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Lung topology characteristics in patients with Chronic Obstructive Pulmonary Disease

Lung topology characteristics in patients with Chronic Obstructive Pulmonary Disease
Lung topology characteristics in patients with Chronic Obstructive Pulmonary Disease
Quantitative features that can currently be obtained from medical imaging do not provide a complete picture of Chronic Obstructive Pulmonary Disease (COPD). In this paper, we introduce a novel analytical tool based on persistent homology that extracts quantitative features from chest CT scans to describe the geometric structure of the airways inside the lungs. We show that these new radiomic features stratify COPD patients in agreement with the GOLD guidelines for COPD and can distinguish between inspiratory and expiratory scans. These CT measurements are very different to those currently in use and we demonstrate that they convey significant medical information. The results of this study are a proof of concept that topological methods can enhance the standard methodology to create a finer classification of COPD and increase the possibilities of more personalized treatment.
COPD, CT, Imaging, phenotyping, emphysema, topological data analysis, persistent homology
2045-2322
1-12
Brodzki, Jacek
b1fe25fd-5451-4fd0-b24b-c59b75710543
Belchi Guillamon, Francisco
41c7c5e5-b259-45d8-89f9-7b7937517c53
Djukanovic, Ratko
d9a45ee7-6a80-4d84-a0ed-10962660a98d
Conway, Joy
bbe9a2e4-fb85-4d4a-a38c-0c1832c32d06
Pirashvili, Mariam
74a0b0b2-acbd-4ee2-9825-d8418ef74b5d
Bennett, Michael
6df5585a-3d93-4870-8797-389759fc82c7
Brodzki, Jacek
b1fe25fd-5451-4fd0-b24b-c59b75710543
Belchi Guillamon, Francisco
41c7c5e5-b259-45d8-89f9-7b7937517c53
Djukanovic, Ratko
d9a45ee7-6a80-4d84-a0ed-10962660a98d
Conway, Joy
bbe9a2e4-fb85-4d4a-a38c-0c1832c32d06
Pirashvili, Mariam
74a0b0b2-acbd-4ee2-9825-d8418ef74b5d
Bennett, Michael
6df5585a-3d93-4870-8797-389759fc82c7

Brodzki, Jacek, Belchi Guillamon, Francisco, Djukanovic, Ratko, Conway, Joy, Pirashvili, Mariam and Bennett, Michael (2018) Lung topology characteristics in patients with Chronic Obstructive Pulmonary Disease. Scientific Reports, 8, 1-12, [5341]. (doi:10.1038/s41598-018-23424-0).

Record type: Article

Abstract

Quantitative features that can currently be obtained from medical imaging do not provide a complete picture of Chronic Obstructive Pulmonary Disease (COPD). In this paper, we introduce a novel analytical tool based on persistent homology that extracts quantitative features from chest CT scans to describe the geometric structure of the airways inside the lungs. We show that these new radiomic features stratify COPD patients in agreement with the GOLD guidelines for COPD and can distinguish between inspiratory and expiratory scans. These CT measurements are very different to those currently in use and we demonstrate that they convey significant medical information. The results of this study are a proof of concept that topological methods can enhance the standard methodology to create a finer classification of COPD and increase the possibilities of more personalized treatment.

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More information

Accepted/In Press date: 12 March 2018
e-pub ahead of print date: 28 March 2018
Published date: 2018
Keywords: COPD, CT, Imaging, phenotyping, emphysema, topological data analysis, persistent homology

Identifiers

Local EPrints ID: 418726
URI: http://eprints.soton.ac.uk/id/eprint/418726
ISSN: 2045-2322
PURE UUID: c4be62de-a07f-4478-be3f-32b2d0c10ec5
ORCID for Ratko Djukanovic: ORCID iD orcid.org/0000-0001-6039-5612
ORCID for Joy Conway: ORCID iD orcid.org/0000-0001-6464-1526

Catalogue record

Date deposited: 20 Mar 2018 17:30
Last modified: 10 Dec 2019 05:30

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Contributors

Author: Jacek Brodzki
Author: Francisco Belchi Guillamon
Author: Joy Conway ORCID iD
Author: Michael Bennett

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