Pancreatic Surgery in Children: Complex, Safe, and Effective.

OBJECTIVE: The aim of this study was to assess indications for and report outcomes of pancreatic surgery in pediatric patients. BACKGROUND: Indications for pancreatic surgery in children are rare and data on surgical outcomes after pediatric pancreatic surgery are scarce. METHODS: All children who underwent pancreatic surgery at a tertiary hospital specializing in pancreatic surgery between 2003 and 2022 were identified from a prospectively maintained database. Indications, surgical procedures, and perioperative as well as long-term outcomes were analyzed. RESULTS: In total, 73 children with a mean age of 12.8 years (range: 4 mo to 18 y) underwent pancreatic surgery during the observation period. Indications included chronic pancreatitis (n=35), pancreatic tumors (n=27), and pancreatic trauma (n=11). Distal pancreatectomy was the most frequently performed procedure (n=23), followed by pancreatoduodenectomy (n=19), duodenum-preserving pancreatic head resection (n=10), segmental pancreatic resection (n=7), total pancreatectomy (n=3), and others (n=11). Postoperative morbidity occurred in 25 patients (34.2%), including 7 cases (9.6%) with major complications (Clavien-Dindo≥III). There was no postoperative (90-d) mortality. The 5-year overall survival was 90.5%. The 5-year event-free survival of patients with chronic pancreatitis was 85.7%, and 69.0% for patients with pancreatic tumors. CONCLUSION: This is the largest single-center study on pediatric pancreatic surgery in a Western population. Pediatric pancreatic surgery can be performed safely. Centralization in pancreatic centers with high expertise in surgery of adult and pediatric patients is important as it both affords the benefits of pancreatic surgery experience and ensures that surgical management is adapted to the specific needs of children.

Towards a Standardization of Learning Curve Assessment in Minimally Invasive Liver Surgery.

OBJECTIVE: The aim was to analyze the learning curves of minimal invasive liver surgery(MILS) and propose a standardized reporting. SUMMARY BACKGROUND DATA: MILS offers benefits compared to open resections. For a safe introduction along the learning curve, formal training is recommended. However, definitions of learning curves and methods to assess it lack standardization. METHODS: A systematic review of PubMed, Web of Science, and CENTRAL databases identified studies on learning curves in MILS. The primary outcome was the number needed to overcome the learning curve. Secondary outcomes included endpoints defining learning curves, and characterization of different learning phases(competency, proficiency and mastery). RESULTS: 60 articles with 12'241 patients and 102 learning curve analyses were included. The laparoscopic and robotic approach was evaluated in 71 and 18 analyses and both approaches combined in 13 analyses. Sixty-one analyses (60%) based the learning curve on statistical calculations. The most often used parameters to define learning curves were operative time (n=64), blood loss (n=54), conversion (n=42) and postoperative complications (n=38). Overall competency, proficiency and mastery were reached after 34 (IQR 19-56), 50 (IQR 24-74), 58 (IQR 24-100) procedures respectively. Intraoperative parameters improved earlier (operative time: competency to proficiency to mastery: -13%, 2%; blood loss: competency to proficiency to mastery: -33%, 0%; conversion rate (competency to proficiency to mastery; -21%, -29%), whereas postoperative complications improved later (competency to proficiency to mastery: -25%, -41%). CONCLUSIONS: This review summarizes the highest evidence on learning curves in MILS taking into account different definitions and confounding factors. A standardized three-phase reporting of learning phases (competency, proficiency, mastery) is proposed and should be followed.

Characteristics and Prognostic Factors of Metachronous Second Primary Upper Gastrointestinal Cancer.

BACKGROUND: Patients with metachronous malignancies before carcinomas of the upper gastrointestinal tract were analyzed regarding clinical parameters, oncological outcome, and prognosis. METHODS: We analyzed the data of 1583 patients with gastroesophageal cancer who underwent oncological resections between 2002 and 2018. Of 1583 patients, 172 had a malignant tumor before the upper gastrointestinal cancer (second primary carcinomas) and 1411 without preceding malignancies served as the control group. The analyses were performed between both groups and within the subgroup of second primary carcinomas. RESULTS: Patients with second primary carcinomas were older (P < 0.0001), had more comorbidities (P < 0.0001), and underwent longer surgical resections (P = 0.0024). They had lower (y)pT-categories (P = 0.0427) and had longer stays in intensive care unit (P = 0.0002) and hospital (P = 0.0018). R0-resection was more frequent (P = 0.0275) while having more surgical complications (P = 0.0378). The median survival was 39.5 mo (primary carcinoma) versus 32.9 mo for (second primary carcinoma) and was not significantly different (P = 0.5359).In the subgroup analysis of second primaries, there were no significant survival differences depending on primary tumor entity (P = 0.4989). pT status (P = 0.0062), pN status (P < 0.0001), pM status (P < 0.0001), and R-status (P < 0.0001) were significant prognostic factors. A time period >9 y after the primary cancer could be identified as a novel and beneficial survival factor (P = 0.0496). Most patients with primary colorectal, prostate, hematogenous, or breast cancer had adenocarcinoma, whereas patients with initial otolaryngologic cancers mainly had squamous cell carcinoma. CONCLUSIONS: Second primary carcinomas of the upper gastrointestinal tract show distinct clinical and oncological characteristics. Common prognostic factors are applicable, and oncologic resection is recommended.

[Organ donation and organ assessment after primary circulatory death and secondary brain death]. / Organspende und Organassessment nach primärem Herz-Kreislauf-Stillstand und sekundärem Hirntod.

