Comparing a virtual reality head-mounted display to on-screen three-dimensional visualization and two-dimensional computed tomography data for training in decision making in hepatic surgery: a randomized controlled study.

OBJECTIVE: Evaluation of the benefits of a virtual reality (VR) environment with a head-mounted display (HMD) for decision-making in liver surgery. BACKGROUND: Training in liver surgery involves appraising radiologic images and considering the patient's clinical information. Accurate assessment of 2D-tomography images is complex and requires considerable experience, and often the images are divorced from the clinical information. We present a comprehensive and interactive tool for visualizing operation planning data in a VR environment using a head-mounted-display and compare it to 3D visualization and 2D-tomography. METHODS: Ninety medical students were randomized into three groups (1:1:1 ratio). All participants analyzed three liver surgery patient cases with increasing difficulty. The cases were analyzed using 2D-tomography data (group "2D"), a 3D visualization on a 2D display (group "3D") or within a VR environment (group "VR"). The VR environment was displayed using the "Oculus Rift ™" HMD technology. Participants answered 11 questions on anatomy, tumor involvement and surgical decision-making and 18 evaluative questions (Likert scale). RESULTS: Sum of correct answers were significantly higher in the 3D (7.1 ± 1.4, p < 0.001) and VR (7.1 ± 1.4, p < 0.001) groups than the 2D group (5.4 ± 1.4) while there was no difference between 3D and VR (p = 0.987). Times to answer in the 3D (6:44 ± 02:22 min, p < 0.001) and VR (6:24 ± 02:43 min, p < 0.001) groups were significantly faster than the 2D group (09:13 ± 03:10 min) while there was no difference between 3D and VR (p = 0.419). The VR environment was evaluated as most useful for identification of anatomic anomalies, risk and target structures and for the transfer of anatomical and pathological information to the intraoperative situation in the questionnaire. CONCLUSIONS: A VR environment with 3D visualization using a HMD is useful as a surgical training tool to accurately and quickly determine liver anatomy and tumor involvement in surgery.

HeiPorSPECTRAL - the Heidelberg Porcine HyperSPECTRAL Imaging Dataset of 20 Physiological Organs.

Hyperspectral Imaging (HSI) is a relatively new medical imaging modality that exploits an area of diagnostic potential formerly untouched. Although exploratory translational and clinical studies exist, no surgical HSI datasets are openly accessible to the general scientific community. To address this bottleneck, this publication releases HeiPorSPECTRAL ( https://www.heiporspectral.org ; https://doi.org/10.5281/zenodo.7737674 ), the first annotated high-quality standardized surgical HSI dataset. It comprises 5,758 spectral images acquired with the TIVITA® Tissue and annotated with 20 physiological porcine organs from 8 pigs per organ distributed over a total number of 11 pigs. Each HSI image features a resolution of 480 × 640 pixels acquired over the 500-1000 nm wavelength range. The acquisition protocol has been designed such that the variability of organ spectra as a function of several parameters including the camera angle and the individual can be assessed. A comprehensive technical validation confirmed both the quality of the raw data and the annotations. We envision potential reuse within this dataset, but also its reuse as baseline data for future research questions outside this dataset. Measurement(s) Spectral Reflectance Technology Type(s) Hyperspectral Imaging Sample Characteristic - Organism Sus scrofa.

Robotic-assisted versus laparoscopic bowel anastomoses: randomized crossover in vivo experimental study.

