|Subject Specific, Multiscale Simulation of Electrophysiology|
Over the past year the CIBC, in partnership with our collaborators, has begun to introduce a generalized processing pipeline and associated software to the biomedical community. This work has been largely influenced by DBP collaborators such as those collaborating to develop optimization strategies for ICD placement in children; Dr. John Triedman at the Department of Cardiology, Children's Hospital Boston, Dr. Matthew Jolley, Stanford University Medical Center. and Drs. Elizabeth Saarel, Tom Pilcher, and Michael Puchalski, all from the Department of Cardiology at Primary Childrens' Hospital in Salt Lake City. Additionally, collaborative work with the goal of the making osseointegrated amputee implants part of an electrical system to accelerate skeletal attachment also influenced the creation of the pipeline described below; collaborators are Brad Isaacson, Dr. Joseph Webster, Dr. James Beck, and Dr. Roy Bloebaum from the Department of Veteran Affairs and University of Utah.
Implementation of the pipeline
We have implemented within SCIRun several meshing and mesh refinement schemes based on hexahedral and tetrahedral elements and used them extensively in the example of simulation of cardiac defibrillation. Most of these meshing schemes start by overlaying a regular grid on top of the voxelized images and then turning them into a model by adding local refinements and boundaries based on the needs of the simulation. Although carrying out refinement to an existing mesh is a relatively straightforward task, it becomes much more challenging when maintaining good mesh quality, i.e. controlling the shape and size of the elements. In biological problems, meshes often require embedding of irregularly shaped boundaries of different tissue properties as well as adding local refinements for detailed simulations around biological sources. We have developed novel methods to approximate such features using hexahedral meshes that also allow the addition of irregular boundaries while still maintaining high mesh quality.
The key to benefitting from the bottom-up approach is creating efficient and flexible elemental pieces that can interact through simple passing of data via files. Pipeline structures, in general, lend themselves well to this concept and we have implemented image-based modeling pipelines from such elements. Elements of this strategy include ImageVis3D and Seg3D (www.seg3d.org), which provide volume rendering and segmentation capabilities, respectively. ImageVis3D is based on our own volume rendering capabilities and Seg3D uses tools from the ITK (www.itk.org) and has a relatively focused technical breadth. Seg3D reads stacks of images as a volume using standard file formats and provides a set of tools to identify different regions within the image volume and thus generate a 'label map' of the volume.
The nomenclature of both ImageVis3D and Seg3D is largely generic and not specific to any particular application domain and both are small programs, created within a year by a small team with the goal of facilitating rapid addition of new features or adjustments to the user interface. While these are separate programs, they integrate functionally into the workflow through files, which they can flexibly read and write.
In some applications, we have also used a second segmentation tool, 3D Slicer (www.slicer.org), which is part of the NA-MIC kit. Although Slicer is much more than a segmentation program, it is also portable and flexible enough to serve as a dedicated segmentation tool in the simulation pipeline. Integration occurs, as with Seg3D, by means of compatible file formats using the Nearly Raw Raster Data (NRRD) format and the associated TEEM toolkit for accessing and writing NRRD files.
Another component of all our tetrahedral mesh generation pipelines is TETGEN (tetgen.berlios.de), at the moment the most effective and robust open-source tetrahedral mesh generation program, especially for cases with multiple embedded surfaces. It is this ability to deal effectively with the internal boundaries between regions of different characteristics (e.g. electrical conductivity or optical opacity) and to maintain the integrity of outer boundaries, especially when they are concave, which are essential and challenging requirements for applications in biomedicine. Additionally, we recently outlined the details of a new mesh generation tool, BioMesh3D, which includes support for both hexahedral and tetrahedral mesh elements. BioMesh3D makes use of TETGEN and other meshing tools and handles the integration and user interface to modular programs and libraries.
In many areas of biomedical simulation there is the lack of available software, especially those in the public domain, to carry out all the steps of the simulation pipeline. A major goal of our research and development is to address this need and we have created a set of software tools that support simulation pipelines in at least a few application domains. Wherever possible, we have maintained a high level of generality in the software and the algorithms they combine; however, we propose that, in many situations, there are substantial benefits to adapting software to a particular application that outweighs the resulting inevitable loss of generality. Moreover, by striking a suitable balance between the generality of the simulation pipeline and the specific requirements of a problem domain, our experience suggests that one can achieve another major objective of contemporary biomedical simulation, which is creating subject-specific implementations of clinically relevant numerical simulations.
M. Callahan, M.J. Cole, J.F. Shepherd, J.G. Stinstra, C.R. Johnson. "A Meshing Pipeline for Biomedical Models," In Engineering with Computers, Vol. 25, No. 1, Note: DOI:10.1007/s00366-008-0106-1, SpringerLink, pp. 115-130. 2009.
R.S. MacLeod, J.G. Stinstra, S. Lew, R.T. Whitaker, D.J. Swenson, M.J. Cole, J. Krueger, D.H. Brooks, C.R. Johnson. "Subject-specific, multiscale simulation of electrophysiology: a software pipeline for image-based models and application examples," In Philosophical Transactions of The Royal Society A, Mathematical, Physical & Engineering Sciences, Vol. 367, No. 1896, pp. 2293--2310. 2009.