Deep Learning Histology for Prediction of Lymph Node Metastases and Tumor Regression after Neoadjuvant FLOT Therapy of Gastroesophageal Adenocarcinoma.

BACKGROUND: The aim of this study was to establish a deep learning prediction model for neoadjuvant FLOT chemotherapy response. The neural network utilized clinical data and visual information from whole-slide images (WSIs) of therapy-naïve gastroesophageal cancer biopsies. METHODS: This study included 78 patients from the University Hospital of Cologne and 59 patients from the University Hospital of Heidelberg used as external validation. RESULTS: After surgical resection, 33 patients from Cologne (42.3%) were ypN0 and 45 patients (57.7%) were ypN+, while 23 patients from Heidelberg (39.0%) were ypN0 and 36 patients (61.0%) were ypN+ (p = 0.695). The neural network had an accuracy of 92.1% to predict lymph node metastasis and the area under the curve (AUC) was 0.726. A total of 43 patients from Cologne (55.1%) had less than 50% residual vital tumor (RVT) compared to 34 patients from Heidelberg (57.6%, p = 0.955). The model was able to predict tumor regression with an error of ±14.1% and an AUC of 0.648. CONCLUSIONS: This study demonstrates that visual features extracted by deep learning from therapy-naïve biopsies of gastroesophageal adenocarcinomas correlate with positive lymph nodes and tumor regression. The results will be confirmed in prospective studies to achieve early allocation of patients to the most promising treatment.

The role of length of oral resection margin and survival in esophageal cancer surgery after neoadjuvant therapy: A retrospective propensity score-matched study.

BACKGROUND: Multimodal therapy regimens became the standard of care for patients with esophageal cancer, whereas surgical resection remains at the center of curative treatment modalities. Current guidelines provide no recommendations on the extent of the oral resection margin, especially in the era of neoadjuvant therapy. Therefore, this study aimed to evaluate the relationship between the oral tumor-free resection margin and overall survival. METHODS: Retrospective study with 382 1:1 propensity-matched patients out of 660 patients, operated between 2013 and 2019, with an Ivor-Lewis-esophagectomy for adenocarcinoma and squamous cell carcinoma of the esophagus or esophagogastric junction after neoadjuvant therapy. Independent pathologists measured the oral resection margin after formalin fixation. RESULTS: The mean oral tumor-free resection margin was 37.2 ± 0.6 mm. The ideal cut-off for survival differences was determined for 33 mm. Patients with an oral resection margin of more than 33 mm had a better median overall survival (≤33 mm: 45.0 months, 95% confidence interval: 22.4-67.6 months, >33 mm: not reached, P = .005). An oral resection margin of more than 33 mm proved to be an independent favorable prognostic factor for patients' overall survival in multivariate Cox regression analyses (P = .049). CONCLUSION: This study analyzed a patient cohort retrospectively after curative intended Ivor-Lewis-esophagectomy after neoadjuvant therapy. An oral resection margin of more than 33 mm is a factor for improved overall survival. Therefore, a minimum resection margin of 34 mm after fixation could be suggested.

Surgical and multimodal treatment of metastatic oesophageal cancer: retrospective cohort study.

