Evaluation of automated airway morphological quantification for assessing fibrosing lung disease
Abnormal airway dilatation, termed traction bronchiectasis, is a typical feature of idiopathic pulmonary fibrosis (IPF). Volumetric computed tomography (CT) imaging captures the loss of normal airway tapering in IPF. We postulated that automated quantification of airway abnormalities could provide e...
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2024-12-01
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| Series: | Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization |
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| Online Access: | https://www.tandfonline.com/doi/10.1080/21681163.2024.2325361 |
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| author | A. Pakzad WK. Cheung CHM. Van Moorsel K. Quan N. Mogulkoc BJ. Bartholmai HW. Van Es A. Ezircan F. Van Beek M. Veltkamp R. Karwoski T. Peikert RD. Clay F. Foley C. Braun R. Savas C. Sudre T. Doel DC. Alexander P. Wijeratne D. Hawkes Y. Hu JR. Hurst J. Jacob |
| author_facet | A. Pakzad WK. Cheung CHM. Van Moorsel K. Quan N. Mogulkoc BJ. Bartholmai HW. Van Es A. Ezircan F. Van Beek M. Veltkamp R. Karwoski T. Peikert RD. Clay F. Foley C. Braun R. Savas C. Sudre T. Doel DC. Alexander P. Wijeratne D. Hawkes Y. Hu JR. Hurst J. Jacob |
| author_sort | A. Pakzad |
| collection | DOAJ |
| description | Abnormal airway dilatation, termed traction bronchiectasis, is a typical feature of idiopathic pulmonary fibrosis (IPF). Volumetric computed tomography (CT) imaging captures the loss of normal airway tapering in IPF. We postulated that automated quantification of airway abnormalities could provide estimates of IPF disease extent and severity. We propose AirQuant, an automated computational pipeline that takes an airway segmentation and CT image as input and systematically parcellates the airway tree into its lobes and generational branches, deriving airway structural measures from chest CT. Importantly, AirQuant prevents the occurrence of spurious airway branches by thick wave propagation and removes loops in the airway-tree by graph search, overcoming limitations of existing airway skeletonisation algorithms. Tapering between airway segments (intertapering) and airway tortuosity computed by AirQuant were compared between 14 healthy participants and 14 IPF patients. Airway intertapering was significantly reduced in IPF patients, and airway tortuosity was significantly increased when compared to healthy controls. Differences were most marked in the lower lobes, conforming to the typical distribution of IPF-related damage. AirQuant is an open-source pipeline that avoids limitations of existing airway quantification algorithms and has clinical interpretability. Automated airway measurements may have potential as novel imaging biomarkers of IPF severity and disease extent. |
| format | Article |
| id | doaj-art-535c1bb3615943859d2f77761bad01e8 |
| institution | Kabale University |
| issn | 2168-1163 2168-1171 |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization |
| spelling | doaj-art-535c1bb3615943859d2f77761bad01e82024-11-29T10:29:56ZengTaylor & Francis GroupComputer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization2168-11632168-11712024-12-0112110.1080/21681163.2024.2325361Evaluation of automated airway morphological quantification for assessing fibrosing lung diseaseA. Pakzad0WK. Cheung1CHM. Van Moorsel2K. Quan3N. Mogulkoc4BJ. Bartholmai5HW. Van Es6A. Ezircan7F. Van Beek8M. Veltkamp9R. Karwoski10T. Peikert11RD. Clay12F. Foley13C. Braun14R. Savas15C. Sudre16T. Doel17DC. Alexander18P. Wijeratne19D. Hawkes20Y. Hu21JR. Hurst22J. Jacob23Centre for Medical Image Computing, University College London, London, UKCentre for Medical Image Computing, University College London, London, UKDepartment of Pulmonology, Interstitial Lung Diseases Center of Excellence, St Antonius Hospital, Nieuwegein, the NetherlandsCentre for Medical Image Computing, University College London, London, UKDepartment of Respiratory Medicine, Ege University Hospital, Izmir, TurkeyDivision of Radiology, Mayo Clinic Rochester, Rochester, MN, USADepartment of Radiology, St