Impact of the COVID-19 pandemic on short-term outcomes after pancreaticoduodenectomy for pancreatic cancer: A retrospective study from the Japanese National Clinical Database, 2018-2021.

Aim: The coronavirus disease 2019 (COVID-19) pandemic greatly impacted medical resources such as cancer screening, diagnosis, and treatment given to people for various diseases. We surveyed the impacts of the pandemic on the incidence of complications and mortality following pancreaticoduodenectomy for pancreatic cancer in Japan. Methods: Data on patients who underwent pancreaticoduodenectomy for pancreatic cancer were extracted from the Japanese National Clinical Database (NCD) between 2018 and 2021. The number of the pancreaticoduodenectomy for pancreatic cancer were obtained and then the morbidity and mortality rates were evaluated using a standardized morbidity/mortality ratio (SMR), which is the ratio of the observed number of incidences to the expected number of incidences calculated by the risk calculator previously developed by the NCD. Results: This study included 22 255 cases. The number of pancreaticoduodenectomies exhibited an increasing trend even during the COVID-19 pandemic. The mean observed incidence rates of Grade C pancreatic fistula and Clavien-Dindo grade ≥4 complications, and the 30-day mortality and surgical mortality rates were 0.8%, 1.8%, 0.8% and 0.9%, respectively. The standardized morbidity ratios did not increase during the COVID-19 pandemic. The standardized mortality ratios remained within the range of variations observed before the COVID-19 pandemic. Conclusion: The increasing trend in the number of pancreaticoduodenectomies and favorable short-term outcomes even in the COVID-19 pandemic suggest the medical care for pancreatic cancer in Japan functioned well during the pandemic.

Impact of SARS-CoV-2 infection on short-term postoperative outcomes after gastroenterological cancer surgery using data from a nationwide database in Japan.

Background: Due to the coronavirus disease 2019 (COVID-19) pandemic, cancer screening, diagnosis, and treatment have changed. This study aimed to investigate the impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection prior to gastroenterological cancer surgeries on postoperative complications using data from a nationwide database in Japan. Methods: Data on patients who underwent surgery for cancer including esophageal, gastric, colon, rectal, liver, and pancreatic cancer between July 1, 2019, and September 300, 2022, from real-world sources in Japan were analyzed. The association between preoperative SARS-CoV-2 infection and short-term postoperative outcomes was evaluated. A similar analysis stratified according to the interval from SARS-CoV-2 infection to surgery (<4 vs. >4 weeks) was conducted. Results: In total, 60 604 patients were analyzed, and 227 (0.4%) patients were diagnosed with SARS-CoV-2 infection preoperatively. The median interval from SARS-CoV-2 infection to surgery was 25 days. Patients diagnosed with SARS-CoV-2 infection preoperatively had a significantly higher incidence of pneumonia (odds ratio: 2.05; 95% confidence interval: 1.05-3.74; p = 0.036) than those not diagnosed with SARS-CoV-2 infection based on the exact logistic regression analysis adjusted for the characteristics of the patients. A similar finding was observed in patients who had SARS-CoV-2 infection <4 weeks before surgery. Conclusions: Patients with a history of SARS-CoV-2 infection had a significantly higher incidence of pneumonia. This finding can be particularly valuable for countries that have implemented strict regulations in response to the COVID-19 pandemic and have lower SARS-CoV-2 infection-related mortality rates.

Usefulness of an Artificial Intelligence Model in Recognizing Recurrent Laryngeal Nerves During Robot-Assisted Minimally Invasive Esophagectomy.

BACKGROUND: Recurrent laryngeal nerve (RLN) palsy is a common complication in esophagectomy and its main risk factor is reportedly intraoperative procedure associated with surgeons' experience. We aimed to improve surgeons' recognition of the RLN during robot-assisted minimally invasive esophagectomy (RAMIE) by developing an artificial intelligence (AI) model. METHODS: We used 120 RAMIE videos from four institutions to develop an AI model and eight other surgical videos from another institution for AI model evaluation. AI performance was measured using the Intersection over Union (IoU). Furthermore, to verify the AI's clinical validity, we conducted the two experiments on the early identification of RLN and recognition of its location by eight trainee surgeons with or without AI. RESULTS: The IoUs for AI recognition of the right and left RLNs were 0.40 ± 0.26 and 0.34 ± 0.27, respectively. The recognition of the right RLN presence in the beginning of right RLN lymph node dissection (LND) by surgeons with AI (81.3%) was significantly more accurate (p = 0.004) than that by surgeons without AI (46.9%). The IoU of right RLN during right RLN LND recognized by surgeons with AI (0.59 ± 0.18) was significantly higher (p = 0.010) than that by surgeons without AI (0.40 ± 0.29). CONCLUSIONS: Surgeons' recognition of anatomical structures in RAMIE was improved by our AI system with high accuracy. Especially in right RLN LND, surgeons could recognize the RLN more quickly and accurately by using the AI model.

