Meniscectomy is still a frequent orthopedic procedure: a pending need for education on the meniscus treatment possibilities.

PURPOSE: The purpose of this study was to evaluate the current status of education of polish surgeons in the subject of meniscus repair possibilities. The analysis of the possible correlations between the number of knee arthroscopy procedures performed by polish surgeons and their decision whether to remove or to repair the damaged meniscus has been performed. METHODS: Two-hundred and five registered orthopedic surgeons took part in surveys. The questionnaire contained the description of 20 patients with different types of meniscus damage and three questions concerning the experience in knee arthroscopy (two questions) and a choice of the treatment method (one question). Comparisons were made between knee arthroscopy experts (> 100 arthroscopies performed per year) and non-experts (≤ 100 cases). RESULTS: The questionnaire was completed by 194 knee surgeons from Poland with different levels in knee arthroscopy experience. For most cases, experts and non-experts agreed on the meniscus treatment method. Statistically significant differences in the recommended treatment between experts and non-experts were observed in 4 cases, where experts decided to repair the damage rather than to perform the meniscectomy. CONCLUSIONS: Meniscectomy remains a frequent orthopedic procedure, despite meniscal sparing having been advocated for several decades now and despite the existence of meniscus repair technique which gives good clinical outcomes-augmentation of the damaged meniscus with a collagen membrane. Polish surgeons still need education on the meniscus treatment possibilities. LEVEL OF EVIDENCE: V.

Effect of Surgical Expertise on Biomechanical Properties of Sutures After Abdominal Wall Closure.

BACKGROUND: Despite preventive methods and careful surgical technique, surgical site infection and incisional hernias are of main concern after the closure of surgical incisions and keep haunting abdominal wall wound healing. The aim of this study is to find how surgical expertise level modifies biomechanical properties of sutures commonly used in abdominal wall fascial closure (polypropylene, polyglactin 910, polydioxanone). MATERIALS AND METHODS: Surgery residents with different experience levels performed abdominal wall fascial closure in swine models with the previously mentioned suture materials. A standardized technique was used. Sutures were removed, and a tensile stress test was performed on the removed sutures. A total of 81 abdominal fascial closures were achieved. Time, extension, maximum tensile force (Ftmax), and maximum stress were measured and analyzed. RESULTS: The results of the polydioxanone stress test present a trend in three variables: extension, tensile force, and stress. The trend shows higher medians in the expert group and lower medians in the novice group. While using polypropylene sutures, medians in the expert group are the highest; however, a trend is not observed. Polyglactin 910 sutures have nonspecific behavior among the different experience groups and variables. Polypropylene is the material with the lowest Ftmax tested and fails at 42.64 (IQR 40.98-44.89) N. Regarding the elastic properties of the material, polyglactin demonstrates the least extension of all sutures tested, with a 14 (IQR 13.33-14.83) mm extension. This study demonstrates that polydioxanone has a superior Ftmax compared with polypropylene and has a superior extension at failure properties compared with polyglactin, confirming that polydioxanone could be the suture of choice used for abdominal wall fascial closure. CONCLUSIONS: Study results do not show statistically significant differences regarding the impact of the experience level of different general surgery residents in the biomechanical properties of sutures used in abdominal wall fascial closure.

Clinical practice and postoperative rehabilitation after knee arthroscopy vary according to surgeons' expertise: a survey among polish arthroscopy society members.

