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Author(s):  
Andrea Moglia ◽  
Luca Morelli ◽  
Roberto D’Ischia ◽  
Lorenzo Maria Fatucchi ◽  
Valentina Pucci ◽  
...  

Abstract Background Artificial intelligence (AI) has the potential to enhance patient safety in surgery, and all its aspects, including education and training, will derive considerable benefit from AI. In the present study, deep-learning models were used to predict the rates of proficiency acquisition in robot-assisted surgery (RAS), thereby providing surgical programs directors information on the levels of the innate ability of trainees to facilitate the implementation of flexible personalized training. Methods 176 medical students, without prior experience with surgical simulators, were trained to reach proficiency in five tasks on a virtual simulator for RAS. Ensemble deep neural networks (DNN) models were developed and compared with other ensemble AI algorithms, i.e., random forests and gradient boosted regression trees (GBRT). Results DNN models achieved a higher accuracy than random forests and GBRT in predicting time to proficiency, 0.84 vs. 0.70 and 0.77, respectively (Peg board 2), 0.83 vs. 0.79 and 0.78 (Ring walk 2), 0.81 vs 0.81 and 0.80 (Match board 1), 0.79 vs. 0.75 and 0.71 (Ring and rail 2), and 0.87 vs. 0.86 and 0.84 (Thread the rings 2). Ensemble DNN models outperformed random forests and GBRT in predicting number of attempts to proficiency, with an accuracy of 0.87 vs. 0.86 and 0.83, respectively (Peg board 2), 0.89 vs. 0.88 and 0.89 (Ring walk 2), 0.91 vs. 0.89 and 0.89 (Match board 1), 0.89 vs. 0.87 and 0.83 (Ring and rail 2), and 0.96 vs. 0.94 and 0.94 (Thread the rings 2). Conclusions Ensemble DNN models can identify at an early stage the acquisition rates of surgical technical proficiency of trainees and identify those struggling to reach the required expected proficiency level.


2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Rohan Bhimani ◽  
Reza Shahriarirad ◽  
Keivan Ranjbar ◽  
Amirhossein Erfani ◽  
Soheil Ashkani-Esfahani

Abstract Background Transportal (TP) and all-inside techniques (AIT) are the most commonly used anterior cruciate ligament (ACL) reconstruction procedures in current clinical practice. However, there is an ongoing debate over which procedure is superior. Therefore, the purpose of this systematic review was to evaluate and compare the clinical outcomes and complications of these two techniques to propose recommendations for future application. Our primary hypothesis was that AIT is a superior ACLR technique compared to TP. Methods A systematic literature review, using PRISMA guidelines, was conducted using PubMed, Medline, Google Scholar, and EMBASE, up to February 2021 to identify studies focusing on AIT and TP techniques of ACL reconstruction. We excluded animal experiments, cadaveric studies, retrospective studies, case reports, technical notes, and studies without quantitative data. Patients’ characteristics, surgical technical features, along with postoperative follow-up and complications were extracted and reported accordingly. Methodological quality of the included studies was assessed using the Modified Coleman Methodology Score (MCMS). Results A total of 44 studies were selected for this review, of which four were comparative studies. A total of 923 patients underwent AIT and 1678 patients underwent the TP technique for ACLR. A single semitendinosus graft was commonly used in the AIT compard to combined semitendinosus and gracilis graft in the TP group. The postoperative increase in International Knee Documentation Committee (IKDC), Lysholm, KT-1000, and Short Form-12 (physical and mental) scores were similar in the AIT group and the TP group. Contrastingly, the VAS pain score was significantly lower in the AIT group compared to the TP group. Furthermore, the pooled complication rates from all studies were similar between the two groups (AIT: 54 patients, 8.26% vs. PT: 55 patients, 6.62%). However, the four studies that prospectively compared AIT and TP techniques showed lesser complications in the AIT group than the TP group. Conclusion Since the future trend in orthopedic surgery is toward less invasive and patients’ satisfaction with good outcomes, AIT is a good alternative method considering preserving bony tissue and gracilis tendon with less post-operative pain, along with more knee flexor strength and equal outcomes compared to conventional ACL reconstruction surgery. Level of Evidence II.


2021 ◽  
Vol 108 (Supplement_9) ◽  
Author(s):  
Priyantha Siriwardana ◽  
Bruno Lorenzi ◽  
Mohammad Qamruddin ◽  
Sritharan Kadirkamanathan

