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Introduction

Abstract

Pulmonary dosimetry models provide quantitative information on the locations and amounts of deposition of inhaled toxins, both gaseous and particulate. The specification of location may be quite broad, as in an entire region (head, tracheobronchial airways, or parenchyma), or very specific, for example within each of the many generations of the tracheobronchial tree. The uses for such information include proper selection of laboratory animalspecies in toxicologic studies, refined interpretation of laboratory animal toxicologic data, and prediction of potential sites of high local-injury from inhaled materials. Further, dosimetry models tend to identify the roles of relevant factors in potential lung injury. Such relevant factors may be physical-chemical (particle size, gas water solubility, etc.), physiologic (air flow patterns, mucus characteristics, etc.), or anatomical (airway dimensions, branch angles, etc.).Predictive dosimetry models are of two major types, theoretical and empirical. In both types, the ultimate requirements for acceptability are the same; they must be realistic, must be validated, and must be of use in predicting whatwould occur in unexamined circumstances. Theoretical dosimetry models are constructs which usually begin with simplifications of the real world. Such simplifications occur in theselection of equations describing movement of gases and particles toward airway walls, use of manageable airflow descriptions, and incorporation of anatomical geometries that represent averages of actual lung morphology. Such models are later made more sophisticated by the incorporation of additional complexities.Empirical modeling usually involves analysis of dosimetric data obtained in constructed hollow models, or less often in actual lungs, which have been exposed to airborne materialunder conditions simulating breathing. The analysis of such data permits development of mathematical relationships that describe the distribution of material deposited. Such relationships are then used to predict deposition patterns in unstudied circumstances. In addition to their value for predicting dose patterns, the equations that result from theoretical and empirical models can shed light on the mechanisms which control such dose patterns. Knowledge regarding mechanism is a fuel which fires scientific inquiry, stimulating the design of future studies. © 1984 by Hemisphere Publishing Corporation.

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