BACKGROUND: Meniscus repair is a challenging task in knee arthroscopy. Currently, there are a variety of arthroscopic methods available for meniscus repair. The purpose of this study was to determine a consensus in meniscus tear treatment in the environment of Polish orthopaedists. METHODS: A total of 205 registered orthopaedic surgeons participated in the surveys. The survey consisted of 35 questions regarding general arthroscopy and postoperative management, including physicians' level of expertise, anaesthesia, postoperative treatment, rehabilitation and procedures performed. Comparisons were made between knee arthroscopy experts (> 100 arthroscopies performed per year) and non-experts (≤ 100 cases) on aspects of patient care. RESULTS: The most important finding of this study was the agreement among almost all aspects of the knee arthroscopy approach. Consensus among Polish surgeons was noticed in choosing regional anaesthesia for knee arthroscopy, the lack of need for knee braces and knee medications, the of use of LMW heparin for thromboprophylaxis, 1-2 days of hospitalization, the recommendation of rehabilitation and the use of magnetic resonance as a diagnostic test for meniscus damage. Surgical expertise was significantly associated with the performance of meniscus suture procedures (p = 0.009). Experts recommended starting rehabilitation on the day of surgery (p = 0.007) and were more likely to use objective physical tests (p = 0.003). Non-expert surgeons recommended a longer period from meniscus suture to full-range knee motion (p = 0.001) and admitted that patient age does matter for meniscus repair qualification (p = 0.002). CONCLUSIONS: There is consensus among almost all issues of meniscus tear treatment in the environment of Polish orthopaedists; however, the issues of rehabilitation and the use of advanced meniscus repair techniques are associated with surgical expertise.

Survey results from an international hip course: comparison between experts and non-experts on hip arthroscopy clinical practice and post-operative rehabilitation.

PURPOSE: The purpose of this study was to compare the clinical practices between expert and non-expert arthroscopy hip surgeons. METHODS: Registered orthopedic surgeons completed anonymous surveys during a hip arthroscopy meeting. The survey included 60 questions on physician's level of expertise, surgical anesthesia, procedures performed, hospital stay, pain control, rehabilitation and socioeconomic parameters, and the results are presented. Comparisons were made between hip arthroscopy experts (> 500 cases performed) and non-experts (≤ 500 cases performed) on aspects of patient care. RESULTS: Forty-eight (74%) surgeons responded. Forty-four questionnaires were filled out completely. There were no significant differences in recommendations between 15 (34%) hip arthroscopy experts and 29 (66%) non-experts on hip capsular management and cartilage repair techniques, use of antithrombotic prophylaxis and opioid analgesics, time of rehabilitation initiation and patient compliance factors, use of hip brace and CPM, and patient evaluation to return to sports following surgery. Surgical expertise was significantly associated with the performance of hip labral reconstruction (p = 0.016), subspine decompression (p = 0.039) and recommendation of a longer period of restricted weight bearing following the performance of microfractures (p = 0.011). There were no significant differences in clinical practice between surgeons who performed hip arthroscopy exclusively versus those who did not. CONCLUSIONS: Hip arthroscopy is a relatively new field, and clinical practice may vary among physicians based on the surgical expertise. In this study, hip arthroscopy experts agree with non-experts on most aspects of patient care. Surgical expertise was associated with performance of advanced techniques and recommendation of longer period of restricted weight bearing following performance of microfractures. This study highlights different care patterns that need to be investigated to determine which treatment results in improved patient care. LEVEL OF EVIDENCE: V.

Systematic Surgical Assessment of Deceased-Donor Kidneys as a Predictor of Short-Term Transplant Outcomes.

