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.

Intraoperative liver deformation and organ motion caused by ventilation, laparotomy, and pneumoperitoneum in a porcine model for image-guided liver surgery.

BACKGROUND: Image-guidance promises to make complex situations in liver interventions safer. Clinical success is limited by intraoperative organ motion due to ventilation and surgical manipulation. The aim was to assess influence of different ventilatory and operative states on liver motion in an experimental model. METHODS: Liver motion due to ventilation (expiration, middle, and full inspiration) and operative state (native, laparotomy, and pneumoperitoneum) was assessed in a live porcine model (n = 10). Computed tomography (CT)-scans were taken for each pig for each possible combination of factors. Liver motion was measured by the vectors between predefined landmarks along the hepatic vein tree between CT scans after image segmentation. RESULTS: Liver position changed significantly with ventilation. Peripheral regions of the liver showed significantly higher motion (maximal Euclidean motion 17.9 ± 2.7 mm) than central regions (maximal Euclidean motion 12.6 ± 2.1 mm, p < 0.001) across all operative states. The total average motion measured 11.6 ± 0.7 mm (p < 0.001). Between the operative states, the position of the liver changed the most from native state to pneumoperitoneum (14.6 ± 0.9 mm, p < 0.001). From native state to laparotomy comparatively, the displacement averaged 9.8 ± 1.2 mm (p < 0.001). With pneumoperitoneum, the breath-dependent liver motion was significantly reduced when compared to other modalities. Liver motion due to ventilation was 7.7 ± 0.6 mm during pneumoperitoneum, 13.9 ± 1.1 mm with laparotomy, and 13.5 ± 1.4 mm in the native state (p < 0.001 in all cases). CONCLUSIONS: Ventilation and application of pneumoperitoneum caused significant changes in liver position. Liver motion was reduced but clearly measurable during pneumoperitoneum. Intraoperative guidance/navigation systems should therefore account for ventilation and intraoperative changes of liver position and peripheral deformation.

Development of biotissue training models for anastomotic suturing in pancreatic surgery.

BACKGROUND: Anastomotic suturing is the Achilles heel of pancreatic surgery. Especially in laparoscopic and robotically assisted surgery, the pancreatic anastomosis should first be trained outside the operating room. Realistic training models are therefore needed. METHODS: Models of the pancreas, small bowel, stomach, bile duct, and a realistic training torso were developed for training of anastomoses in pancreatic surgery. Pancreas models with soft and hard textures, small and large ducts were incrementally developed and evaluated. Experienced pancreatic surgeons (n = 44) evaluated haptic realism, rigidity, fragility of tissues, and realism of suturing and knot tying. RESULTS: In the iterative development process the pancreas models showed high haptic realism and highest realism in suturing (4.6 ± 0.7 and 4.9 ± 0.5 on 1-5 Likert scale, soft pancreas). The small bowel model showed highest haptic realism (4.8 ± 0.4) and optimal wall thickness (0.1 ± 0.4 on -2 to +2 Likert scale) and suturing behavior (0.1 ± 0.4). The bile duct models showed optimal wall thickness (0.3 ± 0.8 and 0.4 ± 0.8 on -2 to +2 Likert scale) and optimal tissue fragility (0 ± 0.9 and 0.3 ± 0.7). CONCLUSION: The biotissue training models showed high haptic realism and realistic suturing behavior. They are suitable for realistic training of anastomoses in pancreatic surgery which may improve patient outcomes.

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.

Vascularization in Bioartificial Parenchymal Tissue: Bioink and Bioprinting Strategies.

