Biomarkers of regional lung function, coupled with validated low dose methods of assessing anatomic features of the lung are critical to promote discovery and testing of new interventions in COPD and asthma. This proposed bioengineering research partnership seeks to take advantage of the emerging acquisition technique of multi-spectral computed tomography (currently dual energy CT: DECT), careful evaluation of dose lowering methods, and novel approaches to statistical cluster anlaysis to expand the biomarkers used in multi-center studies to identify sub-populations of lung disease. Current CT methods have focused largely on parenchymal destruction, air trapping and airway remodeling. With our recent findings reported in the Proceedings of the National Acedemy of Sciences and the New England Journal of Medicine, there is growing evidence that the etiology of emphysema may be correlated with abnormal vascular responses to inflammation in COPD. To further validate these findings, we focus on multi-spectral CT to simplify the current dynamic CT approach in its assessment of ventilation and perfusion. With DECT we can simplify to a single breath of xenon gas or a slow peripheral injection of iodinated contrast agent to assess regional ventilation or perfused blood volume (PBV). Our approach consists of 5 tightly integrated aims seeking to: 1) establish the minimum dose required to achieve the measurements of importance in defining COPD and asthma sub-populations;2) use our well characterized CT assessment of pulmonary perfusion and ventilation using dynamic axial imaging to validate metrics from DECT, providing indices of ventilation and perfusion via single breath hold / single lung volume techniques;3) expand image segmentation of the lung to the pulmonary arterial and venous trees to further link structure to function as well as to reliabily provide a framework for dividing the lung into sublobar segments as the standard region of interest;4) test the application of a novel statistica approach to cluster analysis such that the measures from quantitative CT fully account for specific phenotypes for disease subgroups and link to a computational fluid dynamics model such that a putative phenotype can be better understood;and finally 5) provide a framework whereby newly developed protocols are harmonized across manufacturers and scanner models, allowing for cross institutional data collection and a means whereby technology is allowed to progress within the context of longitudial studies.

Public Health Relevance

Quantitative x-ray CT of lung structure has been successful in providing objective methods for detecting early lung disease and dividing subjects into sub-groups to aid in seeking new therapies for COPD and asthma. We now seek to: 1) add CT-based measures of function which we believe will provide greater insight into the actual cause of the lung abnormality;2) lower x-ray dose needed for the measures;3) develop new methods to make use of these large amounts of information;and 4) provide ways whereby cross institutional studies can accommodate multiple manufacturer's equipment as well as accommodate changes in equipment over time.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
5R01HL112986-02
Application #
8514716
Study Section
Special Emphasis Panel (ZRG1-DTCS-U (81))
Program Officer
Punturieri, Antonello
Project Start
2012-08-01
Project End
2016-12-31
Budget Start
2014-01-01
Budget End
2014-12-31
Support Year
2
Fiscal Year
2014
Total Cost
$1,069,688
Indirect Cost
$357,772
Name
University of Iowa
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
062761671
City
Iowa City
State
IA
Country
United States
Zip Code
52242
Choi, Sanghun; Hoffman, Eric A; Wenzel, Sally E et al. (2017) Quantitative computed tomographic imaging-based clustering differentiates asthmatic subgroups with distinctive clinical phenotypes. J Allergy Clin Immunol 140:690-700.e8
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
Herrmann, Jacob; Hoffman, Eric A; Kaczka, David W (2017) Frequency-Selective Computed Tomography: Applications During Periodic Thoracic Motion. IEEE Trans Med Imaging 36:1722-1732
Jahani, Nariman; Choi, Sanghun; Choi, Jiwoong et al. (2017) A four-dimensional computed tomography comparison of healthy and asthmatic human lungs. J Biomech 56:102-110
Hammond, Emily; Sloan, Chelsea; Newell Jr, John D et al. (2017) Comparison of low- and ultralow-dose computed tomography protocols for quantitative lung and airway assessment. Med Phys 44:4747-4757
Miyawaki, Shinjiro; Tawhai, Merryn H; Hoffman, Eric A et al. (2017) Automatic construction of subject-specific human airway geometry including trifurcations based on a CT-segmented airway skeleton and surface. Biomech Model Mechanobiol 16:583-596
Miyawaki, Shinjiro; Hoffman, Eric A; Lin, Ching-Long (2017) Numerical simulations of aerosol delivery to the human lung with an idealized laryngeal model, image-based airway model, and automatic meshing algorithm. Comput Fluids 148:1-9
Miyawaki, Shinjiro; Hoffman, Eric A; Wenzel, Sally E et al. (2017) Aerosol deposition predictions in computed tomography-derived skeletons from severe asthmatics: A feasibility study. Clin Biomech (Bristol, Avon) :
Kalpathy-Cramer, Jayashree; Mamomov, Artem; Zhao, Binsheng et al. (2016) Radiomics of Lung Nodules: A Multi-Institutional Study of Robustness and Agreement of Quantitative Imaging Features. Tomography 2:430-437
Miyawaki, Shinjiro; Hoffman, Eric A; Lin, Ching-Long (2016) Effect of static vs. dynamic imaging on particle transport in CT-based numerical models of human central airways. J Aerosol Sci 100:129-139

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