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Lung tumors on multimodal radiographs derived from grating-based X-ray imaging - A feasibility study

Meinel, Felix G.; Schwab, Felix; Yaroshenko, Andre; Velroyen, Astrid; Bech, Martin LU ; Hellbach, Katharina; Fuchs, Jeanette; Stiewe, Thorsten; Yildirim, Ali Oe and Bamberg, Fabian, et al. (2014) In Physica Medica 30(3). p.352-357
Abstract
Purpose: The purpose of this study was to assess whether grating-based X-ray imaging may have a role in imaging of pulmonary nodules on radiographs. Materials and methods: A mouse lung containing multiple lung tumors was imaged using a small-animal scanner with a conventional X-ray source and a grating interferometer for phase-contrast imaging. We qualitatively compared the signal characteristics of lung nodules on transmission, dark-field and phase-contrast images. Furthermore, we quantitatively compared signal characteristics of lung tumors and the adjacent lung tissue and calculated the corresponding contrast-to-noise ratios. Results: Of the 5 tumors visualized on the transmission image, 3/5 tumors were clearly visualized and 1 tumor... (More)
Purpose: The purpose of this study was to assess whether grating-based X-ray imaging may have a role in imaging of pulmonary nodules on radiographs. Materials and methods: A mouse lung containing multiple lung tumors was imaged using a small-animal scanner with a conventional X-ray source and a grating interferometer for phase-contrast imaging. We qualitatively compared the signal characteristics of lung nodules on transmission, dark-field and phase-contrast images. Furthermore, we quantitatively compared signal characteristics of lung tumors and the adjacent lung tissue and calculated the corresponding contrast-to-noise ratios. Results: Of the 5 tumors visualized on the transmission image, 3/5 tumors were clearly visualized and 1 tumor was faintly visualized in the dark-field image as areas of decreased small angle scattering. In the phase-contrast images, 3/5 tumors were clearly visualized, while the remaining 2 tumors were faintly visualized by the phase-shift occurring at their edges. No additional tumors were visualized in either the dark-field or phase-contrast images. Compared to the adjacent lung tissue, lung tumors were characterized by a significant decrease in transmission signal (median 0.86 vs. 0.91, p = 0.04) and increase in dark-field signal (median 0.71 vs. 0.65, p = 0.04). Median contrast-to-noise ratios for the visualization of lung nodules were 4.4 for transmission images and 1.7 for dark-field images (p = 0.04). Conclusion: Lung nodules can be visualized on all three radiograph modalities derived from grating-based X-ray imaging. However, our initial data suggest that grating-based multimodal X-ray imaging does not increase the sensitivity of chest radiographs for the detection of lung nodules. (C) 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved. (Less)
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Contribution to journal
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published
subject
keywords
X-ray phase-contrast imaging, X-ray dark-field imaging, Chest, radiography, Lung tumors
in
Physica Medica
volume
30
issue
3
pages
352 - 357
publisher
ISTITUTI EDITORIALI E POLGRAFICI INTERNAZIONALI
external identifiers
  • wos:000334094200014
  • scopus:84896093861
ISSN
1120-1797
DOI
10.1016/j.ejmp.2013.11.001
language
English
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yes
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b3d3870f-dc03-48b0-b420-5964b9036fb1 (old id 4438900)
date added to LUP
2014-07-01 07:43:13
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2017-06-04 03:12:36
@article{b3d3870f-dc03-48b0-b420-5964b9036fb1,
  abstract     = {Purpose: The purpose of this study was to assess whether grating-based X-ray imaging may have a role in imaging of pulmonary nodules on radiographs. Materials and methods: A mouse lung containing multiple lung tumors was imaged using a small-animal scanner with a conventional X-ray source and a grating interferometer for phase-contrast imaging. We qualitatively compared the signal characteristics of lung nodules on transmission, dark-field and phase-contrast images. Furthermore, we quantitatively compared signal characteristics of lung tumors and the adjacent lung tissue and calculated the corresponding contrast-to-noise ratios. Results: Of the 5 tumors visualized on the transmission image, 3/5 tumors were clearly visualized and 1 tumor was faintly visualized in the dark-field image as areas of decreased small angle scattering. In the phase-contrast images, 3/5 tumors were clearly visualized, while the remaining 2 tumors were faintly visualized by the phase-shift occurring at their edges. No additional tumors were visualized in either the dark-field or phase-contrast images. Compared to the adjacent lung tissue, lung tumors were characterized by a significant decrease in transmission signal (median 0.86 vs. 0.91, p = 0.04) and increase in dark-field signal (median 0.71 vs. 0.65, p = 0.04). Median contrast-to-noise ratios for the visualization of lung nodules were 4.4 for transmission images and 1.7 for dark-field images (p = 0.04). Conclusion: Lung nodules can be visualized on all three radiograph modalities derived from grating-based X-ray imaging. However, our initial data suggest that grating-based multimodal X-ray imaging does not increase the sensitivity of chest radiographs for the detection of lung nodules. (C) 2013 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.},
  author       = {Meinel, Felix G. and Schwab, Felix and Yaroshenko, Andre and Velroyen, Astrid and Bech, Martin and Hellbach, Katharina and Fuchs, Jeanette and Stiewe, Thorsten and Yildirim, Ali Oe and Bamberg, Fabian and Reiser, Maximilian F. and Pfeiffer, Franz and Nikolaou, Konstantin},
  issn         = {1120-1797},
  keyword      = {X-ray phase-contrast imaging,X-ray dark-field imaging,Chest,radiography,Lung tumors},
  language     = {eng},
  number       = {3},
  pages        = {352--357},
  publisher    = {ISTITUTI EDITORIALI E POLGRAFICI INTERNAZIONALI},
  series       = {Physica Medica},
  title        = {Lung tumors on multimodal radiographs derived from grating-based X-ray imaging - A feasibility study},
  url          = {http://dx.doi.org/10.1016/j.ejmp.2013.11.001},
  volume       = {30},
  year         = {2014},
}