BACKGROUND: ALCAM (activated leucocyte cell adhesion molecule, synonym CD166) is a cell adhesion molecule, which belongs to the Ig superfamily. Disruption of the ALCAM-mediated adhesiveness by proteolytic sheddases such as ADAM17 has been suggested to have a relevant impact on tumour invasion. Although the expression of ALCAM is a valuable prognostic and predictive marker in several types of epithelial tumours, its role as a prognostic marker in pancreatic cancer has not yet been reported. METHODS: In this study, paraffin-embedded samples of 97 patients with pancreatic cancer undergoing potentially curative resection were immunostained against ALCAM, ADAM17 and CK19. Expression of ALCAM and ADAM17 was semiquantitatively evaluated and correlated to clinical and histopathological parameters. RESULTS: We could show that in normal pancreatic tissue, ALCAM is predominantly expressed at the cellular membrane, whereas in pancreatic tumour cells, it is mainly localised in the cytoplasm. In addition, univariate and multivariate analyses show that increased expression of ALCAM is an adverse prognostic factor for recurrence-free and overall survival. Overexpression of ADAM17 in pancreatic cancer, however, failed to be a significant prognostic marker and was not coexpressed with ALCAM. CONCLUSIONS: Our findings support the hypothesis that the disruption of ALCAM-mediated adhesiveness is a relevant step in pancreatic cancer progression. Moreover, ALCAM overexpression is a relevant independent prognostic marker for poor survival and early tumour relapse in pancreatic cancer.

TS is an accepted serious gaming application for learning cognitive aspects of LC with established construct, face, and content validity. There appeared to be a synergy between TS and the VR trainer. Therefore, the two training modalities should accompany one another in a multimodal training approach to laparoscopy.

This study compared virtual reality (VR) training with low cost-blended learning (BL) in a structured training program.Training of laparoscopic skills outside the operating room is mandatory to reduce operative times and risks.Laparoscopy-naïve medical students were randomized in 2 groups stratified for sex. The BL group (n = 42) used E-learning for laparoscopic cholecystectomy (LC) and practiced basic skills with box trainers. The VR group (n = 42) trained basic skills and LC on the LAP Mentor II (Simbionix, Cleveland, OH). Each group trained 3 × 4 hours followed by a knowledge test concerning LC. Blinded raters assessed the operative performance of cadaveric porcine LC using the Objective Structured Assessment of Technical Skills (OSATS). The LC was discontinued when it was not completed within 80 min. Students evaluated their training modality with questionnaires.The VR group completed the LC significantly faster and more often within 80 min than BL (45% v 21%, P = .02). The BL group scored higher than the VR group in the knowledge test (13.3 ± 1.3 vs 11.0 ± 1.7, P < 0.001). Both groups showed equal operative performance of LC in the OSATS score (49.4 ± 10.5 vs 49.7 ± 12.0, P = 0.90). Students generally liked training and felt well prepared for assisting in laparoscopic surgery. The efficiency of the training was judged higher by the VR group than by the BL group.VR and BL can both be applied for training the basics of LC. Multimodality training programs should be developed that combine the advantages of both approaches.

The results show that RAS is feasible and safe. It appears to be an alternative to OS due to lower intraoperative blood loss and potentially fewer postoperative complications, as well as shorter hospital stay. Though, RAS is not superior to CLS.

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.

The OntoSPM Collaborative Action has been in operation for 24 months, with a growing dedicated membership. Its main result is a modular ontology, undergoing constant updates and extensions, based on the experts' suggestions. It remains an open collaborative action, which always welcomes new contributors and applications.

Validity and reliability of the self-developed sensor-and expert model-based laparoscopic training system "iSurgeon" were established. Using multiple parameters proved more reliable than single metric parameters. Wrapping of the needle around the thread and needle positioning were identified as difficult key steps for laparoscopic suturing and knot tying. The iSurgeon could generate automated real-time feedback based on expert models which may result in shorter learning curves for laparoscopic tasks. Our next steps will be the implementation and evaluation of full procedural training in an experimental model.

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.