Ebook: Medicine Meets Virtual Reality 19

When treating their patients, physicians confront a living system that is astoundingly complex, with checks and balances that are incompletely understood, and sensitive to pain. Technologists, on the other hand, work with man-made objects within the less emotional domains of materials and mathematics, creating anew or building upon prior work as creativity inspires and economics allow. The former juggles individual make-up with personal histories and emotional ramifications; the latter can take a good outcome and multiply it with industrial production methods. To a programmer and a surgeon, for example, “crisis” and “success” necessarily imply very different scenarios.

In spite of those inherent differences, for two decades MMVR has helped bridge gaps between doctors and engineers—biology versus physics, clinic versus lab bench, and patient versus device. At MMVR, two professional cultures, with their respective methods and idioms, unite with a singular goal: to improve healthcare by creating new solutions to old healthcare problems. Informatics stirs up medicine's traditionalism, as modeling, simulation, visualization, sensors, robotics, data networks, and other informatics-enabled applications let doctors approach the human body with fresh understanding.

It has been a pleasure to work with so many creative and industrious researchers during the organization of this year's conference. During a time when political and economic experts seem unable to find solutions to pressing global problems, it is encouraging to be part of a culture that, even when experts disagree, is notable for its civility, enthusiasm, and ability to keep in mind shared goals.

Thanks to all of you who have made possible another edition of the MMVR/NextMed proceedings.

James D. Westwood

Aligned Management Associates, Inc.

The meshless element-free Galerkin method was generalized and an algorithm was developed for 3D dynamic modeling of deformable bodies in real time. The efficacy of the algorithm was investigated in a 3D linear viscoelastic model of human spleen subjected to a time-varying compressive force exerted by a surgical grasper. The model remained stable in spite of the considerably large deformations occurred. There was a good agreement between the results and those of an equivalent finite element model. The computational cost, however, was much lower, enabling the proposed algorithm to be effectively used in real-time applications.

In this paper, a 4-DOF robotic arm for tool handling in laparoscopic surgery is introduced. The robot provides sufficient force to handle endoscopic tools used for large organ manipulation and is capable of measuring the tool-tissue forces. The RCM constraint is achieved using a spherical mechanism and roll and insertion motions are provided using time pulley and spindle-drive, respectively. The forward and inverse kinematics of the robot was solved and the dimensions of its links were determined, using particle swarm optimization method, so that the maximum kinematic and dynamic performance could be achieved.

Awake surgery can be highly stressful for patients. In fact, being awake, patients could perceive that the environmental demands are taxing or exceed their adaptive abilities. We proposed the use of Virtual Reality as a functional and effective tool for a new class of clinical applications aimed at helping patients to cope with these specific stressful situations. Using coping skills that have been learnt during the virtual experience, patients can reduce their psychological stress and improve their collaboration and - in general - the outcome of the intervention.

The aim of this work is to increase the effectiveness of real world medical training simulations by helping trainees gain a better understanding of the importance of communication and teamwork. Therefore we develop an online application which can be used together with real world simulations to improve training. To produce the online application we reconstructed two real world scenarios (one with students and one with practitioners) in an immersive virtual environment. Our application enables the trainees to view the scenario from different perspectives or to freely explore the environment. We aim to integrate it into the medical student curriculum at the University of Tübingen.

Physicians' biases for skin color and obesity may negatively affect health-care outcomes. Identification of these biases is the first step to address the problem. We randomized 128 U.S medical students into one of four animated videos of avatar physician–patient counseling sessions, varying the weight and skin color of an elderly patient avatar: white-thin, black-thin, white-obese and black-obese. Medical students viewed white obese avatars as unattractive, ugly, noncompliant, lazy, and sloppy. Medical students' comments suggested a paternalistic attitude toward avatar patients. Avatar-mediated experiences can elicit medical students' bias potentially enabling medical educators to implement bias reduction interventions.

Features like size, shape, and volume of red blood cells are important factors in diagnosing related blood disorders such as iron deficiency and anemia. This paper proposes a method to detect abnormality in red blood cells using cell microscopic images. Adaptive local thresholding and bounding box methods are used to extract inner and outer diameters of red cells. An adaptive network-based fuzzy inference system (ANFIS) is used to classify blood samples to normal and abnormal. Accuracy of the proposed method and area under ROC curve are 96.6% and 0.9950 respectively.