Among advanced therapy medicinal products, tissue-engineered products have the potential to address the current critical shortage of donor organs and provide future alternative options in organ replacement therapy. The clinically available tissue-engineered products comprise bradytrophic tissue such as skin, cornea, and cartilage. A sufficient macro- and microvascular network to support the viability and function of effector cells has been identified as one of the main challenges in developing bioartificial parenchymal tissue. Three-dimensional bioprinting is an emerging technology that might overcome this challenge by precise spatial bioink deposition for the generation of a predefined architecture. Bioinks are printing substrates that may contain cells, matrix compounds, and signaling molecules within support materials such as hydrogels. Bioinks can provide cues to promote vascularization, including proangiogenic signaling molecules and cocultured cells. Both of these strategies are reported to enhance vascularization. We review pre-, intra-, and postprinting strategies such as bioink composition, bioprinting platforms, and material deposition strategies for building vascularized tissue. In addition, bioconvergence approaches such as computer simulation and artificial intelligence can support current experimental designs. Imaging-derived vascular trees can serve as blueprints. While acknowledging that a lack of structured evidence inhibits further meta-analysis, this review discusses an end-to-end process for the fabrication of vascularized, parenchymal tissue.

Machine Learning for Surgical Phase Recognition: A Systematic Review.

OBJECTIVE: To provide an overview of ML models and data streams utilized for automated surgical phase recognition. BACKGROUND: Phase recognition identifies different steps and phases of an operation. ML is an evolving technology that allows analysis and interpretation of huge data sets. Automation of phase recognition based on data inputs is essential for optimization of workflow, surgical training, intraoperative assistance, patient safety, and efficiency. METHODS: A systematic review was performed according to the Cochrane recommendations and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statement. PubMed, Web of Science, IEEExplore, GoogleScholar, and CiteSeerX were searched. Literature describing phase recognition based on ML models and the capture of intraoperative signals during general surgery procedures was included. RESULTS: A total of 2254 titles/abstracts were screened, and 35 full-texts were included. Most commonly used ML models were Hidden Markov Models and Artificial Neural Networks with a trend towards higher complexity over time. Most frequently used data types were feature learning from surgical videos and manual annotation of instrument use. Laparoscopic cholecystectomy was used most commonly, often achieving accuracy rates over 90%, though there was no consistent standardization of defined phases. CONCLUSIONS: ML for surgical phase recognition can be performed with high accuracy, depending on the model, data type, and complexity of surgery. Different intraoperative data inputs such as video and instrument type can successfully be used. Most ML models still require significant amounts of manual expert annotations for training. The ML models may drive surgical workflow towards standardization, efficiency, and objectiveness to improve patient outcome in the future. REGISTRATION PROSPERO: CRD42018108907.

A learning robot for cognitive camera control in minimally invasive surgery.

BACKGROUND: We demonstrate the first self-learning, context-sensitive, autonomous camera-guiding robot applicable to minimally invasive surgery. The majority of surgical robots nowadays are telemanipulators without autonomous capabilities. Autonomous systems have been developed for laparoscopic camera guidance, however following simple rules and not adapting their behavior to specific tasks, procedures, or surgeons. METHODS: The herein presented methodology allows different robot kinematics to perceive their environment, interpret it according to a knowledge base and perform context-aware actions. For training, twenty operations were conducted with human camera guidance by a single surgeon. Subsequently, we experimentally evaluated the cognitive robotic camera control. A VIKY EP system and a KUKA LWR 4 robot were trained on data from manual camera guidance after completion of the surgeon's learning curve. Second, only data from VIKY EP were used to train the LWR and finally data from training with the LWR were used to re-train the LWR. RESULTS: The duration of each operation decreased with the robot's increasing experience from 1704 s ± 244 s to 1406 s ± 112 s, and 1197 s. Camera guidance quality (good/neutral/poor) improved from 38.6/53.4/7.9 to 49.4/46.3/4.1% and 56.2/41.0/2.8%. CONCLUSIONS: The cognitive camera robot improved its performance with experience, laying the foundation for a new generation of cognitive surgical robots that adapt to a surgeon's needs.

Effects of laparoscopy, laparotomy, and respiratory phase on liver volume in a live porcine model for liver resection.