BACKGROUND: In contrast to the well-established multimodal therapy for localized oesophageal cancer, the metastatic stage is commonly treated only with systemic therapy as current international guidelines recommend. However, evidence suggesting that multimodal therapy including surgery could benefit selected patients with metastasized oesophageal cancer is increasing. The aim of this study was to investigate the survival of patients diagnosed with metastatic oesophageal cancer after different treatment regimens. METHODS: This was a retrospective single-centre study of patients with adenocarcinoma or squamous cell carcinoma of the oesophagus with synchronous or metachronous metastases who underwent Ivor Lewis oesophagectomy between 2010 and 2021. Each patient received an individual treatment for their metastatic burden based on an interdisciplinary tumour board conference. Survival differences between different treatments were assessed using the Kaplan-Meier method, as well as univariable and multivariable Cox regression models. RESULTS: Out of 1791 patients undergoing Ivor Lewis oesophagectomy, 235 patients diagnosed with metastases were included. Of all of the included patients, 42 (17.9%) only underwent surgical resection of their metastatic disease, 37 (15.7%) underwent multimodal therapy including surgery, 78 (33.2%) received chemotherapy alone, 49 (20.9%) received other therapies, and 29 (12.3%) received best supportive care. Patients who underwent resection or multimodal therapy including surgery of their metastatic burden showed superior overall survival compared with chemotherapy alone (median overall survival of 19.0, 18.0, and 11.0 months respectively) (P < 0.001). This was confirmed in subcohorts of patients with metachronous solid-organ metastases and with a single metastasis. In multivariable analyses, resection with or without multimodal therapy was an independent factor for favourable survival. CONCLUSION: Surgical resection could be a feasible treatment option for metastasized oesophageal cancer, improving survival in selected patients. Further prospective randomized studies are needed to confirm these findings and define reliable selection criteria.

European Robotic Surgery Consensus (ERSC): Protocol for the development of a consensus in robotic training for gastrointestinal surgery trainees.

BACKGROUND: The rapid adoption of robotic surgical systems across Europe has led to a critical gap in training and credentialing for gastrointestinal (GI) surgeons. Currently, there is no existing standardised curriculum to guide robotic training, assessment and certification for GI trainees. This manuscript describes the protocol to achieve a pan-European consensus on the essential components of a comprehensive training programme for GI robotic surgery through a five-stage process. METHODS AND ANALYSIS: In Stage 1, a Steering Committee, consisting of international experts, trainees and educationalists, has been established to lead and coordinate the consensus development process. In Stage 2, a systematic review of existing multi-specialty robotic training curricula will be performed to inform the formulation of key position statements. In Stage 3, a comprehensive survey will be disseminated across Europe to capture the current state of robotic training and identify potential challenges and opportunities for improvement. In Stage 4, an international panel of GI surgeons, trainees, and robotic theatre staff will participate in a three-round Delphi process, seeking ≥ 70% agreement on crucial aspects of the training curriculum. Industry and patient representatives will be involved as external advisors throughout this process. In Stage 5, the robotic training curriculum for GI trainees will be finalised in a dedicated consensus meeting, culminating in the production of an Explanation and Elaboration (E&E) document. REGISTRATION DETAILS: The study protocol has been registered on the Open Science Framework (https://osf.io/br87d/).

A senior surgical resident can safely perform complex esophageal cancer surgery after surgical mentoring program-experience of a European high-volume center.

Previous studies have shown that surgical residents can safely perform a variation of complex abdominal surgeries when provided with adequate training, proper case selection, and appropriate supervision. Their outcomes are equivalent when compared to experienced board-certified surgeons. Our previously published training curriculum for robotic assisted minimally invasive esophagectomy already demonstrated a possible reduction in time to reach proficiency. However, esophagectomy is a technically challenging procedure and comes with high morbidity rates of up to 60%, making it difficult to provide opportunities to train surgical residents. We aimed to investigate if a surgical resident could safely perform complex esophageal surgery when a structured modular teaching curriculum is applied. A structured teaching program based on our previously published modular step-up approach was applied by two experienced board-certified esophageal surgeons. Our IRB-approved (Institutional Review Board) database was searched to identify all Ivor-Lewis esophagectomies performed by the selected surgical resident from August 2019 to July 2021. The cumulative sum method was used to analyze the learning curve of the surgical resident. Outcomes of patients operated by the resident were then compared to our overall cohort of open, hybrid, and robotic Ivor-Lewis esophagectomies from May 2016 to May 2020. The total cohort included 567 patients, of which 65 were operated by the surgical resident and 502 patients were operated by experienced esophageal cancer surgeons as the control group. For baseline characteristics, a significant difference for BMI (Body mass index) was observed, which was lower in the resident's group (25.5 kg/m2 vs. 26.8 kg/m2 (P = 0.046). A significant difference of American Society of Anesthesiologists- and Eastern Cooperative Oncology Group-scores was seen, and a subgroup analysis including all patients with American Society of Anesthesiologists I and Eastern Cooperative Oncology Group 0 was performed revealing no significant differences. Postoperative complications did not differ between groups. The anastomotic leak rate was 13.8% in the resident's cohort and 12% in the control cohort (P = 0.660). Major complications (Clavien-Dindo ≥ IIIb) occurred in 16.9% of patients in both groups. Oncological outcome, defined by harvested lymph nodes (35 vs. 32.33, P = 0.096), proportion of lymph node compliant performed operations (86.2% vs. 88.4%, P = 0.590), and R0-resection rate (96.9% vs. 96%, P = 0.766), was not compromised when esophagectomies were performed by the resident. The resident completed the learning curves after 39 cases for the total operating time, 38 cases for the thoracic operating time, 26 cases for the number of harvested lymph nodes, 29 cases for anastomotic leak rate, and finally 58 cases for the comprehensive complication index. For postoperative complications, no significant difference was seen between patients operated in the resident group versus the control group, with a third of patients being discharged with a textbook outcome in both cohorts. Furthermore, no difference in oncological quality of the resection was found, emphasizing safety and feasibility of our training program. A structured modular step-up for training a surgical resident to perform complex esophageal cancer surgery can successfully maintain patient safety and outcomes.

