The goals of this research are to use high-resolution maps of regional lung mechanical properties to detect and follow the progression of lung disease. Pulmonary disease processes, including emphysema, interstitial fibrosis, cancer, pulmonary embolism, acute lung injury and more, alter the material properties of lung tissue and change the mechanics of the respiratory system. Furthermore, while these mechanical changes (and the disease process itself) originate at a local level, they are largely asymptomatic and invisible to currently available global measures of lung function such as pulmonary function tests until they have significantly advanced. We will use image registration to construct a high-resolution 3D map of the regional distribution of lung tissue specific volume change (related to specific compliance) and the lung tissue strain tensor between multiple respiratory-gated volumetric images of the breathing lung. The computational tools to be developed in this project will provide the ability to assess local volume, grayscale, and shape changes for arbitrary regions of interest in the lung parenchyma across the respiratory cycle. We expect that, by tracking the 3D distribution of regional lung specific volume change and the magnitude and direction of lung strain, we can examine the effects that localized pathological processes have on diseased tissue as well as surrounding normal tissue. Such information may provide new insights regarding pulmonary pathophysiology in, for instance, the proliferation of lung destruction in emphysema, the ventilation and perfusion mismatches in pulmonary emboli episodes, the effect of regional airway closure in asthma, and the regional mechanics of acute lung injury and the propagation of ventilator-associated lung injury. This information is now critical to the development and evaluation of new pulmonary disease therapies.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL079406-04
Application #
7645008
Study Section
Biomedical Imaging Technology Study Section (BMIT)
Program Officer
Croxton, Thomas
Project Start
2006-07-01
Project End
2011-06-30
Budget Start
2009-07-01
Budget End
2010-06-30
Support Year
4
Fiscal Year
2009
Total Cost
$319,483
Indirect Cost
Name
University of Iowa
Department
Biomedical Engineering
Type
Schools of Engineering
DUNS #
062761671
City
Iowa City
State
IA
Country
United States
Zip Code
52242
Bhatt, Surya P; Bodduluri, Sandeep; Hoffman, Eric A et al. (2017) Computed Tomography Measure of Lung at Risk and Lung Function Decline in Chronic Obstructive Pulmonary Disease. Am J Respir Crit Care Med 196:569-576
Bodduluri, Sandeep; Bhatt, Surya P; Hoffman, Eric A et al. (2017) Biomechanical CT metrics are associated with patient outcomes in COPD. Thorax 72:409-414
Bodduluri, Sandeep; Bhatt, Surya P; Reinhardt, Joseph M (2016) Computed Tomography Image Matching in Chronic Obstructive Pulmonary Disease. Crit Rev Biomed Eng 44:411-425
Amelon, Ryan E; Cao, Kunlin; Reinhardt, Joseph M et al. (2014) A measure for characterizing sliding on lung boundaries. Ann Biomed Eng 42:642-50
Du, Kaifang; Reinhardt, Joseph M; Christensen, Gary E et al. (2013) Respiratory effort correction strategies to improve the reproducibility of lung expansion measurements. Med Phys 40:123504
Du, Kaifang; Bayouth, John E; Ding, Kai et al. (2013) Reproducibility of intensity-based estimates of lung ventilation. Med Phys 40:063504
Bodduluri, Sandeep; Newell Jr, John D; Hoffman, Eric A et al. (2013) Registration-based lung mechanical analysis of chronic obstructive pulmonary disease (COPD) using a supervised machine learning framework. Acad Radiol 20:527-36
Ding, Kai; Cao, Kunlin; Fuld, Matthew K et al. (2012) Comparison of image registration based measures of regional lung ventilation from dynamic spiral CT with Xe-CT. Med Phys 39:5084-98
Cao, Kunlin; Ding, Kai; Reinhardt, Joseph M et al. (2012) Improving Intensity-Based Lung CT Registration Accuracy Utilizing Vascular Information. Int J Biomed Imaging 2012:285136
Lo, Pechin; van Ginneken, Bram; Reinhardt, Joseph M et al. (2012) Extraction of airways from CT (EXACT'09). IEEE Trans Med Imaging 31:2093-107

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