LapTrain: multi-modality training curriculum for laparoscopic cholecystectomy-results of a randomized controlled trial.

BACKGROUND: Multiple training modalities for laparoscopy have different advantages, but little research has been conducted on the benefit of a training program that includes multiple different training methods compared to one method only. This study aimed to evaluate benefits of a combined multi-modality training program for surgical residents. METHODS: Laparoscopic cholecystectomy (LC) was performed on a porcine liver as the pre-test. Randomization was stratified for experience to the multi-modality Training group (12 h of training on Virtual Reality (VR) and box trainer) or Control group (no training). The post-test consisted of a VR LC and porcine LC. Performance was rated with the Global Operative Assessment of Laparoscopic Skills (GOALS) score by blinded experts. RESULTS: Training (n = 33) and Control (n = 31) were similar in the pre-test (GOALS: 13.7 ± 3.4 vs. 14.7 ± 2.6; p = 0.198; operation time 57.0 ± 18.1 vs. 63.4 ± 17.5 min; p = 0.191). In the post-test porcine LC, Training had improved GOALS scores (+ 2.84 ± 2.85 points, p < 0.001), while Control did not (+ 0.55 ± 2.34 points, p = 0.154). Operation time in the post-test was shorter for Training vs. Control (40.0 ± 17.0 vs. 55.0 ± 22.2 min; p = 0.012). Junior residents improved GOALS scores to the level of senior residents (pre-test: 13.7 ± 2.7 vs. 18.3 ± 2.9; p = 0.010; post-test: 15.5 ± 3.4 vs. 18.8 ± 3.8; p = 0.120) but senior residents remained faster (50.1 ± 20.6 vs. 25.0 ± 1.9 min; p < 0.001). No differences were found between groups on the post-test VR trainer. CONCLUSIONS: Structured multi-modality training is beneficial for novices to improve basics and overcome the initial learning curve in laparoscopy as well as to decrease operation time for LCs in different stages of experience. Future studies should evaluate multi-modality training in comparison with single modalities. TRIAL REGISTRATION: German Clinical Trials Register DRKS00011040.

[Intelligent operating room suite : From passive medical devices to the self-thinking cognitive surgical assistant]. / Der intelligente Operationssaal : Vom passiven Gerätepark zum mitdenkenden, kognitiven Assistenten.

Modern operating room (OR) suites are mostly digitally connected but until now the primary focus was on the presentation, transfer and distribution of images. Device information and processes within the operating theaters are barely considered. Cognitive assistance systems have triggered a fundamental rethinking in the automotive industry as well as in logistics. In principle, tasks in the OR, some of which are highly repetitive, also have great potential to be supported by automated cognitive assistance via a self-thinking system. This includes the coordination of the entire workflow in the perioperative process in both the operating theater and the whole hospital. With corresponding data from hospital information systems, medical devices and appropriate models of the surgical process, intelligent systems could optimize the workflow in the operating theater in the near future and support the surgeon. Preliminary results on the use of device information and automatically controlled OR suites are already available. Such systems include, for example the guidance of laparoscopic camera systems. Nevertheless, cognitive assistance systems that make use of knowledge about patients, processes and other pieces of information to improve surgical treatment are not yet available in the clinical routine but are urgently needed in order to automatically assist the surgeon in situation-related activities and thus substantially improve patient care.

Computer-assisted abdominal surgery: new technologies.

BACKGROUND: Computer-assisted surgery is a wide field of technologies with the potential to enable the surgeon to improve efficiency and efficacy of diagnosis, treatment, and clinical management. PURPOSE: This review provides an overview of the most important new technologies and their applications. METHODS: A MEDLINE database search was performed revealing a total of 1702 references. All references were considered for information on six main topics, namely image guidance and navigation, robot-assisted surgery, human-machine interface, surgical processes and clinical pathways, computer-assisted surgical training, and clinical decision support. Further references were obtained through cross-referencing the bibliography cited in each work. Based on their respective field of expertise, the authors chose 64 publications relevant for the purpose of this review. CONCLUSION: Computer-assisted systems are increasingly used not only in experimental studies but also in clinical studies. Although computer-assisted abdominal surgery is still in its infancy, the number of studies is constantly increasing, and clinical studies start showing the benefits of computers used not only as tools of documentation and accounting but also for directly assisting surgeons during diagnosis and treatment of patients. Further developments in the field of clinical decision support even have the potential of causing a paradigm shift in how patients are diagnosed and treated.

OpenHELP (Heidelberg laparoscopy phantom): development of an open-source surgical evaluation and training tool.

BACKGROUND: Apart from animal testing and clinical trials, surgical research and laparoscopic training mainly rely on phantoms. The aim of this project was to design a phantom with realistic anatomy and haptic characteristics, modular design and easy reproducibility. The phantom was named open-source Heidelberg laparoscopic phantom (OpenHELP) and serves as an open-source platform. METHODS: The phantom was based on an anonymized CT scan of a male patient. The anatomical structures were segmented to obtain digital three-dimensional models of the torso and the organs. The digital models were materialized via rapid prototyping. One flexible, using an elastic abdominal wall, and one rigid method, using a plastic shell, to simulate pneumoperitoneum were developed. Artificial organ production was carried out sequentially starting from raw gypsum models to silicone molds to final silicone casts. The reproduction accuracy was exemplarily evaluated for ten silicone rectum models by comparing the digital 3D surface of the original rectum with CT scan by calculating the root mean square error of surface variations. Haptic realism was also evaluated to find the most realistic silicone compositions on a visual analog scale (VAS, 0-10). RESULTS: The rigid and durable plastic torso and soft silicone organs of the abdominal cavity were successfully produced. A simulation of pneumoperitoneum could be created successfully by both methods. The reproduction accuracy of ten silicone rectum models showed an average root mean square error of 2.26 (0-11.48) mm. Haptic realism revealed an average value on a VAS of 7.25 (5.2-9.6) for the most realistic rectum. CONCLUSION: The OpenHELP phantom proved to be feasible and accurate. The phantom was consecutively applied frequently in the field of computer-assisted surgery at our institutions and is accessible as an open-source project at www.open-cas.org for the academic community.