Tetrahedral Image-to-Mesh Conversion Software for Anatomic Modeling of Arteriovenous Malformations

We describe a new implementation of an adaptive multi-tissue tetrahedral mesh generator targeting anatomic modeling of Arteriovenous Malformation (AVM) for surgical simulations. Our method, initially constructs an adaptive Body-Centered Cubic (BCC) mesh of high quality elements. Then, it deforms the mesh surfaces to their corresponding physical image boundaries, hence, improving the mesh fidelity and smoothness. Our deformation scheme, which builds upon the ITK toolkit, is based on the concept of energy minimization, and relies on a multi-material point-based registration. It uses non-connectivity patterns to implicitly control the number of the extracted feature points needed for the registration, and thus, adjusts the trade-off between the achieved mesh fidelity and the deformation speed. While many medical imaging applications require robust mesh generation, there are few codes available to the public. We compare our implementation with two similar open-source image-to-mesh conversion codes: (1) Cleaver from US, and (2) CGAL from EU. Our evaluation is based on five isotropic/anisotropic segmented images, and relies on metrics like geometric & topologic fidelity, mesh quality, gradation and smoothness. The implementation we describe is open- source and it will be available within: (i) the 3D Slicer package for visualization and image analysis from Harvard Medical School, and (ii) an interactive simulator for neurosurgical procedures involving vasculature using SOFA, a framework for real-time medical simulation developed by INRIA

The Virtual Pediatric Airways Workbench

The Virtual Pediatric Airways Workbench (VPAW) is a patient-centered surgical planning software system targeted to pediatric patients with airway obstruction. VPAW provides an intuitive surgical planning interface for clinicians and supports quantitative analysis regarding prospective surgeries to aid clinicians deciding on potential surgical intervention. VPAW enables a full surgical planning pipeline, including importing DICOM images, segmenting the airway, interactive 3D editing of airway geometries to express potential surgical treatment planning options, and creating input files for offline geometric analysis and computational fluid dynamics simulations for evaluation of surgical outcomes. In this paper, we describe the VPAW system and its use in one case study with a clinician to successfully describe an intended surgery outcome

The interactive medical simulation toolkit (iMSTK): an open source platform for surgical simulation

Introduction: Human error is one of the leading causes of medical error. It is estimated that human error leads to between 250,000 and 440,000 deaths each year. Medical simulation has been shown to improve the skills and confidence of clinicians and reduce medical errors. Surgical simulation is critical for training surgeons in complicated procedures and can be particularly effective in skill retention.Methods: The interactive Medical Simulation Toolkit (iMSTK) is an open source platform with position-based dynamics, continuous collision detection, smooth particle hydrodynamics, integrated haptics, and compatibility with Unity and Unreal, among others. iMSTK provides a wide range of real-time simulation capabilities with a flexible open-source license (Apache 2.0) that encourages adoption across the research and commercial simulation communities. iMSTK uses extended position-based dynamics and an established collision and constraint implementations to model biological tissues and their interactions with medical tools and other tissues.Results: The platform demonstrates performance, that is, compatible with real-time simulation that incorporates both visualization and haptics. iMSTK has been used in a variety of virtual simulations, including for laparoscopic hiatal hernia surgery, laparoscopic cholecystectomy, osteotomy procedures, and kidney biopsy procedures.Discussion: iMSTK currently supports building simulations for a wide range of surgical scenarios. Future work includes expanding Unity support to make it easier to use and improving the speed of the computation to allow for larger scenes and finer meshes for larger surgical procedures

3D of brain shape and volume after cranial vault remodeling surgery for craniosynostosis correction in infants

ABSTRACT The skull of young children is made up of bony plates that enable growth. Craniosynostosis is a birth defect that causes one or more sutures on an infant's skull to close prematurely. Corrective surgery focuses on cranial and orbital rim shaping to return the skull to a more normal shape. Functional problems caused by craniosynostosis such as speech and motor delay can improve after surgical correction, but a post-surgical analysis of brain development in comparison with age-matched healthy controls is necessary to assess surgical outcome. Full brain segmentations obtained from pre-and post-operative computed tomography (CT) scans of 8 patients with single suture sagittal (n=5) and metopic (n=3), nonsyndromic craniosynostosis from 41 to 452 days-of-age were included in this study. Age-matched controls obtained via 4D acceleration-based regression of a cohort of 402 full brain segmentations from healthy controls magnetic resonance images (MRI) were also used for comparison (ages 38 to 825 days). 3D point-based models of patient and control cohorts were obtained using SPHARM-PDM shape analysis tool. From a full dataset of regressed shapes, 240 healthy regressed shapes between 30 and 588 days-of-age (time step = 2.34 days) were selected. Volumes and shape metrics were obtained for craniosynostosis and healthy age-matched subjects. Volumes and shape metrics in single suture craniosynostosis patients were larger than age-matched controls for pre-and post-surgery. The use of 3D shape and volumetric measurements show that brain growth is not normal in patients with single suture craniosynostosis

Identifying Opportunities for Virtual Reality Simulation in Surgical Education: A Review of the Proceedings from the Innovation, Design, and Emerging Alliances in Surgery (IDEAS) Conference: VR Surgery

To conduct a review of the state of virtual reality (VR) simulation technology, to identify areas of surgical education that have the greatest potential to benefit from it, and to identify challenges to implementation

Interactive Continuous Collision Detection for Topology Changing Models Using Dynamic Clustering

Figure 1 : This simulation is generated using finite element solver on a mesh with about 9K triangles [Tang et al. 2011b]. Our novel continuous collision detection (CCD) algorithm takes about 1.1 second (on average) on a single CPU core to perform all intra-object and self-collision queries. It is about 5X faster than prior CCD algorithms for deformable models. Abstract We present a fast algorithm for continuous collision detection between deformable models. Our approach performs no precomputation and can handle general triangulated models undergoing topological changes. We present a fast decomposition algorithm that represents the mesh boundary using hierarchical clusters and only needs to perform inter-cluster collision checks. The key idea is to compute such clusters quickly and merge them to generate a dynamic bounding volume hierarchy. The overall approach reduces the overhead of computing the hierarchy and also reduces the number of false positives. We highlight the the algorithm's performance on many complex benchmarks generated from medical simulations and crash analysis. In practice, we observe 1.4 to 5 times speedup over prior CCD algorithms for deformable models in our benchmarks

Calibration Software for Quantitative PET/CT Imaging Using Pocket Phantoms

Multicenter clinical trials that use positron emission tomography (PET) imaging frequently rely on stable bias in imaging biomarkers to assess drug effectiveness. Many well-documented factors cause variability in PET intensity values. Two of the largest scanner-dependent errors are scanner calibration and reconstructed image resolution variations. For clinical trials, an increase in measurement error significantly increases the number of patient scans needed. We aim to provide a robust quality assurance system using portable PET/computed tomography “pocket” phantoms and automated image analysis algorithms with the goal of reducing PET measurement variability. A set of the “pocket” phantoms was scanned with patients, affixed to the underside of a patient bed. Our software analyzed the obtained images and estimated the image parameters. The analysis consisted of 2 steps, automated phantom detection and estimation of PET image resolution and global bias. Performance of the algorithm was tested under variations in image bias, resolution, noise, and errors in the expected sphere size. A web-based application was implemented to deploy the image analysis pipeline in a cloud-based infrastructure to support multicenter data acquisition, under Software-as-a-Service (SaaS) model. The automated detection algorithm localized the phantom reliably. Simulation results showed stable behavior when image properties and input parameters were varied. The PET “pocket” phantom has the potential to reduce and/or check for standardized uptake value measurement errors