Accepted Article

SIMULATION-BASED TRAINING FOR PROSTATE SURGERY 1

Authors:

Raheej Khan

Abdullatif Aydin BSc (Hons) Mohammed Shamim Khan FRCS Urol, FEBU, OBE Prokar Dasgupta MSc, MD, FRCS Urol, FEBU Kamran Ahmed MRCS, PhD

King's College London - MRC Centre for Transplantation, London, United Kingdom.

Correspondence:

Kamran Ahmed Academic Clinical Lecturer / Urology Registrar MRC Centre for Transplantation, King's College London, King’s Health Partners, St Thomas Street, London SE1 9RT, UK

Ph: +44 (0)20 7188 8580

Fax: +44 (0)20 3312 6787 Email: [email protected]

Keywords: prostate, training, simulation, assessment

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: 10.1111/bju.12721 This article is protected by copyright. all rights reserved.

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ABSTRACT

What’s known on the subject? And what does the study add? 

The advance of medical technology has had a significant impact upon the management of prostatic disease. Trainees are expected to embrace new technologies and also meet increasing patient expectations, within the time constraints imposed by the European Working-Time Directive. There is increasing concern that surgical training is currently inadequate. Therefore, numerous training methods have been developed to supplement operating experience on patients. Surgical simulation is one such method, which aims to teach trainees technical and non-technical skills outside operating theatre without compromising patient safety. The field of simulation is rapidly expanding in both training and assessment of urological procedures. However, there is relatively little research evaluating the effectiveness of simulation in urology.



This article identifies currently available simulators pertaining to prostate surgery and attempts to scientifically evaluate the evidence available, assessing their efficacy in terms of face, content, construct, concurrent and predictive validity. Suggestions are provided for further assessment of the cost effectiveness of simulation, the need for research to validate simulated environments and determine which simulators are more effective than others and the need to investigate the transferability of skills learnt in the simulated environment through randomized controlled trials.

Objective: 

To identify and review the currently available simulators and explore the evidence supporting their efficacy for training in prostate surgery.

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Materials and Methods:

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

A review of the current literature was performed between 1999 and 2013. The search terms included a combination of urology, prostate surgery, robotic prostatectomy, laparoscopic prostatectomy, TURP, simulation, virtual reality, animal model, human cadavers, training, assessment, technical skills, validation and learning curves. Furthermore, relevant abstracts from the AUA, EAU, BAUS and WCE meetings, between 1999 and 2013, were included. Only studies related to prostate surgery simulators were included and studies regarding other urological simulators were excluded.

Results: 

A total of 22 studies were identified, which carried out a validation study. Five validated models and/or simulators were identified for transurethral resection of the prostate (TURP), one for GreenLight laser therapy, three for laparoscopic radical prostatectomy (LRP) and four for robotic surgery. Of the TURP simulators, all five demonstrated content validity, three demonstrated face validity and four construct validity. The GreenLight laser simulator demonstrated face, content and construct validities. All three animal models for LRP demonstrated construct validity whilst The Chicken Skin Model was also content valid. Only two robotic simulators were identified with relevance to robot-assisted laparoscopic prostatectomy (RALP), both of which demonstrated construct validity.

Conclusions: 

A wide range of different simulators are available for prostate surgery including synthetic bench models, virtual-reality platforms, animal models, human cadavers, distributed simulation and advanced training programmes and modules. The currently validated simulators may be used by healthcare organisations to provide supplementary training sessions for trainee surgeons. Further research should be

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conducted to validate simulated environments, determine which simulators have greater efficacy than others, assess the cost effectiveness of the simulators and the transferability of skills learnt. However, with surgeons investigating new possibilities for easily reproducible and valid methods of training, simulation offers a great scope to be implemented alongside traditional methods of training.

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INTRODUCTION

Over the last two decades, the advance of medical technology has revolutionised surgical practice. This has undoubtedly had a major effect upon all surgical specialties including urology. The surgical methods for treatment of kidney, bladder and prostatic disease have radically evolved from open wound surgery to routinely being performed through minimally invasive modalities.

These changes in surgical practice, coupled with the introduction of European WorkingTime Directives, greater patient expectations, and financial constraints in the NHS and other healthcare organisations, has raised fundamental questions on postgraduate surgical training. The concern that surgical residents are not receiving adequate training is becoming greater. As a result, various training methods have been developed to improve performance in the operating room. Amongst these, surgical simulation has advanced at a rapid pace, becoming an established and valid method of training and assessment. [1-3]

Surgical simulators may be divided into two broad categories: physical simulators including synthetic bench, animal and human cadaver models and computer-assisted “virtual reality” (VR) simulators. VR simulators have the added benefit of reusability and providing statistical feedback through an objective performance evaluation report whereas physical simulators lack a quantifiable inherent means of measuring performance [4]. Thus, a trained observer is usually required to make an assessment using a global or generic skills assessment scales such as the objective structured assessment of technical skills (OSATS) [5]. This is a validated assessment tool composed of multiple stations assessing different features of surgical skills, including knowledge, instrument handling and quality of the end product through a Global Rating Scale (GRS) [6]. This article is protected by copyright. all rights reserved.