Abstract Background Heller’s cardiomyotomy (HC) using a computer-enhanced (robotic) laparoscopic platform allows for a more precise dissection. This is achieved by utilizing the superior optics of a 3D camera and greater degrees of freedom provided by robotic instrumentation. Our aim was to assess short to long term outcomes in terms of mucosal integrity, hospital stay and symptom improvement and quality of life. Methods A retrospective review of prospectively collected data was performed of patients who underwent robotic HC between July 2009- May 2021. HC was performed using a Da Vinci robot S and Xi (Intuitive Surgical Inc.) with 4 laparoscopic ports and liver retractor. Anterior mobilization of the oesophagus was performed leaving the posterior component of phreno-oesophageal ligament intact. A longitudinal myotomy was made extending into the proximal stomach. An anti-reflux procedure (ARP) was not routinely performed. Data collected including demography, Eckardt symptom score, Quality of Life (QoL) with SF-36, surgical technical data and surgical outcome (post-op morbidity, mortality, hospital stay). Results Fifty-seven patients underwent surgery (28 males). Median age was 46 years (18-71). Two had surgery for recurrent dysphagia following laparoscopic HC elsewhere. Median length of myotomy was 8cm (5-11). No mucosal breaches were identified at surgery, but one had postoperative leak. Median length of hospital stay was 2 days (1-148). One had chest infection and another DVT. Median follow-up was 61 months (2- 86). There was no mortality. Three patients (5%) needed oesophageal dilatation during follow-up. There was a significant improvement in Eckardt score from 10 (9-12) to 2 (0-6), and in all components of QoL (p < 0.05). Conclusions Heller’s myotomy can be performed very precisely using a Da Vinci Robot. It minimises the risk of mucosal breach reflecting in the low leak rate. No patient had developed troublesome reflux which may well be due to the preservation of the posterior component of the phreno-oesophageal ligament. It also improves symptoms and quality of life for many years. Robotic HC may become the standard treatment for achalasia in the very near future.


Author(s):  
Sonia Guerin ◽  
Arnaud Huaulmé ◽  
Vincent Lavoue ◽  
Pierre Jannin ◽  
Krystel Nyangoh Timoh

2021 ◽  
Vol 2021 ◽  
pp. 1-4
Author(s):  
Kyriacos Papadopoulos ◽  
Panayiotis Avraamides

Saphenous vein graft aneurysms (SVGAs) occur as a rare complication of coronary artery bypass graft but increases the risk of morbidity and mortality. Atherosclerosis is considered to be the most common cause of saphenous vein graft aneurysms. Other etiologies include infections, varicosities of vein grafts, and surgical technical issues. These aneurysms usually present as an incidental finding of a mediastinal or cardiac mass on chest radiograph. Symptomatic aneurysms may present with a wide variety of clinical manifestations such as chest pain/angina, shortness of breath, and myocardial infarction. Treatment options of SVG aneurysms include surgery, percutaneous intervention (including vascular plugs, covered stents, and embolization coils), and conservative management. Herein, we describe a case of a saphenous vein graft aneurysm that developed after percutaneous intervention, which has never been described, to our knowledge, in the previous literature. The aneurysm was treated with polytetrafluoroethylene covered stent implantation.


2021 ◽  
pp. 103952
Author(s):  
Pablo Castillo-Segura ◽  
Carmen Fernández-Panadero ◽  
Carlos Alario-Hoyos ◽  
Pedro J. Muñoz-Merino ◽  
Carlos Delgado Kloos

2021 ◽  
Vol 108 (Supplement_7) ◽  
Author(s):  
Recai Yilmaz ◽  
Alexander Winkler-Schwartz ◽  
Aiden Reich ◽  
Rolando Del Maestro

Abstract Aims Excellent surgical technical skills are of paramount importance to perform surgical procedures, safely and efficiently. Virtual reality surgical simulators can both simulate real operations while providing standardized, risk-free surgical hands-on experience. The integration of AI (artificial intelligence) and virtual reality simulators provides opportunities to carry out comprehensive continuous assessments of surgical performance. We developed and tested a deep learning algorithm which can continuously monitor and assess surgical bimanual performance on virtual reality surgical simulators. Methods Fifty participants from four expertise levels (14 experts/neurosurgeons, 14 senior residents, 10 junior residents, 12 medical students) performed a simulated subpial tumor resection 5 times and a complex simulated brain tumor operation once on the NeuroVR platform. Participants were asked to remove the tumors completely while minimizing bleeding and damage to surrounding tissues employing a simulated ultrasonic aspirator and bipolar forceps. A deep neural network continually tracked the surgical performance utilizing 16 performance metrics generated every 0.2-seconds. Results The deep neural network was successfully trained using neurosurgeons and medical students’ data, learning the composites of expertise comparing high and lower skill levels. The trained algorithm was able to score the technical skills of individuals continuously at 0.2-second intervals. Statistically significant differences in average scores were identified between the 4 groups. Conclusions AI-powered surgical simulators provide continuous assessment of bimanual technical skills during surgery which may further define the composites necessary to train surgical expertise. To our knowledge, this is the first attempt in surgery to continuously assess surgical technical skills using deep learning.


2021 ◽  
Vol 14 (9) ◽  
pp. e245635
Author(s):  
Neil Robert Lowrie ◽  
Monica Jane Londahl ◽  
Konrad Klaus Richter

Non-parasitic splenic cysts are rare and are seldom diagnosed outside the paediatric surgical practice. Giant true primary epithelial cysts greater than 14 cm in diameter are even rarer. Laparoscopic surgery is preferable; however, bleeding, splenectomy and recurrence are recognised risks. Here, we report a young female patient with a 21 cm symptomatic primary splenic cyst. The patient underwent a spleen-preserving laparoscopy and was followed up for 2 years when she had an MRI of the abdomen. Surgical, technical and perioperative treatment aspects are discussed here, in the context of the current literature.


2021 ◽  
Vol 206 (Supplement 3) ◽  
Author(s):  
Daniel I. Sanford ◽  
Balint Der ◽  
Ryan Hakim ◽  
Runzhuo Ma ◽  
Erik Vanstrum ◽  
...  

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