Treatment of local recurrence of esophageal cancer following Ivor-Lewis esophagectomy-Experiences of a high-volume center.

PURPOSE: Patients with local recurrence of esophageal cancer have a highly decreased overall survival. There is currently no standardized treatment algorithm for this group. This retrospective cohort study aimed to evaluate the survival of patients with local recurrence, despite receiving individualized treatment options. METHODS: 241 of 1791 patients were diagnosed with a local recurrence following Ivor-Lewis esophagectomy at the University Hospital of Cologne. 59 patients, who were diagnosed only with a local recurrence of adeno- or squamous cell carcinoma and received their individualized therapy regimes at our high-volume center, were included. RESULTS: The study included 52 patients with adenocarcinoma and 7 with squamous cell carcinoma. Among these, 6 patients underwent resection, 19 received solely chemotherapy, 29 received chemoradiotherapy, and 5 were provided with best supportive care. Patients who underwent resection showed a better survival outcome compared to patients without resection (median OS: not reached vs. 15.1 months, p = 0.012). Best supportive care and palliative care were found to be independent risk factors for shorter overall survival compared to curative intended treatment options like local resection or chemoradiotherapy. CONCLUSION: In this study, different treatment strategies for patients with local recurrence of esophageal cancer were depicted. Resection as well as chemoradiotherapy could play a role in selected patients. Further prospective studies are needed to improve the selection of eligible patients.

[Tailored surgery in the treatment of gastroesophageal cancer]. / Maßgeschneiderte Chirurgie in der Behandlung gastroösophagealer Tumoren.

The surgical options and particularly perioperative treatment, have significantly advanced in the case of gastroesophageal cancer. This progress enables a 5-year survival rate of nearly 50% to be achieved through curative multimodal treatment concepts for locally advanced cancer. Therefore, in tumor boards and surgical case discussions the question increasingly arises regarding the type of treatment that provides optimal oncological and functional outcomes for individual patients with pre-existing diseases. It is therefore essential to carefully assess whether organ-preserving treatment might also be considered in the future or in what way minimally invasive or robotic surgery can offer advantages. Simultaneously, the boundaries of surgical and oncological treatment are currently being shifted in order to enable curative forms of treatment for patients with pre-existing conditions or those with oligometastatic diseases. With the integration of artificial intelligence into decision-making processes, new possibilities for information processing are increasingly becoming available to incorporate even more data into making decisions in the future.

Correlation of primary tumor volume and histopathologic response following neoadjuvant treatment of esophageal adenocarcinoma.

