Highly accelerated dynamic acquisition of 3D grid‐tagged hyperpolarized‐gas lung images using compressed sensing.
Saved in:
| Title: | Highly accelerated dynamic acquisition of 3D grid‐tagged hyperpolarized‐gas lung images using compressed sensing. |
|---|---|
| Authors: | Garrison, William J.1 (AUTHOR), Qing, Kun2,3 (AUTHOR), Tafti, Sina4 (AUTHOR), Mugler, John P.1,2 (AUTHOR), Shim, Y. Michael5 (AUTHOR), Mata, Jaime F.2 (AUTHOR), Cates, Gordon D.2,4 (AUTHOR), de Lange, Eduard E.2 (AUTHOR), Meyer, Craig H.1,2 (AUTHOR), Cai, Jing6 (AUTHOR), Miller, G. Wilson1,2,4 (AUTHOR) gwm2n@virginia.edu |
| Source: | Magnetic Resonance in Medicine. Jun2023, Vol. 89 Issue 6, p2255-2263. 9p. |
| Subjects: | Lungs, Generating functions, Magnetic resonance imaging, Compressed sensing |
| Abstract: | Purpose: To develop and test compressed sensing–based multiframe 3D MRI of grid‐tagged hyperpolarized gas in the lung. Theory and Methods: Applying grid‐tagging RF pulses to inhaled hyperpolarized gas results in images in which signal intensity is predictably and sparsely distributed. In the present work, this phenomenon was used to produce a sampling pattern in which k‐space is undersampled by a factor of approximately seven, yet regions of high k‐space energy remain densely sampled. Three healthy subjects received multiframe 3D 3He tagging MRI using this undersampling method. Images were collected during a single exhalation at eight timepoints spanning the breathing cycle from end‐of‐inhalation to end‐of‐exhalation. Grid‐tagged images were used to generate 3D displacement maps of the lung during exhalation, and time‐resolved maps of principal strains and fractional volume change were generated from these displacement maps using finite‐element analysis. Results: Tags remained clearly resolvable for 4–6 timepoints (5–8 s) in each subject. Displacement maps revealed noteworthy temporal and spatial nonlinearities in lung motion during exhalation. Compressive normal strains occurred along all three principal directions but were primarily oriented in the head–foot direction. Fractional volume changes displayed clear bilateral symmetry, but with the lower lobes displaying slightly higher change than the upper lobes in 2 of the 3 subjects. Conclusion: We developed a compressed sensing–based method for multiframe 3D MRI of grid‐tagged hyperpolarized gas in the lung during exhalation. This method successfully overcomes previous challenges for 3D dynamic grid‐tagging, allowing time‐resolved biomechanical readouts of lung function to be generated. [ABSTRACT FROM AUTHOR] |
| Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
|
Full text is not displayed to guests.
Login for full access.
