Virtual trainer for intra-detrusor injection of botulinum toxin to treat urinary incontinence.

Here we introduce a new virtual reality (VR) based simulation system for training the urological procedure of intra-detrusor botulinum toxin (Botox®) injections into the bladder. 6 cases with different bladder anatomy and 3 subtasks are included in the curriculum; this design is guided by several expert urologists according to clinical needs and experience. These virtual bladder models can be deformed by a cystoscope model or penetrated by a needle model. Data of location and dose per injection are collected during the training. After compared among various options, magnetic motion-tracking devices are chosen and integrated onto replicas of cystoscopic instruments as the VR interface for the specific operation. A web/database based learning management platform (LMP) is developed for online data access and validation studies of the training system.

Phenomenological model of laser-tissue interaction with application to Benign Prostatic Hyperplasia (BPH) simulation.

Laser-tissue interaction is a multi-physics phenomenon not yet mathematically describable and computationally predictable. It is a challenge to model the laser-tissue interaction for real time laser Benign Prostatic Hyperplasia (BPH) simulation which requires the laser-tissue interaction model to be computationally efficient and accurate. Under the consideration and enforcement of the thermodynamic first law and treating the laser-tissue interaction as a gray-box, utilizing the sensitivity analysis of some key parameters that will affect the laser intensity on the tissue surface with respect to the tissue vaporization rate, a phenomenological model of laser-tissue interaction is developed. The developed laser-tissue interaction model has been implemented for a laser BPH simulator and achieves real time performance (more than 30 frames per second). The model agrees well with the available experimental data.

The Minnesota pelvic trainer: a hybrid VR/physical pelvis for providing virtual mentorship.

Obtaining accurate understanding of three dimensional structures and their relationships is important in learning human anatomy. To leverage the learning advantages of using both physical and virtual models, we built a hybrid platform consisting of virtual and mannequin pelvis, motion tracking interface, anatomy and pathology knowledge base. The virtual mentorship concept is to allow learners to conveniently manipulate and explore the virtual pelvic structures through the mannequin model and VR interface, and practice on anatomy identification tasks and pathology quizzes more intuitively and interactively than in a traditional self-study classroom, and to reduce the demands of access to dissection lab or wet lab.

Laser surgery simulation platform: toward full-procedure training and rehearsal for benign prostatic hyperplasia (BPH) therapy.

Recently, photo-selective vaporization of the prostate (PVP) has been a popular alternative to the standard electrocautery - transurethral resection of prostate (TURP). Here we introduce a new training system for practicing the laser therapy by using a virtual reality (VR) simulator. To interactively and realistically simulate PVP on a virtual organ with an order of a quarter million elements, a few novel and practical solutions have been applied to handle the challenges in modeling tissue ablation, contact/collision and deformation; endoscopic instruments tracking, haptic rendering and a web/database curriculum management module are integrated into the system. Over 40 urologists and surgical experts have been invited nationally and participated in the system verification.

Volumetric modeling in laser BPH therapy simulation.

In this paper, we introduce a novel application of volume modeling techniques on laser Benign Prostatic Hyperplasia (BPH) therapy simulation. The core technique in our system is an algorithm for simulating the tissue vaporization process by laser heating. Different from classical volume CSG operations, our technique takes experimental data as the guidance to determine the vaporization amount so that only a specified amount of tissue is vaporized in each time. Our algorithm uses a predictor-corrector strategy. First, we apply the classical CSG algorithm on a tetrahedral grid based distance field to estimate the vaporized tissue amount. Then, a volume-correction phase is applied on the distance field. To improve the performance, we further propose optimization approaches for efficient implementation.

A discrete mechanics framework for real time virtual surgical simulations with application to virtual laparoscopic nephrectomy.

The inability to render realistic soft-tissue behavior in real time has remained a barrier to face and content aspects of validity for many virtual reality surgical training systems. Biophysically based models are not only suitable for training purposes but also for patient-specific clinical applications, physiological modeling and surgical planning. When considering the existing approaches for modeling soft tissue for virtual reality surgical simulation, the computer graphics-based approach lacks predictive capability; the mass-spring model (MSM) based approach lacks biophysically realistic soft-tissue dynamic behavior; and the finite element method (FEM) approaches fail to meet the real-time requirement. The present development stems from physics fundamental thermodynamic first law; for a space discrete dynamic system directly formulates the space discrete but time continuous governing equation with embedded material constitutive relation and results in a discrete mechanics framework which possesses a unique balance between the computational efforts and the physically realistic soft-tissue dynamic behavior. We describe the development of the discrete mechanics framework with focused attention towards a virtual laparoscopic nephrectomy application.

Realistic soft tissue deformation strategies for real time surgery simulation.

A volume-preserving deformation method (VPDM) is developed in complement with the mass-spring method (MSM) to improve the deformation quality of the MSM to model soft tissue in surgical simulation. This method can also be implemented as a stand-alone model. The proposed VPDM satisfies the Newton's laws of motion by obtaining the resultant vectors form an equilibrium condition. The proposed method has been tested in virtual surgery systems with haptic rendering demands.

Physically accurate mesh simulation in a laparoscopic hernia surgery simulator.

In this paper we use the 2D angular spring based mass-spring-damper (AMSD) model to simulate the plastic mesh in a laparoscopic hernia surgery simulator. We propose a physically based method to systematically derive the optimal parameters of the 2D AMSD model. While the traditional 2D MSD model lacks resistance against bending, the 2D AMSD model with optimized parameters can provide correct bending resistance as well as stretching resistance. The simulated mesh is demonstrated to be much more realistic.

Selective tessellation algorithm for modeling interactions between surgical instruments and tissues.