BACKGROUND: Hepatectomy, living donor liver transplantations and other major hepatic interventions rely on precise calculation of the total, remnant and graft liver volume. However, liver volume might differ between the pre- and intraoperative situation. To model liver volume changes and develop and validate such pre- and intraoperative assistance systems, exact information about the influence of lung ventilation and intraoperative surgical state on liver volume is essential. METHODS: This study assessed the effects of respiratory phase, pneumoperitoneum for laparoscopy, and laparotomy on liver volume in a live porcine model. Nine CT scans were conducted per pig (N = 10), each for all possible combinations of the three operative (native, pneumoperitoneum and laparotomy) and respiratory states (expiration, middle inspiration and deep inspiration). Manual segmentations of the liver were generated and converted to a mesh model, and the corresponding liver volumes were calculated. RESULTS: With pneumoperitoneum the liver volume decreased on average by 13.2% (112.7 ml ± 63.8 ml, p < 0.0001) and after laparotomy by 7.3% (62.0 ml ± 65.7 ml, p = 0.0001) compared to native state. From expiration to middle inspiration the liver volume increased on average by 4.1% (31.1 ml ± 55.8 ml, p = 0.166) and from expiration to deep inspiration by 7.2% (54.7 ml ± 51.8 ml, p = 0.007). CONCLUSIONS: Considerable changes in liver volume change were caused by pneumoperitoneum, laparotomy and respiration. These findings provide knowledge for the refinement of available preoperative simulation and operation planning and help to adjust preoperative imaging parameters to best suit the intraoperative situation.

Does rating with a checklist improve the effect of E-learning for cognitive and practical skills in bariatric surgery? A rater-blinded, randomized-controlled trial.

BACKGROUND: Mental training of laparoscopic procedures with E-learning has been shown to translate to the operating room. The present study aims to explore whether the use of checklists during E-learning improves transfer of skills to the simulated OR on a Virtual Reality (VR) trainer for Roux-en-Y gastric bypass (RYGB). METHODS: Laparoscopy naive medical students (n = 80) were randomized in two groups. After an E-learning introduction to RYGB, checklist group rated RYGB videos using the validated Bariatric Objective Structured Assessment of Technical Skills (BOSATS) checklist while group without checklist only observed the videos. Participants then performed RYGB on a VR-trainer twice and were evaluated by a blinded expert rater using BOSATS. A multiple choice (MC) knowledge test on RYGB was performed. Suturing on a cadaveric porcine small bowel was evaluated using objective structured assessment of technical skill (OSATS). RESULTS: Checklist group was better in the knowledge test (A 8.3 ± 1.1 vs. B 7.1 ± 1.3; p ≤ 0.001) and there was a trend towards better VR RYGB performance (BOSATS) on the first try (85.9 ± 10.2 vs. 81.1 ± 11.5; p = 0.058), but not on the second try (92.0 ± 9.7 vs. 89.3 ± 10.5; p = 0.251). Suturing as measured by OSATS was not different (29.5 ± 3.0 vs. 29.0 ± 3.5; p = 0.472). CONCLUSION: This study presents evidence that the use of a BOSATS checklist during E-learning helps trainees to improve their knowledge acquisition with E-learning. The transfer from mental training to the simulated OR environment seems to be partially enhanced by use of the BOSATS checklist. However, more research is required to investigate potential benefits.

One or two trainees per workplace for laparoscopic surgery training courses: results from a randomized controlled trial.