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Synthetic bench models are commonly used and are usually made from latex, rubber or plastic and are used to represent various organs and their associated pathological states. They have the benefit of recreating the tangible sensations of the real surgical environment and may be useful for improving hand-eye co-ordination as well as technical motor skills. A number of studies have demonstrated the validity and reliability of using these models for specific surgical skills development in urology [7] including intra-corporeal suturing techniques [8]. However these are only used for part-task training. In contrast, human cadaver and animal models allow full procedural training [5]. Although human cadavers are the most realistic and gold standard modality of training, their cost and lack

of availability limits their use. Animal models offer many advantages over bench models, such as respiratory movement and authentic haptic feedback [9]. However, their use is

also problematic due to licensing and ethical issues [10].

Integration of non-technical skills training into procedural simulation has also been validated. For instance, distributed simulation (DS) is a concept which aims to create a high-fidelity environment at a relatively small cost to teach and assess technical and nontechnical skills [11]. A portable inflatable simulated operating room is created with integrated audio-visual equipment, operating light and posters depicting the real operating room environment [11].

However, before any surgical simulator can be used for training and assessment, it must undergo an initial internal assessment across a variety of parameters (Figure 1) [12, 13]. In this article, we will identify and review the currently available simulators and explore the evidence supporting their efficacy for training in prostate surgery.

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METHODS

A broad search of the current literature was performed using MEDLINE and EMBASE between 1999 and 2013. The search terms included a combination of urology, prostate surgery, robotic prostatectomy, laparoscopic prostatectomy, TURP, simulation, virtual reality, animal model, human cadavers, training, assessment, technical skills, validation and learning curves. References of published review articles were checked for further relevant studies. Relevant articles were identified, the full text for each obtained and further screened for relevance to the study. Furthermore, Technology, Simulation and Surgical Education sections of abstracts of the American Urological Association (AUA), European Association of Urology (EAU), British Association of Urological Surgeons (BAUS) and the World Congress of Endourology (WCE) meetings were reviewed for relevant studies, between 1999 and 2013. Only studies pertaining to prostate surgery related simulators were included and studies regarding other urological simulators were excluded.

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RESULTS

SIMULATION FOR TRANSURETHRAL RESECTION OF THE PROSTATE (TURP)

The current gold standard surgical treatment for Benign Prostatic Hyperplasia (BPH) is transurethral resection of the prostate (TURP) [14] and all trainees are required to master this procedure [15]. Therefore, a number of simulators have been developed to help trainees reach a proficient level of practice (Figure 2).

Synthetic (Bench) Models The Bristol TURP Trainer (Limbs and Things, UK) is a disposable bench model, which gives trainees the opportunity to exercise basic skills required for a transurethral resection of the prostate (TURP) procedure. The prostate model is placed within a sealed plastic chamber and allows the user to identify and manipulate instruments, identify relevant anatomical landmarks, real fluid management and resect and evacuate the resected chips.

As with all synthetic models, directional force feedback is provided but lacks a quantifiable inherent means of measuring performance [4]. Thus, assessment of performance is often

made using the OSATS global rating form [5, 16]. Face, content and construct validity of this model was recently demonstrated by Brewin et al. [16]. Expert and trainee surgeons felt the simulator was a good training tool, which should be included in their training curriculum, but thought its realism was limited by the lack of bleeding.

Virtual Reality (VR) Simulators The VR TURP simulator, developed by Ballaro et al. [17] at University College London (UCL; London, UK), demonstrated content validity but its realism was limited by delayed images
and a lack of haptic feedback. Having been developed over a decade ago, the This article is protected by copyright. all rights reserved.

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technology is most probably outdated and not suited for current use.

In 2005, Kallstrom et. al. [18] introduced the University Hospital Linkoping TURP simulator and demonstrated its content validity. The simulator gives a view of the virtual prostatic lumen as well as the resectoscope tip, with force-feedback from the haptic device, and allows the simulation of pressure gradients and bleeding. A basic construct validity test amongst nine participants showed improved performance after repeated use of the simulator.

Another university led initiative is The University of Washington TURP Trainer, developed by Sweet et al. [19]. This simulator allows trainees to perform a full TURP procedure and provides a detailed performance evaluation report. The developers demonstrated both face and content validity of this simulator with as many as 136 participants [19, 20].

Furthermore, construct validity was demonstrated amongst surgeons with varying levels of experience [19, 21] and also similar levels of experience [20]. To date, this is the most extensively validated TURP simulator available.

The TURPSim™ (VirtaMed, Zurich, Switzerland) is a commercial TURP simulator that has recently been evaluated [22, 23]. This simulator is able to successfully imitate endoscopic

movement and allows users to carry out procedures, such as resection and coagulation, and complete full TURP procedures. The simulator includes modules of a variety of difficulty levels, at the end of which, a comprehensive report is provided listing the operation parameters. Face and content validity of the simulator was established in two studies [22, 23] whilst Bright et al. [23] also demonstrated construct validity in 18 participants.

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Distributed Simulation (Full Immersion Simulation) Although the face, content and construct validity, feasibility, educational impact and costeffectiveness of the DS have been established in a number of studies in general surgery [24-26], “The Igloo” is the only noted attempt to carry out DS in urology. Brewin et al. [27] used a TURP bench-top model, a scrub nurse and an anaesthetist to simulate an operating theatre (Figure 3) and established face and content validity. Furthermore, significant differences were observed between novices and experts in both technical and non-technical skills, thereby establishing construct validity.