|
|
| FullText | Links: – Type: pdflink Text: Availability: 1 |
|---|---|
| Header | DbId: egs DbLabel: Engineering Source An: 162707263 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
| IllustrationInfo | |
| Items | – Name: Title Label: Title Group: Ti Data: Highly accelerated dynamic acquisition of 3D grid‐tagged hyperpolarized‐gas lung images using compressed sensing. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Garrison%2C+William+J%2E%22">Garrison, William J.</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Qing%2C+Kun%22">Qing, Kun</searchLink><relatesTo>2,3</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Tafti%2C+Sina%22">Tafti, Sina</searchLink><relatesTo>4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mugler%2C+John+P%2E%22">Mugler, John P.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Shim%2C+Y%2E+Michael%22">Shim, Y. Michael</searchLink><relatesTo>5</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Mata%2C+Jaime+F%2E%22">Mata, Jaime F.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cates%2C+Gordon+D%2E%22">Cates, Gordon D.</searchLink><relatesTo>2,4</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22de+Lange%2C+Eduard+E%2E%22">de Lange, Eduard E.</searchLink><relatesTo>2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Meyer%2C+Craig+H%2E%22">Meyer, Craig H.</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cai%2C+Jing%22">Cai, Jing</searchLink><relatesTo>6</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Miller%2C+G%2E+Wilson%22">Miller, G. Wilson</searchLink><relatesTo>1,2,4</relatesTo> (AUTHOR)<i> gwm2n@virginia.edu</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Magnetic+Resonance+in+Medicine%22">Magnetic Resonance in Medicine</searchLink>. Jun2023, Vol. 89 Issue 6, p2255-2263. 9p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Lungs%22">Lungs</searchLink><br /><searchLink fieldCode="DE" term="%22Generating+functions%22">Generating functions</searchLink><br /><searchLink fieldCode="DE" term="%22Magnetic+resonance+imaging%22">Magnetic resonance imaging</searchLink><br /><searchLink fieldCode="DE" term="%22Compressed+sensing%22">Compressed sensing</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Purpose: To develop and test compressed sensing–based multiframe 3D MRI of grid‐tagged hyperpolarized gas in the lung. Theory and Methods: Applying grid‐tagging RF pulses to inhaled hyperpolarized gas results in images in which signal intensity is predictably and sparsely distributed. In the present work, this phenomenon was used to produce a sampling pattern in which k‐space is undersampled by a factor of approximately seven, yet regions of high k‐space energy remain densely sampled. Three healthy subjects received multiframe 3D 3He tagging MRI using this undersampling method. Images were collected during a single exhalation at eight timepoints spanning the breathing cycle from end‐of‐inhalation to end‐of‐exhalation. Grid‐tagged images were used to generate 3D displacement maps of the lung during exhalation, and time‐resolved maps of principal strains and fractional volume change were generated from these displacement maps using finite‐element analysis. Results: Tags remained clearly resolvable for 4–6 timepoints (5–8 s) in each subject. Displacement maps revealed noteworthy temporal and spatial nonlinearities in lung motion during exhalation. Compressive normal strains occurred along all three principal directions but were primarily oriented in the head–foot direction. Fractional volume changes displayed clear bilateral symmetry, but with the lower lobes displaying slightly higher change than the upper lobes in 2 of the 3 subjects. Conclusion: We developed a compressed sensing–based method for multiframe 3D MRI of grid‐tagged hyperpolarized gas in the lung during exhalation. This method successfully overcomes previous challenges for 3D dynamic grid‐tagging, allowing time‐resolved biomechanical readouts of lung function to be generated. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=162707263 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1002/mrm.29595 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 9 StartPage: 2255 Subjects: – SubjectFull: Lungs Type: general – SubjectFull: Generating functions Type: general – SubjectFull: Magnetic resonance imaging Type: general – SubjectFull: Compressed sensing Type: general Titles: – TitleFull: Highly accelerated dynamic acquisition of 3D grid‐tagged hyperpolarized‐gas lung images using compressed sensing. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Garrison, William J. – PersonEntity: Name: NameFull: Qing, Kun – PersonEntity: Name: NameFull: Tafti, Sina – PersonEntity: Name: NameFull: Mugler, John P. – PersonEntity: Name: NameFull: Shim, Y. Michael – PersonEntity: Name: NameFull: Mata, Jaime F. – PersonEntity: Name: NameFull: Cates, Gordon D. – PersonEntity: Name: NameFull: de Lange, Eduard E. – PersonEntity: Name: NameFull: Meyer, Craig H. – PersonEntity: Name: NameFull: Cai, Jing – PersonEntity: Name: NameFull: Miller, G. Wilson IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Jun2023 Type: published Y: 2023 Identifiers: – Type: issn-print Value: 07403194 Numbering: – Type: volume Value: 89 – Type: issue Value: 6 Titles: – TitleFull: Magnetic Resonance in Medicine Type: main |
| ResultId | 1 |