BACKGROUND: Initial learning curves are potentially shorter in robotic-assisted surgery (RAS) than in conventional laparoscopic surgery (LS). There is little evidence to support this claim. Furthermore, there is limited evidence how skills from LS transfer to RAS. METHODS: A randomized controlled, assessor blinded crossover study to compare how RAS naïve surgeons (n = 40) performed linear-stapled side-to-side bowel anastomoses in an in vivo porcine model with LS and RAS. Technique was rated using the validated anastomosis objective structured assessment of skills (A-OSATS) score and the conventional OSATS score. Skill transfer from LS to RAS was measured by comparing the RAS performance of LS novices and LS experienced surgeons. Mental and physical workload was measured with the NASA-task load index (NASA-Tlx) and the Borg-scale. OUTCOMES: In the overall cohort, there were no differences between RAS and LS for surgical performance (A-OSATS, time, OSATS). Surgeons that were naïve in both LS and RAS had significantly higher A-OSATS scores in RAS (Mean (Standard deviation (SD)): LS: 48.0 ± 12.1; RAS: 52.0 ± 7.5); p = 0.044) mainly deriving from better bowel positioning (LS: 8.7 ± 1.4; RAS: 9.3 ± 1.0; p = 0.045) and closure of enterotomy (LS: 12.8 ± 5.5; RAS: 15.6 ± 4.7; p = 0.010). There was no statistically significant difference in how LS novices and LS experienced surgeons performed in RAS [Mean (SD): novices: 48.9 ± 9.0; experienced surgeons: 55.9 ± 11.0; p = 0.540]. Mental and physical demand was significantly higher after LS. CONCLUSION: The initial performance was improved for RAS versus LS for linear stapled bowel anastomosis, whereas workload was higher for LS. There was limited transfer of skills from LS to RAS.

Video-based training of situation awareness enhances minimally invasive surgical performance: a randomized controlled trial.

BACKGROUND: Many training curricula were introduced to deal with the challenges that minimally invasive surgery (MIS) presents to the surgeon. Situational awareness (SA) is the ability to process information effectively. It depends on general cognitive abilities and can be divided into three steps: perceiving cues, linking cues to knowledge and understanding their relevance, and predicting possible outcomes. Good SA is crucial to predict and avoid complications and respond efficiently. This study aimed to introduce the concept of SA into laparoscopic training. METHODS: This is a prospective, randomized, controlled study conducted at the MIS Training Center of Heidelberg University Hospital. Video sessions showing the steps of the laparoscopic cholecystectomy (LC) were used for cognitive training. The intervention group trained SA with interposed questions inserted into the video clips. The identical video clips, without questions, were presented to the control group. Performance was assessed with validated scores such as the Objective Structured Assessment of Technical Skills (OSATS) during LC. RESULTS: 72 participants were enrolled of which 61 were included in the statistical analysis. The SA-group performed LC significantly better (OSATS-Score SA: 67.0 ± 11.5 versus control: 59.1 ± 14.0, p value = 0.034) and with less errors (error score SA: 3.5 ± 1.9 versus control: 4.7 ± 2.0, p value = 0.027). No difference in the time taken to complete the procedure was found. The benefit assessment analysis showed no difference between the groups in terms of perceived learning effect, concentration, or expediency. However, most of the control group indicated retrospectively that they believed they would have benefitted from the intervention. CONCLUSION: This study suggests that video-based SA training for laparoscopic novices has a positive impact on performance and error rate. SA training should thus be included as one aspect besides simulation and real cases in a multimodal curriculum to improve the efficiency of laparoscopic surgical skills training.

Comparative validation of machine learning algorithms for surgical workflow and skill analysis with the HeiChole benchmark.

PURPOSE: Surgical workflow and skill analysis are key technologies for the next generation of cognitive surgical assistance systems. These systems could increase the safety of the operation through context-sensitive warnings and semi-autonomous robotic assistance or improve training of surgeons via data-driven feedback. In surgical workflow analysis up to 91% average precision has been reported for phase recognition on an open data single-center video dataset. In this work we investigated the generalizability of phase recognition algorithms in a multicenter setting including more difficult recognition tasks such as surgical action and surgical skill. METHODS: To achieve this goal, a dataset with 33 laparoscopic cholecystectomy videos from three surgical centers with a total operation time of 22 h was created. Labels included framewise annotation of seven surgical phases with 250 phase transitions, 5514 occurences of four surgical actions, 6980 occurences of 21 surgical instruments from seven instrument categories and 495 skill classifications in five skill dimensions. The dataset was used in the 2019 international Endoscopic Vision challenge, sub-challenge for surgical workflow and skill analysis. Here, 12 research teams trained and submitted their machine learning algorithms for recognition of phase, action, instrument and/or skill assessment. RESULTS: F1-scores were achieved for phase recognition between 23.9% and 67.7% (n = 9 teams), for instrument presence detection between 38.5% and 63.8% (n = 8 teams), but for action recognition only between 21.8% and 23.3% (n = 5 teams). The average absolute error for skill assessment was 0.78 (n = 1 team). CONCLUSION: Surgical workflow and skill analysis are promising technologies to support the surgical team, but there is still room for improvement, as shown by our comparison of machine learning algorithms. This novel HeiChole benchmark can be used for comparable evaluation and validation of future work. In future studies, it is of utmost importance to create more open, high-quality datasets in order to allow the development of artificial intelligence and cognitive robotics in surgery.

