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Computer-aided analysis of airway trees in micro-CT scans of ex vivo porcine lung tissue

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Title: Computer-aided analysis of airway trees in micro-CT scans of ex vivo porcine lung tissue
Authors: Bauer, Christian1,2 christian-bauer@uiowa.edu, Adam, Ryan3,4, Stoltz, David A.3,4, Beichel, Reinhard R.1,2,3
Source: Computerized Medical Imaging & Graphics. Dec2012, Vol. 36 Issue 8, p601-609. 9p.
Subjects: Computer-aided diagnosis, Airway (Anatomy), Tomography, Lung diseases, Tissues, Cystic fibrosis, Laboratory swine
Abstract: Abstract: We present a highly automated approach to obtain detailed structural models of airway trees from ex vivo porcine lung tissue imaged with a high resolution micro-CT scanner. Such information is an important prerequisite to systematically study models of lung disease that affect airway morphology. The method initially identifies all tubular airway-like structures in the lung. In a second processing step, these structures are grouped into a connected airway tree by utilizing prior knowledge about the airway trees branching pattern. The method was evaluated on 12 micro-CT scans from four tracheal lobes of piglets imaged at three different inflation levels. For this study, two control piglets and two cystic fibrosis piglets were used. For systematic validation of our approach, an airway nomenclature was developed for the pig airway tree. Out of more than 3500 airway tree segments assessed during evaluation, 88.45% were correctly identified by the method. No false positive airway branches were found. A detailed performance analysis for different airway tree hierarchy levels, lung inflation levels and piglets with/without cystic fibrosis is presented in the paper. [Copyright &y& Elsevier]
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Database: Engineering Source
Description
Abstract:Abstract: We present a highly automated approach to obtain detailed structural models of airway trees from ex vivo porcine lung tissue imaged with a high resolution micro-CT scanner. Such information is an important prerequisite to systematically study models of lung disease that affect airway morphology. The method initially identifies all tubular airway-like structures in the lung. In a second processing step, these structures are grouped into a connected airway tree by utilizing prior knowledge about the airway trees branching pattern. The method was evaluated on 12 micro-CT scans from four tracheal lobes of piglets imaged at three different inflation levels. For this study, two control piglets and two cystic fibrosis piglets were used. For systematic validation of our approach, an airway nomenclature was developed for the pig airway tree. Out of more than 3500 airway tree segments assessed during evaluation, 88.45% were correctly identified by the method. No false positive airway branches were found. A detailed performance analysis for different airway tree hierarchy levels, lung inflation levels and piglets with/without cystic fibrosis is presented in the paper. [Copyright &y& Elsevier]
ISSN:08956111
DOI:10.1016/j.compmedimag.2012.08.001