BariSurg trial: Sleeve gastrectomy versus Roux-en-Y gastric bypass in obese patients with BMI 35–60 kg/m2 – a multi-centre randomized patient and observer blind non-inferiority trial

Background: Roux-en-Ygastric bypass (RYGB) and sleeve gastrectomy (SG) rank among the most frequently applied bariatric procedures worldwide due to their positive risk/benefit correlation. A systematic review revealed a similar excess weight loss (EWL) 2 years postoperatively between SG and RYGB. However, there is a lack of randomized controlled multi-centre trials comparing SG and RYGB, not only concerning EWL, but also in terms of remission of obesity-related co-morbidities, gastroesophageal reflux disease (GERD) and quality of life (QoL) in the mid- and long-term. Methods: The BariSurg trial was designed as a multi-centre, randomized controlled patient and observer blind trial. The trial protocol was approved by the corresponding ethics committees of the centres. To demonstrate EWL non-inferiority of SG compared to RYGB, power calculation was performed according to a non-inferiority study design. Morbidity, mortality, remission of obesity-related co-morbidities, GERD course and QoL are major secondary endpoints. 248 patients between 18 and 70 years, with a body mass index (BMI) between 35–60 kg/m2 and indication for bariatric surgery according to the most recent German S3-guidelines will be randomized. The primary and secondary endpoints will be assessed prior to surgery and afterwards at discharge and at the time points 3–6, 12, 24, 36, 48 and 60 months postoperatively. Discussion: With its five year follow-up, the BariSurg-trial will provide further evidence based data concerning the impact of SG and RYGB on EWL, remission of obesity-related co-morbidities, the course of GERD and QoL. Trial registration: The trial protocol has been registered in the German Clinical Trials Register DRKS0000476

Erratum to: LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition

International audienceno abstrac

LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition.

International audiencePurpose - The rise of intraoperative information threatens to outpace our abilities to process it. Context-aware systems, filtering information to automatically adapt to the current needs of the surgeon, are necessary to fully profit from computerized surgery. To attain context awareness, representation of medical knowledge is crucial. However, most existing systems do not represent knowledge in a reusable way, hindering also reuse of data. Our purpose is therefore to make our computational models of medical knowledge sharable, extensible and interoperational with established knowledge representations in the form of the LapOntoSPM ontology. To show its usefulness, we apply it to situation interpretation, i.e., the recognition of surgical phases based on surgical activities. Methods - Considering best practices in ontology engineering and building on our ontology for laparoscopy, we formalized the workflow of laparoscopic adrenalectomies, cholecystectomies and pancreatic resections in the framework of OntoSPM, a new standard for surgical process models. Furthermore, we provide a rule-based situation interpretation algorithm based on SQWRL to recognize surgical phases using the ontology. Results - The system was evaluated on ground-truth data from 19 manually annotated surgeries. The aim was to show that the phase recognition capabilities are equal to a specialized solution. The recognition rates of the new system were equal to the specialized one. However, the time needed to interpret a situation rose from 0.5 to 1.8 s on average which is still viable for practical application. Conclusion - We successfully integrated medical knowledge for laparoscopic surgeries into OntoSPM, facilitating knowledge and data sharing. This is especially important for reproducibility of results and unbiased comparison of recognition algorithms. The associated recognition algorithm was adapted to the new representation without any loss of classification power. The work is an important step to standardized knowledge and data representation in the field on context awareness and thus toward unified benchmark data sets

Context-aware Augmented Reality in laparoscopic surgery

Augmented Reality is a promising paradigm for intraoperative assistance. Yet, apart from technical issues, a major obstacle to its clinical application is the man-machine interaction. Visualization of unnecessary, obsolete or redundant information may cause confusion and distraction, reducing usefulness and acceptance of the assistance system.We propose a system capable of automatically filtering available information based on recognized phases in the operating room. Our system offers a specific selection of available visualizations which suit the surgeon's needs best. The system was implemented for use in laparoscopic liver and gallbladder surgery and evaluated in phantom experiments in conjunction with expert interviews.publishe