BACKGROUND: There are no standards for optimal utilization of workplaces in laparoscopic training. This study aimed to define whether laparoscopy training should be done alone or in pairs (known as dyad training). METHODS: This was a three-arm randomized controlled trial with laparoscopically naïve medical students (n = 100). Intervention groups participated alone (n = 40) or as dyad (n = 40) in a multimodality training curriculum with e-learning, basic, and procedural skills training using box and VR trainers. The control group (n = 20) had no training. Post-performance of a cadaveric porcine laparoscopic cholecystectomy (LC) was measured as the primary outcome by blinded raters using the objective structured assessment of technical skills (OSATS). Global operative assessment of laparoscopic skills (GOALS), time for LC, and VR performances were secondary outcomes. RESULTS: There were no differences between groups for performance scores [OSATS: alone (40.2 ± 9.8) vs. dyad (39.8 ± 8.6), p = 0.995; alone vs. control (37.1 ± 7.4), p = 0.548; or dyad vs. control, p = 0.590; and GOALS score: alone (10.6 ± 3.0) vs. dyad (10.0 ± 2.7), p = 0.599; alone vs. control (10.1 ± 3.0), p = 0.748; or dyad vs. control, p = 0.998]. Dyad finished LC faster than control [median = 62.5 min (CI 58.0-73.0) vs. 76.5 min (CI 72.0-80+); p = 0.042], while there were no inter-group differences between alone vs. control [median = 69.0 min (CI 62.0-76.0) vs. control; p = 0.099] or alone vs. dyad (p = 0.840). Dyad and alone showed superior performance on the VR trainer vs. control for time, number of movements, and path length, but not for complications and application of cautery. CONCLUSIONS: The curriculum provided trainees with the laparoscopic skills needed to perform LC safely, irrespective of the number of trainees per workplace. Dyad training reduced the operation time needed for LC. Therefore, dyad training seems to be a promising alternative, especially if training time is limited and resources must be used as efficiently as possible. Trial registration German Clinical Trials Register: DRKS00004675.

An ad hoc three dimensionally printed tool facilitates intraesophageal suturing in experimental surgery.

BACKGROUND: Three-dimensional printing (3DP) has become popular for development of anatomic models, preoperative planning, and production of tailored implants. A novel laparoscopic, transgastric procedure for distal esophageal mucosectomy was developed. During this procedure, a space holder had to be introduced into the distal esophagus for exposure during suturing. The production process and evaluation of a 3DP space holder are described herein. MATERIALS AND METHODS: Computer-aided design software was used to develop models printed from polylactic acid. The prototype was adapted after testing in a cadaveric model. Subsequently, the device was evaluated in a nonsurvival porcine model. A mucosal purse-string suture was placed as orally as possible in the esophagus, in the intervention group with and in the control group without use of the tool (n = 8 each). The distance of the stitches from the Z-line was measured. The variability of stitches indicated the suture quality. RESULTS: The median maximum distance from the Z-line to purse-string suture was larger in the intervention group (5.0 [3.3-6.4] versus 2.4 [2.0-4.1] cm; P = 0.013). The time taken to place the sutures was shorter in the control group (P < 0.001). Stitch variance tended to be greater in the intervention group (2.3 [0.9-2.5] versus 0.7 [0.2-0.4] cm; P = 0.051). The time required for design and production of a tailored tool was less than 24 h. CONCLUSIONS: 3DP in experimental surgery enables rapid production, permits repeated adaptation until a tailored tool is obtained, and ensures independence from industrial partners. With the aid of the space holder more orally located esophageal lesions came within reach.

Impact of visual-spatial ability on laparoscopic camera navigation training.

BACKGROUND: Technical limitations of minimally invasive surgery challenge both surgeons and camera assistants. Current research indicates that visual-spatial ability (VSA) has impact on learning of laparoscopic camera navigation (LCN). However, it remains unclear if complexity of LCN tasks influences the impact of VSA. The aim of this study was to examine the influence of VSA on LCN training within tasks of different complexity levels. METHODS: The present study was conducted as a monocentric prospective trial. VSA was assessed with a cube comparison test before participants underwent LCN training. LCN training consisted of three tasks with increasing complexity. Each task was performed four times and performance was assessed each time. Correlations and multivariate regression analysis were used to assess the influence of VSA on LCN skills. RESULTS: Seventy-one participants were included (35 males). Significant performance improvement and faster completion times were observed from the first to fourth trial of all three LCN training tasks. Significant positive correlations between VSA and performance on LCN task 3 were found (performance: r s = 0.47; p < 0.001, time: r s = -0.43; p < 0.001). Multivariate regression revealed that higher VSA resulted in greater reduction of time between the first trials of LCN training task 3 (B = -1.67, p = 0.031). CONCLUSION: In the present study, all trainees improved LCN performance during the training. VSA seems to have impact on LCN performance and training progress particularly for complex LCN tasks. The relation of VSA and LCN performance was stronger for less experienced participants and in the beginning of the learning phase.