BACKGROUND: Short-term kidney graft dysfunction is correlated with complications and it is associated with a decreased long-term survival; therefore, a scoring system to predict short-term renal transplant outcomes is warranted. AIM: The aim of this study is to quantify the impression of the organ procurement surgeon in correlation with the following kidney transplant outcomes: immediate graft function (IGF), delayed graft function (DGF), and primary nonfunction (PNF). Results are compared to factors associated with the 1-year outcome. METHODS: A regional prospective pilot study was performed using deceased-donor organ assessment forms to be filled out by procurement surgeons after procurement. Data were gathered on kidney temperature, perfusion, anatomy, atherosclerosis, and overall quality. RESULTS: Included were 90 donors who donated 178 kidneys, 166 of which were transplanted. Variables that were significantly more prevalent in the DGF-or-PNF group (n = 65) are: large kidney size (length, p = 0.008; width, p = 0.036), poor perfusion quality (p = 0.037), lower diuresis (p = 0.039), fewer hypotensive episodes (p = 0.003), and donation-after-circulatory-death donors (p = 0.017). Multivariable analysis showed that perfusion quality and kidney width significantly predicted the short-term outcome. However multivariable analysis of long-term outcomes showed that the first measured donor creatinine, kidney donor risk index, IGF vs. DGF+PNG, and kidney length predicted outcomes. CONCLUSIONS: Results show that short-term graft function and 1-year graft function indeed are influenced by different variables. DGF and PNF occur more frequently in kidneys with poor perfusion and in larger kidneys. A plausible explanation for this is that these kidneys might be insufficiently washed out, or even congested, which may predispose to DGF. These kidneys would probably benefit most from reconditioning strategies, such as machine perfusion. A scoring system including these variables might aid in decision-making towards allocation and potential reconditioning strategies.

Unveiling surgical expertise through machine learning in a novel VR/AR spinal simulator: A multilayered approach using transfer learning and connection weights analysis.

BACKGROUND: Virtual and augmented reality surgical simulators, integrated with machine learning, are becoming essential for training psychomotor skills, and analyzing surgical performance. Despite the promise of methods like the Connection Weights Algorithm, the small sample sizes (small number of participants (N)) typical of these trials challenge the generalizability and robustness of models. Approaches like data augmentation and transfer learning from models trained on similar surgical tasks address these limitations. OBJECTIVE: To demonstrate the efficacy of artificial neural network and transfer learning algorithms in evaluating virtual surgical performances, applied to a simulated oblique lateral lumbar interbody fusion technique in an augmented and virtual reality simulator. DESIGN: The study developed and integrated artificial neural network algorithms within a novel simulator platform, using data from the simulated tasks to generate 276 performance metrics across motion, safety, and efficiency. Innovatively, it applies transfer learning from a pre-trained ANN model developed for a similar spinal simulator, enhancing the training process, and addressing the challenge of small datasets. SETTING: Musculoskeletal Biomechanics Research Lab; Neurosurgical Simulation and Artificial Intelligence Learning Centre, McGill University, Montreal, Canada. PARTICIPANTS: Twenty-seven participants divided into 3 groups: 9 post-residents, 6 senior and 12 junior residents. RESULTS: Two models, a stand-alone model trained from scratch and another leveraging transfer learning, were trained on nine selected surgical metrics achieving 75 % and 87.5 % testing accuracy respectively. CONCLUSIONS: This study presents a novel blueprint for addressing limited datasets in surgical simulations through the strategic use of transfer learning and data augmentation. It also evaluates and reinforces the application of the Connection Weights Algorithm from our previous publication. Together, these methodologies not only enhance the precision of performance classification but also advance the validation of surgical training platforms.

Enhancing surgical performance in cardiothoracic surgery with innovations from computer vision and artificial intelligence: a narrative review.

When technical requirements are high, and patient outcomes are critical, opportunities for monitoring and improving surgical skills via objective motion analysis feedback may be particularly beneficial. This narrative review synthesises work on technical and non-technical surgical skills, collaborative task performance, and pose estimation to illustrate new opportunities to advance cardiothoracic surgical performance with innovations from computer vision and artificial intelligence. These technological innovations are critically evaluated in terms of the benefits they could offer the cardiothoracic surgical community, and any barriers to the uptake of the technology are elaborated upon. Like some other specialities, cardiothoracic surgery has relatively few opportunities to benefit from tools with data capture technology embedded within them (as is possible with robotic-assisted laparoscopic surgery, for example). In such cases, pose estimation techniques that allow for movement tracking across a conventional operating field without using specialist equipment or markers offer considerable potential. With video data from either simulated or real surgical procedures, these tools can (1) provide insight into the development of expertise and surgical performance over a surgeon's career, (2) provide feedback to trainee surgeons regarding areas for improvement, (3) provide the opportunity to investigate what aspects of skill may be linked to patient outcomes which can (4) inform the aspects of surgical skill which should be focused on within training or mentoring programmes. Classifier or assessment algorithms that use artificial intelligence to 'learn' what expertise is from expert surgical evaluators could further assist educators in determining if trainees meet competency thresholds. With collaborative efforts between surgical teams, medical institutions, computer scientists and researchers to ensure this technology is developed with usability and ethics in mind, the developed feedback tools could improve cardiothoracic surgical practice in a data-driven way.

