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ISSN: 2161-105X

Journal of Pulmonary & Respiratory Medicine
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Research Article

Detection of Smoking Induced Emphysema: Visual Scoring versus Computerised Algorithms

Martin Anderson1,2*, Gunnar Engström3, Lars H Nordenmark4, Dag Mohlkert5, Elmira Rouzbeh5, Maria Gerhardsson de Verdier4, Ulf Nihlén4,6, Thomas Fehniger7, Magnus Dahlbäck4 and Magnus Svartengren1,8

1Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden

2Division of Clinical Physiology, Karolinska University Hospital, Huddinge, Sweden

3Department of Clinical Sciences, Lund University, Lund, Sweden

4AstraZeneca R&D Mölndal, Mölndal, Sweden

5Department of Radiology, Södersjukhuset, Stockholm, Sweden

6Department of Respiratory Medicine and Allergology, Lund University, Sweden

7Department of Biomedical Engineering, Lunds Technical University, Lund, Sweden

8Occupational and Environmental Medicine, Uppsala University, Uppsala, Sweden

*Corresponding Author:
Martin Anderson
Division of clinical physiology, Department of Laboratory Medicine (LABMED)
H5, Karolinska Universitetssjukhuset, Huddinge C1 88, 14186 Stockholm, Sweden
E-mail: [email protected] gmail.com

Received date: July 20, 2014 Accepted date: October 26, 2015 Published date: October 30, 2015

Citation: Anderson M, Engström G, Nordenmark LH, Mohlkert D, Rouzbeh E, et al. (2015) Detection of Smoking Induced Emphysema: Visual Scoring versus Computerised Algorithms. J Pulm Respir Med 5:291. doi:10.4172/2161-105X.1000291

Copyright: © 2015 Anderson M, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Abstract

Purpose: Computed tomography (CT) has been applied to assess signs of early disease in a population study. Comparisons were made of histogram based methods to quantitatively determine lung density; relative area of emphysema below -910 and -950 Hounsfield units, and 15th percentile density (RA -910, RA -950 and PD15), as well as visual assessment of computed tomography (CT) images, to lung function indices in a population based study of smokers and non-smokers.

Methods: 138 subjects from a study of lung function in COPD were included in the study. Computerised assessments and visual scoring were used to analyse CT scans of different regions of identifying subjects with emphysema.

Results: Subjects visually diagnosed with centrilobular emphysema had significantly lower lung density (n=27, PD15=-932 HU, RA-950=6.6%) compared to subjects without emphysema (n=106, PD15=-917 HU, RA-950=2.3%). In the group with low PD15, the proportion with visually determined centrilobular emphysema was 38%, compared to 15% in the groups with high PD15.

Conclusion: Evaluation of patterns of lung attenuation by automated assessment and visual scoring provided similar classifications of disease in patients with mild COPD but differed in identifying regions of low density in healthy subjects. Visual assessment showed better correlation to both lung function and smoking habits than quantitative measures in this study. Quantitative measures should be used in the upper third of the lungs to detect smoking induced emphysema. Measurements of early attenuation changes within healthy subjects may require additional measures of validation by radiologists by visual assessment.

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