Skills in minimally invasive and open surgery show limited transferability to robotic surgery: results from a prospective study.

BACKGROUND: There is limited evidence on the transferability of conventional laparoscopic and open surgical skills to robotic-assisted surgery. The primary aim of this study was to evaluate the transferability of expertise in conventional laparoscopy and open surgery to robotic-assisted surgery using the da Vinci Skills Simulator (dVSS). Secondary aims included evaluating the influence of individual participants' characteristics. METHODS: Participants performed four tasks on the dVSS: Peg Board 1 (PB), Pick and Place (PP), Thread the Rings (TR), and Suture Sponge 1 (SS). Participants were classified into three groups (Novice, Intermediate, Experts) according to experience in laparoscopic and open surgery. All tasks were performed twice except for SS. Performance was assessed using the built-in scoring system. RESULTS: 37 medical students and 25 surgeons participated. Experts did not perform significantly better than less experienced participants on the dVSS. Specifically, with regard to laparoscopic experience, total simulator scores were: Novices 68.2 ± 28.8; Intermediates 65.1 ± 31.2; Experts 65.1 ± 30.0; p = 0.611. Regarding open surgical experience, scores were: Novices 68.6 ± 28.7; Intermediates 68.2 ± 30.8; Experts 63.2 ± 30.3; p = 0.305. Although there were some significant differences among groups for single parameters in specific tasks, there was no constant superiority of one group. Laparoscopic and open surgical Novices improved significantly in overall score and time for all three tasks (p < 0.05). Laparoscopic intermediates improved only in PP time (4.64 ± 3.42; p = 0.006), open Intermediates in PB score (11.98 ± 13.01; p = 0.025), and open Experts in PP score (6.69 ± 11.48; p = 0.048). Laparoscopic experts showed no improvement. Participants with gaming experience had better overall scores than non-gamers when comparing all second attempts (Gamer 83.62 ± 7.57; Non-Gamer 76.31 ± 12.78; p = 0.008) as well as first and second attempts together (Gamer 72.08 ± 8.86; Non-Gamer 65.45 ± 11.68; p = 0.039). Musical and sports experience showed no correlation with robotic performance. CONCLUSIONS: Robotic-assisted surgery requires skills distinct from conventional laparoscopy or open surgery. Basic robotic skills training prior to patient contact should be required.

Computer tomographic analysis of organ motion caused by respiration and intraoperative pneumoperitoneum in a porcine model for navigated minimally invasive esophagectomy.

BACKGROUND: Navigation systems have the potential to facilitate intraoperative orientation and recognition of anatomical structures. Intraoperative accuracy of navigation in thoracoabdominal surgery depends on soft tissue deformation. We evaluated esophageal motion caused by respiration and pneumoperitoneum in a porcine model for minimally invasive esophagectomy. METHODS: In ten pigs (20-34 kg) under general anesthesia, gastroscopic hemoclips were applied to the cervical (CE), high (T1), middle (T2), and lower thoracic (T3) level, and to the gastroesophageal junction (GEJ) of the esophagus. Furthermore, skin markers were applied. Three-dimensional (3D) and four-dimensional (4D) computed tomography (CT) scans were acquired before and after creation of pneumoperitoneum. Marker positions and lung volumes were analyzed with open source image segmentation software. RESULTS: Respiratory motion of the esophagus was higher at T3 (7.0 ± 3.3 mm, mean ± SD) and GEJ (6.9 ± 2.8 mm) than on T2 (4.5 ± 1.8 mm), T1 (3.1 ± 1.8 mm), and CE (1.3 ± 1.1 mm). There was significant motion correlation in between the esophageal levels. T1 motion correlated with all other esophagus levels (r = 0.51, p = 0.003). Esophageal motion correlated with ventilation volume (419 ± 148 ml) on T1 (r = 0.29), T2 (r = 0.44), T3 (r = 0.54), and GEJ (r = 0.58) but not on CE (r = - 0.04). Motion correlation of the esophagus with skin markers was moderate to high for T1, T2, T3, GEJ, but not evident for CE. Pneumoperitoneum led to considerable displacement of the esophagus (8.2 ± 3.4 mm) and had a level-specific influence on respiratory motion. CONCLUSIONS: The position and motion of the esophagus was considerably influenced by respiration and creation of pneumoperitoneum. Esophageal motion correlated with respiration and skin motion. Possible compensation mechanisms for soft tissue deformation were successfully identified. The porcine model is similar to humans for respiratory esophageal motion and can thus help to develop navigation systems with compensation for soft tissue deformation.

