To construct a convolutional neural network (CNN) model that can recognize and delineate anatomic structures on intraoperative video frames of robot-assisted radical prostatectomy (RARP) and to use these annotations to predict the surgical urethral length (SUL). Urethral dissection during RARP impacts patient urinary incontinence (UI) outcomes, and requires extensive training. Large differences exist between incontinence outcomes of different urologists and hospitals.
View Article and Find Full Text PDFBackground: The minimum volume standard is 100 robot-assisted radical prostatectomy (RARP) procedures per hospital in the Netherlands, so patients have to be referred to high-volume surgical centers for RARP. During preoperative work-up, prostate biopsies taken elsewhere are reassessed, with upgrading or downgrading of the initial Gleason grade group a possible consequence.
Objective: To determine if prostate biopsy reassessment leads to adjustment of the surgical plan regarding a nerve-sparing approach and extended pelvic lymph node dissection (ePLND) during RARP.
Introduction And Hypotheses: valuation of surgical skills, both technical and nontechnical, is possible through observations and video analysis. Besides technical failures, adverse outcomes in surgery can also be related to hampered communication, moderate teamwork, lack of leadership, and loss of situational awareness. Even though some surgeons are convinced about nontechnical skills being an important part of their professionalisation, there is paucity of data about a possible relationship between nontechnical skills and surgical outcome.
View Article and Find Full Text PDFObjective: To investigate the feasibility of urethral stump length and width measurements in recorded videos of robot assisted radical prostatectomy procedures using the Kinovea software and to assess if these measurements could be used as predictors of postoperative urinary continence.
Methods: Fifty-three patients were selected from an institutional database of 1400 cases and included in the study. All videos were analysed using the computer software 'Kinovea'.
Backgrounds: Robot-assisted surgery facilitated the possibility to evaluate the surgeon's skills by recording and evaluating the robot surgical images. The aim of this study was to investigate the possibility of using a computer programme (Kinovea) for objective assessment of surgical movements in previously recorded in existing robot-assisted radical prostatectomy (RARP) videos.
Methods: Twelve entire RARP procedures were analysed by a trained researcher using the computer programme "Kinovea" to perform semi-automated assessment of surgical movements.
Purpose: The aim of the current narrative review was to summarize the available evidence in the literature on artificial intelligence (AI) methods that have been applied during robotic surgery.
Methods: A narrative review of the literature was performed on MEDLINE/Pubmed and Scopus database on the topics of artificial intelligence, autonomous surgery, machine learning, robotic surgery, and surgical navigation, focusing on articles published between January 2015 and June 2019. All available evidences were analyzed and summarized herein after an interactive peer-review process of the panel.
Background: For most elderly patients with muscle-invasive bladder cancer (MIBC), surgery is not an option because of patient frailty. Conventional radiotherapy, with its high-dose irradiation of surrounding healthy tissues, remains the only curative treatment for this patient population.
Objective: To determine whether targeted radiotherapy with Lipiodol demarcation and plan-of-the-day integrated boost technique (LPOD) is a viable curative treatment for elderly patients with MIBC.
Introduction: To fulfil the need for a basic level of competence in robotic surgery (Brinkman et al., Surg Endosc Other Interv Tech 31(1):281-287, 2017; Dutch Health inspectorate (Inspectie voor de gezondheidszorg), Insufficient carefulness at the introduction of surgical robots (in Dutch: Onvoldoende zorgvuldigheid bij introductie van operatierobots), Igz, Utrecht, 2010), the NIVEL (Netherlands Institute for Healthcare Research) developed the 'Basic proficiency requirements for the safe use of robotic surgery' (BPR). Based on the BPR a 1-day robotic surgery training was organised to answer the following research questions: (1) Are novice robot surgeons able to accurately self-assess their knowledge and dexterity skills? (2) Is it possible to include the teaching of all BPRs in a 1-day training?
Materials And Methods: Based on the BPR, a robot surgery course was developed for residents and specialists (surgery, gynaecology and urology).