INTRODUCTION: In esophageal cancer, histopathologic response following neoadjuvant therapy and transthoracic esophagectomy is a strong predictor of long-term survival. At the present, it is not known whether the initial tumor volume quantified by computed tomography (CT) correlates with the degree of pathologic regression. METHODS: In a retrospective analysis of a consecutive patient cohort with esophageal adenocarcinoma, tumor volume in CT prior to chemoradiotherapy or chemotherapy alone was quantified using manual segmentation. Primary tumor volume was correlated to the histomorphological regression based on vital residual tumor cells (VRTC) (Cologne regression scale, CRS: grade I, >50% VRTC; grade II, 10-50% VRTC; grade III, <10% VRTC and grade IV, complete response without VRTC). RESULTS: A total of 287 patients, 165 with neoadjuvant chemoradiotherapy according to the CROSS protocol and 122 with chemotherapy according to the FLOT regimen, were included. The initial tumor volume for patients following CROSS and FLOT therapy was measured (CROSS: median 24.8 ml, IQR 13.1-41.1 ml, FLOT: 23.4 ml, IQR 10.6-37.3 ml). All patients underwent an Ivor-Lewis esophagectomy. 180 patients (62.7 %) were classified as minor (CRS I/II) and 107 patients (37.3 %) as major or complete responder (CRS III/IV). The median tumor volume was calculated as 24.2 ml (IQR 11.9-40.3 ml). Ordered logistic regression revealed no significant dependence of CRS from tumor volume (OR = 0.99, p-value = 0.99) irrespective of the type of multimodal treatment. CONCLUSION: The initial tumor volume on diagnostic CT does not aid to differentiate between potential histopathological responders and non-responders to neoadjuvant therapy in esophageal cancer patients. The results emphasize the need to establish other biological markers of prediction.

Privacy-proof Live Surgery Streaming: Development and Validation of a Low-cost, Real-time Robotic Surgery Anonymization Algorithm.

OBJECTIVE: Develop a pioneer surgical anonymization algorithm for reliable and accurate real-time removal of out-of-body images validated across various robotic platforms. BACKGROUND: The use of surgical video data has become a common practice in enhancing research and training. Video sharing requires complete anonymization, which, in the case of endoscopic surgery, entails the removal of all nonsurgical video frames where the endoscope can record the patient or operating room staff. To date, no openly available algorithmic solution for surgical anonymization offers reliable real-time anonymization for video streaming, which is also robotic-platform and procedure-independent. METHODS: A data set of 63 surgical videos of 6 procedures performed on four robotic systems was annotated for out-of-body sequences. The resulting 496.828 images were used to develop a deep learning algorithm that automatically detected out-of-body frames. Our solution was subsequently benchmarked against existing anonymization methods. In addition, we offer a postprocessing step to enhance the performance and test a low-cost setup for real-time anonymization during live surgery streaming. RESULTS: Framewise anonymization yielded a receiver operating characteristic area under the curve score of 99.46% on unseen procedures, increasing to 99.89% after postprocessing. Our Robotic Anonymization Network outperforms previous state-of-the-art algorithms, even on unseen procedural types, despite the fact that alternative solutions are explicitly trained using these procedures. CONCLUSIONS: Our deep learning model, Robotic Anonymization Network, offers reliable, accurate, and safe real-time anonymization during complex and lengthy surgical procedures regardless of the robotic platform. The model can be used in real time for surgical live streaming and is openly available.

[The "surgical track"-Innovative approaches to counteract the shortage of young recruits in surgery]. / Der "Surgical Track" ­ innovative Ansätze gegen den Nachwuchsmangel in der Chirurgie.

