Jean Nehme

The use of multimedia consent programs for surgical procedures: a systematic review.

Objective. To compare multimedia and standard consent, in respect to patient comprehension, anxiety, and satisfaction, for various surgical/interventional procedures. Data sources. Electronic searches of PubMed, MEDLINE, Ovid, Embase, and Google Scholar were performed. Relevant articles were assessed by 2 independent reviewers. Study selection. Comparative (randomized and nonrandomized control trials) studies of multimedia and standard consent for a variety of surgical/interventional procedures were included. Studies had to report on at least one of the outcome measures. Data extraction. Studies were reviewed by 2 independent investigators. The first investigator extracted all relevant data, and consensus of each extraction was performed by a second investigator to verify the data. Conclusion. Overall, this review suggests that the use of multimedia as an adjunct to conventional consent appears to improve patient comprehension. Multimedia leads to high patient satisfaction in terms of feasibility, ease of use, and availability of information. There is no conclusive evidence demonstrating a significant reduction in preoperative anxiety.

Surgical smartphone applications across different platforms: their evolution, uses, and users.

Introduction. There are a vast array of smartphone applications that could benefit both surgeons and their patients. To review and identify all relevant surgical smartphone applications available for the Apple iPhone iOS and Google Android platform based on their user group and subspecialty for which they were designed. Method. Both the literature using PubMed and Google Scholar were searched using the following terms: application

A randomized controlled trial evaluating endoscopic and laparoscopic training in skills transfer for novices performing a simulated NOTES task.

, smartphone

Endoscopic Horizon Stabilization in Natural Orifice Translumenal Endoscopic Surgery A Randomized Controlled Trial

, app

Can surgical simulation be used to train detection and classification of neural networks

, app*, surgery, surgical, surg*, general surgery, general surg*, bariatric

Touch Surgery Supporting the Plastic Surgical Community

, urology and plastic surgery, ortho*, orthop(a)edic, cardiac surgery, cardiothoracic, neurosurgery, and ophthalmology. Results. The search yielded 38 articles of which 23 were eligible. Each of the key specialties was searched in the Apple iTunes App Store for iPhone iOS and the Google Play Android application store. In total, there were 621 surgical applications for Apple iPhone iOS and 97 identified on Android’s Google Play. There has been a 9-fold increase in the number of surgical applications available for the Apple iPhone iOS from 2009 to 2012. Of these applications there were 126 dedicated to plastic surgery, 79 to orthopedics, 41 to neurosurgical, 180 to general surgery, 36 to cardiac surgery, 121 to ophthalmology, and 44 to urology. There was a wide range of applications ranging from simple flashcards to be used for revision to virtual surgery applications that provided surgical exposure and familiarization with common operative procedures. Conclusions. Despite the plethora of surgical applications available for smartphones, there is no taxonomy for medical applications. Only 12% were affiliated with an academic institution or association, which highlights the need for greater regulation of surgical applications.

Fat harvesting: spare your thumb, don't spoil the fat.

Background. The NOSCAR white paper lists training as an important step to the safe clinical application of natural orifice translumenal endoscopic surgery (NOTES). The aim of this randomized controlled trial was to evaluate whether training novices in either a laparoscopic or endoscopic simulator curriculum would affect performance in a NOTES simulator task. Methods. A total of 30 third-year medical undergraduates were recruited. They were randomized to 3 groups: no training (control; n = 10), endoscopy training on a validated colonoscopy simulator protocol (n = 10), and training on a validated laparoscopy simulator curriculum (n = 10). All participants subsequently completed a simulated NOTES task, consisting of 7 steps, on the ELITE (endoscopic-laparoscopic interdisciplinary training entity) model. Performance was assessed as time taken to complete individual steps, overall task time, and number of errors. Results. The endoscopy group was significantly faster than the control group at accessing the peritoneal cavity through the gastric incision (median 27 vs 78 s; P = .015), applying diathermy to the base of the appendix (median 103.5 vs 173 s; P = .014), and navigating to the gallbladder (median 76 vs 169.5 s; P = .049). Endoscopy participants completed the full NOTES procedure in a shorter time than the laparoscopy group (median 863 vs 2074 s; P < .001). Conclusion. This study highlights the importance of endoscopic training for a simulated NOTES task that involves both navigation and resection with operative maneuvers. Although laparoscopic training confers some benefit for operative steps such as applying diathermy to the gallbladder fossa, this was not as beneficial as training in endoscopy.