Does Surgeon Level of Expertise Correlate with Patient Outcomes?

Background It is difficult to evaluate the results of surgical techniques as there is inherent variability between surgeons in regard to experience, skill level, and knowledge. Tang suggested a classification system in 2009 in an attempt to standardize surgeon level of expertise, with categories ranging from nonspecialist (Level I) to expert (Level V). This epidemiological analysis of all articles citing Tang's original paper examines if a surgeon's self-reported level of expertise correlates with outcomes and evaluates whether the current definition of Tang level is sufficient to account for expertise bias. Methods In May 2021, all articles citing Tang level of expertise were identified ( N = 222). Articles were included if they described a novel technique and provided author(s)' levels ( n = 205). Statistical analysis was conducted, and p -values less than 0.05 were considered significant. Results The most common specialties reporting Tang level of expertise were orthopaedic surgery (82.9%) and plastic surgery (15.5%). The most common subspecialty was hand surgery. 2020 was the year with the most studies reporting level of expertise (31.7%), followed by 2021 (20.0%) and 2019 (17.1%). The majority of studies (80.5%) reported positive results with their technique, and of these, 63.3% were statistically significant. Level of expertise was not significantly associated with a doctoral degree, type of residency completed, fellowship completion, hand fellowship, author sex, study type, or result significance. Discussion The current Tang classification is both underreported and incomplete in its present state. To account for expertise bias, we recommend all authors report Tang level when describing surgical techniques. Studies with multiple authors should explicitly state the level of each author, as well as a weighted average accounting for the total contribution of each individual.

Neuromonitoring Correlates of Expertise Level in Surgical Performers: A Systematic Review.

Surgical expertise does not have a clear definition and is often culturally associated with power, authority, prestige, and case number rather than more objective proxies of excellence. Multiple models of expertise progression have been proposed including the Dreyfus model, however, they all currently require subjective evaluation of skill. Recently, efforts have been made to improve the ways in which surgical excellence is measured and expertise is defined using artificial intelligence, video recordings, and accelerometers. However, these aforementioned methods of assessment are still subjective or indirect proxies of expertise, thus uncovering the neural mechanisms that differentiate expert surgeons from trainees may enhance the objectivity of surgical expertise validation. In fact, some researchers have already suggested that their neural imaging-based expertise classification methods outperform currently used methods of surgical skill certification such as the Fundamentals of Laparoscopic Surgery (FLS) scores. Such imaging biomarkers would not only help better identify the highest performing surgeons, but could also improve residency programs by providing more objective, evidence-based feedback and developmental milestones for those in training and perhaps act as a marker of surgical potential in medical students. Despite the potential advantages of using neural imaging in the assessment of surgical expertise, this field of research remains in its infancy. This systematic review identifies studies that have applied neuromonitoring in assessing surgical skill across levels of expertise. The goals of this review are to identify (1) the strongest neural indicators of surgical expertise, (2) the limitations of the current literature on this subject, (3) the most sensible future directions for further study. We found substantial evidence that surgical expertise can be delineated by differential activation and connectivity in the prefrontal cortex (PFC) across multiple task and neuroimaging modalities. Specifically, novices tend to have greater PFC activation than experts under standard conditions in bimanual and decision-making tasks. However, under high temporal demand tasks, experts had increased PFC activation whereas novices had decreased PFC activation. Common limitations uncovered in this review were that task difficulty was often insufficient to delineate between residents and attending. Moreover, attending level involvement was also low in multiple studies which may also have contributed to this issue. Most studies did not analyze the ability of their neuromonitoring findings to accurately classify subjects by level of expertise. Finally, the predominance of fNIRS as the neuromonitoring modality limits our ability to uncover the neural correlates of surgical expertise in non-cortical brain regions. Future studies should first strive to address these limitations. In the longer term, longitudinal within-subjects design over the course of a residency or even a career will also advance the field. Although logistically arduous, such studies would likely be most beneficial in demonstrating effects of increasing surgical expertise on regional brain activation and inter-region connectivity.