Surgery faces significant challenges resulting from changes in medical education and the declining attractiveness of the surgical career path for aspiring doctors in the western world. For example, students' expectations of their future workplace have changed, with issues such as career planning uncertainties, an unbalanced work-life balance, and a lack of compatibility of family and occupation becoming increasingly more relevant. The entry of Generation Z into the workforce will also impact surgery. Although women comprise the largest proportion of graduates only a few opt for a career in surgery. The resulting shortage of young surgeons will negatively impact medical care in German surgical units. Intense competition for talents is already emerging in all medical specialties. Thus, hospitals and academic centers are taking various measures to counteract the impending staff shortage, such as summer schools or scholarships with work commitments. Furthermore, regional funding laws are being established. In addition, as there is a declining interest in surgical training, particularly during the course of medical studies, early integration of surgical skills is crucial to counteract this trend. For this reason, we have developed the "surgical track", designed to offer targeted innovative teaching concepts to get students attracted to surgery at an early stage. The "surgical track" is based on virtual reality (VR) and robotics. Students can practice operations and emergency scenarios through VR simulations and complete practical exercises with robotic systems. High-quality training concepts such as the "surgical track" can help to promote enthusiasm for surgery and impart knowledge at the same time, even if the long-term benefits still need to be evaluated. Through virtual simulations, robotic surgery and innovative teaching, students gain insights into visceral surgery that combine theoretical understanding and practical experience.

An international Delphi consensus for surgical quality assessment of lymphadenectomy and anastomosis in minimally invasive total gastrectomy for gastric cancer.

BACKGROUND: Minimally invasive total gastrectomy (MITG) is a mainstay for curative treatment of patients with gastric cancer. To define and standardize optimal surgical techniques and further improve clinical outcomes through the enhanced MITG surgical quality, there must be consensus on the key technical steps of lymphadenectomy and anastomosis creation, which is currently lacking. This study aimed to determine an expert consensus from an international panel regarding the technical aspects of the performance of MITG for oncological indications using the Delphi method. METHODS: A 100-point scoping survey was created based on the deconstruction of MITG into its key technical steps through local and international expert opinion and literature evidence. An international expert panel comprising upper gastrointestinal and general surgeons participated in multiple rounds of a Delphi consensus. The panelists voted on the issues concerning importance, difficulty, or agreement using an online questionnaire. A priori consensus standard was set at > 80% for agreement to a statement. Internal consistency and reliability were evaluated using Cronbach's α. RESULTS: Thirty expert upper gastrointestinal and general surgeons participated in three online Delphi rounds, generating a final consensus of 41 statements regarding MITG for gastric cancer. The consensus was gained from 22, 12, and 7 questions from Delphi rounds 1, 2, and 3, which were rephrased into the 41 statetments respectively. For lymphadenectomy and aspects of anastomosis creation, Cronbach's α for round 1 was 0.896 and 0.886, and for round 2 was 0.848 and 0.779, regarding difficulty or importance. CONCLUSIONS: The Delphi consensus defined 41 steps as crucial for performing a high-quality MITG for oncological indications based on the standards of an international panel. The results of this consensus provide a platform for creating and validating surgical quality assessment tools designed to improve clinical outcomes and standardize surgical quality in MITG.

Combined score of Y chromosome loss and T-cell infiltration improves UICC based stratification of esophageal adenocarcinoma.

Background: Staging, especially clinical lymph node staging in esophageal adenocarcinoma has only moderate sensitivity and specificity. Therefore, we evaluated combined molecular markers to predict prognosis. Patients and methods: 890 tumor tissue samples were obtained from patients who underwent surgery for esophageal adenocarcinoma with curative intent. These were stained by tissue micro array for 48 markers which are associated with tumorigenesis and correlated with clinical data (TNM-staging, overall survival) by multivariate Cox regression. Results: Two markers (preserved Y chromosome and high grade of (CD3+) T-cell infiltration) were found to be significantly and independently associated with better overall survival. We formed a score (called CY score) from the two markers. The more markers are positive and thus the higher the score (ranging from 0 to 2), the better the overall survival, independently of UICC. Moreover, we developed a combination score of the UICC and CY score based on cluster analysis. Patients with a UICC stage of III with the presence of both traits (CY=2) can be assigned to a better prognosis group (group II), whereas patients with a UICC stage of I without both traits (CY=0) must be assigned to a worse prognosis group (group II). Therefore, patients in stage I with adverse molecular signature might benefit of multimodal therapy. Conclusion: In summary, the CY score adds prognostic information to the UICC stage based on tumor biology in esophageal adenocarcinoma and warrants further evaluations in independent clinical cohorts.