We present a selective spatial tessellation algorithm that is specifically optimized for instrument-to-tissue and instrument-to-instrument collision detection cases, which are the essential part of interaction modeling in surgery simulation with haptic feedback. Virtual surgeries demand haptic rate collision solutions only when instruments are involved in collisions. Other collision cases can be processed at slower rates. The proposed selective tessellation algorithm is capable of differentiating among various collision cases and assigning different priorities to their processing. Without making assumptions about any object movement, the algorithm derives clipping volume as collision detection regions which tightly enclose the objects of interest. Results of implementation of the algorithm in a surgical simulation are provided.

A Motion Tracking and Sensor Fusion Module for Medical Simulation.

Here we introduce a motion tracking or navigation module for medical simulation systems. Our main contribution is a sensor fusion method for proximity or distance sensors integrated with inertial measurement unit (IMU). Since IMU rotation tracking has been widely studied, we focus on the position or trajectory tracking of the instrument moving freely within a given boundary. In our experiments, we have found that this module reliably tracks instrument motion.

A New Design for Airway Management Training with Mixed Reality and High Fidelity Modeling.

Restoring airway function is a vital task in many medical scenarios. Although various simulation tools have been available for learning such skills, recent research indicated that fidelity in simulating airway management deserves further improvements. In this study, we designed and implemented a new prototype for practicing relevant tasks including laryngoscopy, intubation and cricothyrotomy. A large amount of anatomical details or landmarks were meticulously selected and reconstructed from medical scans, and 3D-printed or molded to the airway intervention model. This training model was augmented by virtually and physically presented interactive modules, which are interoperable with motion tracking and sensor data feedback. Implementation results showed that this design is a feasible approach to develop higher fidelity airway models that can be integrated with mixed reality interfaces.

Haptic herniorrhaphy simulation with robust and fast collision detection algorithm.

Collision detection and soft tissue deformation are two major research challenges in real time VR based simulation, especially when haptic feedback is required. We have developed a real time collision detection algorithm for a prototype laparoscopic surgery trainer. However, this algorithm makes no assumptions about its applications and thus can be a generic solution to complicated collision detection problems. For soft tissue modeling, we use the mass-spring model enhanced with volume constraint and, stability control methods. We use both the new collision detection and tissue modeling algorithms in a bimanual hernia repair simulator which performs a mesh prosthesis stapling operation in real time.

Sparse Representation of Deformable 3D Organs with Spherical Harmonics and Structured Dictionary.

This paper proposed a novel algorithm to sparsely represent a deformable surface (SRDS) with low dimensionality based on spherical harmonic decomposition (SHD) and orthogonal subspace pursuit (OSP). The key idea in SRDS method is to identify the subspaces from a training data set in the transformed spherical harmonic domain and then cluster each deformation into the best-fit subspace for fast and accurate representation. This algorithm is also generalized into applications of organs with both interior and exterior surfaces. To test the feasibility, we first use the computer models to demonstrate that the proposed approach matches the accuracy of complex mathematical modeling techniques and then both ex vivo and in vivo experiments are conducted using 3D magnetic resonance imaging (MRI) scans for verification in practical settings. All results demonstrated that the proposed algorithm features sparse representation of deformable surfaces with low dimensionality and high accuracy. Specifically, the precision evaluated as maximum error distance between the reconstructed surface and the MRI ground truth is better than 3 mm in real MRI experiments.

Task deconstruction facilitates acquisition of transurethral resection of prostate skills on a virtual reality trainer.

AIM: To determine whether task deconstruction is superior to full-task training for the acquisition of transurethral resection skills on a transurethral resection of prostate (TURP) virtual reality trainer previously validated for use in residency training. METHODS: Eighteen first- and second-year medical students with no previous exposure to TURP in the operating room participated in the study. The subjects were randomized to two treatment arms: full-task TURP training versus task deconstruction training. A 5-minute full-task exercise was done as a pretest and posttest in both groups. Training time was held constant at 45 minutes for both groups. The first group practiced the full-task resection for 45 minutes, while the second group performed four deconstructed tasks for a total of 45 minutes. This comprised of cystoscopy and identification of anatomy, coagulation, cutting, and complete resection exercises. Statistical analysis was performed by the Mann-Whitney test. RESULTS: There was a significant difference in improvement comparing the pretest and posttest performance between the two groups, favoring task deconstruction over full-task training in the amount of tissue resected and grams resected/time on cutting pedal. There was no significant difference noted in number of bleeders coagulated, fluid consumed/gram resected, or bleeders coagulated/time on coagulation pedal. There was no difference in perforation rate between two groups. The mean approval rating of the curricular experience on the simulator was 4.0/5.0 in the task deconstruction group and 3.1/5.0 in the case of the full-task training group. CONCLUSION: For the acquisition of transurethral resection skills, task deconstruction is superior to full-task training alone, in training novices on the virtual reality TURP trainer. Such a study provides more validity evidence to the unique value of simulation in the urology minimally invasive curriculum.

A novel laparoscopic mesh placement part task trainer.

BACKGROUND: We present a surgical simulator, developed for the training of a laparoscopic surgery and in particular for mesh placement during an inguinal herniorrhaphy. METHODS: Major technical issues related to virtual surgery training systems include virtual patient modelling, collision detection and collision response, haptic and graphic rendering, 3-D motion tracking and some special effects, such as bleeding, cauterizing and so on. Among these problems, real-time deformation modelling and collision detection are the most challenging research topics. RESULTS: In this paper, we describe novel approaches addressing the above issues, which have been successfully adopted in our bimanual hernia repair simulator. CONCLUSION: The implementations of our new collision detection and deformation appear to work well, even at haptic rates for the limited scope of mesh placement training. More sophisticated techniques are needed for full organ deformation especially for blunt dissection simulation.