Operative terminology and post-operative management approaches applied to hepatic surgery: Trainee perspectives

Operative and Hepatic Function Outcomes of Laparoscopic vs. Open Liver Resection: A Systematic Review and Meta-Analysis

Liver resection is a pivotal treatment for various liver diseases, and the choice between laparoscopic (LR) and open (OR) methods is debatable. This study aims to compare their respective complications and hepatic outcomes comprehensively, providing critical insights to guide clinical decisions and optimize patient results. We conducted a comprehensive review across PubMed, SCOPUS, WOS, and the Cochrane Library until September 2023. Randomized controlled trials (RCTs) comparing laparoscopic (LR) and open (OR) liver resections were included. Data screening, extraction, and quality assessments utilized the Risk of Bias (ROB-2). We conducted our analysis using Review Manager (RevMan 5.4) software, and the data were presented as risk ratios (RR) and mean differences (MD) with 95% confidence intervals (CI). Our comprehensive research yielded 3,192 relevant records, and 9 RCTs were finally included. LR exhibited reduced operative bleeding (MD = -82.87 ml, 95% CI: -132.45 to -33.30, P=0.001) and shorter hospital stays (MD = -2.32 days, 95% CI: -3.65 to -0.98, P=0.0007). The risk of complications was significantly lower in the LR group (RR = 0.57, 95% CI: 0.43-0.76, P<0.0001), especially in Clavian-Dindo classification degree 1 and 2 complications (RR = 0.47, 95% CI: 0.28-0.79, P=0.005). LR patients also had lower postoperative AST levels at one day (MD = -123.16 U/L, 95% CI: -206.08 to -40.24, P=0.004) and three days (MD = -35.95 U/L, 95% CI: -65.83 to -6.06, P=0.02). These findings underscore LR's superiority, emphasizing its potential to significantly enhance patient outcomes, reduce complications, and improve recovery in liver resection procedures.

Do 3D Printing Models Improve Anatomical Teaching About Hepatic Segments to Medical Students? A Randomized Controlled Study

BACKGROUND

It is a difficult and frustrating task for young surgeons and medical students to understand the anatomy of hepatic segments. We tried to develop an optimal 3D printing model of hepatic segments as a teaching aid to improve the teaching of hepatic segments.

METHODS

A fresh human cadaveric liver without hepatic disease was CT scanned. After 3D reconstruction, three types of 3D computer models of hepatic structures were designed and 3D printed as models of hepatic segments without parenchyma (type 1) and with transparent parenchyma (type 2), and hepatic ducts with segmental partitions (type 3). These models were evaluated by six experts using a five-point Likert scale. Ninety two medical freshmen were randomized into four groups to learn hepatic segments with the aid of the three types of models and traditional anatomic atlas (TAA). Their results of two quizzes were compared to evaluate the teaching effects of the four methods.

RESULTS

Three types of models were successful produced which displayed the structures of hepatic segments. By experts' evaluation, type 3 model was better than type 1 and 2 models in anatomical condition, type 2 and 3 models were better than type 1 model in tactility, and type 3 model was better than type 1 model in overall satisfaction (P < 0.05). The first quiz revealed that type 1 model was better than type 2 model and TAA, while type 3 model was better than type 2 and TAA in teaching effects (P < 0.05). The second quiz found that type 1 model was better than TAA, while type 3 model was better than type 2 model and TAA regarding teaching effects (P < 0.05). Only TAA group had significant declines between two quizzes (P < 0.05).

CONCLUSIONS

The model with segmental partitions proves to be optimal, because it can best improve anatomical teaching about hepatic segments.

The "Triple-Q Algorithm:" A practical approach to the identification of liver topography

The descriptive identification and interpretation of liver pathology continue to raise debate, especially for trainees and junior physicians. There is wide diversity in the description of liver segmentation with sometimes contradictory terminology between French and American literature. Attempts were made to create a unified nomenclature that simplifies the problem. We propose a simple approach to describe the location of liver pathology in different settings by referring to an algorithm based on three questions. Explanations to answer these questions and correctly describe the location of liver pathology are herein described. In conclusion, we think that the adoption of such an algorithm called arbitrary “the Triple-Q Algorithm” will facilitate the understanding of liver topography for the young physicians, as well as it will allow for the accurate description and localization of the pathological lesions in the liver. This could be achieved after testing and validating this algorism in prospective studies. This could have academic and clinical implications in the medical education and the patient care.