SIMULATION TRAINING FOR LASER TREATMENT OF BPH

More recently, alternative therapies have also been developed in an attempt to reduce complication rates associated with TURP. These include microwave therapy, transurethral needle ablation, and a range of laser procedures including Holmium, Diode, Thulium and GreenLight Laser Photoselective Vaporisation of the Prostate (PVP) [28].

Green Light Laser PVP Simulation A virtual reality simulator for Green Light Laser PVP has been developed by Shen et al. [29], in collaboration with AMS (American Medical Systems Inc, Minnetonka, MN, USA). The simulator (Figure 2) includes six core full operative cases and five part-task exercises

including anatomy identification, sweep speed, tissue-fibre distance, power settings and

coagulation. The simulator modules were guided by a consortium of key opinion leaders and 40 members of the American Urological Association (AUA) [30]. The simulator was recently validated by Herlemann et al. [31], who conducted a study with 18 participants and demonstrated face, content and basic construct validity. Aydin et al. [32] evaluated the learning curves of this simulator with 25 novices and concluded that there was significant

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improvement in all part-task training modules and a significant reduction in case operative time, and error. The authors also developed a training curriculum to help trainees acquire transferrable skills.

Training Modalities for HoLEP The other common laser modality, used in the treatment of BPH is Holmium Laser Enucleation of the Prostate (HoLEP). Although a number simulators, both bench and VR, have been introduced by Lumenis (Yokneam, Israel) [33, 34], none have been validated yet. These are the TRUlase Prostate (Figure 2; TruCorp, Belfast, N. Ireland) [35] and the newly-developed Prostatic Hyperplasia Model and Holmium Laser Surgery Simulator

(Figure 2) [36]. Both bench models consist of a “hypertrophied” prostate model, which can be fitted and installed into a box simulator, and can be used with standard endoscopy equipment Holmium laser. These models also allow for real-life fluid management and can be interchanged after each procedure. However, being a synthetic model, it only allows a certain number of surgeons to train due to limited supply.

TRAINING FOR LAPAROSCOPIC AND ROBOTIC PROSTATECTOMY

In an effort to decrease the morbidity associated with open radical prostatectomy, Schuessler et al. [37] performed the first minimally invasive laparoscopic radical

prostatectomy (LRP). This was shortly followed by the first Robot-assisted laparoscopic prostatectomy (RALP) in 2000 [38]. Since its introduction, the procedure has undergone significant improvement, and has been widely accepted [39]. However, the competency of the performing surgeon is crucial and with the limited availability of consoles, training for

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Accepted Article

RALP has become a challenge. Therefore, a number of training modalities have been developed to overcome this problem.

Human Cadavers Human cadavers remain the gold standard for surgical training specific to individual procedures. However their use remains limited due to restricted availability. There are currently no studies that have reported or evaluated the use of human cadaveric models to perform part or full procedure standard LRP or RALP. Nonetheless, a number of studies have reported the use of cadaveric models to evaluate the feasibility of novel approaches or methods such as natural-orifice translumenal endoscopic surgical (NOTES) radical prostatectomy [40], transvesical robotic radical prostatectomy (TRRP) [41], laparoendoscopic single-site (LESS) radical prostatectomy and robot-assisted LESS radical prostatectomy [42].

Animal Models Amongst proposed animal models, the rabbit model of training has been validated for improving basic surgical skills including suturing, knot-tying and dissection, all essential in performing any robotic procedure [43]. Laguna et al. [44] assessed the effectiveness of the Chicken Chest Model for laparoscopic urethro-vesical anastomosis (UVA) training, required during LRP and RALP, and demonstrated basic construct validity. However, the model failed to reflect the different levels of experience among the most experienced subjects. Similarly, Nadu et al. [45, 46] developed the Chicken Skin Model and found that

after using the model, trainees were able to acquire skills to perform laparoscopic UVA in addition to developing other fundamental skills such as manual dexterity. This model was shown to have both construct and content validity in a study carried out by Yang and Bellman [47], who suggested the use of this model as a means of laparoscopic skills This article is protected by copyright. all rights reserved.

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assessment in urological trainees. The Chicken Gizzard Model has also been proposed and used to perform UVA [48], but has not undergone any validation.

Another model used for laparoscopic UVA is the porcine-intestine model, which also demonstrated construct validity in the study carried out by Boon et al. [49]. Jiang et al. [50]

proposed the Porcine Model as a more effective, realistic and cheaper alternative to the Chicken Skin Model for laparoscopic training. It has been demonstrated that the transferability of laparoscopic UVA skills to a high fidelity, animal model is far greater when training is carried out using a urethro-vesical model as opposed to practicing basic laparoscopic suturing on foam pads [51].

Price et al. [52] conducted a study to determine the feasibility of performing LRP in a canine model. The authors performed full LRP procedures on six adult male canines, five of which recovered uneventfully from the procedure and four of the surviving animals were clinically continent within 10 days after catheter removal. The authors, thereby, demonstrated the feasibility of LRP in a canine model however did not report any validity.