DeepPhase: Surgical Phase Recognition in CATARACTS Videos

Background. Spatial orientation in natural orifice translumenal endoscopic surgery (NOTES) has been identified as a potential barrier to clinical application. We aim to evaluate a triaxial inertial sensor and software that automatically corrects any movements on the roll axis of the flexible endoscope, allowing for stabilization of the image horizon during NOTES operations in a randomized controlled trial. Methods. A total of 18 participants (11 surgeons/7 gastroenterologists) performed a transgastric task in the ELITE simulator, which included navigation to the appendix and gallbladder, diathermy of the appendix base and gallbladder fossa, and clipping of the cystic duct using a single-channel gastroscope. Each participant performed the task twice with randomization to horizon stabilization occurring at the second attempt. The primary end point was change in overall performance (time taken and errors made) between the first and second attempt, and secondary end points were absolute performances in the second attempt and subjective evaluation. Results. Without horizon stabilization, there was a median improvement of 42.4% in time taken and 38% in number of errors made from the first to the second attempt; however, with the software turned on, there was a statistically significant deterioration of 4.9% (P = .038) in time taken and an increase in errors made of 183% (P = ns). Conclusions. Although the software corrects the view to that preferred during surgery, the endoscopic control mechanism as well as the exit point of the instrument are altered in this process, leading to a deterioration of overall performance. Potential solutions include deploying intermittent horizon stabilization or using a robotic interface to achieve fully aligned perceptual-motor control.

Teaching millennial surgeons

Computer-assisted interventions (CAI) aim to increase the effectiveness, precision and repeatability of procedures to improve surgical outcomes. The presence and motion of surgical tools is a key information input for CAI surgical phase recognition algorithms. Vision-based tool detection and recognition approaches are an attractive solution and can be designed to take advantage of the powerful deep learning paradigm that is rapidly advancing image recognition and classification. The challenge for such algorithms is the availability and quality of labelled data used for training. In this Letter, surgical simulation is used to train tool detection and segmentation based on deep convolutional neural networks and generative adversarial networks. The authors experiment with two network architectures for image segmentation in tool classes commonly encountered during cataract surgery. A commercially-available simulator is used to create a simulated cataract dataset for training models prior to performing transfer learning on real surgical data. To the best of authors’ knowledge, this is the first attempt to train deep learning models for surgical instrument detection on simulated data while demonstrating promising results to generalise on real data. Results indicate that simulated data does have some potential for training advanced classification methods for CAI systems.

MRI-induced soft tissue pain: incidental finding of a 15-year-old foreign body

One of the Sir Harold Gillies first principles “thou shalt make a plan” shapes the mind-set and toolbox of any plastic and reconstructive surgeon. For surgeons in training, exposure to expert operative planning and cognitive decision making is essential to developing the competency of an independent surgeon. However, as a result of changes in working hours, financial constraints, and patient safety concerns, these opportunities are increasingly harder to come by. Furthermore, the plastic surgeon’s toolbox continues to expand with newer technologies resulting in a wider breadth of surgical techniques with slow dissemination to the wider surgical audience. Touch Surgery is a cognitive task simulation and rehearsal application freely available on mobile devices. Touch Surgery maps surgical procedures with expert surgeons, making surgical plans and simulations widely available to the surgical community. As a software solution that is accessible through touch screen devices, Touch Surgery is a scalable platform available to surgical users globally, and in less than 2 years, it has become the largest surgical community on mobile with over 1 million downloads. Touch Surgery builds on a process called cognitive task analysis, a method for obtaining sophisticated performance expertise for areas where many covert decisions are linked with complex overt actions.1 Using cognitive task analysis, Touch Surgery maps surgical procedures step by step combining the cognitive steps with a mapped anatomical virtual reality patient. This enables a surgical user to simulate, plan, and rehearse different procedures. Touch Surgery has an inbuilt assessment tool, which uses objective decision and precision metrics to evaluate knowledge of simulated procedures. This provides surgical users with immediate feedback and a record of their learning curve. In US residency programs (Harvard Orthopedics and Hopkins Orthopedics), individual residents share their scores with program directors and certificates of competence can be issued. This for the first time creates a data set that allows residents to demonstrate cognitive competence before they enter the operating room. A number of studies have evaluated the simulation and learning validity of Touch Surgery. Sugand et al2 have demonstrated Touch Surgery to have construct validity (the ability to identify between experts and novices), face validity (the impression of simulating the procedure), and content validity (the comparison to content to the true operation). Follow-up studies from the same group have shown learning curves of engaging with the content of the application and an improved understanding of the procedure.3 In a randomized controlled trial by Brewer et al,4 the team showed that training on Touch Surgery demonstrated a significant improvement over traditional textbook learning. Touch Surgery represents a tool that could make a significant difference to global surgical practice through facilitating dissemination of surgical techniques, approaches, and giving surgeons in training uncapped exposure to operative cases. Technological initiatives, such as Touch Surgery, mean that Sir Harold Gillies principles can be disseminated to a wider audience for better patient care and stand the test of time.