Multispectral diffusion‐weighted imaging near metal implants
Purpose The need for diffusion‐weighted‐imaging (DWI) near metallic implants is becoming increasingly relevant for a variety of clinical diagnostic applications. Conventional DWI methods are significantly hindered by metal‐induced image artifacts. A novel approach relying on multispectral susceptibi...
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Published in | Magnetic resonance in medicine Vol. 79; no. 2; pp. 987 - 993 |
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Main Authors | , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Wiley Subscription Services, Inc
01.02.2018
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Subjects | |
Online Access | Get full text |
ISSN | 0740-3194 1522-2594 1522-2594 |
DOI | 10.1002/mrm.26737 |
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Summary: | Purpose
The need for diffusion‐weighted‐imaging (DWI) near metallic implants is becoming increasingly relevant for a variety of clinical diagnostic applications. Conventional DWI methods are significantly hindered by metal‐induced image artifacts. A novel approach relying on multispectral susceptibility artifact reduction techniques is presented to address this unmet need.
Methods
DWI near metal implants is achieved through a combination of several advanced MRI acquisition technologies. Previously described approaches to Carr–Purcell–Meiboom–Gill spin‐echo train DWI sequences using the periodically rotated overlapping parallel lines with enhanced reconstruction are combined with multispectral‐imaging metal artifact reduction principles to provide DWI with substantially reduced artifact levels. The presented methods are applied to limited sets of slices over areas of sarcoma risk near six implanted devices.
Results
Using the presented methods, DWI assessment without bulk image distortions is demonstrated in the immediate vicinity of metallic interfaces. In one subject, the apparent diffusion coefficient was reduced in a region of suspected sarcoma directly adjacent to fixation hardware.
Conclusions
An initial demonstration of minimal‐artifact multispectral DWI in the near vicinity of metallic hardware is described and successfully demonstrated on clinical subjects. Magn Reson Med 79:987–993, 2018. © 2017 International Society for Magnetic Resonance in Medicine. |
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Bibliography: | Drs. Gaddipati, Gui, Peters, and Kaushik are employed by GE Healthcare. ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
ISSN: | 0740-3194 1522-2594 1522-2594 |
DOI: | 10.1002/mrm.26737 |