The effects of cerebral oximetry in mechanically ventilated newborns: a protocol for the SafeBoosC-IIIv randomised clinical trial.

BACKGROUND: The SafeBoosC project aims to test the clinical value of non-invasive cerebral oximetry by near-infrared spectroscopy in newborn infants. The purpose is to establish whether cerebral oximetry can be used to save newborn infants' lives and brains or not. Newborns contribute heavily to total childhood mortality and neonatal brain damage is the cause of a large part of handicaps such as cerebral palsy. The objective of the SafeBoosC-IIIv trial is to evaluate the benefits and harms of cerebral oximetry added to usual care versus usual care in mechanically ventilated newborns. METHODS/DESIGN: SafeBoosC-IIIv is an investigator-initiated, multinational, randomised, pragmatic phase-III clinical trial. The inclusion criteria will be newborns with a gestational age more than 28 + 0 weeks, postnatal age less than 28 days, predicted to require mechanical ventilation for at least 24 h, and prior informed consent from the parents or deferred consent or absence of opt-out. The exclusion criteria will be no available cerebral oximeter, suspicion of or confirmed brain injury or disorder, or congenital heart disease likely to require surgery. A total of 3000 participants will be randomised in 60 neonatal intensive care units from 16 countries, in a 1:1 allocation ratio to cerebral oximetry versus usual care. Participants in the cerebral oximetry group will undergo cerebral oximetry monitoring during mechanical ventilation in the neonatal intensive care unit for as long as deemed useful by the treating physician or until 28 days of life. The participants in the cerebral oximetry group will be treated according to the SafeBoosC treatment guideline. Participants in the usual care group will not receive cerebral oximetry and will receive usual care. We use two co-primary outcomes: (1) a composite of death from any cause or moderate to severe neurodevelopmental disability at 2 years of corrected age and (2) the non-verbal cognitive score of the Parent Report of Children's Abilities-Revised (PARCA-R) at 2 years of corrected age. DISCUSSION: There is need for a randomised clinical trial to evaluate cerebral oximetry added to usual care versus usual care in mechanically ventilated newborns. TRIAL REGISTRATION: The protocol is registered at www. CLINICALTRIALS: gov (NCT05907317; registered 18 June 2023).

Postesophagectomy Diaphragmatic Prolapse after Robot-Assisted Minimally Invasive Esophagectomy (RAMIE).

BACKGROUND: Postesophagectomy diaphragmatic prolapse (PDP) is a major complication after esophagectomy with significant mortality and morbidity. However, in the current literature, treatment and outcomes are not evaluated for patients undergoing an Ivor Lewis Robot-assisted minimally invasive esophagectomy (IL-RAMIE). The aim of this study is to evaluate the incidence of PDP after IL-RAMIE. Moreover, the study aims to determine whether using a minimally invasive approach in the management of PDP after an IL-RAMIE procedure is safe and feasible. MATERIALS AND METHODS: This study includes all patients who received an IL-RAMIE at our high-volume center (>200 esophagectomies/year) between April 2017 and December 2022 and developed PDP. The analysis focuses on time to prolapse, symptoms, treatment, surgical method, and recurrence rates of these patients. RESULTS: A total of 185 patients underwent an IL-RAMIE at our hospital. Eleven patients (5.9%) developed PDP. Patients presented with PDP after a medium time of 241 days with symptoms like reflux, nausea, vomiting, and pain. One-third of these patients did not suffer from any symptoms. In all cases, a CT scan was performed in which the colon transversum always presented as the herniated organ. In one patient, prolapse of the small intestine, pancreas, and greater omentum also occurred. A total of 91% of these patients received a revisional surgery in a minimally invasive manner with a mean hospital stay of 12 days. In four patients, PDP recurred (36%) after 13, 114, 119 and 237 days, respectively. CONCLUSION: This study shows that a minimally invasive approach in repositioning PDP is a safe and effective option after IL-RAMIE.

Analysis of training pathway to reach expert performance levels based on proficiency-based progression in robotic-assisted minimally invasive esophagectomy (RAMIE).

