Lynn L. Trease

Application of Magnetic Resonance (MR) Imaging for the Development and Validation of Computational Fluid Dynamic (CFD) Models of the Rat Respiratory System

Computational fluid dynamic (CFD) models of the respiratory system provide a quantitative basis for extrapolating the localized dose of inhaled materials and improving human health risk assessments based upon inhalation studies conducted in animals. Nevertheless, model development and validation have historically been tedious and time-consuming tasks. In recognition of this, we previously reported on the use of proton (1H) magnetic resonance (MR) imaging for visualizing nasal-sinus passages in the rat, and for speeding computational mesh generation. Here, the generation and refinement of meshes for rat nasal airways are described in more detail and simulated airflows are presented. To extend the CFD models to the complete respiratory tract, three-dimensional (3D) 1H MR imaging of rat pulmonary casts was also utilized to construct pulmonary airway meshes using procedures developed for the nasal airways. Furthermore, the feasibility of validating CFD predictions with MR was tested by imaging hyperpolarized 3He gas at physiological flow rates in a straight pipe with a diameter comparable to the rat trachea. Results from these diverse studies highlight the potential utility of MR imaging not only for speeding CFD development but also possibly for model validation.

Three-Dimensional Mapping of Ozone-Induced Injury in the Nasal Airways of Monkeys Using Magnetic Resonance Imaging and Morphometric Techniques

Age-related changes in gross and microscopic structure of the nasal cavity may alter local tissue susceptibility as well as the dose of inhaled toxicant delivered to susceptible sites. This article describes a novel method for the use of magnetic resonance imaging, 3-dimensional airway modeling, and morphometric techniques to characterize the distribution and magnitude of ozone-induced nasal injury in infant monkeys. Using this method, we generated age-specific, 3-dimensional, epithelial maps of the nasal airways of infant Rhesus macaques. The principal nasal lesions observed in this primate model of ozone-induced nasal toxicology were neutrophilic rhinitis, along with necrosis and exfoliation of the epithelium lining the anterior maxilloturbinate. These lesions, induced by acute or cyclic (episodic) exposures, were examined by light microscopy, quantified by morphometric techniques, and mapped on 3-dimensional models of the nasal airways. Here, we describe the histopathologic, imaging, and computational biology methods developed to precisely characterize, localize, quantify, and map these nasal lesions. By combining these techniques, the location and severity of the nasal epithelial injury were correlated with epithelial type, nasal airway geometry, and local biochemical and molecular changes on an individual animal basis. These correlations are critical for accurate predictive modeling of exposure-dose-response relationships in the nasal airways, and subsequent extrapolation of nasal findings in animals to humans for determining risk.

Potential Technology for Studying Dosimetry and Response to Airborne Chemical and Biological Pollutants

Advances in computational, and imaging techniques have enabled the rapid development of three-dimensional (3-D) models of biological systems in unprecedented detail. Using these advances, 3-D models of the lungs and nasal passages of the rat and human are being developed to ultimately improve predictions of airborne pollutant dosimetry. Techniques for imaging the respiratory tract by magnetic resonance imaging (MRI) were developed to improve the speed and accuracy of geometric data collection for mesh reconstruction. The MRI resolution is comparable to that obtained by manual measurements but at much greater speed and accuracy. Newly developed software (NWGrid) was utilized to translate imaging data from MR into 3-D mesh structures. Together, these approaches significantly reduced the time to develop a 3-D model. This more robust airway structure will ultimately facilitate modeling gas or vapor exchange between the respiratory tract and vasculature as well as enable linkages of dosimetry with cell response models. The 3-D, finite volume, viscoelastic mesh structures form the geometric basis for computational fluid dynamics modeling of inhalation, exhalation and the delivery of individual particles (or concentrations of gas or vapors) to discrete regions of the respiratory tract. The ability of these 3-D models to resolve dosimetry at such a high level of detail will require new techniques to measure regional airflows and particulate deposition for model validation.

Enabling Systems Biology: A Scientific Problem-Solving Environment

Biologists today are striving to solve multidisciplinary, complex systems biology questions. To successfully address these questions, software tools must be created to allow scientists to capture data and information, to share this information, and to analyze the data as elements of a complete system. At Pacific Northwest National Laboratory, we are creating the Computational Cell Environment, a biology-centered collaborative problem-solving environment with the goal of providing data retrieval, management, and analysis through all aspects of biological study. A horizontal prototype called SysBioPSE, demonstrates this vision. Our initial work is centered on developing the Distributed Data Management and Analysis subsystem, which is a specific tool for retrieving data from multiple heterogeneous data stores, providing storage facilities that support pedigree tracking and data and information analysis under a common user interface. With time, many such individual subsystems will be developed and integrated to fulfill the Computational Cell Environment vision.

Bioinformatics Approach for Exploring MS/MS Proteomics Data

The use of computer tools and technologies is unavoidable when it comes to conducting mass spectrometry (MS) research at any significant level. This is mainly due to the large volume of MS data and the processing rates required. Most of the existing tools focus on one particular task: be it storing and maintaining the data or visualizing the dataset to draw inferences from the data. But for the researcher the problem of manually retrieving a large dataset from a datasource and customizing it for a particular visualization application is a daunting task in itself. This paper describes the Computational Cell Environment (CCE) which is a problem-solving environment for systems biology that provides uniform and integrated access to distributed, heterogeneous biological data sources and analysis applications, through a multi-tiered architecture. This paper also illustrates the necessity for such a tool by discussing its usage in proteomics research being performed on the diseased and normal states of Deinococcus Radiodurans along with corresponding curated data collected from community resources.