Characterizing robotic surgical expertise: An exploratory study of neural activation during mental imagery of robotic suturing.

BACKGROUND: Mental imagery (MI) aids skill acquisition, however, it is unclear to what extend MI is used by experienced surgeons. The purpose of this study was to assess differences in MI of participants with varying surgical expertise in robotic surgery. METHODS: Students, residents, and surgeons completed the Mental Imagery Questionnaire to assess MI for robotic suturing. Participants then completed robotic simulator tasks, and imagined performing robotic suturing while being assessed with electroencephalogram (EEG). RESULTS: Attending surgeons reported higher MI for robotic suturing, and EEG revealed higher neural activation during imagery of robotic suturing than other groups. CONCLUSIONS: Experienced surgeons displayed higher MI ability for robotic suturing, and displayed higher cortical activity in the frontal and parietal areas of the brain, which is associated with more advanced motor imagery. MI appears to be a component of robotic surgery expertise.

Utilizing a multilayer perceptron artificial neural network to assess a virtual reality surgical procedure.

BACKGROUND: Virtual reality surgical simulators are a safe and efficient technology for the assessment and training of surgical skills. Simulators allow trainees to improve specific surgical techniques in risk-free environments. Recently, machine learning has been coupled to simulators to classify performance. However, most studies fail to extract meaningful observations behind the classifications and the impact of specific surgical metrics on the performance. One benefit from integrating machine learning algorithms, such as Artificial Neural Networks, to simulators is the ability to extract novel insights into the composites of the surgical performance that differentiate levels of expertise. OBJECTIVE: This study aims to demonstrate the benefits of artificial neural network algorithms in assessing and analyzing virtual surgical performances. This study applies the algorithm on a virtual reality simulated annulus incision task during an anterior cervical discectomy and fusion scenario. DESIGN: An artificial neural network algorithm was developed and integrated. Participants performed the simulated surgical procedure on the Sim-Ortho simulator. Data extracted from the annulus incision task were extracted to generate 157 surgical performance metrics that spanned three categories (motion, safety, and efficiency). SETTING: Musculoskeletal Biomechanics Research Lab; Neurosurgical Simulation and Artificial Intelligence Learning Center, McGill University, Montreal, Canada. PARTICIPANTS: Twenty-three participants were recruited and divided into 3 groups: 11 post-residents, 5 senior and 7 junior residents. RESULTS: An artificial neural network model was trained on nine selected surgical metrics, spanning all three categories and achieved 80% testing accuracy. CONCLUSIONS: This study outlines the benefits of integrating artificial neural networks to virtual reality surgical simulators in understanding composites of expertise performance.

Predicting the quality of surgical exposure using spatial and procedural features from laparoscopic videos.