Declined Organs for Liver Transplantation: A Right Decision or a Missed Opportunity for Patients with Hepatocellular Carcinoma?

BACKGROUND: Liver transplantation is the only promising treatment for end-stage liver disease and patients with hepatocellular carcinoma. However, too many organs are rejected for transplantation. METHODS: We analyzed the factors involved in organ allocation in our transplant center and reviewed all livers that were declined for transplantation. Reasons for declining organs for transplantation were categorized as major extended donor criteria (maEDC), size mismatch and vascular problems, medical reasons and risk of disease transmission, and other reasons. The fate of the declined organs was analyzed. RESULTS: 1086 declined organs were offered 1200 times. A total of 31% of the livers were declined because of maEDC, 35.5% because of size mismatch and vascular problems, 15.8% because of medical reasons and risk of disease transmission, and 20.7% because of other reasons. A total of 40% of the declined organs were allocated and transplanted. A total of 50% of the organs were completely discarded, and significantly more of these grafts had maEDC than grafts that were eventually allocated (37.5% vs. 17.7%, p < 0.001). CONCLUSION: Most organs were declined because of poor organ quality. Donor-recipient matching at time of allocation and organ preservation must be improved by allocating maEDC grafts using individualized algorithms that avoid high-risk donor-recipient combinations and unnecessary organ declination.

Bariatric surgery in patients with obesity and end-stage renal disease.

BACKGROUND: Bariatric surgery has been suggested as a treatment for obesity and end-stage renal disease (ESRD). Although the number of bariatric surgeries in patients with ESRD is increasing, its safety and effectiveness in these patients are still controversial and the surgical method of choice in these patients is under debate. OBJECTIVES: To compare the outcomes of bariatric surgery between patients with and without ESRD and to assess different methods of bariatric surgery in patients with ESRD. SETTING: Meta-analysis. METHODS: A comprehensive search was conducted in Web of Science and Medline (via Pubmed) until May 2022. Tow meta-analyses were performed: A) to compare bariatric surgery outcomes among patients with and without ESRD, and B) to compare outcomes of Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) in patients with ESRD. Using a random-effect model, odds ratios (ORs) and mean differences (MDs) with 95% confidence intervals (CIs) were computed for surgical and weight loss outcomes. RESULTS: Of 5895 articles, 6 studies were included in meta-analysis A and 8 studies in meta-analysis B. The risk of bias was moderate to serious among studies. Major postoperative complications (OR = 2.82; 95% CI = 1.66-4.77; P = .0001), reoperation (OR = 2.66; 95% CI = 1.99-3.56; P < .00001), readmission (OR = 2.37; 95% CI = 1.55-3.64; P < .0001), and in-hospital/90-d mortality (OR = 4.03; 95% CI = 1.80-9.03; P = .0007) were higher in patients with ESRD. Patients with ESRD also had a longer hospital stay (MD = 1.23; 95% CI = .32-2.14; P = .008). Bleeding, leakage, and total weight loss were comparable among groups. SG showed a 10% lower rate of overall complications and significantly shorter hospital stay than RYGB did. The quality of evidence was very low for the outcomes CONCLUSIONS: Bariatric surgery in patients with ESRD seems to have higher rates of major complications and perioperative mortality than in patients without ESRD, but a comparable rate of overall complications. SG has fewer postoperative complications and could be the method of choice in these patients. These findings should be interpreted cautiously in light of the moderate to high risk of bias in most included studies.

Telestration with augmented reality improves surgical performance through gaze guidance.