A prototype version of the ImmersiveTouch® virtual reality simulator was applied to capsulorhexis, the creation of circular tear or “rhexis” in the lens capsule of the eye during cataract surgery. Virtual and live surgery scores by residents were compared. The same three metrics are used in each mode: circularity of the rhexis, duration of surgery (sec), and number of forceps grabs of the capsule per completed rhexis (fewer is better). The average simulator circularity score correlated closely with the average live score (P = 0.0002; N = 4), establishing “concurrent validity” for this metric. Individuals performed similarly to each other in both modes, as shown by the low standard deviations for average circularity (virtual 0.92 ± 0.04; live 0.88 ± 0.04). By contrast, the standard deviations are high for the other two metrics, capsulorhexis duration (virtual 96.91 ± 44.23 sec; live 94.42 ± 65.74 sec, N = 8) and number of forceps grabs (virtual 10.66 ± 4.81; live 10.31 ± 5.23, N = 8). Nevertheless, the simulator was able to demonstrate that the surgeons with wide variations in total duration and number of capsular grabs in 2 to 4 trials of simulated surgery also had similar variations in live surgery, so that the simulator retains some realism or “face validity.”

Having introduced NeuroSim, the prototype of a neurosurgical training simulator at MMVR18, we present our first medical training module. NeuroSim is based on virtual reality and uses real-time algorithms for simulating tissue. It provides a native interface by using a real surgical microscope and original instruments. Having implemented some abstract tasks to train basic skills like hand-eye coordination or the handling of the microscope last year, we now present a medical module where an aneurysm has to be clipped. NeuroSim has been developed in cooperation with the neurosurgical clinic of the University of Heidelberg and VRmagic GmbH in Mannheim.

We have developed a distributed, standards-based architecture that enables simulation and simulator designers to leverage adaptive learning systems. Our approach, which incorporates an electronic competency record, open source LMS, and open source microcontroller hardware, is a low-cost, pragmatic option to integrating simulators with traditional courseware.

This paper presents an extension visual attention maps for volume data visualization, where eye fixation points become rays in the 3D space, and the visual attention map becomes a volume. This Volume Visual Attention Map (VVAM) is used to interactively enhance a ray-casting based direct volume rendering (DVR) visualization. The practical application of this idea into the biomedical image visualization field is explored for interactive visualization.

In current research, haptic feedback in robot assisted interventions plays an important role. However most approaches to haptic feedback only regard the mapping of the current forces at the surgical instrument to the haptic input devices, whereas surgeons demand a combination of medical imaging and telemanipulated robotic setups. In this paper we describe how this feature is integrated in our robotic research platform OP:Sense. The proposed method allows the automatic transfer of segmented imaging data to the haptic renderer and therefore allows enriching the haptic feedback with virtual fixtures based on imaging data. Anatomical structures are extracted from pre-operative generated medical images or virtual walls are defined by the surgeon inside the imaging data. Combining real forces with virtual fixtures can guide the surgeon to the regions of interest as well as helps to prevent the risk of damage to critical structures inside the patient. We believe that the combination of medical imaging and telemanipulation is a crucial step for the next generation of MIRS-systems.

Robotic surgery, i.e. master-slave telemanipulators for surgery, is rapidly developing. One of the key components is the surgeon's console, and, within the console, especially the “handles” (the “joysticks”) for manipulation control. Two examples of haptic (force-feedback) handle designs developed and realized at the LSRO lab are briefly presented along with design considerations (ergonomics, usability). Incidence on patient safety and patient benefit and future trends in this field are hinted at, especially the possibilities offered VR in this context.

The Medical Seminar (MEDSEM) is a medical operation that shares culturally appropriate medical information with a defined indigenous population based upon a “train the trainer” concept. This work describes the development of a hand washing training toolkit designed to support a MEDSEM action in Afghanistan.

The hemorrhagic airway makes visualization during laryngoscopy and intubation difficult. A specially designed videolaryngoscope blade with integrated suction was developed and studied in a simulated hemorrhagic airway at the Omaha VA Medical Center. Results show that, if available, many users would choose to include this new suction device in their standard airway carts due to its “always there” design.

The preoperative evaluation is vital in providing information to reduce the risks associated with the anesthesia and surgery and improve the quality of care. In the VA Nebraska-Western Iowa Health Care System, we introduced a computer-based cardiac algorithm as part of the preoperative evaluation software. Following the pre-op examination and use of the algorithm, the provider completed a survey regarding their perceived usefulness of the algorithm software. The survey results showed that effective preoperative evaluation can be performed using a preoperative evaluation clinic, users are receptive to the computer-based format and, in most cases, prefer to have the algorithm software available for use in preoperative assessment.

