Literature DB >> 26947221

A Robust Emphysema Severity Measure Based on Disease Subtypes.

Rola Harmouche1, James C Ross2, Alejandro A Diaz3, George R Washko3, Raul San Jose Estepar2.   

Abstract

RATIONALE AND
OBJECTIVES: We propose a novel single index for the quantification of emphysema severity based on an aggregation of multiple computed tomographic features evident in the lung parenchyma of smokers. Our goal was to demonstrate that this single index provides complementary information to the current standard measure of emphysema, percent emphysema (percent low attenuation areas [LAA%]), and may be superior in its association with clinically relevant outcomes.
MATERIALS AND METHODS: The inputs to our algorithm were objective assessments of multiple emphysema subtypes (normal tissue; panlobular; paraseptal; and mild, moderate, and severe centrilobular emphysema). We applied dimensionality reduction techniques to the emphysema quantities to find a space that maximizes the variance of these subtypes. A single emphysema severity index was then derived from a parametrization of the reduced space, and the clinical utility of the measure was explored in a large cross-sectional cohort of 8914 subjects from the COPDGene Study.
RESULTS: There was a statistically significant association between the severity index and the LAA%. Subjects with more severe chronic obstructive pulmonary disease (higher Global initiative for Obstructive Lung Disease stage) tended to have a higher computed tomography severity index. Finally, the severity index was associated with clinical outcomes such as lung function and provided a stronger association to these measures than the LAA%.
CONCLUSIONS: The method provides a single clinically relevant index that can assess the severity of emphysema and that provides information that is complimentary to the more commonly used LAA%.
Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Emphysema severity measure; local histogram analysis

Mesh:

Year:  2016        PMID: 26947221      PMCID: PMC4813794          DOI: 10.1016/j.acra.2015.12.021

Source DB:  PubMed          Journal:  Acad Radiol        ISSN: 1076-6332            Impact factor:   3.173


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