BACKGROUND: In minimally invasive surgery (MIS), trainees need to learn how to interpret the operative field displayed on the laparoscopic screen. Experts currently guide trainees mainly verbally during laparoscopic procedures. A newly developed telestration system with augmented reality (iSurgeon) allows the instructor to display hand gestures in real-time on the laparoscopic screen in augmented reality to provide visual expert guidance (telestration). This study analysed the effect of telestration guided instructions on gaze behaviour during MIS training. METHODS: In a randomized-controlled crossover study, 40 MIS naive medical students performed 8 laparoscopic tasks with telestration or with verbal instructions only. Pupil Core eye-tracking glasses were used to capture the instructor's and trainees' gazes. Gaze behaviour measures for tasks 1-7 were gaze latency, gaze convergence and collaborative gaze convergence. Performance measures included the number of errors in tasks 1-7 and trainee's ratings in structured and standardized performance scores in task 8 (ex vivo porcine laparoscopic cholecystectomy). RESULTS: There was a significant improvement 1-7 on gaze latency [F(1,39) = 762.5, p < 0.01, ηp2 = 0.95], gaze convergence [F(1,39) = 482.8, p < 0.01, ηp2 = 0.93] and collaborative gaze convergence [F(1,39) = 408.4, p < 0.01, ηp2 = 0.91] upon instruction with iSurgeon. The number of errors was significantly lower in tasks 1-7 (0.18 ± 0.56 vs. 1.94 ± 1.80, p < 0.01) and the score ratings for laparoscopic cholecystectomy were significantly higher with telestration (global OSATS: 29 ± 2.5 vs. 25 ± 5.5, p < 0.01; task-specific OSATS: 60 ± 3 vs. 50 ± 6, p < 0.01). CONCLUSIONS: Telestration with augmented reality successfully improved surgical performance. The trainee's gaze behaviour was improved by reducing the time from instruction to fixation on targets and leading to a higher convergence of the instructor's and the trainee's gazes. Also, the convergence of trainee's gaze and target areas increased with telestration. This confirms augmented reality-based telestration works by means of gaze guidance in MIS and could be used to improve training outcomes.

Machine learning for optimized individual survival prediction in resectable upper gastrointestinal cancer.

PURPOSE: Surgical oncologists are frequently confronted with the question of expected long-term prognosis. The aim of this study was to apply machine learning algorithms to optimize survival prediction after oncological resection of gastroesophageal cancers. METHODS: Eligible patients underwent oncological resection of gastric or distal esophageal cancer between 2001 and 2020 at Heidelberg University Hospital, Department of General Surgery. Machine learning methods such as multi-task logistic regression and survival forests were compared with usual algorithms to establish an individual estimation. RESULTS: The study included 117 variables with a total of 1360 patients. The overall missingness was 1.3%. Out of eight machine learning algorithms, the random survival forest (RSF) performed best with a concordance index of 0.736 and an integrated Brier score of 0.166. The RSF demonstrated a mean area under the curve (AUC) of 0.814 over a time period of 10 years after diagnosis. The most important long-term outcome predictor was lymph node ratio with a mean AUC of 0.730. A numeric risk score was calculated by the RSF for each patient and three risk groups were defined accordingly. Median survival time was 18.8 months in the high-risk group, 44.6 months in the medium-risk group and above 10 years in the low-risk group. CONCLUSION: The results of this study suggest that RSF is most appropriate to accurately answer the question of long-term prognosis. Furthermore, we could establish a compact risk score model with 20 input parameters and thus provide a clinical tool to improve prediction of oncological outcome after upper gastrointestinal surgery.

ICG-augmented hyperspectral imaging for visualization of intestinal perfusion compared to conventional ICG fluorescence imaging: an experimental study.