Robotic Simulators Robotic simulators allow trainees to familiarise with general instrument operation, docking, gain experience in operating the console and work without tactile feedback. They also allow basic skills acquisition such as suturing, precision cutting and ring-peg transfer, which are required to progress to more complex tasks, in a risk-free environment. Since virtual reality simulators are suggested to enhance progression along the initial learning curve without compromise to patient safety, they may be utilised in both training and objective assessment of surgical skills [53]. To date, there are only two robotic simulators with prostate training modules. This article is protected by copyright. all rights reserved.

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The dV-Trainer™ (MdVT, MIMIC Technologies, Seattle, WA, USA) was the first commercially available VR simulator for robotic surgery. It is the most extensively studied and evaluated simulator and has demonstrated face, content and construct validities on several occasions [54-58]. MIMIC have also collaborated with Intuitive Surgical® to integrate the dV-Trainer™ simulation software with the da Vinci® Si Surgeon Console (dVSS) to produce da Vinci® Skills Simulator. Hung et al. [59] demonstrated the face, content and construct validity of this simulator. Although currently limited to basic skills training, they concluded that it was a very useful and realistic tool for training that is likely to influence robotic surgical training across all specialties. The same authors also

evaluated the concurrent and predictive validity of the simulator in a prospective, randomized study [60]. Analysis of baseline simulator performance with baseline ex vivo

tissue performance (concurrent validity) and final tissue performance (predictive validity) revealed significant correlation, thereby suggesting the benefit of simulator training for trainees with low baseline robotic skills.

A similar platform, the Robotic Surgical Simulator (RoSS; Simulated Surgical Systems, Williamsville, NY, USA), has also demonstrated face [61] and content validity [62]. Seixas-

Mikelus et al. [61] found that the RoSS was very close to the dVSS console in terms of realism. In their following study [62], the authors found that 94% of their participants thought that RoSS would be useful for training purposes and as an appropriate means of training and assessment before operating room experience (88%). Training on the RoSS simulator has shown to reduce time taken on the dVSS to carry out a procedure [63, 64].

Ahmed et al. [65] developed and validated an augmented reality based module for UVA training for RALP, utilizing the Hands on Surgical Training (HoST) Software. In this

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prospective, single-blinded randomized controlled trial, the authors recruited 22 surgeons across three institutions and randomly allocated them to performing UVA on the dVSS or performing the HoST-based UVA module five times on the RoSS. The latter group were then assessed on the dVSS, considered the gold standard method of training (concurrent validity). The first group were given the opportunity to enrol on the HoST-based UVA module followed by assessment on the dVSS. This study demonstrated face, construct and concurrent validity of the HoST-based UVA module and concluded it to be a feasible, reliable and valid training tool with acceptable educational impact.

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Accepted Article DISCUSSION

The surgical field is continually evolving. Development of new technologies and subsequent introduction of new procedures have raised concerns about patient safety. A prime example of such development is the evolution of prostatic surgery from open-wound to minimally invasive surgery. The widespread use of procedures such as robot-assisted laparoscopic prostatectomy (RALP) has made it essential to combine work based surgical training with simulation, in order to acquire skills outside the operating theatre without compromising patient safety.

Simulation may enhance progression along the initial learning curve, which is defined as the number of procedures performed before an acceptable plateau is achieved in outcome factors such as the amount of blood loss, rate of complications, and the time taken for the operation [66]. The length of the learning curve is generally dependent upon the level of difficulty of a procedure. With the implementation of the European Working Time Directive in 2004, the time available for training has dramatically fallen from 30 000h to 8000h [67]. Thus, shortening the initial stages of the learning curve may compensate for the greatly reduced training time and hence enhance patient safety.

Surgical simulators have been developed and validated in a number of surgical disciplines including general surgery [68, 69], endovascular surgery [70], orthopaedic surgery [71] and urology [72]. Amongst the urological sub-specialties, simulators developed for procedures relating to the kidney and ureters demonstrate the highest levels of available and validated surgical simulators [72]. Closely in range are simulators pertaining to the range of surgical procedures performed for benign and malignant disease of the prostate [53, 72].

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A variety of simulators have been developed for TURP, laser treatment of BPH, LRP and RALP. These include synthetic models, animal and human cadaver models and virtual reality simulators, only a selection of which have undergone extensive validation studies (Table 1). However, as discussed by McDougall [12], the establishment of construct validity is mandatory before acceptance of a simulator as a means to evaluate surgical competency.

Synthetic models have proved to be beneficial for basic surgical skills training such as suturing, cutting and knot-tying. Although a number of studies have demonstrated the validity of these models for skills development in urology [7, 8], The Bristol TURP Trainer remains the only validated bench model available for TURP training [16]. Due to costeffectiveness, portability and availability, synthetic models are the most commonly used models. However, replacement of the models are required following each use.

Surgical training using human cadavers and animal models has been a fundamental part of training for minimally invasive surgery [73]. It has been integrated into many surgical training courses as it has the advantage of replicating human anatomy. Such training allows surgeons to perform and practice more complex tasks as well as full operative procedures after reaching a level of proficiency in basic surgical skills and part-tasks. However, despite having a higher degree of face validity, their use as a training method is often limited by their availability. Thus, human cadaver and animal models are mainly used for advanced high fidelity training such as robotic training [74].