Evaluating surgical expertise with AI-based automated instrument recognition for robotic distal gastrectomy.

Introduction: Complexities of robotic distal gastrectomy (RDG) give reason to assess physician's surgical skill. Varying levels in surgical skill affect patient outcomes. We aim to investigate how a novel artificial intelligence (AI) model can be used to evaluate surgical skill in RDG by recognizing surgical instruments. Methods: Fifty-five consecutive robotic surgical videos of RDG for gastric cancer were analyzed. We used Deeplab, a multi-stage temporal convolutional network, and it trained on 1234 manually annotated images. The model was then tested on 149 annotated images for accuracy. Deep learning metrics such as Intersection over Union (IoU) and accuracy were assessed, and the comparison between experienced and non-experienced surgeons based on usage of instruments during infrapyloric lymph node dissection was performed. Results: We annotated 540 Cadiere forceps, 898 Fenestrated bipolars, 359 Suction tubes, 307 Maryland bipolars, 688 Harmonic scalpels, 400 Staplers, and 59 Large clips. The average IoU and accuracy were 0.82 ± 0.12 and 87.2 ± 11.9% respectively. Moreover, the percentage of each instrument's usage to overall infrapyloric lymphadenectomy duration predicted by AI were compared. The use of Stapler and Large clip were significantly shorter in the experienced group compared to the non-experienced group. Conclusions: This study is the first to report that surgical skill can be successfully and accurately determined by an AI model for RDG. Our AI gives us a way to recognize and automatically generate instance segmentation of the surgical instruments present in this procedure. Use of this technology allows unbiased, more accessible RDG surgical skill.

Identifying the Trends of Urinary microRNAs within Extracellular Vesicles for Esophageal Cancer.

Background: The advancement of multidisciplinary treatment has increased the need to develop tests to monitor tumor burden during treatment. We herein analyzed urinary microRNAs within extracellular vesicles from patients with esophageal squamous cell carcinoma (ESCC) and normal individuals using a microarray. Methods: Patients with advanced ESCC who underwent esophagectomy (A), endoscopic submucosal resection (ESD) (B), and healthy donors (C) were included. Based on microRNA expression among the groups (Analysis 1), microRNAs with significant differences between groups A and C were selected (Analysis 2). Of these candidates, microRNAs in which the change between A and C was consistent with the change between B and C were selected for downstream analysis (Analysis 3). Finally, microRNA expression was validated in patients with recurrence from A (exploratory analysis). Results: For analysis 1, 205 microRNAs were selected. For Analyses 2 and 3, the changes in 18 microRNAs were consistent with changes in tumor burden as determined by clinical imaging and pathological findings. The AUC for the detection of ESCC using 18 microRNAs was 0.72. In exploratory analysis, three of eighteen microRNAs exhibited a concordant trend with recurrence. Conclusions: The current study identified the urinary microRNAs which were significantly expressed in ESCC patients. Validation study is warranted to evaluate whether these microRNAs could reflect tumor burden during multidisciplinary treatment for ESCC.

Impact of the COVID-19 pandemic on the number and short-term outcomes in hepatectomy for hepatocellular carcinoma: Results from the Japanese National Clinical Database, 2018-2021.