Computer-assisted 3D bowel length measurement for quantitative laparoscopy.

BACKGROUND: This study aimed at developing and evaluating a tool for computer-assisted 3D bowel length measurement (BMS) to improve objective measurement in minimally invasive surgery. Standardization and quality of surgery as well as its documentation are currently limited by lack of objective intraoperative measurements. To solve this problem, we developed BMS as a clinical application of Quantitative Laparoscopy (QL). METHODS: BMS processes images from a conventional 3D laparoscope. Computer vision algorithms are used to measure the distance between laparoscopic instruments along a 3D reconstruction of the bowel surface. Preclinical evaluation was performed in phantom, ex vivo porcine, and in vivo porcine models. A bowel length of 70 cm was measured with BMS and compared to a manually obtained ground truth. Afterwards 70 cm of bowel (ground truth) was measured and compared to BMS. RESULTS: Ground truth was 66.1 ± 2.7 cm (relative error + 5.8%) in phantom, 65.8 ± 2.5 cm (relative error + 6.4%) in ex vivo, and 67.5 ± 6.6 cm (relative error + 3.7%) in in vivo porcine evaluation when 70 cm was measured with BMS. Using 70 cm of bowel, BMS measured 75.0 ± 2.9 cm (relative error + 7.2%) in phantom and 74.4 ± 2.8 cm (relative error + 6.3%) in ex vivo porcine evaluation. After thorough preclinical evaluation, BMS was successfully used in a patient undergoing laparoscopic Roux-en-Y gastric bypass for morbid obesity. CONCLUSIONS: QL using BMS was shown to be feasible and was successfully translated from studies on phantom, ex vivo, and in vivo porcine bowel to a clinical feasibility study.

Mobile, real-time, and point-of-care augmented reality is robust, accurate, and feasible: a prospective pilot study.

BACKGROUND: Augmented reality (AR) systems are currently being explored by a broad spectrum of industries, mainly for improving point-of-care access to data and images. Especially in surgery and especially for timely decisions in emergency cases, a fast and comprehensive access to images at the patient bedside is mandatory. Currently, imaging data are accessed at a distance from the patient both in time and space, i.e., at a specific workstation. Mobile technology and 3-dimensional (3D) visualization of radiological imaging data promise to overcome these restrictions by making bedside AR feasible. METHODS: In this project, AR was realized in a surgical setting by fusing a 3D-representation of structures of interest with live camera images on a tablet computer using marker-based registration. The intent of this study was to focus on a thorough evaluation of AR. Feasibility, robustness, and accuracy were thus evaluated consecutively in a phantom model and a porcine model. Additionally feasibility was evaluated in one male volunteer. RESULTS: In the phantom model (n = 10), AR visualization was feasible in 84% of the visualization space with high accuracy (mean reprojection error ± standard deviation (SD): 2.8 ± 2.7 mm; 95th percentile = 6.7 mm). In a porcine model (n = 5), AR visualization was feasible in 79% with high accuracy (mean reprojection error ± SD: 3.5 ± 3.0 mm; 95th percentile = 9.5 mm). Furthermore, AR was successfully used and proved feasible within a male volunteer. CONCLUSIONS: Mobile, real-time, and point-of-care AR for clinical purposes proved feasible, robust, and accurate in the phantom, animal, and single-trial human model shown in this study. Consequently, AR following similar implementation proved robust and accurate enough to be evaluated in clinical trials assessing accuracy, robustness in clinical reality, as well as integration into the clinical workflow. If these further studies prove successful, AR might revolutionize data access at patient bedside.