Animal models offer many advantages over bench models, such as respiratory movement and authentic haptic feedback [9] and, as illustrated by Price et al. [52], despite the This article is protected by copyright. all rights reserved.

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anatomical and physiological differences, animal models have the added benefit of observing outcomes of full procedures as opposed to human cadaveric training. Although assessment within the animal laboratory is much more cost effective and reproducible when compared to human cadavers, their use is also limited as a result of licensing and ethical issues [10]. Therefore trainees often travel to certain countries to receive wet-lab training.

There are also a wide variety of virtual simulators available for TURP, laparoscopy and robotics. These have the advantage of producing objective performance evaluation reports and their use is not limited by quantity. Although many have demonstrated construct validity, very few have also demonstrated concurrent and predictive validities. Amongst, the TURP VR simulators, only the University of Washington TURP simulator has demonstrated concurrent validity and has been evaluated with a large number of participants [19]. The remaining simulators have shown construct validity amongst a small cohort of novices and experts. Many robotic and laparoscopic VR simulators have also demonstrated construct validity, but amongst a small cohort [75-77]. The most thoroughly studied are the MdVT by MIMIC Technologies [54-58] and the Da Vinci Skills Simulator [59, 60], of which the latter has also demonstrated concurrent and predictive validities. However, its use necessitates a functional robot and their current expense limits widespread use. Furthermore, the technology is only available for a limited number of procedures.

Based on the currently available data, simulation-based training for prostate surgery should be adopted by healthcare organisations, where possible (Figure 4). TURP training using one of the construct valid simulators such as the Bristol TURP Trainer, University of Washington TURP Trainer or the TURPSim may be offered to residents as regular This article is protected by copyright. all rights reserved.

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supplementary sessions to their work-based training. The GreenLight SIM has also proven construct validity and may be used by trainers. Furthermore, these simulators may also be used in conjunction with distributed simulation for technical and non-technical skills acquisition.

With the increasing use of laparoscopy in surgery, many centres have opted for initial simulation training on physical and/or VR simulators, followed by wet-lab training and operating under the mentorship of an experienced surgeon. A number of validated physical simulators are available for learning basic laparoscopic surgical skills such as the EZ trainer [78]. The Heilbronn laparoscopic training programme is one such example, where a standardized step-by-step programme for laparoscopic suturing has incorporated the use of both bench and animal models. Teber et al. [79, 80] assessed and validated this training program and found that it can be incorporated in various departments aiming to develop a laparoscopic training program. This programme may be applied for LRP and can be followed by urethro-vesical anastomosis (UVA) training, using the validated animal models (Table 1). Similarly, following basic skills acquisition with any of the appropriate robotic simulators, RALP training can be further enhanced using the HoST-based UVA module on the RoSS and also the dVSS for UVA training. The animal models, validated for LRP, may be used to consolidate this training.

In both LRP and RALP, full-procedure training on live animals and/or human cadaveric models should follow basic skills acquisition and part-task training. Blaschko et al. [81] described the importance of human cadavers as a superior method of training for minimally invasive procedures such as laparoscopy and robot-assisted surgical procedures. They proposed that the restricted availability of cadavers could be improved through coordinated use for multiple teaching sessions across different specialties. This article is protected by copyright. all rights reserved.

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Although it remains to be validated for LRP and RALP, this can be followed by distributed simulation in order to improve both technical and non-technical skills.

It is generally argued that training is best achieved under active instruction and feedback by an expert. However, van Bruwaene et al. [82] investigated the feasibility of substituting expert feedback with structured training using video demonstrations and peer feedback. Using a study population of two balanced groups of 10 senior medical students, training under expert supervision was compared with structured training with peer feedback and video demonstrations. Both methods were found to be very effective in improving laparoscopic suturing skills and skill retention. Hence, peer feedback and video demonstrations may be utilised in the absence of experts or in basic skills acquisition.

A major limitation with incorporating simulation as a training method is the lack of data on cost effectiveness. Moreover, since most validation studies have been conducted on a small scale, further research is required to validate simulated environments and determine which simulators are more effective than others. The transferability of skills learnt in the simulated environment must also be investigated through randomized controlled trials. Nevertheless, with surgeons exploring new possibilities for easily reproducible and valid methods of training, simulation offers a great scope.

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CONCLUSIONS

Prostate surgery utilises a wide range of different surgical simulators including synthetic bench models and VR simulators for training in BPH treatment and animal models, human cadavers and advanced training programmes and modules in LRP and RALP. The currently validated simulators may be used by healthcare organisations to provide supplementary training sessions and the remaining should be scientifically evaluated. Although simulation cannot be an alternative to hand-on-training in the operating room, it

can be implemented alongside traditional methods of training in order to provide future surgeons with the skills and knowledge required to operate in a safe manner with successful outcomes. CONFLICTS OF INTEREST None disclosed.

