Erik Butterworth

JSim, an open-source modeling system for data analysis

JSim is a simulation system for developing models, designing experiments, and evaluating hypotheses on physiological and pharmacological systems through the testing of model solutions against data. It is designed for interactive, iterative manipulation of the model code, handling of multiple data sets and parameter sets, and for making comparisons among different models running simultaneously or separately. Interactive use is supported by a large collection of graphical user interfaces for model writing and compilation diagnostics, defining input functions, model runs, selection of algorithms solving ordinary and partial differential equations, run-time multidimensional graphics, parameter optimization (8 methods), sensitivity analysis, and Monte Carlo simulation for defining confidence ranges. JSim uses Mathematical Modeling Language (MML) a declarative syntax specifying algebraic and differential equations. Imperative constructs written in other languages (MATLAB, FORTRAN, C++, etc.) are accessed through procedure calls. MML syntax is simple, basically defining the parameters and variables, then writing the equations in a straightforward, easily read and understood mathematical form. This makes JSim good for teaching modeling as well as for model analysis for research. For high throughput applications, JSim can be run as a batch job. JSim can automatically translate models from the repositories for Systems Biology Markup Language (SBML) and CellML models. Stochastic modeling is supported. MML supports assigning physical units to constants and variables and automates checking dimensional balance as the first step in verification testing. Automatic unit scaling follows, e.g. seconds to minutes, if needed. The JSim Project File sets a standard for reproducible modeling analysis: it includes in one file everything for analyzing a set of experiments: the data, the models, the data fitting, and evaluation of parameter confidence ranges. JSim is open source; it and about 400 human readable open source physiological/biophysical models are available at http://www.physiome.org/jsim/.

Multiscale modeling of metabolism, flows, and exchanges in heterogeneous organs

Large‐scale models accounting for the processes supporting metabolism and function in an organ or tissue with a marked heterogeneity of flows and metabolic rates are computationally complex and tedious to compute. Their use in the analysis of data from positron emission tomography (PET) and magnetic resonance imaging (MRI) requires model reduction since the data are composed of concentration–time curves from hundreds of regions of interest (ROI) within the organ. Within each ROI, one must account for blood flow, intracapillary gradients in concentrations, transmembrane transport, and intracellular reactions. Using modular design, we configured a whole organ model, GENTEX, to allow adaptive usage for multiple reacting molecular species while omitting computation of unused components. The temporal and spatial resolution and the number of species are adaptable and the numerical accuracy and computational speed is adjustable during optimization runs, which increases accuracy and spatial resolution as convergence approaches. An application to the interpretation of PET image sequences after intravenous injection of 13NH3 provides functional image maps of regional myocardial blood flows.

SBML and CellML translation in Antimony and JSim

MOTIVATION The creation and exchange of biologically relevant models is of great interest to many researchers. When multiple standards are in use, models are more readily used and re-used if there exist robust translators between the various accepted formats. SUMMARY Antimony 2.4 and JSim 2.10 provide translation capabilities from their own formats to SBML and CellML. All provided unique challenges, stemming from differences in each formats inherent design, in addition to differences in functionality. AVAILABILITY AND IMPLEMENTATION Both programs are available under BSD licenses; Antimony from http://antimony.sourceforge.net/and JSim from http://physiome.org/jsim/. CONTACT lpsmith@u.washington.edu.

Error detection and unit conversion

The article discusses the accuracy mathematical modeling languages (MML) for biomedicine, for example in cardiac electrophysiology. Unit balance checking is showed that it can be automated. The implemented example is JSim (http://www.physiome.org/ jsim/), which is general and can be applied to other systems in which units can be specified and checked. ODE-based simulator Physiome CellML Environment is also discussed.

Quantitative imaging of coronary blood flow

Adam M. Alessio received his PhD in Electrical Engineering from the University of Notre Dame in 2003. During his graduate studies he developed tomographic reconstruction methods for correlated data and helped construct a high-resolution PET system. He is currently a Research Assistant Professor in Radiology at the University of Washington. His research interests focus on improved data processing and reconstruction algorithms for PET/CT systems with an emphasis on quantitative imaging. Erik Butterworth recieved the BA degree in Mathematics from the University of Chicago in 1977. Between 1977 and 1987 he worked as a computer programmer/analyst for several small commercial software firms. Since 1988, he has worked as a software engineer on various research projects at the University of Washington. Between 1988 and 1993 he developed a real-time data aquisition for the analysis of estuarine sediment transport in the department of Geophysics. Between 1988 and 2002 he developed I4, a system for the display and analysis of cardic PET images in the department of Cardiology. Since 1993 he has worked on physiological simulation systems (XSIM from 1993 to 1999, JSim since 1999) at the National Simulation Resource Facility in Cirulatory Mass Transport and Exchange, in the Department of Bioengineering. His research interests include simulation systems and medical imaging. James H. Caldwell, MD, University of Missouri-Columbia 1970, is Professor of Medicine (Cardiology) and Radiology and Adjunct Professor of Bioengineering at the University of Washington School of Medicine and Acting Head, Division of Cardiology and Director of Nuclear Cardiology for the University of Washington Hospitals, Seattle WA, USA. James B. Bassingthwaighte, MD, Toronto 1955, PhD Mayo Grad Sch Med 1964, was Professor of Physiology and of Medicine at Mayo Clinic until 1975 when he moved to the University of Washington to chair Bioengineering. He is Professor of Bioengineering and Radiology. In 1979, he established a National Simulation Resource Facility in Circulatory Mass Transport and Exchange and in 1997, he initiated the Human Physiome Projects. He is a member of the US National Academy of Engineering. His research is on quantitative integration of cellular and cardiovascular systems. Positron emission tomography (PET) is a nuclear medicine imaging modality based on the administration of a positron-emitting radiotracer, the imaging of the distribution and kinetics of the tracer, and the interpretation of the physiological events and their meaning with respect to health and disease. PET imaging was introduced in the 1970s and numerous advances in radiotracers and detection systems have enabled this modality to address a wide variety of clinical tasks, such as the detection of cancer, staging of Alzheimers disease, and assessment of coronary artery disease (CAD). This review provides a description of the logic and the logistics of the processes required for PET imaging and a discussion of its use in guiding the treatment of CAD. Finally, we outline prospects and limitations of nanoparticles as agents for PET imaging.