Validation of the mobile serious game application Touch Surgery™ for cognitive training and assessment of laparoscopic cholecystectomy.

BACKGROUND: Touch Surgery™ (TS) is a serious gaming application for cognitive task simulation and rehearsal of key steps in surgical procedures. The aim was to establish face, content, and construct validity of TS for laparoscopic cholecystectomy (LC). Furthermore, learning curves with TS and a virtual reality (VR) trainer were compared in a randomized trial. METHODS: The performance of medical students and general surgeons was compared for all three modules of LC in TS to establish construct validity. Questionnaires assessed face and content validity. For analysis of learning curves, students were randomized to train on VR or TS first, and then switched to the other training modality. Performance data were recorded. RESULTS: 54 Surgeons and 51 medical students completed the validation study. Surgeons outperformed students with TS: patient preparation (students = 45.0 ± 19.1%; surgeons = 57.3 ± 15.2%; p < 0.001), access and laparoscopy (students = 70.2 ± 10.9%; surgeons = 75.9 ± 9.7%; p = 0.008) and LC (students = 69.8 ± 12.4%; surgeons = 77.7 ± 9.6%; p < 0.001). Both groups agreed that TS was a highly useful and realistic application. 46 students were randomized for learning curve analysis. It took them 2-4 attempts to reach a 100% score with TS. Training with TS first did not improve students' performance on the VR trainer; however, students who trained with VR first scored significantly higher in module 3 of TS. CONCLUSION: 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.

Face validity of the pulsatile organ perfusion trainer for laparoscopic cholecystectomy.

BACKGROUND: The pulsatile organ perfusion (POP) trainer provides training of minimally invasive surgery (MIS) with real instruments and cadaveric organs. It provides training of full procedures with simulation of bleeding. Although widely used, the face validity has not yet been evaluated. This study aimed to establish face validity of the POP trainer for laparoscopic cholecystectomy (LC) and its usefulness compared with other training modalities. MATERIALS AND METHODS: During MIS courses, the participants (n = 52) used the POP trainer to perform LC. Face validity was assessed with questionnaires for realism and usefulness on a five-point Likert scale. Participants were divided into two groups: experts (n = 15) who had performed more than 50 laparoscopic procedures and novices (n = 37) with less than 50 procedures. Secondary aims included the ranking of training modalities, as well as exploration of their specific advantages and disadvantages. RESULTS: The POP trainer was found to be realistic (3.8 ± 0.9) and useful (4.6 ± 0.9). Differences between experts and novices were only found for "The training modality resembles reality" (3.1 ± 0.8 vs. 3.8 ± 0.7; p = 0.010), "The operation on the POP trainer is realistic" (3.4 ± 1.1 vs. 4.5 ± 0.8; p = 0.003), and "It would be desirable to have a POP trainer at my own hospital" (4.2 ± 1.1 vs. 4.8 ± 0.8; p = 0.040). In the ranking, the animal training (1.1 ± 0.3) placed first, the POP trainer (2.3 ± 0.9) second, and the VR trainer (2.8 ± 0.9) and box trainer (2.8 ± 1.1) third. The realistic simulation of animal training was named as an advantage most often, while the unrealistic simulation of the VR trainer was the most often named disadvantage. CONCLUSIONS: The POP trainer was rated a highly realistic and useful training modality with face validity for LC. Differences between experts and novices existed concerning realism and desirability. Future studies should evaluate the POP trainer for more advanced surgical procedures. The POP trainer widens the spectrum of modalities for training of MIS in a safe environment outside the operating room.

Development and validation of a sensor- and expert model-based training system for laparoscopic surgery: the iSurgeon.

