Towards an advanced virtual ultrasound-guided renal biopsy trainer

Ultrasound (US)-guided renal biopsy is a critically important tool in the evaluation and management of non-malignant renal pathologies with diagnostic and prognostic significance. It requires a good biopsy technique and skill to safely and consistently obtain high yield biopsy samples for tissue analysis. This project aims to develop a virtual trainer to help clinicians to improve procedural skill competence in real-time ultrasound-guided renal biopsy. This paper presents a cost-effective, high-fidelity trainer built using low-cost hardware components and open source visualization and interactive simulation libraries: interactive medical simulation toolkit (iMSTK) and 3D Slicer. We used a physical mannequin to simulate the tactile feedback that trainees experience while scanning a real patient and to provide trainees with spatial awareness of the US scanning plane with respect to the patient’s anatomy. The ultrasound probe and biopsy needle were modeled using commonly used clinical tools and were instrumented to communicate with the simulator. 3D Slicer was used to visualize an image sliced from a pre-acquired 3-D ultrasound volume based on the location of the probe, with a realistic needle rendering. The simulation engine in iMSTK modeled the interaction between the needle and the virtual tissue to generate visual deformations on the tissue and tactile forces on the needle which are transmitted to the needle that the user holds. Initial testing has shown promising results with respect to quality of simulated images and system responsiveness. Further evaluation by clinicians is planned for the next stage.

[1]  Hang Si,et al.  TetGen, a Delaunay-Based Quality Tetrahedral Mesh Generator , 2015, ACM Trans. Math. Softw..

[2]  Raul N Uppot,et al.  Imaging-guided percutaneous renal biopsy: rationale and approach. , 2010, AJR. American journal of roentgenology.

[3]  Andreas Rieger,et al.  A Review of Computer-Based Simulators for Ultrasound Training , 2013, Simulation in healthcare : journal of the Society for Simulation in Healthcare.

[4]  M. Bridges,et al.  The financial impact of teaching surgical residents in the operating room. , 1999, American journal of surgery.

[5]  Gabor Fichtinger,et al.  OpenIGTLink: an open network protocol for image‐guided therapy environment , 2009, The international journal of medical robotics + computer assisted surgery : MRCAS.

[6]  S. S. Yesudas,et al.  Percutaneous real-time ultrasound-guided renal biopsy performed solely by nephrologists: A case series , 2010, Indian journal of nephrology.

[7]  Andrew P. Witkin,et al.  Large steps in cloth simulation , 1998, SIGGRAPH.

[8]  Uri M. Ascher,et al.  On the modified conjugate gradient method in cloth simulation , 2003, The Visual Computer.

[9]  J. Barsuk,et al.  Does Simulation-Based Medical Education With Deliberate Practice Yield Better Results Than Traditional Clinical Education? A Meta-Analytic Comparative Review of the Evidence , 2011, Academic medicine : journal of the Association of American Medical Colleges.

[10]  Katherine Slawsky,et al.  The clinical economics of ultrasound-guided procedures , 2011 .

[11]  George Shorten,et al.  Simulators for training in ultrasound guided procedures. , 2013, Medical ultrasonography.

[12]  Andras Lasso,et al.  Open-source platforms for navigated image-guided interventions , 2016, Medical Image Anal..

[13]  Milan Sonka,et al.  3D Slicer as an image computing platform for the Quantitative Imaging Network. , 2012, Magnetic resonance imaging.

[14]  Carlos A. Felippa,et al.  A unified formulation of small-strain corotational finite elements: I. Theory , 2005 .

[15]  Andras Lasso,et al.  PLUS: Open-Source Toolkit for Ultrasound-Guided Intervention Systems , 2014, IEEE Transactions on Biomedical Engineering.