Prediction of Robotic Anastomosis Competency Evaluation (RACE) metrics during vesico-urethral anastomosis using electroencephalography, eye-tracking, and machine learning.

Residents learn the vesico-urethral anastomosis (VUA), a key step in robot-assisted radical prostatectomy (RARP), early in their training. VUA assessment and training significantly impact patient outcomes and have high educational value. This study aimed to develop objective prediction models for the Robotic Anastomosis Competency Evaluation (RACE) metrics using electroencephalogram (EEG) and eye-tracking data. Data were recorded from 23 participants performing robot-assisted VUA (henceforth 'anastomosis') on plastic models and animal tissue using the da Vinci surgical robot. EEG and eye-tracking features were extracted, and participants' anastomosis subtask performance was assessed by three raters using the RACE tool and operative videos. Random forest regression (RFR) and gradient boosting regression (GBR) models were developed to predict RACE scores using extracted features, while linear mixed models (LMM) identified associations between features and RACE scores. Overall performance scores significantly differed among inexperienced, competent, and experienced skill levels (P value < 0.0001). For plastic anastomoses, R2 values for predicting unseen test scores were: needle positioning (0.79), needle entry (0.74), needle driving and tissue trauma (0.80), suture placement (0.75), and tissue approximation (0.70). For tissue anastomoses, the values were 0.62, 0.76, 0.65, 0.68, and 0.62, respectively. The models could enhance RARP anastomosis training by offering objective performance feedback to trainees.

Performance and learning rate prediction models development in FLS and RAS surgical tasks using electroencephalogram and eye gaze data and machine learning.

OBJECTIVE: This study explored the use of electroencephalogram (EEG) and eye gaze features, experience-related features, and machine learning to evaluate performance and learning rates in fundamentals of laparoscopic surgery (FLS) and robotic-assisted surgery (RAS). METHODS: EEG and eye-tracking data were collected from 25 participants performing three FLS and 22 participants performing two RAS tasks. Generalized linear mixed models, using L1-penalized estimation, were developed to objectify performance evaluation using EEG and eye gaze features, and linear models were developed to objectify learning rate evaluation using these features and performance scores at the first attempt. Experience metrics were added to evaluate their role in learning robotic surgery. The differences in performance across experience levels were tested using analysis of variance. RESULTS: EEG and eye gaze features and experience-related features were important for evaluating performance in FLS and RAS tasks with reasonable results. Residents outperformed faculty in FLS peg transfer (p value = 0.04), while faculty and residents both excelled over pre-medical students in the FLS pattern cut (p value = 0.01 and p value < 0.001, respectively). Fellows outperformed pre-medical students in FLS suturing (p value = 0.01). In RAS tasks, both faculty and fellows surpassed pre-medical students (p values for the RAS pattern cut were 0.001 for faculty and 0.003 for fellows, while for RAS tissue dissection, the p value was less than 0.001 for both groups), with residents also showing superior skills in tissue dissection (p value = 0.03). CONCLUSION: Findings could be used to develop training interventions for improving surgical skills and have implications for understanding motor learning and designing interventions to enhance learning outcomes.

Developing surgical skill level classification model using visual metrics and a gradient boosting algorithm.

Objective: Assessment of surgical skills is crucial for improving training standards and ensuring the quality of primary care. This study aimed to develop a gradient boosting classification model (GBM) to classify surgical expertise into inexperienced, competent, and experienced levels in robot-assisted surgery (RAS) using visual metrics. Methods: Eye gaze data were recorded from 11 participants performing four subtasks; blunt dissection, retraction, cold dissection, and hot dissection using live pigs and the da Vinci robot. Eye gaze data were used to extract the visual metrics. One expert RAS surgeon evaluated each participant's performance and expertise level using the modified Global Evaluative Assessment of Robotic Skills (GEARS) assessment tool. The extracted visual metrics were used to classify surgical skill levels and to evaluate individual GEARS metrics. Analysis of Variance (ANOVA) was used to test the differences for each feature across skill levels. Results: Classification accuracies for blunt dissection, retraction, cold dissection, and burn dissection were 95%, 96%, 96%, and 96%, respectively. The time to complete only the retraction was significantly different among the 3 skill levels (p-value = 0.04). Performance was significantly different for 3 categories of surgical skill level for all subtasks (p-values<0.01). The extracted visual metrics were strongly associated with GEARS metrics (R2>0.7 for GEARS metrics evaluation models). Conclusions: Machine learning (ML) algorithms trained by visual metrics of RAS surgeons can classify surgical skill levels and evaluate GEARS measures. The time to complete a surgical subtask may not be considered a stand-alone factor for skill level assessment.

The Comparison of the Advantages of Neoadjuvant Chemoradiotherapy versus Postoperative Chemoradiotherapy: Outcomes in Esophageal Cancer Patients.