PURPOSE : Evaluating the quality of surgical procedures is a major concern in minimally invasive surgeries. We propose a bottom-up approach based on the study of Sleeve Gastrectomy procedures, for which we analyze what we assume to be an important indicator of the surgical expertise: the exposure of the surgical scene. We first aim at predicting this indicator with features extracted from the laparoscopic video feed, and second to analyze how the extracted features describing the surgical practice influence this indicator. METHOD : Twenty-nine patients underwent Sleeve Gastrectomy performed by two confirmed surgeons in a monocentric study. Features were extracted from spatial and procedural annotations of the videos, and an expert surgeon evaluated the quality of the surgical exposure at specific instants. The features were used as input of a classifier (linear discriminant analysis followed by a support vector machine) to predict the expertise indicator. Features selected in different configurations of the algorithm were compared to understand their relationships with the surgical exposure and the surgeon's practice. RESULTS : The optimized algorithm giving the best performance used spatial features as input ([Formula: see text]). It also predicted equally the two classes of the indicator, despite their strong imbalance. Analyzing the selection of input features in the algorithm allowed a comparison of different configurations of the algorithm and showed a link between the surgical exposure and the surgeon's practice. CONCLUSION : This preliminary study validates that a prediction of the surgical exposure from spatial features is possible. The analysis of the clusters of feature selected by the algorithm also shows encouraging results and potential clinical interpretations.

Work domain constraints for modelling surgical performance.

PURPOSE: Three main approaches can be identified for modelling surgical performance: a competency-based approach, a task-based approach, both largely explored in the literature, and a less known work domain-based approach. The work domain-based approach first describes the work domain properties that constrain the agent's actions and shape the performance. This paper presents a work domain-based approach for modelling performance during cervical spine surgery, based on the idea that anatomical structures delineate the surgical performance. This model was evaluated through an analysis of junior and senior surgeons' actions. METHOD: Twenty-four cervical spine surgeries performed by two junior and two senior surgeons were recorded in real time by an expert surgeon. According to a work domain-based model describing an optimal progression through anatomical structures, the degree of adjustment of each surgical procedure to a statistical polynomial function was assessed. RESULTS: Each surgical procedure showed a significant suitability with the model and regression coefficient values around 0.9. However, the surgeries performed by senior surgeons fitted this model significantly better than those performed by junior surgeons. Analysis of the relative frequencies of actions on anatomical structures showed that some specific anatomical structures discriminate senior from junior performances. CONCLUSION: The work domain-based modelling approach can provide an overall statistical indicator of surgical performance, but in particular, it can highlight specific points of interest among anatomical structures that the surgeons dwelled on according to their level of expertise.

Cross-sectional survey on minimally invasive mitral valve surgery.

BACKGROUND: Minimally invasive mitral valve surgery (MIMVS) has become a standard technique to perform mitral valve surgery in many cardiac centers. However, there remains a question regarding when MIMVS should not be performed due to an increased surgical risk. Consequently, expert surgeons were surveyed regarding their opinions on patient factors, mitral valve pathology and surgical skills in MIMVS. METHODS: Surgeons experienced in MIMVS were identified through an electronic search of the literature. A link to an online survey platform was sent to all surgeons, as well as two follow-up reminders. Survey responses were then submitted to a central database and analyzed. RESULTS: The survey was completed by 20 surgeons. Overall results were not uniform with regard to contraindications to performing MIMVS. Some respondents do not consider left atrial enlargement (95% of surgeons), complexity of surgery (75%), age (70%), aortic calcification (70%), EuroSCORE (60%), left ventricular ejection fraction (55%), or obesity (50%) to be contraindication to surgery. Ninety percent of respondents believe more than 20 cases are required to gain familiarity with the procedure, while 85% believe at least one MIMVS case needs to be performed per week to maintain proficiency. Eighty percent recommend establishment of multi-institutional databases and standardized surgical mentoring courses, while 75% believe MIMVS should be incorporated into current training programs for trainees. CONCLUSIONS: These results suggest that MIMVS has been accepted as a treatment option for patients with mitral valve pathologies according the expert panel. Initial training and continuing practice is recommended to maintain proficiency, as well as further research and formalization of training programs.