BACKGROUND: The global organ shortage is the biggest obstacle to expand urgently needed liver transplantation activities. In addition to donation after brain death (DBD), donation after primary circulatory death (DCD) has also been introduced in many European countries to increase the number of donated organs. OBJECTIVE: This article summarizes the legal and ethical aspects of DCD, the practical donation process of DCD, the clinical results of DCD liver transplantation with a special focus on organ assessment before a planned DCD liver transplantation. RESULTS: In Europe 11 countries have active DCD liver transplantation programs and a total of 1230 DCD liver transplantations were performed in Europe in 2023. The highest proportion of DCD liver transplantations were recorded in Belgium (52.8%), the Netherlands (42.8%) and Switzerland (32.1%). The adequate selection of donors and recipients is crucial in DCD transplantation and the use of DCD livers particularly depends on the preparedness of the healthcare system for routine machine perfusion. The leaders are Belgium, France and Italy which implant around 68-74% of DCD organs. With an adequate organ assessment, the long-term results of DBD and DCD liver transplantations are comparable. To assess mitochondrial damage and thus organ quality, hypothermic oxygenated machine perfusion (HOPE) was introduced and has the secondary benefit of mitochondrial protection through oxygenation. The establishment of aerobic metabolism in mitochondria under hypothermia leads to a reduction of toxic metabolites and the restoration of ATP storage, which subsequently leads to a reperfusion light during implantation. CONCLUSION: Expanding the donor pool with DCD donors can counteract the global organ shortage. With adequate patient selection and routine organ assessment short-term and also long-term outcomes of DBD and DCD liver transplantation are comparable.

Development of predictive model for predicting postoperative BMI and optimize bariatric surgery: a single center pilot study.

BACKGROUND: The pilot study addresses the challenge of predicting postoperative outcomes, particularly body mass index (BMI) trajectories, following bariatric surgery. The complexity of this task makes preoperative personalized obesity treatment challenging. OBJECTIVES: To develop and validate sophisticated machine learning (ML) algorithms capable of accurately forecasting BMI reductions up to 5 years following bariatric surgery aiming to enhance planning and postoperative care. The secondary goal involves the creation of an accessible web-based calculator for healthcare professionals. This is the first article that compares these methods in BMI prediction. SETTING: The study was carried out from January 2012 to December 2021 at GZOAdipositas Surgery Center, Switzerland. Preoperatively, data for 1004 patients were available. Six months postoperatively, data for 1098 patients were available. For the time points 12 months, 18 months, 2 years, 3 years, 4 years, and 5 years the following number of follow-ups were available: 971, 898, 829, 693, 589, and 453. METHODS: We conducted a comprehensive retrospective review of adult patients who underwent bariatric surgery (Roux-en-Y gastric bypass or sleeve gastrectomy), focusing on individuals with preoperative and postoperative data. Patients with certain preoperative conditions and those lacking complete data sets were excluded. Additional exclusion criteria were patients with incomplete data or follow-up, pregnancy during the follow-up period, or preoperative BMI ≤30 kg/m2. RESULTS: This study analyzed 1104 patients, with 883 used for model training and 221 for final evaluation, the study achieved reliable predictive capabilities, as measured by root mean square error (RMSE). The RMSE values for three tasks were 2.17 (predicting next BMI value), 1.71 (predicting BMI at any future time point), and 3.49 (predicting the 5-year postoperative BMI curve). These results were showcased through a web application, enhancing clinical accessibility and decision-making. CONCLUSION: This study highlights the potential of ML to significantly improve bariatric surgical outcomes and overall healthcare efficiency through precise BMI predictions and personalized intervention strategies.

Physics-based shape matching for intraoperative image guidance.

PURPOSE: Soft-tissue deformations can severely degrade the validity of preoperative planning data during computer assisted interventions. Intraoperative imaging such as stereo endoscopic, time-of-flight or, laser range scanner data can be used to compensate these movements. In this context, the intraoperative surface has to be matched to the preoperative model. The shape matching is especially challenging in the intraoperative setting due to noisy sensor data, only partially visible surfaces, ambiguous shape descriptors, and real-time requirements. METHODS: A novel physics-based shape matching (PBSM) approach to register intraoperatively acquired surface meshes to preoperative planning data is proposed. The key idea of the method is to describe the nonrigid registration process as an electrostatic-elastic problem, where an elastic body (preoperative model) that is electrically charged slides into an oppositely charged rigid shape (intraoperative surface). It is shown that the corresponding energy functional can be efficiently solved using the finite element (FE) method. It is also demonstrated how PBSM can be combined with rigid registration schemes for robust nonrigid registration of arbitrarily aligned surfaces. Furthermore, it is shown how the approach can be combined with landmark based methods and outline its application to image guidance in laparoscopic interventions. RESULTS: A profound analysis of the PBSM scheme based on in silico and phantom data is presented. Simulation studies on several liver models show that the approach is robust to the initial rigid registration and to parameter variations. The studies also reveal that the method achieves submillimeter registration accuracy (mean error between 0.32 and 0.46 mm). An unoptimized, single core implementation of the approach achieves near real-time performance (2 TPS, 7-19 s total registration time). It outperforms established methods in terms of speed and accuracy. Furthermore, it is shown that the method is able to accurately match partial surfaces. Finally, a phantom experiment demonstrates how the method can be combined with stereo endoscopic imaging to provide nonrigid registration during laparoscopic interventions. CONCLUSIONS: The PBSM approach for surface matching is fast, robust, and accurate. As the technique is based on a preoperative volumetric FE model, it naturally recovers the position of volumetric structures (e.g., tumors and vessels). It cannot only be used to recover soft-tissue deformations from intraoperative surface models but can also be combined with landmark data from volumetric imaging. In addition to applications in laparoscopic surgery, the method might prove useful in other areas that require soft-tissue registration from sparse intraoperative sensor data (e.g., radiation therapy).