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Accepted Article

[15] Bachmann A, Muir GH, Wyler SF, Rieken M. Surgical benign prostatic hyperplasia trials: the future is now! European urology. 2013 Apr;63(4):677-9; discussion 9-80. PubMed PMID: 23158588. [16] Brewin JW, Ahmed K, Khan MS, Jaye P, Dasgupta P. Validation of the Bristol TURP simulator. BJU Int. 2013;111(S3):17-70. [17] Ballaro A, Briggs T, Garcia-Montes F, MacDonald D, Emberton M, Mundy AR. A computer generated interactive transurethral prostatic resection simulator. J Urol. 1999 Nov;162(5):1633-5. PubMed PMID: 10524885. [18] Kallstrom R, Hjertberg H, Kjolhede H, Svanvik J. Use of a virtual reality, real-time, simulation model for the training of urologists in transurethral resection of the prostate. Scandinavian journal of urology and nephrology. 2005;39(4):313-20. PubMed PMID: 16118107. [19] Sweet R, Kowalewski T, Oppenheimer P, Weghorst S, Satava R. Face, content and construct validity of the University of Washington virtual reality transurethral prostate resection trainer. J Urol. 2004 Nov;172(5 Pt 1):1953-7. PubMed PMID: 15540764. [20] Rashid HH, Kowalewski T, Oppenheimer P, Ooms A, Krieger JN, Sweet RM. The virtual reality transurethral prostatic resection trainer: evaluation of discriminate validity. J Urol. 2007 Jun;177(6):2283-6. PubMed PMID: 17509340. [21] Hudak SJ, Landt CL, Hernandez J, Soderdahl DW. External validation of a virtual reality transurethral resection of the prostate simulator. J Urol. 2010 Nov;184(5):2018-22. PubMed PMID: 20850819. [22] Zhu H, Zhang Y, Liu JS, Wang G, Yu CF, Na YQ. Virtual reality simulator for training urologists on transurethral prostatectomy. Chinese medical journal. 2013 Apr;126(7):1220-3. PubMed PMID: 23557547. [23] Bright E, Vine S, Wilson MR, Masters RS, McGrath JS. Face validity, construct validity and training benefits of a virtual reality TURP simulator. International journal of surgery. 2012;10(3):163-6. PubMed PMID: 22366646. [24] Harris A, Kassab E, Tun JK, Kneebone R. Distributed Simulation in surgical training: an off-site feasibility study. Medical teacher. 2013 Apr;35(4):e1078-81. PubMed PMID: 23137260. [25] Kassab E, Kyaw Tun J, Kneebone RL. A novel approach to contextualized surgical simulation training. Simulation in healthcare : journal of the Society for Simulation in Healthcare. 2012 Jun;7(3):155-61. PubMed PMID: 22495386. [26] Kassab E, Tun JK, Arora S, King D, Ahmed K, Miskovic D, et al. "Blowing up the barriers" in surgical training: exploring and validating the concept of distributed simulation. Ann Surg. 2011 Dec;254(6):1059-65. PubMed PMID: 21738021. [27] Brewin J, Ahmed K, Tang J, Bello F, Kneebone R, Dasgupta P, et al. Validation and Educational Impact of Distributed Simulation in Urology. J Endourol. 2012;26(S1):147. [28] Zorn KC, Liberman D. GreenLight 180W XPS photovaporization of the prostate: how I do it. The Canadian journal of urology. 2011 Oct;18(5):5918-26. PubMed PMID: 22018158. This article is protected by copyright. all rights reserved.

23

Accepted Article

[29] Shen Y, Konchada V, Zhang N, Jain S, Zhou X, Burke D, et al. Laser surgery simulation platform: toward full-procedure training and rehearsal for benign prostatic hyperplasia (BPH) therapy. Studies in health technology and informatics. 2011;163:57480. PubMed PMID: 21335859. [30] Sweet R, Konchada V, Jain S, Zhang N, Zhou X, Burke D, et al. Training Laser Prostate Surgery with an Advanced Simulatoin Based Vurriculum: The Victor GreenLight Trainer. J Urol. 2011;185(4S):e596. [31] Herlemann A, Strittmatter F, Buchner A, Karl A, Reich O, Bachmann A, et al. Virtual Reality Systems in Urologic Surgery: An Evaluation of the GreenLight Simulator. European urology. 2013 Jun 15. PubMed PMID: 23790439. [32] Aydin A, Muir G, Khan MS, Dasgupta P, Ahmed K. Evaluation of the Learning Curve for the AMS GreenLight SIM and Development of a Virtual Reality Training Curriculum for GreenLight Laser Prostatectomy. J Endourol. 2013;27(S1):A56. [33] Lumenis. Lumenis Unveils New Simulator to Train Urologists on Gold Standard HoLEP Procedure for Benign Prostatic Hyperplasia 2013. Available from: http://www.lumenis.com/press/pr_1367503088. [34] Lumenis. Lumenis Introduces the HoLEP Simulator and the PolyScope Disposable Ureteroscope at American Urology Association 2009 Annual Meeting 2009. Available from: http://www.lumenis.com/press/pr_1240512932. [35]

TruCorp.

TRULASE

PROSTATE

[14.04.2013].

Available

from:

http://www.trucorp.com/products/trulase/prostate/.

[36] Matsuda K, Kinoshita H, Okamoto Y. Prostatic Hyperplasia Model and Prostate Surgery Simulator. World Intellectual Property Organization [Internet]. 2013. Accessed on: 08.07.2013. Available from: http://patentscope.wipo.int/search/en/detail.jsf?docId=WO2013073210&recNum=290&maxRec=80502&off ice=&prevFilter=&sortOption=&queryString=pa%2Funiversity&tab=FullText - 0012.

