virtual reality simulator_padilla

Virtual Reality Simulator of TransurethralResection of the Prostate

M.A. Padilla, S. Teodoro, E. Lira, D. Soriano, F. Altamirano & F. Arámbula

Image Analysis and Visualization Lab., CCADET, UNAM, México, D.F., 04510

[email protected]

Abstract—In this work we present the current state of development of a virtual reality surgery simulation system for training Transurethral Resection of the Prostate (TURP). The prototype consist on a virtual environment of part of the urinary system which includes 3D models of the bladder, the prostate and the pennile urethra. The system simulates in real-time the endoscopic view of the resectoscope, allows realistic virtual navigation and exploration inside the anatomic structures of the virtual patient. The simulator includes a deformable tissue model of the prostate in order to simulate tissue resection and deformation. The interaction between the trainee and the system is done with a mechatronic interface that emulates a real resectosope and allows to perform the most important movements of the surgical tool during a TURP. We are currently working in incorporating tactile feedback to the interface by adapting an haptic robot device to the mechanism.

Keywords- Transuretral resection of the prostate;Computerized surgery simulation and training.

I. INTRODUCTION The prostate gland is located next to the bladder in human males, with the urethra running from the bladder neck through the prostate to the penile urethra (Fig. 1). A frequent condition in men above 50 years old is the benign enlargement of the prostate known as Benign Prostatic Hyperplasia (BHP), which in some cases results in significant blockage of the urinary flow. The standard surgical procedure to treat a hypertrophied prostate gland is the Transurethral Resection of the Prostate (TURP). It essentially consists of the removal of the inner lobes of the prostate in order to relieve urinary outflow obstruction. Mastering the Transurethral Resection of the Prostate (TURP) technique requires a highly developed handeye coordination which enables the surgeon to orientate inside the prostate, using only the monocular view of the lens of the resectoscope. Currently TURP is taught through example from an experienced surgeon. The resident of urology has very restricted opportunity to practice the procedure.In [1, 2] we reported the development a 3D deformable volumetric model of the prostate for TURP simulation that involves tissue deformation and resection, considering the gland as a viscoelastic solid. In this work we describe the development of the virtual environment

Figure 1: Top) Prostate position and resectoscope interaction in TURP. Bottom) Endoscopic view of the prostate. and the resecting loop of the resectoscope.

which includes the full virtual TURP scenario and physical interaction between the simulator and the trainee. Section 2 of this paper describes the interaction scheme between the virtual resectoscope interface and the user; section 3 describes the development of the virtual environment and tissue modelling. Finally in section 4 we present the conclusions and future perspectives of this work.

II.REAL TIME INTERACTION

In order to obtain a realistic simulation of the most important movements of the surgeon during a TURP, a mechanism was designed based on a disk-ring array (Fig. 2) [4]. We decided to reproduce only the five most important degrees, corresponding to movement axes. We ignore two additional translation degrees of the resectoscope sheath. In opinion of an expert

2009 Pan American Health Care Exchanges – PAHCE. Conference, Workshops, and Exhibits. Cooperation / Linkages. 2009 Intercambios de Cuidado Médico Panamericanos. Conferencia, Talleres y Exhibiciones. Cooperación / Enlaces.

March 16 - 20, 2009, Mexico City, Mexico 116 IEEE Catalog Number CFP0918G ISBN 978 - 1 - 4244 - 3669 - 9 Library of Congress 2008911781

Rubén Pérez

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978-1-4244-3669-9/09/$25.00 ©2009 IEEE

urologist, the five movements chosen are enough for having a realistic reproduction of the real movements during cistoscopies and TURP procedures. Three of these axes are rotational and the other two are linear displacements of the resectoscope. Optical encoders are used in order to sense each of the three rotational movements; the linear displacement of the surgical tool is measured with a linear precision potentiometer; the resecting loop movement is measured with a two linear Hall effect sensors array and two permanent magnets. Monitoring of the resectoscope movements are performed with an embedded electronic system consisting on five microcontrollers: four microcontrollers for digital signal monitoring of the optical sensors, for rotations; one more microcontroller for the analog signals of the linear potentiometer and hall-effect sensors, for translations.

Figure 2: View of the mechatronic device that emulates a real resectoscope.

The five microcontrollers in the embedded system run together in parallel in order to monitoring the movements in real time; the system sends the movements information in the form of moving commands to the virtual model. The real-time resectoscope movements consequently reflect the interaction between the surgeon and the tissue model. The interactions(tissue deformation and resection) between the virtual tool and the prostate model are consequence of the collision between them.