BACKGROUND: Small bowel malperfusion (SBM) can cause high morbidity and severe surgical consequences. However, there is no standardized objective measuring tool for the quantification of SBM. Indocyanine green (ICG) imaging can be used for visualization, but lacks standardization and objectivity. Hyperspectral imaging (HSI) as a newly emerging technology in medicine might present advantages over conventional ICG fluorescence or in combination with it. METHODS: HSI baseline data from physiological small bowel, avascular small bowel and small bowel after intravenous application of ICG was recorded in a total number of 54 in-vivo pig models. Visualizations of avascular small bowel after mesotomy were compared between HSI only (1), ICG-augmented HSI (IA-HSI) (2), clinical evaluation through the eyes of the surgeon (3) and conventional ICG imaging (4). The primary research focus was the localization of resection borders as suggested by each of the four methods. Distances between these borders were measured and histological samples were obtained from the regions in between in order to quantify necrotic changes 6 h after mesotomy for every region. RESULTS: StO2 images (1) were capable of visualizing areas of physiological perfusion and areas of clearly impaired perfusion. However, exact borders where physiological perfusion started to decrease could not be clearly identified. Instead, IA-HSI (2) suggested a sharp-resection line where StO2 values started to decrease. Clinical evaluation (3) suggested a resection line 23 mm (±7 mm) and conventional ICG imaging (4) even suggested a resection line 53 mm (±13 mm) closer towards the malperfused region. Histopathological evaluation of the region that was sufficiently perfused only according to conventional ICG (R3) already revealed a significant increase in pre-necrotic changes in 27% (±9%) of surface area. Therefore, conventional ICG seems less sensitive than IA-HSI with regards to detection of insufficient tissue perfusion. CONCLUSIONS: In this experimental animal study, IA-HSI (2) was superior for the visualization of segmental SBM compared to conventional HSI imaging (1), clinical evaluation (3) or conventional ICG imaging (4) regarding histopathological safety. ICG application caused visual artifacts in the StO2 values of the HSI camera as values significantly increase. This is caused by optical properties of systemic ICG and does not resemble a true increase in oxygenation levels. However, this empirical finding can be used to visualize segmental SBM utilizing ICG as contrast agent in an approach for IA-HSI. Clinical applicability and relevance will have to be explored in clinical trials. LEVEL OF EVIDENCE: Not applicable. Translational animal science. Original article.

Combined non-alcoholic fatty liver disease and type 2 diabetes in severely obese patients-medium term effects of sleeve gastrectomy versus Roux-en-Y-gastric bypass on disease markers.

Background: We aimed to evaluate the medium-term efficacy of sleeve gastrectomy (SG) vs. Roux-en-Y gastric bypass (RYGB) on remission of non-alcoholic fatty liver disease (NAFLD) in patients with type 2 diabetes mellitus (T2DM). Methods: We identified severely obese patients [body mass index (BMI) >35 kg/m2] with NAFLD (as defined by the Longitudinal Assessment of Bariatric Surgery Study) and T2DM (as defined by the American Association of Clinical Endocrinologists and the American College of Endocrinology) who underwent SG or RYGB in a single university surgical centre. The cohorts were match-paired and data were analysed after at least 3 years of follow up. The key outcomes measured were: (I) the improvement of liver function tests and NAFLD markers; (II) glycemic control and insulin resistance. Results: Ninety-six patients were investigated; 44 (45.8%) were women. The mean pre-operative BMI was 45.2 kg/m2 in the SG and 42.0 kg/m2 in the RYGB group. SG and RYGB both significantly reduced serum liver enzyme concentrations. NAFLD markers resolved 2 years after SG in all patients. In contrast, only 78% and 80% of patients achieved remission of NAFLD 2 and 3 years after RYBG respectively. Both procedures resulted in comparable rates of remission of T2DM. Conclusions: Bariatric surgery with SG may be preferable to RYGB for obese patients with NAFLD and T2DM based on the rates of remission of markers of these co-morbidities. However, our results need to be confirmed in prospective trials. Understanding the metabolic effects of specific bariatric surgical procedures may facilitate the development of a personalised approach to weight-loss surgery.

Minimally invasivE versus open total GAstrectomy (MEGA): study protocol for a multicentre randomised controlled trial (DRKS00025765).

