Literature DB >> 21688115

3D airway tree reconstruction in healthy subjects and emphysema.

Caterina Salito1, Livia Barazzetti, Jason C Woods, Andrea Aliverti.   

Abstract

Several algorithms for the segmentation of the 3D human airway tree from computed tomography (CT) images have recently been proposed, but the effects of lung volume and the presence of emphysema on segmentation accuracy has not been investigated. Two different sets of CT images taken on nine healthy subjects and nine patients with severe emphysema (FEV(1) = 19 ± 4.1 SD % pred) were used to reconstruct the trachea-bronchial tree by a region-growing algorithm at two different lung volumes: total lung capacity (TLC) and residual volume (RV). The sixth generation was reached in 67% of the healthy subjects and 22% of the emphysematous patients at TLC. At RV, fifth generation was reached in 33 and 11% of healthy subjects and emphysematous patients. At TLC, 67 ± 2 and 39 ± 2% of airways belonging to the fourth generation were successfully reconstructed, respectively in healthy and emphysematous subjects. At RV, the percentage of successful reconstruction was 33 ± 2 and 16 ± 2%, respectively. Segmentation was significantly influenced by the presence of disease (P < 0.001) and lung volume (P < 0.001) at which the CT scans were acquired. Airway tree reconstruction performed by means of a region-growing algorithm depends on lung volume and presence of emphysema, both of which have significant effect, even at the level of lobar and segmental bronchi.

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Year:  2011        PMID: 21688115     DOI: 10.1007/s00408-011-9305-4

Source DB:  PubMed          Journal:  Lung        ISSN: 0341-2040            Impact factor:   2.584


  16 in total

1.  Three-dimensional human airway segmentation methods for clinical virtual bronchoscopy.

Authors:  Atilla P Kiraly; William E Higgins; Geoffrey McLennan; Eric A Hoffman; Joseph M Reinhardt
Journal:  Acad Radiol       Date:  2002-10       Impact factor: 3.173

2.  Segmentation and analysis of the human airway tree from three-dimensional X-ray CT images.

Authors:  Deniz Aykac; Eric A Hoffman; Geoffrey McLennan; Joseph M Reinhardt
Journal:  IEEE Trans Med Imaging       Date:  2003-08       Impact factor: 10.048

3.  Robust 3-D airway tree segmentation for image-guided peripheral bronchoscopy.

Authors:  Michael W Graham; Jason D Gibbs; Duane C Cornish; William E Higgins
Journal:  IEEE Trans Med Imaging       Date:  2010-03-22       Impact factor: 10.048

4.  Intrathoracic airway trees: segmentation and airway morphology analysis from low-dose CT scans.

Authors:  Juerg Tschirren; Eric A Hoffman; Geoffrey McLennan; Milan Sonka
Journal:  IEEE Trans Med Imaging       Date:  2005-12       Impact factor: 10.048

5.  Quantitative computed tomography: emphysema and airway wall thickness by sex, age and smoking.

Authors:  T B Grydeland; A Dirksen; H O Coxson; S G Pillai; S Sharma; G E Eide; A Gulsvik; P S Bakke
Journal:  Eur Respir J       Date:  2009-03-26       Impact factor: 16.671

6.  Robust segmentation and anatomical labeling of the airway tree from thoracic CT scans.

Authors:  Bram van Ginneken; Wouter Baggerman; Eva M van Rikxoort
Journal:  Med Image Comput Comput Assist Interv       Date:  2008

7.  Quantifying tracheobronchial tree dimensions: methods, limitations and emerging techniques.

Authors:  J P Williamson; A L James; M J Phillips; D D Sampson; D R Hillman; P R Eastwood
Journal:  Eur Respir J       Date:  2009-07       Impact factor: 16.671

8.  Segmentation of intrathoracic airway trees: a fuzzy logic approach.

Authors:  W Park; E A Hoffman; M Sonka
Journal:  IEEE Trans Med Imaging       Date:  1998-08       Impact factor: 10.048

9.  Measurement of three-dimensional lung tree structures by using computed tomography.

Authors:  S A Wood; E A Zerhouni; J D Hoford; E A Hoffman; W Mitzner
Journal:  J Appl Physiol (1985)       Date:  1995-11

10.  Automatic segmentation and recognition of anatomical lung structures from high-resolution chest CT images.

Authors:  Xiangrong Zhou; Tatsuro Hayashi; Takeshi Hara; Hiroshi Fujita; Ryujiro Yokoyama; Takuji Kiryu; Hiroaki Hoshi
Journal:  Comput Med Imaging Graph       Date:  2006-08-22       Impact factor: 4.790

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  5 in total

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Journal:  PLoS One       Date:  2019-12-19       Impact factor: 3.240

2.  Heterogeneity of specific gas volume changes: a new tool to plan lung volume reduction in COPD.

Authors:  Caterina Salito; Livia Barazzetti; Jason C Woods; Andrea Aliverti
Journal:  Chest       Date:  2014-12       Impact factor: 9.410

3.  Optimizing parameters of an open-source airway segmentation algorithm using different CT images.

Authors:  Pietro Nardelli; Kashif A Khan; Alberto Corvò; Niamh Moore; Mary J Murphy; Maria Twomey; Owen J O'Connor; Marcus P Kennedy; Raúl San José Estépar; Michael M Maher; Pádraig Cantillon-Murphy
Journal:  Biomed Eng Online       Date:  2015-06-26       Impact factor: 2.819

4.  Airway Remodelling in Asthma and COPD: Findings, Similarities, and Differences Using Quantitative CT.

Authors:  Gaël Dournes; François Laurent
Journal:  Pulm Med       Date:  2012-02-16

5.  High-quality chest CT segmentation to assess the impact of COVID-19 disease.

Authors:  Michele Bertolini; Alma Brambilla; Samanta Dallasta; Giorgio Colombo
Journal:  Int J Comput Assist Radiol Surg       Date:  2021-08-06       Impact factor: 2.924

  5 in total

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