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24

Accepted Article

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25

Accepted Article

[55] Sethi AS, Peine WJ, Mohammadi Y, Sundaram CP. Validation of a novel virtual reality robotic simulator. J Endourol. 2009 Mar;23(3):503-8. PubMed PMID: 19265469. [56] Kenney PA, Wszolek MF, Gould JJ, Libertino JA, Moinzadeh A. Face, content, and construct validity of dV-trainer, a novel virtual reality simulator for robotic surgery. Urology. 2009 Jun;73(6):1288-92. PubMed PMID: 19362352. [57] Korets R, Mues AC, Graversen JA, Gupta M, Benson MC, Cooper KL, et al. Validating the use of the Mimic dV-trainer for robotic surgery skill acquisition among urology residents. Urology. 2011 Dec;78(6):1326-30. PubMed PMID: 22001096. [58] Liss MA, Abdelshehid C, Quach S, Lusch A, Graversen J, Landman J, et al. Validation, correlation, and comparison of the da Vinci trainer() and the daVinci surgical skills simulator() using the Mimic() software for urologic robotic surgical education. J Endourol. 2012 Dec;26(12):1629-34. PubMed PMID: 22845173. [59] Hung AJ, Zehnder P, Patil MB, Cai J, Ng CK, Aron M, et al. Face, content and construct validity of a novel robotic surgery simulator. J Urol. 2011 Sep;186(3):1019-24. PubMed PMID: 21784469. [60] Hung AJ, Patil MB, Zehnder P, Cai J, Ng CK, Aron M, et al. Concurrent and predictive validation of a novel robotic surgery simulator: a prospective, randomized study. J Urol. 2012 Feb;187(2):630-7. PubMed PMID: 22177176. [61] Seixas-Mikelus SA, Kesavadas T, Srimathveeravalli G, Chandrasekhar R, Wilding GE, Guru KA. Face validation of a novel robotic surgical simulator. Urology. 2010 Aug;76(2):357-60. PubMed PMID: 20299081. [62] Seixas-Mikelus SA, Stegemann AP, Kesavadas T, Srimathveeravalli G, Sathyaseelan G, Chandrasekhar R, et al. Content validation of a novel robotic surgical simulator. BJU Int. 2011 Apr;107(7):1130-5. PubMed PMID: 21029316. [63] Chou DS, Abdelshehid C, Clayman RV, McDougall EM. Comparison of results of virtual-reality simulator and training model for basic ureteroscopy training. J Endourol. 2006 Apr;20(4):266-71. PubMed PMID: 16646655. [64] Kesavadas T, Stegemann A, Sathyaseelan G, Chowriappa A, Srimathveeravalli G, Seixas-Mikelus S, et al. Validation of Robotic Surgery Simulator (RoSS). Studies in health technology and informatics. 2011;163:274-6. PubMed PMID: 21335803. [65] Ahmed K, Chowriappa A, Din R, Field E, Shi Y, Wilding G, et al. A Multi-Institutional Randomized Controlled Trial of an Augmented-Reality Based Technical Skill Acquisition Module for Robot-Assisted Urethro-Vesical Anastomosis. J Urol. 2013;189(4):e643. [66] Schreuder HW, Wolswijk R, Zweemer RP, Schijven MP, Verheijen RH. Training and learning robotic surgery, time for a more structured approach: a systematic review. BJOG. 2012 Jan;119(2):137-49. PubMed PMID: 21981104. [67] Mundy AR. The future of urology. BJU Int. 2003 Sep;92(4):337-9. PubMed PMID: 12930411. [68] Manuel Palazuelos C, Alonso Martin J, Martin Parra JI, Gomez Ruiz M, Maestre JM, Redondo Figuero C, et al. Effects of surgical simulation on the implementation of laparoscopic colorectal procedures. Cirugia espanola. 2013 Sep 20. PubMed PMID: This article is protected by copyright. all rights reserved.

26

Accepted Article

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This article is protected by copyright. all rights reserved.

27

Accepted Article

[81] Blaschko SD, Brooks HM, Dhuy SM, Charest-Shell C, Clayman RV, McDougall EM. Coordinated multiple cadaver use for minimally invasive surgical training. JSLS. 2007 OctDec;11(4):403-7. PubMed PMID: 18237501. Pubmed Central PMCID: 3015855. [82] Van Bruwaene S, De Win G, Miserez M. How much do we need experts during laparoscopic suturing training? Surg Endosc. 2009 Dec;23(12):2755-61. PubMed PMID: 19444512. [83]

Limbs & Things UK. Bristol TURP Trainer 2003 [cited 2013 14.04.]. Available from: http://limbsandthings.com/uk/products/bristol-turp-trainer/. [84]

Simbionix. VirtaMed TURPSim. Available from: http://simbionix.com/simulators/virtamed-

turpsim/.

[85]

HelSim.

SurgicalSIM

TURP.

Available

from:

http://www.hellenic-

simulations.com/TURP.html.

[86]

Simulated

Surgical

Systems.

