Small-Scale MDCT-Based Measures of Ventilation and Perfusion: the Development and Evaluation of New Tools for Examining the Etiology of Regional Lung Disease

• Main Author: Fuld, Matthew Kyle
• Other Authors: Hoffman, Eric A.
• Format: Others
• Language: English
• Published: University of Iowa 2012
• Subjects: COPD; DECT; Heterogeneity; Biomedical Engineering and Bioengineering
• Online Access: https://ir.uiowa.edu/etd/4846; https://ir.uiowa.edu/cgi/viewcontent.cgi?article=4846&context=etd

Pulmonary diseases are characterized by small-scale and large-scale alterations in structure and function of the lung. Multidetector-row computed tomography (MDCT) is a powerful tool for quantitatively assessing small-scale lung structure including parenchymal destruction, air trapping and airway remodeling. When combined with novel imaging techniques and contrast agents, measuring small-scale regional ventilation (rV̇A) and perfusion (rQ̇) also becomes possible. This thesis focuses on developing and evaluating MDCT-based tools for measuring regional lung function in animal models and transitioning them to studying humans. Wash-in xenon-CT rV̇A measurements acquired in an animal model were validated with inhaled fluorescent microspheres (FMS), an invasive but recognized gold standard. Xenon-CT correlated well with FMS, demonstrating similar gradients in prone and supine postures. Small-scale rV̇A measurements from xenon-CT were less susceptible to partial voluming and resulted in reduced scatter. To facilitate the measurement of regional structure and function on awake-free-breathing humans, we developed systems for lung volume standardization during scanning for both static and dynamic breathing. Anesthetic properties dictated using 30% rather than 55% xenon-gas, reducing signal-to-noise ratio. This reduction, in addition to the influence of free breathing, made xenon-CT more susceptible to noise and required additional post-processing to bolster confidence in rV̇A measurements acquired in humans. Improvements to the available curve-fit algorithms were made and 4D image registration was developed to align time-series datasets. Applying these techniques, we compared rV̇A between normal never-smokers (NS), normal smokers (SNI), normal smokers with early signs of centrilobular emphysema not evident by PFTs (SCE) and smokers with COPD. There was increased heterogeneity in SNI versus NS and time constants were lengthened in COPD and in SCE. This is consistent with our earlier hypothesis that while patchy inflammation will occur in all smokers, only a subset of the population with decreased rQ̇ in regions of inflammation stemming from a failure to block HPV will be susceptible to emphysema. In order to facilitate translation into the clinical research environment, we established dual-energy-CT (DECT) methods to replace more elaborate time-series laboratory-centered techniques. Xe-DECT rV̇A measures were optimized through a series of phantom and animal studies to determine the proper three-material decomposition parameters, imaging parameters, gas mixture and delivery protocol. DECT perfused blood volume was validated as a surrogate for rQ̇ in animal studies in which blood flow patterns were altered by increasing lung inflation or occluding a portion of the pulmonary vasculature. To examine the intricacy of lung function, the effects of disease, and give us insight into their etiology we must study gas-exchange on a small-scale. MDCT-based techniques provide the spatial resolution necessary to examine rV̇A and rQ̇ on a small-scale offering an avenue to identify novel phenotypes that may not only yield insights into disease processes but also may provide tools leading to drug and device developments, outcomes assessment and ultimately to the selection of subpopulations suitable for a particular intervention.