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Critical Reviews™ in Biomedical Engineering
SJR: 0.26 SNIP: 0.375 CiteScore™: 1.4

ISSN Print: 0278-940X
ISSN Online: 1943-619X

Critical Reviews™ in Biomedical Engineering

DOI: 10.1615/CritRevBiomedEng.2017021299
pages 411-425

Computed Tomography Image Matching in Chronic Obstructive Pulmonary Disease

Sandeep Bodduluri
Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama, Birmingham, AL 35294; University of Alabama at Birmingham Lung Imaging Core, University of Alabama, Birmingham, AL 35294; University of Alabama at Birmingham Lung Health Center, University of Alabama at Birmingham, AL 35294
Surya P. Bhatt
Division of Pulmonary, Allergy and Critical Care Medicine, University of Alabama, Birmingham, AL 35294; University of Alabama at Birmingham Lung Imaging Core, University of Alabama, Birmingham, AL 35294; University of Alabama at Birmingham Lung Health Center, University of Alabama at Birmingham, AL 35294
Joseph M. Reinhardt
Department of Biomedical Engineering, University of Iowa, Iowa City, IA 52242

ABSTRACT

Chronic obstructive pulmonary disease (COPD), characterized by progressive airflow obstruction due to the combined effects of emphysema and small airways disease, is associated with high morbidity and mortality. The complex link between emphysema and airways disease is associated with significant heterogeneity in clinical presentation. Spirometry is the current gold standard for diagnosis and stratification of the severity of airflow obstruction in COPD. Although spirometry is simple to use, it does not enable the separation of emphysema from airways disease. Computed tomography (CT), on the other hand, provides the anatomic localization of disease and has been increasingly used to phenotype COPD. The majority of current CT measures are extracted from a single-volume CT scan and although useful to characterize emphysema and airways disease, they do not link structural and functional abnormalities. Alternatively, CT image matching combines information from both inspiratory and expiratory CT scans, thus enabling determination of functional changes such as regional ventilation and mechanical properties of the lung. In this review, we discuss recent applications of CT image matching that provide clinically meaningful information beyond spirometry and single-volume CT scan measures.


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