BACKGROUND: Robotic-assisted minimally invasive esophagectomy (RAMIE) was first introduced in 2003 and has since then shown to significantly improve the postoperative course. Previous studies have shown that a structured training pathway based on proficiency-based progression using individual skill levels as measures of reach of competence can enhance surgical performance. The aim of this study was to evaluate and help understand our pathway to reach surgical expert levels using a proficiency-based approach introducing RAMIE at our German high-volume center. METHODS: All patients undergoing RAMIE performed by two experienced surgeons for esophageal cancer since the introduction of the robotic technique in 2017 was included in this analysis. Intraoperative outcomes and postoperative outcomes were included in the analysis. The cumulative sum method was used to analyze how many cases are needed to reach expert levels for different performance characteristics and skill sets during robotic-assisted minimally invasive esophagectomy. RESULTS: From 06/2017 to 03/2022, a total of 154 patients underwent RAMIE at our facility and were included in the analysis. An advancement in performance level was observed for total operating time after 70 cases and for thoracic operative time after 79 cases. Lymph node yield showed an increase up until case 60 in the CUSUM analysis. Length of hospital stay stabilized after case 55. The CCI score inflection point was at case 55 in both CUSUM and regression analyses. Anastomotic leak rate stabilized at case 38 and showed another inflection point after case 83. CONCLUSION: Our data and analysis showed the progression from proficient to expert performance levels during the implementation of RAMIE at a European high-volume center. Further analysis of surgeons, especially with a different training status has yet to reveal if the caseloads found in this study are universally applicable. However, skill acquisition and respective measures of such are diverse and as a great range of number of cases was observed, we believe that the learning curve and ascent in performance levels cannot be defined by one parameter alone.

Impact of the Surgical Approach for Neoadjuvantly Treated Gastroesophageal Junction Type II Tumors: A Multinational, High-volume Center Retrospective Cohort Analysis.

OBJECTIVE: The aim of this study was to explore oncologic outcomes of transhiatal gastrectomy (THG) or transthoracic esophagectomy (TTE) for neoadjuvantly treated gastroesophageal junction (GEJ) Siewert type II adenocarcinomas, a multinational, high-volume center cohort analysis was undertaken. BACKGROUND: Neoadjuvant radiochemotherapy or perioperative chemotherapy (CTx) followed by surgery is the standard therapy for locally advanced GEJ. However, the optimal surgical approach for type II GEJ tumors remains unclear, as the decision is mainly based on individual experience and assessment of operative risk. METHODS: A retrospective analysis of 5 prospectively maintained databases was conducted. Between 2012 and 2021, 800 patients fulfilled inclusion criteria for type II GEJ tumors and neoadjuvant radiochemotherapy or CTx. The primary endpoint was median overall survival (mOS). Propensity score matching was performed to minimize selection bias. RESULTS: Patients undergoing THG (n=163, 20.4%) had higher American Society of Anesthesiologists (ASA) classification and cT stage ( P <0.001) than patients undergoing TTE (n=637, 79.6%). Neoadjuvant therapy was different as the THG group were mainly undergoing CTx (87.1%, P <0.001). The TTE group showed higher tumor regression ( P =0.009), lower ypT/ypM categories (both P <0.001), higher nodal yield ( P =0.009) and higher R0 resection rate ( P =0.001). The mOS after TTE was longer (78.0 vs 40.0 months, P =0.013). After propensity score matching a higher R0 resection rate ( P =0.004) and mOS benefit after TTE remained ( P =0.04). Subgroup analyses of patients without distant metastasis ( P =0.037) and patients only after neoadjuvant chemotherapy ( P =0.021) confirmed the survival benefit of TTE. TTE was an independent predictor of longer survival. CONCLUSION: Awaiting results of the randomized CARDIA trial, TTE should in high-volume centers be considered the preferred approach due to favorable oncologic outcomes.

Clinical utility and applicability of the,Esophagus Complication Consensus Group' (ECCG) classification of anastomotic leakage following hybrid Ivor-Lewis esophagectomy.

