Differences in Lymph Node Metastases Patterns Among Non-pancreatic Periampullary Cancers and Histologic Subtypes: An International Multicenter Retrospective Cohort Study and Systematic Review.

BACKGROUND: Standard lymphadenectomy for pancreatoduodenectomy is defined for pancreatic ductal adenocarcinoma and adopted for patients with non-pancreatic periampullary cancer (NPPC), ampullary adenocarcinoma (AAC), distal cholangiocarcinoma (dCCA), or duodenal adenocarcinoma (DAC). This study aimed to compare the patterns of lymph node metastases among the different NPPCs in a large series and in a systematic review to guide the discussion on surgical lymphadenectomy and pathology assessment. METHODS: This retrospective cohort study included patients after pancreatoduodenectomy for NPPC with at least one lymph node metastasis (2010-2021) from 24 centers in nine countries. The primary outcome was identification of lymph node stations affected in case of a lymph node metastasis per NPPC. A separate systematic review included studies on lymph node metastases patterns of AAC, dCCA, and DAC. RESULTS: The study included 2367 patients, of whom 1535 had AAC, 616 had dCCA, and 216 had DAC. More patients with pancreatobiliary type AAC had one or more lymph node metastasis (67.2% vs 44.8%; P < 0.001) compared with intestinal-type, but no differences in metastasis pattern were observed. Stations 13 and 17 were most frequently involved (95%, 94%, and 90%). Whereas dCCA metastasized more frequently to station 12 (13.0% vs 6.4% and 7.0%, P = 0.005), DAC metastasized more frequently to stations 6 (5.0% vs 0% and 2.7%; P < 0.001) and 14 (17.0% vs 8.4% and 11.7%, P = 0.015). CONCLUSION: This study is the first to comprehensively demonstrate the differences and similarities in lymph node metastases spread among NPPCs, to identify the existing research gaps, and to underscore the importance of standardized lymphadenectomy and pathologic assessment for AAC, dCCA, and DAC.

Surgical optomics: hyperspectral imaging and deep learning towards precision intraoperative automatic tissue recognition-results from the EX-MACHYNA trial.

BACKGROUND: Hyperspectral imaging (HSI), combined with machine learning, can help to identify characteristic tissue signatures enabling automatic tissue recognition during surgery. This study aims to develop the first HSI-based automatic abdominal tissue recognition with human data in a prospective bi-center setting. METHODS: Data were collected from patients undergoing elective open abdominal surgery at two international tertiary referral hospitals from September 2020 to June 2021. HS images were captured at various time points throughout the surgical procedure. Resulting RGB images were annotated with 13 distinct organ labels. Convolutional Neural Networks (CNNs) were employed for the analysis, with both external and internal validation settings utilized. RESULTS: A total of 169 patients were included, 73 (43.2%) from Strasbourg and 96 (56.8%) from Verona. The internal validation within centers combined patients from both centers into a single cohort, randomly allocated to the training (127 patients, 75.1%, 585 images) and test sets (42 patients, 24.9%, 181 images). This validation setting showed the best performance. The highest true positive rate was achieved for the skin (100%) and the liver (97%). Misclassifications included tissues with a similar embryological origin (omentum and mesentery: 32%) or with overlaying boundaries (liver and hepatic ligament: 22%). The median DICE score for ten tissue classes exceeded 80%. CONCLUSION: To improve automatic surgical scene segmentation and to drive clinical translation, multicenter accurate HSI datasets are essential, but further work is needed to quantify the clinical value of HSI. HSI might be included in a new omics science, namely surgical optomics, which uses light to extract quantifiable tissue features during surgery.

Pancreatic Anastomosis in Robotic-Assisted Pancreaticoduodenectomy: Different Surgical Techniques.

Robot-assisted pancreatoduodenectomy (R-PD) may provide challenges but potential benefits for pancreatic-enteric anastomosis fashioning. Despite numerous trials comparing different pancreatic-enteric anastomosis techniques, an ideal method is still missing. This study aims to describe different management strategies and surgical techniques of standardized pancreatic-enteric anastomoses during an R-PD. This study reported the robotic technical steps of the modified end-to-side Blumgart pancreaticojejunostomy, the Cattel-Warren duct-to-mucosa pancreatojejunostomy, with internal or external pancreatic duct stent, and the modified end-to-side, double-layer pancreogastrostomy. A dual-console da Vinci Xi Surgical System® (Intuitive Surgical Xi, Sunnyvale, CA) was used to perform all the R-PD. Different robotic pancreatic-enteric anastomosis techniques can be used during the reconstruction phase, possibly reproducing the open technique. The type of anastomosis and applied mitigation strategies should balance surgical strategy adaptability and operative technique standardization. R-PD should be performed in high-volume centers by surgeons with extensive experience in pancreatic and advanced MI surgery, enabling different but standardized anastomotic techniques based on patients' risk factors and intraoperative findings. Future studies on robotic pancreatic anastomosis should focus on personalized approaches after adequate risk stratification.

Assessment of difficulty in laparoscopic distal pancreatectomy: A modification of the Japanese difficulty scoring system - A single-center high-volume experience.

BACKGROUND: The Japanese difficulty scoring system (DSS) was developed to assess the difficulty of laparoscopic distal pancreatectomy (LDP). The study aimed to validate a modified DSS (mDSS) in a European high-volume center. METHODS: Patients' clinical data underwent LDP for benign and malignant pancreatic lesion between September 2013 and February 2020 were reviewed. Expert laparoscopic surgeons performed the procedures. The mDSS consisted of seven variables, such as type of operation, malignancy, neoadjuvant therapy, pancreatic resection line, tumor close to major vessels, tumor extension to peripancreatic tissue, and left-sided portal hypertension and/or splenomegaly. According to the difficulty level and previous score, the mDSS was subdivided into three classes: low, intermediate, and high. Surrogates of case complexity (operative time, intraoperative blood loss and blood transfusion requirements, conversion rate) were used to validate the new scoring system. RESULTS: The study population included 140 LDP. Ninety-five (68%), 35 (25%) and 10 (7%) patients belonged to low, intermediate, and high difficulty groups. The mDSS identified the complexity of the surgical case of the series for all the surrogates of complexity considered, namely conversion rate (P = .004), operative time (P = .033) and intraoperative blood loss (P = .009). No differences were recorded in the postoperative outcomes (P > .05). CONCLUSION: The mDSS for LDP better stratified the pancreatic procedures according to their complexity. The new scoring system may allow an appropriate preoperative evaluation of surgical difficulty, facilitating LDP's training program. Future prospective studies are needed to validate the mDSS.