Date of Degree
PhD (Doctor of Philosophy)
Eric A. Hoffman
The characterization of the normal pulmonary acinus is a necessary first step in understanding the nature of respiratory physiology and in assessing the etiology of pulmonary pathology. Murine models play a vital role in the advancement of current understanding of the dynamics of gas exchange, particle deposition and the manifestations of diseases such as COPD, Cystic Fibrosis and Asthma. With the advent of interior tomography techniques, high-resolution micro computed tomography (μCT) systems provide the ability to nondestructively assess the pulmonary acinus at micron and sub-micron resolutions. With the application of Systematic Uniform Random Sampling (SURS) principles applied to in-situ fixed, intact, ex-vivo lungs, we seek to characterize the structure of pulmonary acini in mice and study the variations across dimensions of age, location within the lung and strain phenotypes.
Lungs from mice of three common research strains were perfusion fixed in-situ, and imaged using a multi-resolution μCT system (Micro XCT 400, Zeiss Inc.). Using lower resolution whole lung images, SURS methods were used for identification of region-specific acini for high-resolution imaging. Acinar morphometric metrics included diameters, lengths and branching angles for each alveolar duct and total path lengths from entrance of the acinus to the terminal alveolar sacs. In addition, other metrics such as acinar volume, alveolar surface area and surface area/volume ratios were assessed.
A generation-based analysis demonstrated significant differences in acinar morphometry across young and old age groups and across the three strains. The method was successfully adapted to large animals and the data from one porcine specimen has been presented. The registration framework provides a direct technique to assess acinar deformations and provides critical physiological information about the state of alveolar ducts and individual alveoli at different phases of respiration.
The techniques presented here allow us to perform direct assessment of the three-dimensional structure of the pulmonary acinus in previously unavailable detail and present a unique technique for comprehensive quantitative analysis. The acinar morphometric parameters will help develop improved mathematical and near-anatomical models that can accurately represent the geometric structure of acini, leading to improved assessment of flow dynamics in the normal lung.
The pulmonary acinus is a collection of sac-like structures called alveoli that form at the very end of the airways in mammals. The acinus is the site of all gas exchange (oxygen delivery and carbon dioxide clearance) in the lungs and as such, represents the functional part of our respiratory system. A detailed study of the structure of the acinus is essential in furthering our understanding of the nature of respiration and gas exchange; however our understanding of acinar structure has been limited due to the challenges presented in the small size of the over-all structure and the individual components and by the fact that when the components are separated, their geometry is altered. Advancements in technology, such as CT imaging systems with the ability to look at micrometer scale, provide us with unique opportunities to perform detailed measurements of the acinus without the constraints that limited previous work.
We present techniques to study the three-dimensional structure of the pulmonary acinus in mice through the latest developments in imaging technology, without distorting or destroying the sample. We present a method to sample and perform detailed analysis of the normal structure of acini in three genetic strains of mice, and show evidence of how this can be used to explore the human respiratory system. Through this work, we put forward a set of techniques and methods that expand our current understanding of the mammalian lung structure and allow researchers to explore the nature of normal and diseased lungs in great detail.
publicabstract, Acinar Morphometry, CT Image Analysis, High Resolution microCT, microCT, Pulmonary Acinus, Quantitative CT
Copyright 2016 Abhilash Srikumar Kizhakke Puliyakote