Comparison of CT-derived ventilation maps with deposition patterns of inhaled microspheres in rats. (1st April 2015)

• Record Type: Journal Article
• Authors: Jacob, Richard E.; Lamm, Wayne J.; Einstein, Daniel R.; Krueger, Melissa A.; Glenny, Robb W.; Corley, Richard A.
• Is Part Of: Experimental lung research. Volume 41:Number 3(2015:Mar.)
• Page Start: 135
• Page End: 145
• Publication Date: 2015-04-01
• Subjects: animal models -- CT imaging -- fluorescent microspheres -- lung -- particle deposition -- ventilation; Lungs -- Periodicals; Lungs -- Diseases -- Periodicals; Lung Diseases; Lung -- physiology; Respiratory System; 616.24
• DOI: 10.3109/01902148.2014.984085
• Languages: English
• ISSNs: 0190-2148

Abstract

ABSTRACT: Purpose : Computer models for inhalation toxicology and drug-aerosol delivery studies rely on ventilation pattern inputs for predictions of particle deposition and vapor uptake. However, changes in lung mechanics due to disease can impact airflow dynamics and model results. It has been demonstrated that non-invasive, in vivo, 4DCT imaging (3D imaging at multiple time points in the breathing cycle) can be used to map heterogeneities in ventilation patterns under healthy and disease conditions. The purpose of this study was to validate ventilation patterns measured from CT imaging by exposing the same rats to an aerosol of fluorescent microspheres (FMS) and examining particle deposition patterns using cryomicrotome imaging. Materials and Methods : Six male Sprague-Dawley rats were intratracheally instilled with elastase to a single lobe to induce a heterogeneous disease. After four weeks, rats were imaged over the breathing cycle by CT then immediately exposed to an aerosol of ∼1μm FMS for ∼5 minutes. After the exposure, the lungs were excised and prepared for cryomicrotome imaging, where a 3D image of FMS deposition was acquired using serial sectioning. Cryomicrotome images were spatially registered to match the live CT images to facilitate direct quantitative comparisons of FMS signal intensity with the CT-based ventilation maps. Results : Comparisons of fractional ventilation in contiguous, non-overlapping, 3D regions between CT-based ventilation maps and FMS images showed strong correlations in fractional ventilation ( r = 0.888, p < 0.0001). Conclusion : We conclude that ventilation maps derived from CT imaging are predictive of the 1μm aerosol deposition used in ventilation-perfusion heterogeneity inhalation studies.