AIM: The coronavirus disease 2019 (COVID-19) pandemic has significantly impacted the allocation of medical resources, including cancer screening, diagnosis, and treatment. We aimed to investigate the effects of the pandemic on morbidity and mortality following hepatectomy for hepatocellular carcinoma (HCC). METHODS: We identified patients who underwent hepatectomy for HCC between 2018 and 2021 from the Japanese National Clinical Database (NCD). The number of surgical cases, the use of intensive care units, and the incidence of morbidity were assessed. The standardized morbidity / mortality ratio (SMR) was used to evaluate the rates of morbidity (bile leakage and pneumonia) and mortality in each month, which compares the observed incidence to the expected incidence calculated by the NCD's risk calculator. RESULTS: The study included a total of 10 647 cases. The number of patients undergoing hepatectomy for HCC gradually decreased. The proportion of patients aged 80 years or older increased and that of cases with T1 stage decreased. The proportion of patients who were admitted to the intensive care unit did not change between the pre- and postpandemic period. The mean actual incidence rates of bile leakage, pneumonia, 30-day mortality, and surgical mortality were 9.2%, 2.3%, 1.4%, and 2.1%, respectively. The SMR for the mortalities and morbidities in each month did not increase mostly throughout the COVID-19 pandemic. CONCLUSIONS: The present study showed the decreasing number of resected cases for HCC, while the surgical safety for hepatectomy was enough to be maintained by managing medical resources in Japan.

Automated artificial intelligence-based phase-recognition system for esophageal endoscopic submucosal dissection (with video).

BACKGROUND AND AIMS: Endoscopic submucosal dissection (ESD) for superficial esophageal cancer is a multistep treatment involving several endoscopic processes. Although analyzing each phase separately is worthwhile, it is not realistic in practice owing to the need for considerable manpower. To solve this problem, we aimed to establish a state-of-the-art artificial intelligence (AI)-based system, specifically, an automated phase-recognition system that can automatically identify each endoscopic phase based on video images. METHODS: Ninety-four videos of ESD procedures for superficial esophageal cancer were evaluated in this single-center study. A deep neural network-based phase-recognition system was developed in an automated manner to recognize each of the endoscopic phases. The system was trained with the use of videos that were annotated and verified by 2 GI endoscopists. RESULTS: The overall accuracy of the AI model for automated phase recognition was 90%, and the average precision, recall, and F value rates were 91%, 90%, and 90%, respectively. Two representative ESD videos predicted by the model indicated the usability of AI in clinical practice. CONCLUSIONS: We demonstrated that an AI-based automated phase-recognition system for esophageal ESD can be established with high accuracy. To the best of our knowledge, this is the first report on automated recognition of ESD treatment phases. Because this system enabled a detailed analysis of phases, collecting large volumes of data in the future may help to identify quality indicators for treatment techniques and uncover unmet medical needs that necessitate the creation of new treatment methods and devices.

Identifying intense inflammatory subtype of esophageal squamous cell carcinoma using clustering approach.

OBJECTIVE: To establish a risk-stratification system for predicting the postoperative recurrence of esophageal squamous cell carcinoma, this study aimed to evaluate the prognostic value of clusters based on blood inflammation and coagulation markers and investigate their correlation with serum cytokines and genetic alteration. METHOD: This single-center, retrospective cohort study enrolled 491 patients with esophageal cancer who underwent subtotal esophagectomy between 2004 and 2012. For cluster exploration, nonhierarchical cluster analysis and k-means were applied using serum C-reactive protein, albumin, fibrinogen, and platelet-lymphocyte ratio as variables. Then, multivariate survival analysis was conducted to investigate the association of clusters with recurrence-free survival. To characterize the clusters, serum interleukin-6, interleukin-8, and genetic alteration in primary tumors, the PleSSision-Rapid panel, which can evaluate 160 representative driver genes, was used. RESULTS: Patients were classified into clusters 1, 2, and 3, which included 24 (5%), 161 (33%), and 306 (62%) patients, respectively. Compared with cluster 3, cluster 1 or 2 had significantly worse recurrence-free survival. Based on the multivariable analysis using cluster, pStage, and age as covariates, cluster was an independent prognostic factor for recurrence-free survival (hazard ratio, 1.55; 95% confidence interval, 1.08-2.21; P = 0.02). The percentage of serum interleukin-6 and interleukin-8 levels was the highest in cluster 1, followed by clusters 2 and 3. In 23 patients with available genomic profiles, no significant difference in representative genomic alterations was observed. CONCLUSIONS: Non-biased clustering using inflammation and coagulation markers identified the intense inflammatory subtype, which had an independent prognostic effect on recurrence-free survival.