
Proceedings Paper
Application of a computed tomography based cystic fibrosis scoring system to chest tomosynthesisFormat | Member Price | Non-Member Price |
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Paper Abstract
In the monitoring of progression of lung disease in patients with cystic fibrosis (CF), recurrent computed tomography (CT) examinations are often used. The relatively new imaging technique chest tomosynthesis (CTS) may be an interesting alternative in the follow-up of these patients due to its visualization of the chest in slices at radiation doses and costs significantly lower than is the case with CT. A first step towards introducing CTS imaging in the diagnostics of CF patients is to establish a scoring system appropriate for evaluating the severity of CF pulmonary disease based on findings in CTS images. Previously, several such CF scoring systems based on CT imaging have been published. The purpose of the present study was to develop a CF scoring system for CTS, by starting from an existing scoring system dedicated for CT images and making modifications regarded necessary to make it appropriate for use with CTS images. In order to determine any necessary changes, three thoracic radiologists independently used a scoring system dedicated for CT on both CT and CTS images from CF patients. The results of the scoring were jointly evaluated by all the observers, which lead to suggestions for changes to the scoring system. Suggested modifications include excluding the scoring of air trapping and doing the scoring of the findings in quadrants of the image instead of in each lung lobe.
Paper Details
Date Published: 28 March 2013
PDF: 8 pages
Proc. SPIE 8673, Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment, 86731H (28 March 2013); doi: 10.1117/12.2006761
Published in SPIE Proceedings Vol. 8673:
Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Claudia R. Mello-Thoms, Editor(s)
PDF: 8 pages
Proc. SPIE 8673, Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment, 86731H (28 March 2013); doi: 10.1117/12.2006761
Show Author Affiliations
Christina Söderman, Univ. of Gothenburg (Sweden)
Åse Johnsson, Univ. of Gothenburg (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Jenny Vikgren, Univ. of Gothenburg (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Hans Rystedt, Univ. of Gothenburg (Sweden)
Åse Johnsson, Univ. of Gothenburg (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Jenny Vikgren, Univ. of Gothenburg (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Hans Rystedt, Univ. of Gothenburg (Sweden)
Jonas Ivarsson, Univ. of Gothenburg (Sweden)
Rauni Rossi Norrlund, Univ. of Gothenburg (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Lena Nyberg Andersson, Univ. of Gothenburg (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Magnus Båth, Univ. of Gothenburg (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Rauni Rossi Norrlund, Univ. of Gothenburg (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Lena Nyberg Andersson, Univ. of Gothenburg (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Magnus Båth, Univ. of Gothenburg (Sweden)
Sahlgrenska Univ. Hospital (Sweden)
Published in SPIE Proceedings Vol. 8673:
Medical Imaging 2013: Image Perception, Observer Performance, and Technology Assessment
Craig K. Abbey; Claudia R. Mello-Thoms, Editor(s)
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