recently been adopted gradually for liver surgeries including laparoscopy and laparotomy with video-based AR assisted laparoscopic resection as the main technical application. By applying AR technology, blood vessels and tumor structures in the liver can be displayed during surgery,which permits precise navigation during complex surgical procedures. Liver transformation and registration errors during surgery were the main factors that limit the application of AR technology.Conclusions: With recent advances, AR technologies have the potential to improve hepatobiliary surgical procedures. However, additional clinical studies will be required to evaluate AR as a tool for reducing postoperative morbidity and mortality and for the improvement of long-term clinical outcomes. Future research is needed in the fusion of multiple imaging modalities, improving biomechanical liver modeling,and enhancing image data processing and tracking technologies to increase the accuracy of current AR methods.

Prognostic and survival analysis of 837 Chinese colorectal cancer patients

AIM:To develop a prognostic model to predict survival of patients with colorectal cancer (CRC). METHODS:Survival data of 837 CRC patients undergoing surgery between 1996 and 2006 were collected and analyzed by univariate analysis and Cox proportional hazard regression model to reveal the prognostic factors for CRC. All data were recorded using a standard data form and analyzed using SPSS version 18.0 (SPSS, Chicago, IL, United States). Survival curves were calculated by the Kaplan-Meier method. The log rank test was used to assess differences in survival. Univariate hazard ratios and significant and independent predictors of disease-specific survival and were identified by Cox proportional hazard analysis. The stepwise procedure was set to a threshold of 0.05. Statistical significance was defined asP < 0.05. RESULTS:The survival rate was 74% at 3 years and 68% at 5 years. The results of univariate analysis suggested age, preoperative obstruction, serum carcinoembryonic antigen level at diagnosis, status of resection, tumor size, histological grade, pathological type, lymphovascular invasion, invasion of adjacent organs, and tumor node metastasis (TNM) staging were positive prognostic factors (P < 0.05). Lymph node ratio (LNR) was also a strong prognostic factor in stage Ⅲ CRC (P < 0.0001). We divided 341 stage Ⅲ patients into three groups according to LNR values (LNR1, LNR ≤ 0.33, n = 211; LNR2, LNR 0.34-0.66, n = 76; and LNR3, LNR ≥ 0.67, n = 54). Univariate analysis showed a significant statistical difference in 3-year survival among these groups:LNR1, 73%; LNR2, 55%; and LNR3, 42% (P < 0.0001). The multivariate analysis results showed that histological grade, depth of bowel wall invasion, and number of metastatic lymph nodes were the most important prognostic factors for CRC if we did not consider the interaction of the TNM staging system (P < 0.05). When the TNM staging was taken into account, histological grade lost its statistical significance, while the specific TNM staging system showed a statistically significant difference (P < 0.0001). CONCLUSION:The overall survival of CRC patients has improved between 1996 and 2006. LNR is a powerful factor for estimating the survival of stage Ⅲ CRC patients.