III.VIRTUAL ENVIRONMENT AND SOFT TISSUE MODELING We modeled the anatomical structures of the urinary system involved in TURP procedures: the bladder, the prostate and the pennile urethra in order to simulate virtual explorations (cistoscopies) and resections. The prostate mesh was reconstructed from a computer segmented transuretral ultrasound set of images of a real patient. Since computing tissue behaviour for the prostate is a demanding task that depends on the complexity of the mesh, we developed an adaptive reconstruction algorithm that modulates the resolution of the Delaunay tetrahedrization with respect to the 3D distance field of the external shape previously interpolated from the original stack of segmented contours (Fig. 3) [5], in order to have a visual realistic model but at the lowest possible

Figure 3: Prostate model: Top-left) Transurethral ultrasound imaging of the prostate; Top-right) Transverse annotated image set; Bottom) Graphic models of the prostate and the resecting loop;

mesh complexity for numerical computing. The pennile urethra and the virtual resectoscope consist on 3D surface meshes built with a 3D modeling software. The bladder consists also on a 3D triangular mesh reconstructed from segmented images of the Visible Human Dataset (Fig. 4).

Figure 4: Top) Tranvserse images of the visible human Project (VHP); Bottom) Bladder model constructed from the VHP data



We also modeled some other aspects of a real TURP with enough visual realism such: the endoscopic view from the resectocope, the ilumination of the resectoscope lamp and the tissue texture appereance by using procedural textures techniques, and the urethra sphincter (Fig. 6). Due to its simplicity we used a mass-spring method for modeling the deformable behaviour of the soft tissue. Since computing tissue deformation is another crucial demanding task we implemented the equation system solving on a GPU (Graphical Processing Unit) working in parallel with the CPU, in order to achieve real-time interactions. CPU-GPU parallel computing is sincronized with a multithreading scheme [6]. We developed a collision detection mechanism based on the representation of triangular meshes with hierarchical trees of bounding spheres. After a collision is detected between the resectoscope and the prostate the soft tissue must slightly deform before the tissue resection occurs. Tissue deformations result from the reacting forces due to collisions, where reacting forces are the forces needed to separate the penetrating objects and depends on the penetration depth and the mechanical properties of the soft model(Fig. 5). More details of the collision detection mechanism are available in [3]. For tissue resection we are currently developing a mechanism for local and real-time mesh refinement near the contact zone in order to reduce the decimation effect after tissue cutting. Tissue cutting is performed as two operations: removing geometrical elements within the cutting zone of the resecting loop and adding the inner triangles exposed by the cut.

Figure 5: Tissue deformations due to interaction with the resectoscope.

Figure 6: Virtual environment of TURP with endoscopic view from the head of the Resectoscope. Top) View of the pennile urethra ; Middel) View at the prostate entrance near the sphicter; Bottom) Inside view of the bladder.

IV.CONCLUSIONS AND FUTURE WORK

In this communication we reported the recent advances in the development of a computer simulator for RTU virtual training. Nowadays the system includes a real full scenario of TURP



and passive real-time interaction with a mechatronic interface similar to a real resectoscope, without force feedback.

Thanks to the GPU-CPU parallel multithreading computing scheme and the adaptive reconstruction method of the prostate, the simulator is able to run within a frame rate close to 30 Hz, which is quite acceptable for real-time interactions. We are currently working in enhancing the tissue resection mechanism using animation techniques for adding to the user the possibility of practicing tissue coagulation. We are also working in the design, development and instrumentation of a more precise and realistic mechatronic interface which will include the instrumentation of the pedals for controlling coagulation and resection. The new resectoscope interface will be adapted to work in conjuntion with in a PHANTOM haptic robotic arm (Sensable Technologies), in order to provide tactile feedback, as illustrated in Fig. 7.

Figure 7: Scheme for adapting the resectoscope interface with an haptic robot for tactile feedback.

We expect to have, in the near future, a full working prototype with resection and coagulation capabilities, including visual, tactile, and sound feedback, as well as the simulation of bleeders.

ACKNOWLEDGMENT

The authors are grateful to Dr. Sergio Durán, a urologist based at the National Institute of Rehabilitation in México, City. Dr Durán provided very useful comments and insight about TURP.

REFERENCES

[1] F. Arámbula, M.A. Padilla, P.R. Sevilla, “Computer assisted prostate surgery training”, International Journal of Humanoid Robotics, vol.3, pp.485-498, 2006.

[2] M.A. Padilla, F. Arámbula, “Deformable model of the prostate for TURP surgery simulation”, Computers and Graphics, vol. 28, pp.767-777, 2004.

[3] M.A. Padilla, F.Arámbula, “Improved collision detection algorithm for soft tissue deformable models”, 6th IEEE Mexican International Conf. on Computer Science, Pueble, México, pp.41-47, 2005.

[4] M.A. Padilla, F. Altamirano, F. Arámbula, “Virtual resectoscope interface for a surgery simulation training system of the prostate”, VRIPHYS 06, Madrid, Spain, pp.101-108, 2006.

[5] D. Soriano, “Generación de modelos de mallas de tetrahedros para simuladores quirúrgicos”, Tesis de Licenciatura, Facultad de Ingeniería, UNAM, 2008.

[6] E. Lira, “Implementación de un modelo de masas y resortes en un GPU para un simulador de cirugái de próstata”, Tesis de Licenciatura, Facultad de Ingeniería, UNAM, 2008.



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