Literature DB >> 20879315

Early detection of emphysema progression.

Vladlena Gorbunova1, Sander S A M Jacobs, Pechin Lo, Asger Dirksen, Mads Nielsen, Alireza Bab-Hadiashar, Marleen de Bruijne.   

Abstract

Emphysema is one of the most widespread diseases in subjects with smoking history. The gold standard method for estimating the severity of emphysema is a lung function test, such as forced expiratory volume in first second (FEV1). However, several clinical studies showed that chest CT scans offer more sensitive estimates of emphysema progression. The standard CT densitometric score of emphysema is the relative area of voxels below a threshold (RA). The RA score is a global measurement and reflects the overall emphysema progression. In this work, we propose a framework for estimation of local emphysema progression from longitudinal chest CT scans. First, images are registered to a common system of coordinates and then local image dissimilarities are computed in corresponding anatomical locations. Finally, the obtained dissimilarity representation is converted into a single emphysema progression score. We applied the proposed algorithm on 27 patients with severe emphysema with CT scans acquired five time points, at baseline, after 3, after 12, after 21 and after 24 or 30 months. The results showed consistent emphysema progression with time and the overall progression score correlates significantly with the increase in RA score.

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Year:  2010        PMID: 20879315     DOI: 10.1007/978-3-642-15745-5_24

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  5 in total

1.  Computed Tomography Image Matching in Chronic Obstructive Pulmonary Disease.

Authors:  Sandeep Bodduluri; Surya P Bhatt; Joseph M Reinhardt
Journal:  Crit Rev Biomed Eng       Date:  2016

Review 2.  Recent Advances in Computed Tomography Imaging in Chronic Obstructive Pulmonary Disease.

Authors:  Sandeep Bodduluri; Joseph M Reinhardt; Eric A Hoffman; John D Newell; Surya P Bhatt
Journal:  Ann Am Thorac Soc       Date:  2018-03

3.  Influence of Inspiratory/Expiratory CT Registration on Quantitative Air Trapping.

Authors:  Oliver Weinheimer; Benjamin A Hoff; Aleksa B Fortuna; Antonio Fernández-Baldera; Philip Konietzke; Mark O Wielpütz; Terry E Robinson; Craig J Galbán
Journal:  Acad Radiol       Date:  2018-12-10       Impact factor: 3.173

4.  A 3D-CNN model with CT-based parametric response mapping for classifying COPD subjects.

Authors:  Thao Thi Ho; Taewoo Kim; Woo Jin Kim; Chang Hyun Lee; Kum Ju Chae; So Hyeon Bak; Sung Ok Kwon; Gong Yong Jin; Eun-Kee Park; Sanghun Choi
Journal:  Sci Rep       Date:  2021-01-08       Impact factor: 4.379

5.  Computed tomography-based biomarker provides unique signature for diagnosis of COPD phenotypes and disease progression.

Authors:  Craig J Galbán; Meilan K Han; Jennifer L Boes; Komal A Chughtai; Charles R Meyer; Timothy D Johnson; Stefanie Galbán; Alnawaz Rehemtulla; Ella A Kazerooni; Fernando J Martinez; Brian D Ross
Journal:  Nat Med       Date:  2012-10-07       Impact factor: 53.440

  5 in total

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