Tag Archive for: mental training


Article of the week: Cognitive training for technical and non‐technical skills in robotic surgery: a randomised controlled trial

Every week, the Editor-in-Chief selects an Article of the Week from the current issue of BJUI. The abstract is reproduced below and you can click on the button to read the full article, which is freely available to all readers for at least 30 days from the time of this post.

In addition to the article itself, there is an accompanying editorial written by a prominent member of the urological community. These are intended to provoke comment and discussion and we invite you to use the comment tools at the bottom of each post to join the conversation. There is also a video produced by the authors.

If you only have time to read one article this week, it should be this one.

Cognitive training for technical and non‐technical skills in robotic surgery: a randomised controlled trial

Nicholas Raison* , Kamran Ahmed*, Takashige Abe*, Oliver Brunckhorst*, Giacomo Novara, Nicolo Buf§, Craig McIlhenny, Henk van der Poel**, Mieke van Hemelrijck††, Andrea Gavazzi‡‡ and Prokar Dasgupta*


*Division of Transplantation Immunology and Mucosal Biology, Faculty of Life Sciences and Medicine, Kings College London, UK, ††Division of Cancer Studies, Kings College London, UK, Department of Urology, Forth Valley Royal Hospital, Larbert, UK, Department of Urology, Hokkaido University Graduate School of Medicine, Sapporo, Japan, Department of Urology, University of Padua, Padua, §Department of Urology, Humanitas Clinical and Research Centre, Rozzano, Milan, ‡‡Department of Urology, Azienda USL Toscana Centro, Florence, Italy, and **Department of Urology, Netherlands Cancer Institute, Amsterdam, The Netherlands


Visual Abstract created by Rebecca Fisher @beckybeckyfish



To investigate the effectiveness of motor imagery (MI) for technical skill and non‐technical skill (NTS) training in minimally invasive surgery (MIS).

Subjects and Methods

A single‐blind, parallel‐group randomised controlled trial was conducted at the Vattikuti Institute of Robotic Surgery, King’s College London. Novice surgeons were recruited by open invitation in 2015. After basic robotic skills training, participants underwent simple randomisation to either MI training or standard training. All participants completed a robotic urethrovesical anastomosis task within a simulated operating room. In addition to the technical task, participants were required to manage three scripted NTS scenarios. Assessment was performed by five blinded expert surgeons and a NTS expert using validated tools for evaluating technical skills [Global Evaluative Assessment of Robotic Skills (GEARS)] and NTS [Non‐Technical Skills for Surgeons (NOTSS)]. Quality of MI was assessed using a revised Movement Imagery Questionnaire (MIQ).


In all, 33 participants underwent MI training and 29 underwent standard training. Interrater reliability was high, Krippendorff’s α = 0.85. After MI training, the mean (sd) GEARS score was significantly higher than after standard training, at 13.1 (3.25) vs 11.4 (2.97) (P = 0.03). There was no difference in mean NOTSS scores, at 25.8 vs 26.4 (P = 0.77). MI training was successful with significantly higher imagery scores than standard training (mean MIQ score 5.1 vs 4.5, P = 0.04).


Motor imagery is an effective training tool for improving technical skill in MIS even in novice participants. No beneficial effect for NTS was found.


Editorial: Mental imagery: ‘you can observe a lot by watching!’

Urethrovesical anastomosis (UVA), like any other surgical anastomosis, is a key example of motor muscle memory, where aligning two hollow structures should result in a watertight anastomosis defining its success and help avoid complications. The authors [1] investigated the importance of cognitive training during UVA, which has been shown to be a promising supplement to skill‐based training. The authors utilised the Global Evaluative Assessment of Robotic Skills (GEARS), which has been validated for assessment of general robotic rather than procedure‐specific skills. As the authors chose UVA to evaluate training, they could have used the Robotic Anastomosis Competency Evaluation (RACE), which has been developed and validated for specific evaluation of UVA [2]. However, the study eloquently revealed higher scores, using the validated movement imagery questionnaire modified for robot‐assisted surgery whilst evaluating mental imagery.

Motor imagery utilises imagining action without its physical execution and this leads to eliciting activity in regions of brain normally activated during performance. Motor imagery has shown significant neural activity in important brain area involved in somatosensory perception, especially kinesthetic information from motor perception and muscle spindles. Such areas become active when a motor illusion is induced that ultimately share the same basis with areas active during executing movement. Mental imagery also yields more benefits if its sessions are interposed between periods of training [3]. Unfortunately, the ability to imagine more complex tasks is less accurate when utilising mental imagery [4]. In future, studies using procedure‐specific evaluation, such as RACE, may help us understand in depth the role of mental imagery during various steps of complex task, such as UVA. The hypothesis of improvement of skills whilst utilising supplemental cognitive training is reasonable; future studies will benefit from utilising an elaborate cognitive assessment. Metrics such as electroencephalograms (EEGs) and eye tracking, or even less sophisticated tools like the National Aeronautics and Space Administration Task Load Index (NASA‐TLX) self‐assessment questionnaires, have previously been used for assessment of cognitive load [5]. Objective feedback provided by a brain–computer interface (BCI) can increase the brain activation levels produced during motor imagery and thereby help in improving performance [6].

Motor imagery has been used as a popular input for BCI and in future could be used as a link to establishing instruction to semi‐autonomous robotic systems [6]. Meanwhile, a motor imagery BCI using EEG is utilising intention recognition through decoding brain activity, which ultimately could allow for intuitive control of devices like robotic systems.


  1. Raison N, Ahmed K, Abe T et al. Cognitive training for technical and non‐technical skills in robotic surgery: a randomised controlled trial. BJU Int 2018; 122: 1075–81
  2. Raza SJ, Field E, Jay C et al. Surgical competency for urethrovesical anastomosis during robot‐assisted radical prostatectomy: development and validation of the robotic anastomosis competency evaluation. Urology 2015; 85: 27–32
  3. Nicholson VP, Keogh JW, Low Choy NL. Can a single session of motor imagery promote motor learning of locomotion in older adults? A randomized controlled trial. Clin Interv Aging 2018; 13: 713–22
  4. Kalicinski M, Kempe M, Bock O. Motor imagery: effects of age, task complexity, and task setting. Exp Aging Res 2015; 41: 25–3
  5. Besharat Shafiei S, Hussein AA, Ahmed Y, Guru K. Can eye tracking help explain an expert surgeon’s brain performance during robot‐assisted surgery? J Urol 2018; 199 (Suppl.): e1–2
  6. Batula AM, Kim YE, Ayaz H. Virtual and actual humanoid robot control with four‐class motor‐imagery‐based optical brain‐computer interface. Biomed Res Int 2017; 2017: 1463512.


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