title: 3D in silico modeling of the human respiratory system for inhaled drug delivery and imaging analysis.
abstract: The efficacies of inhaled pharmacologic drugs could be improved if drugs could be targeted to appropriate sites within the human respiratory system. The spatial deposition patterns of particles can now be detected with a high degree of resolution using advanced techniques of imaging (e.g., SPECT). However, the effectiveness of such laboratory regimens has been limited by the inability to clearly identify airway composition within images. Therefore, we have developed a theoretical protocol to map airways within human lungs that is designed to be used in a complementary manner with laboratory investigations. The in silico model has two components: a mathematical model based on concepts of topology; and, a computer algorithm which tracks the millions of constituent lung airways. The in silico model produces 3D lung structures that are anatomically correct and can be customized to each patient. We have applied the protocol to a SPECT study where the interiors of lungs were partitioned into a series of ten nested shells. Airway composition in the respective shells provides a heretofore unavailable quantification of scintigraphy images. The protocol can be employed in a practical manner in the medical arena to aid in the interpretation of SPECT images, and to provide a platform for the design of human subject tests.
authors.affiliation: Department of Medicine, University of North Carolina, Chapel Hill, North Carolina 27514, USA.
authors.forename: T B
authors.initials: TB
authors.lastname: Martonen
authors.forename: J D
authors.initials: JD
authors.lastname: Schroeter
authors.forename: J S
authors.initials: JS
authors.lastname: Fleming
mesh_terms: D000280:Administration, Inhalation; D001249:Asthma / Q000188:drug therapy; D003920:Diabetes Mellitus / Q000188:drug therapy; D006801:Humans; D021621:Imaging, Three-Dimensional; D008168:Lung / Q000378:metabolism*; D008962:Models, Theoretical; D015899:Tomography, Emission-Computed, Single-Photon