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BMC Medical Imaging
Published in: BMC Medical Imaging 1/2016

Open Access 01-12-2016 | Technical advance

Radiomics-based differentiation of lung disease models generated by polluted air based on X-ray computed tomography data

Authors: Krisztián Szigeti, Tibor Szabó, Csaba Korom, Ilona Czibak, Ildikó Horváth, Dániel S. Veres, Zoltán Gyöngyi, Kinga Karlinger, Ralf Bergmann, Márta Pócsik, Ferenc Budán, Domokos Máthé

Published in: BMC Medical Imaging | Issue 1/2016

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Abstract

Background

Lung diseases (resulting from air pollution) require a widely accessible method for risk estimation and early diagnosis to ensure proper and responsive treatment. Radiomics-based fractal dimension analysis of X-ray computed tomography attenuation patterns in chest voxels of mice exposed to different air polluting agents was performed to model early stages of disease and establish differential diagnosis.

Methods

To model different types of air pollution, BALBc/ByJ mouse groups were exposed to cigarette smoke combined with ozone, sulphur dioxide gas and a control group was established. Two weeks after exposure, the frequency distributions of image voxel attenuation data were evaluated. Specific cut-off ranges were defined to group voxels by attenuation. Cut-off ranges were binarized and their spatial pattern was associated with calculated fractal dimension, then abstracted by the fractal dimension -- cut-off range mathematical function. Nonparametric Kruskal-Wallis (KW) and Mann–Whitney post hoc (MWph) tests were used.

Results

Each cut-off range versus fractal dimension function plot was found to contain two distinctive Gaussian curves. The ratios of the Gaussian curve parameters are considerably significant and are statistically distinguishable within the three exposure groups.

Conclusions

A new radiomics evaluation method was established based on analysis of the fractal dimension of chest X-ray computed tomography data segments. The specific attenuation patterns calculated utilizing our method may diagnose and monitor certain lung diseases, such as chronic obstructive pulmonary disease (COPD), asthma, tuberculosis or lung carcinomas.
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Metadata
Title
Radiomics-based differentiation of lung disease models generated by polluted air based on X-ray computed tomography data
Authors
Krisztián Szigeti
Tibor Szabó
Csaba Korom
Ilona Czibak
Ildikó Horváth
Dániel S. Veres
Zoltán Gyöngyi
Kinga Karlinger
Ralf Bergmann
Márta Pócsik
Ferenc Budán
Domokos Máthé
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Medical Imaging / Issue 1/2016
Electronic ISSN: 1471-2342
DOI
https://doi.org/10.1186/s12880-016-0118-z

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