Home /Research /V9-10 SIMULATED INANIMATE MODEL FOR PHYSICAL LEARNING EXPERIENCE (SIMPLE) FOR ROBOTIC PARTIAL NEPHRECTOMY USING A 3-D PRINTED KIDNEY MODEL
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V9-10 SIMULATED INANIMATE MODEL FOR PHYSICAL LEARNING EXPERIENCE (SIMPLE) FOR ROBOTIC PARTIAL NEPHRECTOMY USING A 3-D PRINTED KIDNEY MODEL

Ahmed Ghazi, Jonathan J. Stone, Braden Candela, Michael S. Richards, Jean Joseph

Year
2015
Citations
12

Abstract

You have accessJournal of UrologyRobotics – Renal1 Apr 2015V9-10 SIMULATED INANIMATE MODEL FOR PHYSICAL LEARNING EXPERIENCE (SIMPLE) FOR ROBOTIC PARTIAL NEPHRECTOMY USING A 3-D PRINTED KIDNEY MODEL Ahmed Ghazi, Jonathan Stone, Braden Candela, Michael Richards, and Jean Joseph Ahmed GhaziAhmed Ghazi More articles by this author , Jonathan StoneJonathan Stone More articles by this author , Braden CandelaBraden Candela More articles by this author , Michael RichardsMichael Richards More articles by this author , and Jean JosephJean Joseph More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2015.02.2285AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Live operative exposure remains the vanguard of surgical education. Surgical skills simulators have been successful in bridging gaps in training methods. In their current state however, they do not provide a complete operative experience. In this video we demonstrate a high fidelity, inexpensive, simulated inanimate model for physical learning experience in partial nephrectomy (SIMPLE-PN). Our realistic phantoms create a comprehensive operative experience that replicates all vital steps of a robot-assisted partial nephrectomy (RAPN) and permits measurement of procedure specific outcomes as metrics for assessment. METHODS Using a novel method, anatomically correct models of the human kidney and relevant structures were created using poly-vinyl alcohol (PVA) hydrogels. These are achieved through graded polymerization of the hydrogel by inducing crosslinks during freeze/thaw (FT) cycles. This stiffens the phantom organs to the desired consistency one would experience during live surgery. All steps of RAPN were simulated. 3 experts with >250 robotic upper-tract cases were assigned to group 1, 3 novices with < 50 robotic upper-tract cases were assigned to group 2, and 3 medical students that completed a basic skills robotic simulator curriculum were assigned to group 3. Face validity was calculated by ratings of realism. Content validity was calculated by experts' rating of usefulness of the model as a training tool. Construct validity was calculated by comparison of procedural metrics (ischemia time, blood loss, positive margins and estimated blood loss) between the three groups. RESULTS The model was determined to have good face and content validity with an average score of 3/5 and 4/5, respectively. Ischemia time remained <15 minutes, between 20 to 30 minutes and > 40 minutes in groups 1,2 and 3 respectively. A significant difference was demonstrated in overall operative time, ischemia time, and positive surgical margins and estimated blood loss (all values <0.01); yielding good construct validity. CONCLUSIONS SIMPLE provides a realistic, inexpensive, high fidelity model that offers comprehensive training for a RAPN. This form of simulation can be a useful surgical technique teaching tool, and allow objective trainee assessment. Validation for appearance and skill assessment was demonstrated using surveys and procedure specific metrics. This new model provides trainees adequate exposure to a simulated live environment to master skills necessary prior to a live operating room surgical experience. © 2015 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 193Issue 4SApril 2015Page: e778 Advertisement Copyright & Permissions© 2015 by American Urological Association Education and Research, Inc.MetricsAuthor Information Ahmed Ghazi More articles by this author Jonathan Stone More articles by this author Braden Candela More articles by this author Michael Richards More articles by this author Jean Joseph More articles by this author Expand All Advertisement Advertisement PDF DownloadLoading ...

Keywords

NephrectomyMedicineRobotSurgeryArtificial intelligenceMedical physicsKidneyComputer science

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