Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCT
Background: Our study assesses the diagnostic value of different features extracted from high resolution computed tomography (HRCT) images of patients with idiopathic pulmonary fibrosis. These features are investigated over a range of HRCT lung volume measurements (in Hounsfield Units) for which no...
| Main Authors: | , , , , , , , , , , , , , , |
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| Format: | Article |
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MDPI AG
2020-05-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/10/5/306 |
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| author | Alessandro Stefano Mauro Gioè Giorgio Russo Stefano Palmucci Sebastiano Emanuele Torrisi Samuel Bignardi Antonio Basile Albert Comelli Viviana Benfante Gianluca Sambataro Daniele Falsaperla Alfredo Gaetano Torcitto Massimo Attanasio Anthony Yezzi Carlo Vancheri |
| author_facet | Alessandro Stefano Mauro Gioè Giorgio Russo Stefano Palmucci Sebastiano Emanuele Torrisi Samuel Bignardi Antonio Basile Albert Comelli Viviana Benfante Gianluca Sambataro Daniele Falsaperla Alfredo Gaetano Torcitto Massimo Attanasio Anthony Yezzi Carlo Vancheri |
| author_sort | Alessandro Stefano |
| collection | DOAJ |
| description | Background: Our study assesses the diagnostic value of different features extracted from high resolution computed tomography (HRCT) images of patients with idiopathic pulmonary fibrosis. These features are investigated over a range of HRCT lung volume measurements (in Hounsfield Units) for which no prior study has yet been published. In particular, we provide a comparison of their diagnostic value at different Hounsfield Unit (HU) thresholds, including corresponding pulmonary functional tests. Methods: We consider thirty-two patients retrospectively for whom both HRCT examinations and spirometry tests were available. First, we analyse the HRCT histogram to extract quantitative lung fibrosis features. Next, we evaluate the relationship between pulmonary function and the HRCT features at selected HU thresholds, namely −200 HU, 0 HU, and +200 HU. We model the relationship using a Poisson approximation to identify the measure with the highest log-likelihood. Results: Our Poisson models reveal no difference at the −200 and 0 HU thresholds. However, inferential conclusions change at the +200 HU threshold. Among the HRCT features considered, the percentage of normally attenuated lung at −200 HU shows the most significant diagnostic utility. Conclusions: The percentage of normally attenuated lung can be used together with qualitative HRCT assessment and pulmonary function tests to enhance the idiopathic pulmonary fibrosis (IPF) diagnostic process. |
| first_indexed | 2024-03-10T19:49:04Z |
| format | Article |
| id | doaj.art-e5855092623b4a6c9d68b737623bf572 |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-10T19:49:04Z |
| publishDate | 2020-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-e5855092623b4a6c9d68b737623bf5722023-11-20T00:35:56ZengMDPI AGDiagnostics2075-44182020-05-0110530610.3390/diagnostics10050306Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCTAlessandro Stefano0Mauro Gioè1Giorgio Russo2Stefano Palmucci3Sebastiano Emanuele Torrisi4Samuel Bignardi5Antonio Basile6Albert Comelli7Viviana Benfante8Gianluca Sambataro9Daniele Falsaperla10Alfredo Gaetano Torcitto11Massimo Attanasio12Anthony Yezzi13Carlo Vancheri14Institute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), 90015 Cefalù, ItalyDepartment of Economics, Business, and Statistics (DSEAS), University of Palermo, 90133 Palermo, ItalyInstitute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), 90015 Cefalù, ItalyDepartment of Medical Surgical Sciences and Advanced Technologies, Radiology Unit I, University Hospital “Policlinico-Vittorio Emanuele”, 95123 Catania, ItalyRegional Referral Centre for Rare Lung Diseases, A.O.U. Policlinico-Vittorio Emanuele, University of Catania, 95123 Catania, ItalyLaboratory of Computational Computer Vision (LCCV), School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USADepartment of Medical Surgical Sciences and Advanced Technologies, Radiology Unit I, University Hospital “Policlinico-Vittorio Emanuele”, 95123 Catania, ItalyInstitute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), 90015 Cefalù, ItalyInstitute of Molecular Bioimaging and Physiology, National Research Council (IBFM-CNR), 90015 Cefalù, ItalyDepartment of Medical Surgical Sciences and Advanced Technologies, Radiology Unit I, University Hospital “Policlinico-Vittorio Emanuele”, 95123 Catania, ItalyDepartment of Medical Surgical Sciences and Advanced Technologies, Radiology Unit I, University Hospital “Policlinico-Vittorio Emanuele”, 95123 Catania, ItalyDepartment of Medical Surgical Sciences and Advanced Technologies, Radiology Unit I, University Hospital “Policlinico-Vittorio Emanuele”, 95123 Catania, ItalyDepartment of Economics, Business, and Statistics (DSEAS), University of Palermo, 90133 Palermo, ItalyLaboratory of Computational Computer Vision (LCCV), School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USARegional Referral Centre for Rare Lung Diseases, A.O.U. Policlinico-Vittorio Emanuele, University of Catania, 95123 Catania, ItalyBackground: Our study assesses the diagnostic value of different features extracted from high resolution computed tomography (HRCT) images of patients with idiopathic pulmonary fibrosis. These features are investigated over a range of HRCT lung volume measurements (in Hounsfield Units) for which no prior study has yet been published. In particular, we provide a comparison of their diagnostic value at different Hounsfield Unit (HU) thresholds, including corresponding pulmonary functional tests. Methods: We consider thirty-two patients retrospectively for whom both HRCT examinations and spirometry tests were available. First, we analyse the HRCT histogram to extract quantitative lung fibrosis features. Next, we evaluate the relationship between pulmonary function and the HRCT features at selected HU thresholds, namely −200 HU, 0 HU, and +200 HU. We model the relationship using a Poisson approximation to identify the measure with the highest log-likelihood. Results: Our Poisson models reveal no difference at the −200 and 0 HU thresholds. However, inferential conclusions change at the +200 HU threshold. Among the HRCT features considered, the percentage of normally attenuated lung at −200 HU shows the most significant diagnostic utility. Conclusions: The percentage of normally attenuated lung can be used together with qualitative HRCT assessment and pulmonary function tests to enhance the idiopathic pulmonary fibrosis (IPF) diagnostic process.https://www.mdpi.com/2075-4418/10/5/306idiopathic pulmonary fibrosishigh resolution computed tomographyradiomics |
| spellingShingle | Alessandro Stefano Mauro Gioè Giorgio Russo Stefano Palmucci Sebastiano Emanuele Torrisi Samuel Bignardi Antonio Basile Albert Comelli Viviana Benfante Gianluca Sambataro Daniele Falsaperla Alfredo Gaetano Torcitto Massimo Attanasio Anthony Yezzi Carlo Vancheri Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCT Diagnostics idiopathic pulmonary fibrosis high resolution computed tomography radiomics |
| title | Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCT |
| title_full | Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCT |
| title_fullStr | Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCT |
| title_full_unstemmed | Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCT |
| title_short | Performance of Radiomics Features in the Quantification of Idiopathic Pulmonary Fibrosis from HRCT |
| title_sort | performance of radiomics features in the quantification of idiopathic pulmonary fibrosis from hrct |
| topic | idiopathic pulmonary fibrosis high resolution computed tomography radiomics |
| url | https://www.mdpi.com/2075-4418/10/5/306 |
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