INTRODUCTION: The only curative treatment for most gastric cancer is radical gastrectomy with D2 lymphadenectomy (LAD). Minimally invasive total gastrectomy (MIG) aims to reduce postoperative morbidity, but its use has not yet been widely established in Western countries. Minimally invasivE versus open total GAstrectomy is the first Western multicentre randomised controlled trial (RCT) to compare postoperative morbidity following MIG vs open total gastrectomy (OG). METHODS AND ANALYSIS: This superiority multicentre RCT compares MIG (intervention) to OG (control) for oncological total gastrectomy with D2 or D2+LAD. Recruitment is expected to last for 2 years. Inclusion criteria comprise age between 18 and 84 years and planned total gastrectomy after initial diagnosis of gastric carcinoma. Exclusion criteria include Eastern Co-operative Oncology Group (ECOG) performance status >2, tumours requiring extended gastrectomy or less than total gastrectomy, previous abdominal surgery or extensive adhesions seriously complicating MIG, other active oncological disease, advanced stages (T4 or M1), emergency setting and pregnancy.The sample size was calculated at 80 participants per group. The primary endpoint is 30-day postoperative morbidity as measured by the Comprehensive Complications Index. Secondary endpoints include postoperative morbidity and mortality, adherence to a fast-track protocol and patient-reported quality of life (QoL) scores (QoR-15, EUROQOL EuroQol-5 Dimensions-5 Levels (EQ-5D), EORTC QLQ-C30, EORTC QLQ-STO22, activities of daily living and Body Image Scale). Oncological endpoints include rate of R0 resection, lymph node yield, disease-free survival and overall survival at 60-month follow-up. ETHICS AND DISSEMINATION: Ethical approval has been received by the independent Ethics Committee of the Medical Faculty, University of Heidelberg (S-816/2021) and will be received from each responsible ethics committee for each individual participating centre prior to recruitment. Results will be published open access. TRIAL REGISTRATION NUMBER: DRKS00025765.

Surgomics: personalized prediction of morbidity, mortality and long-term outcome in surgery using machine learning on multimodal data.

BACKGROUND: Personalized medicine requires the integration and analysis of vast amounts of patient data to realize individualized care. With Surgomics, we aim to facilitate personalized therapy recommendations in surgery by integration of intraoperative surgical data and their analysis with machine learning methods to leverage the potential of this data in analogy to Radiomics and Genomics. METHODS: We defined Surgomics as the entirety of surgomic features that are process characteristics of a surgical procedure automatically derived from multimodal intraoperative data to quantify processes in the operating room. In a multidisciplinary team we discussed potential data sources like endoscopic videos, vital sign monitoring, medical devices and instruments and respective surgomic features. Subsequently, an online questionnaire was sent to experts from surgery and (computer) science at multiple centers for rating the features' clinical relevance and technical feasibility. RESULTS: In total, 52 surgomic features were identified and assigned to eight feature categories. Based on the expert survey (n = 66 participants) the feature category with the highest clinical relevance as rated by surgeons was "surgical skill and quality of performance" for morbidity and mortality (9.0 ± 1.3 on a numerical rating scale from 1 to 10) as well as for long-term (oncological) outcome (8.2 ± 1.8). The feature category with the highest feasibility to be automatically extracted as rated by (computer) scientists was "Instrument" (8.5 ± 1.7). Among the surgomic features ranked as most relevant in their respective category were "intraoperative adverse events", "action performed with instruments", "vital sign monitoring", and "difficulty of surgery". CONCLUSION: Surgomics is a promising concept for the analysis of intraoperative data. Surgomics may be used together with preoperative features from clinical data and Radiomics to predict postoperative morbidity, mortality and long-term outcome, as well as to provide tailored feedback for surgeons.

[Artificial intelligence and hyperspectral imaging for image-guided assistance in minimally invasive surgery]. / Künstliche Intelligenz und hyperspektrale Bildgebung zur bildgestützten Assistenz in der minimal-invasiven Chirurgie.

BACKGROUND: Intraoperative imaging assists surgeons during minimally invasive procedures. Hyperspectral imaging (HSI) is a noninvasive and noncontact optical technique with great diagnostic potential in medicine. The combination with artificial intelligence (AI) approaches to analyze HSI data is called intelligent HSI in this article. OBJECTIVE: What are the medical applications and advantages of intelligent HSI for minimally invasive visceral surgery? MATERIAL AND METHODS: Within various clinical studies HSI data from multiple in vivo tissue types and oncological resections were acquired using an HSI camera system. Different AI algorithms were evaluated for detection and discrimination of organs, risk structures and tumors. RESULTS: In an experimental animal study 20 different organs could be differentiated with high precision (> 95%) using AI. In vivo, the parathyroid glands could be discriminated from surrounding tissue with an F1 score of 47% and sensitivity of 75%, and the bile duct with an F1 score of 79% and sensitivity of 90%. Furthermore, ex vivo tumor tissue could be successfully detected with an area under the receiver operating characteristic (ROC) curve (AUC) larger than 0.91. DISCUSSION: This study demonstrates that intelligent HSI can automatically and accurately detect different tissue types. Despite great progress in the last decade intelligent HSI still has limitations. Thus, accurate AI algorithms that are easier to understand for the user and an extensive standardized and continuously growing database are needed. Further clinical studies should support the various medical applications and lead to the adoption of intelligent HSI in the clinical routine practice.

