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Transferability of radiomic signatures from experimental to human interstitial lung disease
BACKGROUND: Interstitial lung disease (ILD) defines a group of parenchymal lung disorders, characterized by fibrosis as their common final pathophysiological stage. To improve diagnosis and treatment of ILD, there is a need for repetitive non-invasive characterization of lung tissue by quantitative...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9712180/ https://www.ncbi.nlm.nih.gov/pubmed/36465941 http://dx.doi.org/10.3389/fmed.2022.988927 |
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author | Gabryś, Hubert S. Gote-Schniering, Janine Brunner, Matthias Bogowicz, Marta Blüthgen, Christian Frauenfelder, Thomas Guckenberger, Matthias Maurer, Britta Tanadini-Lang, Stephanie |
author_facet | Gabryś, Hubert S. Gote-Schniering, Janine Brunner, Matthias Bogowicz, Marta Blüthgen, Christian Frauenfelder, Thomas Guckenberger, Matthias Maurer, Britta Tanadini-Lang, Stephanie |
author_sort | Gabryś, Hubert S. |
collection | PubMed |
description | BACKGROUND: Interstitial lung disease (ILD) defines a group of parenchymal lung disorders, characterized by fibrosis as their common final pathophysiological stage. To improve diagnosis and treatment of ILD, there is a need for repetitive non-invasive characterization of lung tissue by quantitative parameters. In this study, we investigated whether CT image patterns found in mice with bleomycin induced lung fibrosis can be translated as prognostic factors to human patients diagnosed with ILD. METHODS: Bleomycin was used to induce lung fibrosis in mice (n_control = 36, n_experimental = 55). The patient cohort consisted of 98 systemic sclerosis (SSc) patients (n_ILD = 65). Radiomic features (n_histogram = 17, n_texture = 137) were extracted from microCT (mice) and HRCT (patients) images. Predictive performance of the models was evaluated with the area under the receiver-operating characteristic curve (AUC). First, predictive performance of individual features was examined and compared between murine and patient data sets. Second, multivariate models predicting ILD were trained on murine data and tested on patient data. Additionally, the models were reoptimized on patient data to reduce the influence of the domain shift on the performance scores. RESULTS: Predictive power of individual features in terms of AUC was highly correlated between mice and patients (r = 0.86). A model based only on mean image intensity in the lung scored AUC = 0.921 ± 0.048 in mice and AUC = 0.774 (CI95% 0.677-0.859) in patients. The best radiomic model based on three radiomic features scored AUC = 0.994 ± 0.013 in mice and validated with AUC = 0.832 (CI95% 0.745-0.907) in patients. However, reoptimization of the model weights in the patient cohort allowed to increase the model’s performance to AUC = 0.912 ± 0.058. CONCLUSION: Radiomic signatures of experimental ILD derived from microCT scans translated to HRCT of humans with SSc-ILD. We showed that the experimental model of BLM-induced ILD is a promising system to test radiomic models for later application and validation in human cohorts. |
format | Online Article Text |
id | pubmed-9712180 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-97121802022-12-02 Transferability of radiomic signatures from experimental to human interstitial lung disease Gabryś, Hubert S. Gote-Schniering, Janine Brunner, Matthias Bogowicz, Marta Blüthgen, Christian Frauenfelder, Thomas Guckenberger, Matthias Maurer, Britta Tanadini-Lang, Stephanie Front Med (Lausanne) Medicine BACKGROUND: Interstitial lung disease (ILD) defines a group of parenchymal lung disorders, characterized by fibrosis as their common final pathophysiological stage. To improve diagnosis and treatment of ILD, there is a need for repetitive non-invasive characterization of lung tissue by quantitative parameters. In this study, we investigated whether CT image patterns found in mice with bleomycin induced lung fibrosis can be translated as prognostic factors to human patients diagnosed with ILD. METHODS: Bleomycin was used to induce lung fibrosis in mice (n_control = 36, n_experimental = 55). The patient cohort consisted of 98 systemic sclerosis (SSc) patients (n_ILD = 65). Radiomic features (n_histogram = 17, n_texture = 137) were extracted from microCT (mice) and HRCT (patients) images. Predictive performance of the models was evaluated with the area under the receiver-operating characteristic curve (AUC). First, predictive performance of individual features was examined and compared between murine and patient data sets. Second, multivariate models predicting ILD were trained on murine data and tested on patient data. Additionally, the models were reoptimized on patient data to reduce the influence of the domain shift on the performance scores. RESULTS: Predictive power of individual features in terms of AUC was highly correlated between mice and patients (r = 0.86). A model based only on mean image intensity in the lung scored AUC = 0.921 ± 0.048 in mice and AUC = 0.774 (CI95% 0.677-0.859) in patients. The best radiomic model based on three radiomic features scored AUC = 0.994 ± 0.013 in mice and validated with AUC = 0.832 (CI95% 0.745-0.907) in patients. However, reoptimization of the model weights in the patient cohort allowed to increase the model’s performance to AUC = 0.912 ± 0.058. CONCLUSION: Radiomic signatures of experimental ILD derived from microCT scans translated to HRCT of humans with SSc-ILD. We showed that the experimental model of BLM-induced ILD is a promising system to test radiomic models for later application and validation in human cohorts. Frontiers Media S.A. 2022-11-17 /pmc/articles/PMC9712180/ /pubmed/36465941 http://dx.doi.org/10.3389/fmed.2022.988927 Text en Copyright © 2022 Gabryś, Gote-Schniering, Brunner, Bogowicz, Blüthgen, Frauenfelder, Guckenberger, Maurer and Tanadini-Lang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Medicine Gabryś, Hubert S. Gote-Schniering, Janine Brunner, Matthias Bogowicz, Marta Blüthgen, Christian Frauenfelder, Thomas Guckenberger, Matthias Maurer, Britta Tanadini-Lang, Stephanie Transferability of radiomic signatures from experimental to human interstitial lung disease |
title | Transferability of radiomic signatures from experimental to human interstitial lung disease |
title_full | Transferability of radiomic signatures from experimental to human interstitial lung disease |
title_fullStr | Transferability of radiomic signatures from experimental to human interstitial lung disease |
title_full_unstemmed | Transferability of radiomic signatures from experimental to human interstitial lung disease |
title_short | Transferability of radiomic signatures from experimental to human interstitial lung disease |
title_sort | transferability of radiomic signatures from experimental to human interstitial lung disease |
topic | Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9712180/ https://www.ncbi.nlm.nih.gov/pubmed/36465941 http://dx.doi.org/10.3389/fmed.2022.988927 |
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