RoSS.

Available

from:

http://www.simulatedsurgicals.com/what-is-ross.htm.

[87]

Intuitive

Surgical.

da

Vinci

Sikills

Simulator.

Available

from:

http://www.intuitivesurgical.com/products/skills_simulator/.

This article is protected by copyright. all rights reserved.

28

Accepted Article

TABLE LEGENDS Table 1: Validated Simulation Models for Prostate Surgery

RALP:

Robot-assisted

laparoscopic

prostatectomy;

LRP:

Laparoscopic

Radical

Prostatectomy; VR: Virtual Reality; DS: Distributed Simulation.

This article is protected by copyright. all rights reserved.

29

Accepted Article

FIGURE LEGENDS

Figure 1: Definitions of terms related to training and assessment [12, 13]

Figure 2: Images of the available prostate simulators A: Bristol TURP Trainer [83]; B: Holmium Laser Surgery Simulator [36]; C: TRULase Prostate [35]; D: GreenLight SIM [29]; E: TURPSim [84]: F: SurgicalSIM® TURP [85]; G: RoSS [86]; H: dVSS [87].

Figure 3: High fidelity full immersion TURP simulation at Guy’s Hospital / King’s College London [27]

Figure 4: An overview of TURP, HoLEP and GreenLight simulation training at Guy’s

Hospital / King’s College London. A: The GreenLight Simulator, B: Bristol TURP Model, C:

Holmium Laser Surgery Simulator, D: TURPSim.

This article is protected by copyright. all rights reserved.

30

Accepted Article

Table 1: Validated Simulation Models for Prostate Surgery

Simulator

Type of Model

Type of Validation Studies Face

Content

Construct

TURP

Bristol TURP Trainer, Bench Limbs & Things, UK

✓

✓

✓

Brewin et al. [16]

University College London, London UK

VR

-

✓

-

Ballaro et al. [17]

University Hospital Linkoping, Sweden

VR

-

✓

✓

Kallstrom et al. [18]

✓

✓

✓

Sweet et al. [19]

-

-

✓

Rashid et al. [20]

-

-

✓

Hudak et al. [21]

✓

✓

✓

✓

✓

Bright et al. [23]

University of Washington, Seattle, WA, USA

VR

TURPSim, VirtaMed, Switzerland

VR

The Igloo, London, UK

DS

✓

✓

✓

Brewin et al. [27]

VR

✓

✓

✓

Herlemann et al. [31]

The Chicken Chest Model

Animal

-

-

✓

Laguna et al. [44]

The Chicken Skin Model

Animal

-

✓

✓

Yang & Bellman [47]

The Pig Intestine Model

Animal

-

-

✓

Boon et al. [49]

✓

✓

✓

Lendvay et al. [54]

✓

✓

✓

Sethi et al. [55]

✓

✓

✓

Kenney et al. [56]

Zhu et al. [22]

Laser Therapies GreenLight SIM, American Medical Systems Inc, Minnetonka, MN, USA LRP

RALP

MdVT™, MIMIC Technologies, Seattle, WA, USA

VR

This article is protected by copyright. all rights reserved.

31

Accepted Article

Da Vinci Skills Simulator

Robotic Surgery Simulator, RoSS

HoST UrethroVesical Anastomosis Module

RALP:

Robot-assisted

VR

✓

-

✓

Korets et al. [57]

-

✓

✓

Liss et al. [58]

✓

✓

✓

Hung et al. [60]

✓

-

-

Seixas-Mikelus et al. [61]

-

✓

-

Seixas-Mikelus et al. [62]

✓

-

✓

Ahmed et al. [65]

VR

VR

laparoscopic

prostatectomy;

LRP:

Laparoscopic

Radical

Prostatectomy; VR: Virtual Reality; DS: Distributed Simulation.

This article is protected by copyright. all rights reserved.

32

Accepted Article

Figure 1: Definitions of terms related to training and assessment [12, 13]

Validity

 Face validity - Extent to which the examination resembles the situation in the real world

 Content validity - Extent to which the intended content domain is being measured by the assessment exercise

 Construct validity - Extent to which a test is able to differentiate between a good and bad performer or >2 groups of performers (eg, experienced vs inexperienced)

 Concurrent validity - Extent to which the results of the test correlate with gold standard tests known to measure the same domain

 Predictive validity - Extent to which this assessment will predict future performance

Reliability

 Inter-rater reliability - Extent of agreement between >2 assessors/observers through correlation between 2 blinded/nonblinded assessors

 Inter-item reliability - Extent to which different components of a test correlate (internal consistency) through correlation of test items

 Inter-test reliability - Ability of a test to generate similar results when applied at 2 different time points through correlations between test and retest

Acceptability - Extent to which an assessment procedure is accepted by the subjects involved in the assessment Feasibility – Extent to which a training and assessment process is capable of being carried out Educational impact - Extent to which test results and feedback contribute to improve the learning strategy on behalf of the trainer and the trainee Cost effectiveness - Does the assessment tool provide maximum value for money

This article is protected by copyright. all rights reserved.

33

Accepted Article

bju_12721_f2

bju_12721_f3 This article is protected by copyright. all rights reserved.

34

Accepted Article This article is protected by copyright. all rights reserved.

35