INTRODUCTION: Training and assessment outside of the operating room is crucial for minimally invasive surgery due to steep learning curves. Thus, we have developed and validated the sensor- and expert model-based laparoscopic training system, the iSurgeon. MATERIALS: Participants of different experience levels (novice, intermediate, expert) performed four standardized laparoscopic knots. Instruments and surgeons' joint motions were tracked with an NDI Polaris camera and Microsoft Kinect v1. With frame-by-frame image analysis, the key steps of suturing and knot tying were identified and registered with motion data. Construct validity, concurrent validity, and test-retest reliability were analyzed. The Objective Structured Assessment of Technical Skills (OSATS) was used as the gold standard for concurrent validity. RESULTS: The system showed construct validity by discrimination between experience levels by parameters such as time (novice = 442.9 ± 238.5 s; intermediate = 190.1 ± 50.3 s; expert = 115.1 ± 29.1 s; p < 0.001), total path length (novice = 18,817 ± 10318 mm; intermediate = 9995 ± 3286 mm; expert = 7265 ± 2232 mm; p < 0.001), average speed (novice = 42.9 ± 8.3 mm/s; intermediate = 52.7 ± 11.2 mm/s; expert = 63.6 ± 12.9 mm/s; p < 0.001), angular path (novice = 20,573 ± 12,611°; intermediate = 8652 ± 2692°; expert = 5654 ± 1746°; p < 0.001), number of movements (novice = 2197 ± 1405; intermediate = 987 ± 367; expert = 743 ± 238; p < 0.001), number of movements per second (novice = 5.0 ± 1.4; intermediate = 5.2 ± 1.5; expert = 6.6 ± 1.6; p = 0.025), and joint angle range (for different axes and joints all p < 0.001). Concurrent validity of OSATS and iSurgeon parameters was established. Test-retest reliability was given for 7 out of 8 parameters. The key steps "wrapping the thread around the instrument" and "needle positioning" were most difficult to learn. CONCLUSION: 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.

Sequential learning of psychomotor and visuospatial skills for laparoscopic suturing and knot tying-a randomized controlled trial "The Shoebox Study" DRKS00008668.

PURPOSE: Learning curves for minimally invasive surgery are prolonged since psychomotor skills and visuospatial orientation differ from open surgery and must be learned. This study explored potential advantages of sequential learning of psychomotor and visuospatial skills for laparoscopic suturing and knot tying compared to simultaneous learning. METHODS: Laparoscopy-naïve medical students were randomized into a sequential learning group (SEQ) or a simultaneous learning group (SIM). SEQ (n = 28) trained on a shoebox with direct 3D view before proceeding on a box trainer with 2D laparoscopic view. SIM (n = 25) trained solely on a box trainer with 2D laparoscopic view. Training time and number of attempts needed were recorded until a clearly defined proficiency level was reached. RESULTS: Groups were not different in total training time (SEQ 5868.7 ± 2857.2 s; SIM 5647.1 ± 2244.8 s; p = 0.754) and number of attempts to achieve proficiency in their training (SEQ 44.0 ± 17.7; SIM 36.8 ± 15.6; p = 0.123). SEQ needed less training time on the box trainer with 2D laparoscopic view than did SIM (SEQ 4170.9 ± 2350.8 s; SIM 5647.1 ± 2244.8 s; p = 0.024), while the number of attempts here was not different (SEQ 29.9 ± 14.1; SIM 36.8 ± 15.6; p = 0.097). SEQ was faster in the first attempts on the shoebox (281.9 ± 113.1 s) and box trainer (270.4 ± 133.1 s) compared to the first attempt of SIM on the box trainer (579.4 ± 323.8 s) (p < 0.001). CONCLUSION: In the present study, SEQ was faster than SIM at the beginning of the learning curve. SEQ did not reduce the total training time needed to reach an ambitious proficiency level. However, SEQ needed less training on the box trainer; thus, laparoscopic experience can be gained to a certain extent with a simple shoebox.