BACKGROUND: Anastomotic leakage (AL) remains the leading surgical complication following Ivor-Lewis (IL) esophagectomy. Different treatment options of AL exist but outcome is difficult to compare due to a lack of generally accepted classifications. This retrospective study was conducted to analyze the clinical significance of a recently proposed classification based on the management of AL. PATIENTS AND METHODS: A cohort of 954 consecutive patients undergoing hybrid IL esophagectomy (laparoscopy/thoracotomy) was analysed. AL was defined according to the,Esophagus Complication Consensus Group' (ECCG) criteria depending on its treatment: conservative (AL type I), interventional endoscopic (AL type II), and surgical (AL type III). Primary outcome was single or multiple organ failure (Clavien-Dindo IVA/B) associated with AL. RESULTS: Overall morbidity was 63.0% and 8.8% (84/954 patients) developed an AL postoperatively. Three patients (3.5%) had an AL type I, 57 patients (67.9%) an AL type II and 24 patients (28.6%) an AL type III. For patients managed surgically, AL was diagnosed significantly earlier (median days: AL type III: 2 vs AL type II: 6, p < 0.001). Associated organ failure (CD IVA/B) was significantly lower for AL type II as compared to AL type III (21.1% versus 45.8%, p < 0.0001). In-hospital mortality was 3.5% for AL type II and 8.3% for AL type III (p = 0.789). There was no difference for re-admission to ICU and overall length of hospital stay. CONCLUSION: The proposed ECCG classification is simply to apply and discriminates the post-treatment severity of AL but does not aid to implement a treatment algorithm.

Prediction of postoperative complications after oesophagectomy using machine-learning methods.

BACKGROUND: Oesophagectomy is an operation with a high risk of postoperative complications. The aim of this single-centre retrospective study was to apply machine-learning methods to predict complications (Clavien-Dindo grade IIIa or higher) and specific adverse events. METHODS: Patients with resectable adenocarcinoma or squamous cell carcinoma of the oesophagus and gastro-oesophageal junction who underwent Ivor Lewis oesophagectomy between 2016 and 2021 were included. The tested algorithms were logistic regression after recursive feature elimination, random forest, k-nearest neighbour, support vector machine, and neural network. The algorithms were also compared with a current risk score (the Cologne risk score). RESULTS: 457 patients had Clavien-Dindo grade IIIa or higher complications (52.9 per cent) versus 407 patients with Clavien-Dindo grade 0, I, or II complications (47.1 per cent). After 3-fold imputation and 3-fold cross-validation, the overall accuracies were: logistic regression after recursive feature elimination, 0.528; random forest, 0.535; k-nearest neighbour, 0.491; support vector machine, 0.511; neural network, 0.688; and Cologne risk score, 0.510. For medical complications, the results were: logistic regression after recursive feature elimination, 0.688; random forest, 0.664; k-nearest neighbour, 0.673; support vector machine, 0.681; neural network, 0.692; and Cologne risk score, 0.650. For surgical complications, the results were: logistic regression after recursive feature elimination, 0.621; random forest, 0.617; k-nearest neighbour, 0.620; support vector machine, 0.634; neural network, 0.667; and Cologne risk score, 0.624. The calculated area under the curve of the neural network was 0.672 for Clavien-Dindo grade IIIa or higher, 0.695 for medical complications, and 0.653 for surgical complications. CONCLUSION: The neural network scored the highest accuracies compared with all of the other models for the prediction of postoperative complications after oesophagectomy.

The human gullet or stomach can develop tumours. Surgery can help to cure patients with these tumours. But the operation is risky because sometimes adverse events can happen afterwards. So far, there is no reliable prediction model. It may help to predict the risk of adverse events accurately. For example, patients with a high risk could be observed more thoroughly. Patients with a low risk may not need unnecessary procedures. The information of all patients with an operation at a specialized hospital was collected. Machine learning is a complex mathematical method and was used in this study. It is able to analyse big data sets of information. One machine-learning method called neural network was best in predicting adverse events. Right now, the performance may not be strong enough to fully rely on the prediction. However, refinement of the prediction and more data could improve the neural network in the future.