Spectral organ fingerprints for machine learning-based intraoperative tissue classification with hyperspectral imaging in a porcine model.

Visual discrimination of tissue during surgery can be challenging since different tissues appear similar to the human eye. Hyperspectral imaging (HSI) removes this limitation by associating each pixel with high-dimensional spectral information. While previous work has shown its general potential to discriminate tissue, clinical translation has been limited due to the method's current lack of robustness and generalizability. Specifically, the scientific community is lacking a comprehensive spectral tissue atlas, and it is unknown whether variability in spectral reflectance is primarily explained by tissue type rather than the recorded individual or specific acquisition conditions. The contribution of this work is threefold: (1) Based on an annotated medical HSI data set (9059 images from 46 pigs), we present a tissue atlas featuring spectral fingerprints of 20 different porcine organs and tissue types. (2) Using the principle of mixed model analysis, we show that the greatest source of variability related to HSI images is the organ under observation. (3) We show that HSI-based fully-automatic tissue differentiation of 20 organ classes with deep neural networks is possible with high accuracy (> 95%). We conclude from our study that automatic tissue discrimination based on HSI data is feasible and could thus aid in intraoperative decisionmaking and pave the way for context-aware computer-assisted surgery systems and autonomous robotics.

Outcomes of bariatric surgery in patients with obesity and compensated liver cirrhosis.

BACKGROUND: Obesity is a major health burden worldwide and is associated with nonalcoholic fatty liver disease, which can lead to cirrhosis. Bariatric surgery is increasingly being used to treat obesity, and the number of patients with obesity and cirrhosis undergoing bariatric surgery is also rising. However, the safety and feasibility of bariatric surgery in patients with obesity and cirrhosis are controversial. OBJECTIVES: In this meta-analysis, we compared postoperative complications, mortality, and weight loss between patients with and without cirrhosis undergoing bariatric surgery. SETTING: An electronic search of Medline, Web of Science, and Cochrane Central Register of Controlled Trials (CENTRAL). METHODS: Patient morbidity and mortality odds ratios (ORs) and mean differences (MDs) with 95% confidence intervals (CIs) were assessed. Intraoperative and overall complications, length of hospital stay, in-hospital mortality, long-term mortality, and total weight loss were recorded. RESULTS: The literature search yielded 2977 articles. Eight studies were included in the analysis. Meta-analysis showed that the overall complications (OR: 2.1; 95% CI: 1.47-3.00; P < .0001), postoperative bleeding (OR: 2.22; 95% CI: 1.95-2.54; P < .00001), length of hospital stay (MD: .68; 95% CI: .14-1.19; P = .01), and in-hospital/90-day mortality (OR: 3.59; 95% CI: 2.84-4.54; P < .00001) were significantly higher in patients with compensated cirrhosis than in patients without cirrhosis. Intraoperative complications, operation time, major complications, and long-term mortality were similar between the groups. Total weight loss was also not significantly different between the groups. CONCLUSION: Bariatric surgery can be considered only in highly selected patients with obesity and compensated cirrhosis.

IMHOTEP: cross-professional evaluation of a three-dimensional virtual reality system for interactive surgical operation planning, tumor board discussion and immersive training for complex liver surgery in a head-mounted display.

