Volumetric MRI of the lungs during forced expiration
Purpose Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung...
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| Published in | Magnetic resonance in medicine Vol. 75; no. 6; pp. 2295 - 2302 |
|---|---|
| Main Authors | , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Blackwell Publishing Ltd
01.06.2016
Wiley Subscription Services, Inc |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0740-3194 1522-2594 1522-2594 |
| DOI | 10.1002/mrm.25798 |
Cover
| Abstract | Purpose
Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack‐of‐stars gradient echo acquisition and compressed sensing reconstruction.
Methods
A technique for dynamic three‐dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data.
Results
Dynamic three‐dimensional images can be captured at sub‐150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of
4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements.
Conclusion
Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three‐dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295–2302, 2016. © 2015 Wiley Periodicals, Inc. |
|---|---|
| AbstractList | Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction.
A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data.
Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements.
Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. © 2015 Wiley Periodicals, Inc. Purpose Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction. Methods A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data. Results Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of [Formulaomitted] mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements. Conclusion Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction.PURPOSELung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction.A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data.METHODSA technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data.Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements.RESULTSDynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements.Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. © 2015 Wiley Periodicals, Inc.CONCLUSIONDynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. © 2015 Wiley Periodicals, Inc. Purpose Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack-of-stars gradient echo acquisition and compressed sensing reconstruction. Methods A technique for dynamic three-dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data. Results Dynamic three-dimensional images can be captured at sub-150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6 ×4.6 ×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements. Conclusion Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three-dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295-2302, 2016. © 2015 Wiley Periodicals, Inc. Purpose Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides spatial information but is challenging due to large movement over a short time. The purpose of this work is to provide a solution to lung imaging during forced expiration using accelerated magnetic resonance imaging. The method uses radial golden angle stack‐of‐stars gradient echo acquisition and compressed sensing reconstruction. Methods A technique for dynamic three‐dimensional imaging of the lungs from highly undersampled data is developed and tested on six subjects. This method takes advantage of image sparsity, both spatially and temporally, including the use of reference frames called bookends. Sparsity, with respect to total variation, and residual from the bookends, enables reconstruction from an extremely limited amount of data. Results Dynamic three‐dimensional images can be captured at sub‐150 ms temporal resolution, using only three (or less) acquired radial lines per slice per timepoint. The images have a spatial resolution of 4.6×4.6×10 mm. Lung volume calculations based on image segmentation are compared to those from simultaneously acquired spirometer measurements. Conclusion Dynamic lung imaging during forced expiration is made possible by compressed sensing accelerated dynamic three‐dimensional radial magnetic resonance imaging. Magn Reson Med 75:2295–2302, 2016. © 2015 Wiley Periodicals, Inc. |
| Author | Altbach, Maria I. Li, Zhitao Jeffries, Lindsie Cortopassi, Felipe Pandey, Abhishek Oliva, Isabel Martin, Diego R. Trouard, Theodore P. Berman, Benjamin P. Bilgin, Ali |
| AuthorAffiliation | 2 Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, USA 3 Department of Biomedical Engineering, University of Arizona, Tucson, Arizona, USA 1 Program in Applied Mathematics, University of Arizona, Tucson, Arizona, USA 4 Department of Medical Imaging, University of Arizona, Tucson, Arizona, USA |
| AuthorAffiliation_xml | – name: 2 Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, USA – name: 4 Department of Medical Imaging, University of Arizona, Tucson, Arizona, USA – name: 1 Program in Applied Mathematics, University of Arizona, Tucson, Arizona, USA – name: 3 Department of Biomedical Engineering, University of Arizona, Tucson, Arizona, USA |
| Author_xml | – sequence: 1 givenname: Benjamin P. surname: Berman fullname: Berman, Benjamin P. organization: Program in Applied Mathematics, University of Arizona, Arizona, Tucson, USA – sequence: 2 givenname: Abhishek surname: Pandey fullname: Pandey, Abhishek organization: Department of Electrical and Computer Engineering, University of Arizona, Arizona, Tucson, USA – sequence: 3 givenname: Zhitao surname: Li fullname: Li, Zhitao organization: Department of Electrical and Computer Engineering, University of Arizona, Arizona, Tucson, USA – sequence: 4 givenname: Lindsie surname: Jeffries fullname: Jeffries, Lindsie organization: Department of Biomedical Engineering, University of Arizona, Arizona, Tucson, USA – sequence: 5 givenname: Theodore P. surname: Trouard fullname: Trouard, Theodore P. organization: Department of Biomedical Engineering, University of Arizona, Tucson, Arizona, USA – sequence: 6 givenname: Isabel surname: Oliva fullname: Oliva, Isabel organization: Department of Medical Imaging, University of Arizona, Arizona, Tucson, USA – sequence: 7 givenname: Felipe surname: Cortopassi fullname: Cortopassi, Felipe organization: Department of Medical Imaging, University of Arizona, Arizona, Tucson, USA – sequence: 8 givenname: Diego R. surname: Martin fullname: Martin, Diego R. organization: Department of Medical Imaging, University of Arizona, Arizona, Tucson, USA – sequence: 9 givenname: Maria I. surname: Altbach fullname: Altbach, Maria I. organization: Department of Medical Imaging, University of Arizona, Arizona, Tucson, USA – sequence: 10 givenname: Ali surname: Bilgin fullname: Bilgin, Ali email: bilgin@email.arizona.edu organization: Department of Electrical and Computer Engineering, University of Arizona, Tucson, Arizona, USA |
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Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation... Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation provides... Purpose Lung function is typically characterized by spirometer measurements, which do not offer spatially specific information. Imaging during exhalation... |
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| SubjectTerms | compressed sensing Exhalation - physiology forced expiration Humans Imaging, Three-Dimensional - methods Lung - diagnostic imaging Lung - physiology Magnetic Resonance Imaging - methods pulmonary spirometry Spirometry - methods |
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| Title | Volumetric MRI of the lungs during forced expiration |
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