BACKGROUND AND OBJECTIVES: Esophageal cancer is the eighth most common type of cancer worldwide. For the treatment of which, surgical intervention alone or with neoadjuvant chemoradiotherapy or chemotherapy is recommended. In this study, we aimed to compare the benefits of neoadjuvant chemoradiotherapy versus postoperative chemoradiotherapy. PATIENTS AND METHODS: We collected data regarding 325 patients admitted for esophageal cancer to Qaem Hospital, Mashhad, Iran, during 2006-2016. The participants were divided into two groups of neoadjuvant and postoperative adjuvant therapies. Chi-square, McNemar, Kaplan-Mayer, and multivariate regression tests were performed using SPSS. RESULTS: Gender, age, stage of the disease, tumor grade and location, disease histopathology, and the recurrence showed no significant differences between the two groups (P Ëƒ 0.05), but there was a significant association between the two types of treatment in terms of postoperative complications (P = 0.03). We followed up 147 patients postoperatively and found no significant differences between the groups (P Ëƒ 0.05). CONCLUSION: No conclusion can be drawn on whether there are any advantages in adjuvant chemoradiotherapy over neoadjuvant approaches. Further confirmatory trials, particularly randomized trials, are necessary before any recommendations can be made.

Intracranial meningiomas: Prognostic factors and treatment outcome in patients undergoing postoperative radiation therapy.

BACKGROUND: Meningioma constitutes 20% of the intracranial neoplasms. Followed by surgery as the primary treatment for most patients, radiotherapy becomes indicated in high-grade tumors with incomplete surgical removal. We evaluated the prognostic factors and overall outcome in meningioma patients who underwent radiotherapy. MATERIALS AND METHODS: In this retrospective analysis, data from all patients with documented diagnosis of meningioma who referred to the Omid and Ghaem Oncology Centers (Mashhad, Iran) from 2002 to 2013 were included. We calculated the overall survival rates using the Kaplan-Meier method and compared the survival curves between groups by the log-rank test. RESULTS: Eighty-three patients with a median age of 50 years (ranging: 16-84) were included. Grade I, II, and III meningiomas were seen in 40 (48%), 31 (37%), and 12 (15%) patients, respectively. Radiation therapy was indicated due to tumor recurrence, incomplete excision, or tumor grade in 32, 8, and 43 patients, respectively. Tumor grade had a significant effect on the overall survival with a 3-year overall survival of 76.7%, 43.5%, and 13.3% in Grade I, II, and III, respectively (P < 0.001). Gender, age, and tumor location were not correlated with the overall survival. Moreover, patients with Grade II and III who underwent total resection had a significantly higher overall survival than those with subtotal resection or biopsy alone (5-year survival rates of 82% vs. 17.1%, respectively; P = 0.008). CONCLUSION: Tumor grade was the most important prognostic factor in meningioma patients undergoing radiation therapy. In patients with Grade II and III tumors, the extent of surgical resection is significantly correlated with the overall survival.

A clinical trial of neoadjuvant concurrent chemoradiotherapy followed by resection for esophageal carcinoma.

BACKGROUND: Esophageal carcinoma is a common malignancy in the North East of Iran. Combined modality treatments have been adopted to improve survival in patients with esophageal carcinoma. In this trial, we evaluated the efficacy and toxicity of a preoperative concurrent chemoradiotherapy protocol in the patients with locally advanced esophageal carcinoma. MATERIALS AND METHODS: Between 2006 and 2011, eligible patients with locally advanced esophageal carcinoma underwent concurrent radiotherapy and chemotherapy and 3-4 weeks later, esophagectomy. Pathologic response, overall survival rate, toxicity, and feasibility were evaluated. RESULTS: One hundred ninety-seven patients with a median age of 59 (range: 27-70) entered the protocol. One hundred ninety-four cases (98.5%) had esophageal squamous cell carcinoma. Grades 3-4 of toxicity in patients undergoing neoadjuvant chemoradotherapy were as follows: Neutropenia in 21% and esophagitis in 2.5% of cases. There were 11 (5.6%) early death probably due to the treatment-related toxicities. One hundred twenty-seven patients underwent surgery with postsurgical mortality of 11%. In these cases, the complete pathological response was shown in 38 cases (29.9%) with a 5-year overall survival rates of 48.2% and median overall survival of 44 months (95% confidence interval, 24.46-63.54). CONCLUSION: The pathological response rate and the overall survival rate are promising in patients who completed the protocol as receiving at least one cycle of chemotherapy. However, the treatment toxicities were relatively high.

Pulmonary metastasectomy and repeat metastasectomy for soft-tissue sarcoma.

BACKGROUND: For patients with lung metastases from soft-tissue sarcoma, pulmonary metastasectomy is considered to be the only chance of possible cure. In this survey, we analyzed some potential prognostic factors affecting the outcome in these patients. PATIENTS AND METHODS: 34 patients who underwent pulmonary metastasectomy for soft-tissue sarcoma from April 1996 to April 2007, were enrolled in our study. The median follow-up period was 26 months. Survival curves, factors affecting the outcome, and treatment success rate were evaluated. RESULTS: Complete resection was achieved in 88.2% of patients. There was no perioperative mortality. The median overall survival and median disease-free survival were 42 and 27 months, respectively. Incomplete resection and bilateral lung metastases had significant adverse effects on overall survival. Shorter disease-free interval (<18 months) was a significant predictor of survival on multivariate analysis. Metastasectomy was attempted in 12 cases of whom 50% remained disease-free to the end of follow-up. CONCLUSION: Complete resection is the most important defining factor of success rate and survival. Patients with bilateral lung metastases or a shorter disease-free interval have significantly lower success rates. Repeat metastasectomy is curative in many patients.