BACKGROUND: Virtual reality (VR) with head-mounted displays (HMD) may improve medical training and patient care by improving display and integration of different types of information. The aim of this study was to evaluate among different healthcare professions the potential of an interactive and immersive VR environment for liver surgery that integrates all relevant patient data from different sources needed for planning and training of procedures. METHODS: 3D-models of the liver, other abdominal organs, vessels, and tumors of a sample patient with multiple hepatic masses were created. 3D-models, clinical patient data, and other imaging data were visualized in a dedicated VR environment with an HMD (IMHOTEP). Users could interact with the data using head movements and a computer mouse. Structures of interest could be selected and viewed individually or grouped. IMHOTEP was evaluated in the context of preoperative planning and training of liver surgery and for the potential of broader surgical application. A standardized questionnaire was voluntarily answered by four groups (students, nurses, resident and attending surgeons). RESULTS: In the evaluation by 158 participants (57 medical students, 35 resident surgeons, 13 attending surgeons and 53 nurses), 89.9% found the VR system agreeable to work with. Participants generally agreed that complex cases in particular could be assessed better (94.3%) and faster (84.8%) with VR than with traditional 2D display methods. The highest potential was seen in student training (87.3%), resident training (84.6%), and clinical routine use (80.3%). Least potential was seen in nursing training (54.8%). CONCLUSIONS: The present study demonstrates that using VR with HMD to integrate all available patient data for the preoperative planning of hepatic resections is a viable concept. VR with HMD promises great potential to improve medical training and operation planning and thereby to achieve improvement in patient care.

Endoscopic Stent Placement Can Successfully Treat Gastric Leak Following Laparoscopic Sleeve Gastrectomy If and Only If an Esophagoduodenal Megastent Is Used.

PURPOSE: Gastric staple line leakage (GL) is a serious complication of laparoscopic sleeve gastrectomy (LSG), with a specific mortality ranging from 0.2 to 3.7%. The current treatment of choice is stent insertion. However, it is unclear whether the type of stent which is inserted affects treatment outcome. Therefore, we aimed not only to determine the effectiveness of stent treatment for GL but also to specifically clarify whether treatment outcome was dependent on the type of stent (small- (SS) or megastent (MS)) which was used. PATIENTS AND METHODS: A single-centre retrospective study of 23 consecutive patients was conducted to compare the outcomes of SS (n = 12) and MS (n = 11) for the treatment of GL following LSG. The primary outcome measure was the success rate of stenting, defined as complete healing of the GL without changing the treatment strategy. Treatment change or death were both coded as failure. RESULTS: The success rate of MS was 91% (10/11) compared to only 50% (6/12) for SS (p = 0.006). An average of 2.3 ± 0.5 and 6.8 ± 3.7 endoscopies were required to achieve healing in the MS and SS groups respectively (p < 0.001). The average time to resumption of oral nutrition was shorter in the MS group (1.4 ± 1.1 days vs. 23.1 ± 33.1 days, p = 0.003). CONCLUSIONS: Stent therapy is only effective and safe for the treatment of GL after LSG if a MS is used. Treatment with a MS may not only increase treatment success rates but may also facilitate earlier resumption of oral nutrition and shorten the duration of hospitalization.

Clinical Relevance of Gastroesophageal Cancer Associated SNPs for Oncologic Outcome After Curative Surgery.

BACKGROUND: Gastric and esophageal cancers are malignant diseases with rising importance in Western countries. To improve oncologic outcome after surgery, it is essential to understand the relevance of germline mutations. The aim of the study was to identify and distinguish clinically relevant single-nucleotide polymorphisms (SNPs). PATIENTS AND METHODS: In total, 190 patients with curative oncological resections of gastric and distal esophageal adenocarcinomas at Heidelberg University Hospital were eligible for this study. Outcome differences were determined for each SNP by analysis of clinical variables, survival, and mRNA expression levels. RESULTS: Significant survival differences were found on univariate analysis for usual prognostic variables (such as pTNM) and for six SNPs. On multivariate survival analysis, the SNPs rs12268840 (intron variant of MGMT, p = 0.045) and rs9972882 (intron variant of STARD3 and eQTL of PGAP3, p = 0.030) were independent and significant survival predictors along with R status and pT/pN category. Group TT of rs12268840 had the highest rate of second primary carcinoma (30.4%, p = 0.0003), lowest expression of MGMT based on cis-eQTL analysis in normal gastroesophageal tissue (p = 1.99 × 10-17), and worst oncologic outcome. Group AA of rs9972882 had the highest rate of distant metastases pM1 (42.9%, p = 0.0117), highest expression of PGAP3 (p = 1.29 × 10-15), and worst oncologic outcome. CONCLUSIONS: Two intron variant SNPs of MGMT and STARD3 were identified that were significant survival predictors and may influence tumor biology. The data indicate that DNA methylation (MGMT) and malfunction of GPI anchoring (PGAP3) are distinct mechanisms that are relevant for tumor progression and relapse.