Antonius Hospital, Nieuwegein, the NetherlandsDepartment of Respiratory Medicine, Ege University Hospital, Izmir, TurkeyDepartment of Respiratory Medicine, Ege University Hospital, Izmir, TurkeyDepartment of Respiratory Medicine, Ege University Hospital, Izmir, TurkeyDepartment of Physiology and Biomedical Engineering, Mayo Clinic Rochester, Rochester, MN, USADivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USADivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USADivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USADivision of Pulmonary and Critical Care Medicine, Mayo Clinic, Rochester, MN, USADepartment of Radiology, Ege University Faculty of Medicine, Izmir, TurkeyCentre for Medical Image Computing, University College London, London, UKCode Choreography Limited, Bolton, UKCentre for Medical Image Computing, University College London, London, UKCentre for Medical Image Computing, University College London, London, UKCentre for Medical Image Computing, University College London, London, UKCentre for Medical Image Computing, University College London, London, UKUCL Respiratory, University College London, London, UKCentre for Medical Image Computing, University College London, London, UKAbnormal airway dilatation, termed traction bronchiectasis, is a typical feature of idiopathic pulmonary fibrosis (IPF). Volumetric computed tomography (CT) imaging captures the loss of normal airway tapering in IPF. We postulated that automated quantification of airway abnormalities could provide estimates of IPF disease extent and severity. We propose AirQuant, an automated computational pipeline that takes an airway segmentation and CT image as input and systematically parcellates the airway tree into its lobes and generational branches, deriving airway structural measures from chest CT. Importantly, AirQuant prevents the occurrence of spurious airway branches by thick wave propagation and removes loops in the airway-tree by graph search, overcoming limitations of existing airway skeletonisation algorithms. Tapering between airway segments (intertapering) and airway tortuosity computed by AirQuant were compared between 14 healthy participants and 14 IPF patients. Airway intertapering was significantly reduced in IPF patients, and airway tortuosity was significantly increased when compared to healthy controls. Differences were most marked in the lower lobes, conforming to the typical distribution of IPF-related damage. AirQuant is an open-source pipeline that avoids limitations of existing airway quantification algorithms and has clinical interpretability. Automated airway measurements may have potential as novel imaging biomarkers of IPF severity and disease extent.https://www.tandfonline.com/doi/10.1080/21681163.2024.2325361Airway morphologyBronchiectasisComputed tomography |
| spellingShingle | A. Pakzad WK. Cheung CHM. Van Moorsel K. Quan N. Mogulkoc BJ. Bartholmai HW. Van Es A. Ezircan F. Van Beek M. Veltkamp R. Karwoski T. Peikert RD. Clay F. Foley C. Braun R. Savas C. Sudre T. Doel DC. Alexander P. Wijeratne D. Hawkes Y. Hu JR. Hurst J. Jacob Evaluation of automated airway morphological quantification for assessing fibrosing lung disease Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization Airway morphology Bronchiectasis Computed tomography |
| title | Evaluation of automated airway morphological quantification for assessing fibrosing lung disease |
| title_full | Evaluation of automated airway morphological quantification for assessing fibrosing lung disease |
| title_fullStr | Evaluation of automated airway morphological quantification for assessing fibrosing lung disease |
| title_full_unstemmed | Evaluation of automated airway morphological quantification for assessing fibrosing lung disease |
| title_short | Evaluation of automated airway morphological quantification for assessing fibrosing lung disease |
| title_sort | evaluation of automated airway morphological quantification for assessing fibrosing lung disease |
| topic | Airway morphology Bronchiectasis Computed tomography |
| url | https://www.tandfonline.com/doi/10.1080/21681163.2024.2325361 |
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