In image-guided surgery, a new generation of Computer-Assisted-Surgical (CAS) systems based on information from the Operating Room (OR) has recently been developed to improve situation awareness in the OR. Our main project is to develop an application-dependant framework able to extract high-level tasks (surgical phases) using microscope videos data only. In this paper, we present two methods: one method to segment the pupil and one to extract and recognize surgical tools. We show how both methods improve the accuracy of the framework for analysis of cataract surgery videos, to detect eight surgical phases.

As one of the more difficult components of any curricula, neuroanatomy poses many challenges to students – not only because of the numerous discrete structures, but also due to the complicated spatial relations between them, which must be learned. Traditional anatomical education uses 2D images with a focus on dissection. This approach tends to underestimate the cognitive leaps required between textbook, lecture, and dissection cases. With reduced anatomical teaching time available, and varying student spatial abilities, new techniques are needed for training. The goal of this study is to assess the improvement of trainee understanding of 3D brain anatomy, orientation, visualization, and navigation through the use of digital training regimes in comparison with current methods. Two subsets of health science and medical students were tested individually after being given a group lecture and either a pre- or post-dissection digital lab. Results suggest that exposure to a 3D digital lab may improve knowledge acquisition and understanding by the students, particularly for first time learners.

Robotic surgical platforms require vision feedback systems, which often consist of low-resolution, expensive, single-imager analog cameras. These systems are retooled for 3D display by simply doubling the cameras and outboard control units. Here, a fully-integrated digital stereoscopic video camera employing high-definition sensors and a class-compliant USB video interface is presented. This system can be used with low-cost PC hardware and consumer-level 3D displays for tele-medical surgical applications including military medical support, disaster relief, and space exploration.

This pilot study explored the use of tensiometry as a measure of retention of knot tying skills. Medical students learned a one-handed square knot tying technique. Their final performances were video recorded and these videos were uploaded on to a website. Students were divided into two groups: an observational learning group that had access to videos before a retention test, and a control group that did not. After a two-week retention period, all students came back and performed one more trial to test the amount of retention of the skill. Tensiometry was used to measure strengths of the knots before and after the retention period. The scores showed no significant difference between the groups (p>0.308) or tests (p>0.737). We interpret the results to suggest that tensiometry is not sensitive enough to detect degradation in the performance of fundamental clinical skills as they are forgotten after being taught.

In this study we consider neurophysiological aspects for the assessment of stress-related disorders. EEG Alpha Asymmetry could represent an effective method to be used in the virtual environment. Nonetheless, new protocols need to be defined. In this study herein, we present two methods and a case study.

Virtual Basic Laparoscopic Skills Trainer (VBLaST) is a virtual reality trainer that replicates the Fundamentals of Laparoscopic Surgery (FLS) tasks for training in minimally invasive surgery. For the ligation loop task, we have developed a novel hardware interface using a linear motion stroke potentiometer to accurately sense the linear translation of the ligation loop and a mechanism to attach the tool interface to a PHANToM Omni for force feedback. Testing shows that the interface provided a realistic feel and control of the loop similar to the endoloop device used in FLS ligation loop task.

Accurate measurement of tool motion in minimally invasive procedures is an essential component of proficiency assessment. This is particularly important to automate the scoring procedures in, e.g., the Fundamentals of Laparoscopic Surgery (FLS) trainer box. Existing techniques are bulky, require extensive modifications to the surgical tool or trocar mechanism and are expensive. In this work, we propose a new system - the ToolTrack™ consisting of an optical mouse sensor and a MEMS inertial unit that can be easily integrated with any laparoscopic tool, provide accurate and reliable sensing, is light weight and low cost.

Hepatectomies are resections in which segments of the liver are extracted. While medical images are fundamental in the surgery planning procedure, the process of analysis of such images slice-by-slice is still tedious and inefficient. In this work we propose a strategy to efficiently and semi-automatically segment and classify patient-specific liver models in 3D through a mobile display device. The method is based on volume visualization of standard CT datasets and allows accurate estimation of functional remaining liver volume. Experiments showing effectiveness of the method are presented, and quantitative and qualitative results are discussed.

Numerous models have been developed to describe the mechanical behavior of soft tissue in virtual reality medical environments. Very high credibility must be established before clinicians trust these simulations for diagnostic or treatment. Validating models to obtain the right compromise between accuracy and computational efficiency for the targeted medical application is a long, costly and time-consuming task. We have developed a freely available open-source framework for helping scientists in the difficult problem of evaluating and comparing biomechanical models in a more systematic and automatic manner.