Signal‐to‐noise ratio‐enhancing joint reconstruction for improved diffusion imaging of mouse spinal cord white matter injury. Issue 2 (30th March 2015)
- Record Type:
- Journal Article
- Title:
- Signal‐to‐noise ratio‐enhancing joint reconstruction for improved diffusion imaging of mouse spinal cord white matter injury. Issue 2 (30th March 2015)
- Main Title:
- Signal‐to‐noise ratio‐enhancing joint reconstruction for improved diffusion imaging of mouse spinal cord white matter injury
- Authors:
- Kim, Joong Hee
Song, Sheng‐Kwei
Haldar, Justin P. - Abstract:
- Abstract : Purpose: To assess the capability of signal‐to‐noise ratio enhancing reconstruction (SER) to reduce the acquisition time for quantitative white matter injury assessment. Methods: Four single‐average diffusion tensor imaging (DTI) datasets were acquired for each animal from four mouse cohorts: two models of spinal cord injury and two control groups. Quantitative parameters (apparent diffusion coefficient, relative anisotropy, axial and radial diffusivities) were computed from (I) single‐average data with traditional reconstruction; (II) single‐average data with SER; (III) four‐average data with traditional reconstruction; and (IV) single‐average data with optimized multicomponent nonlocal means (OMNLM) denoising. These approaches were compared based on coefficients of variation (COVs) and whether estimated diffusion parameters were sensitive to injury. Results: SER yielded better COVs for diffusivity and anisotropy than traditional reconstruction of single‐average data, and yielded comparable COVs to that achieved with four‐average data. In addition, diffusion parameters obtained using SER with single‐average data had comparable injury sensitivity to those obtained from four‐average data, while diffusion parameters obtained from OMNLM and traditional reconstruction of single‐average data had limited sensitivity. Conclusion: A four‐fold reduction in the number of averages for quantitative diffusion imaging of small animal white matter injury is feasible using SER.Abstract : Purpose: To assess the capability of signal‐to‐noise ratio enhancing reconstruction (SER) to reduce the acquisition time for quantitative white matter injury assessment. Methods: Four single‐average diffusion tensor imaging (DTI) datasets were acquired for each animal from four mouse cohorts: two models of spinal cord injury and two control groups. Quantitative parameters (apparent diffusion coefficient, relative anisotropy, axial and radial diffusivities) were computed from (I) single‐average data with traditional reconstruction; (II) single‐average data with SER; (III) four‐average data with traditional reconstruction; and (IV) single‐average data with optimized multicomponent nonlocal means (OMNLM) denoising. These approaches were compared based on coefficients of variation (COVs) and whether estimated diffusion parameters were sensitive to injury. Results: SER yielded better COVs for diffusivity and anisotropy than traditional reconstruction of single‐average data, and yielded comparable COVs to that achieved with four‐average data. In addition, diffusion parameters obtained using SER with single‐average data had comparable injury sensitivity to those obtained from four‐average data, while diffusion parameters obtained from OMNLM and traditional reconstruction of single‐average data had limited sensitivity. Conclusion: A four‐fold reduction in the number of averages for quantitative diffusion imaging of small animal white matter injury is feasible using SER. Our results also underscore the need to validate nonlinear methods using task‐based measures on an application‐by‐application basis. Magn Reson Med 75:852–858, 2016. © 2015 Wiley Periodicals, Inc. … (more)
- Is Part Of:
- Magnetic resonance in medicine. Volume 75:Issue 2(2016:Feb.)
- Journal:
- Magnetic resonance in medicine
- Issue:
- Volume 75:Issue 2(2016:Feb.)
- Issue Display:
- Volume 75, Issue 2 (2016)
- Year:
- 2016
- Volume:
- 75
- Issue:
- 2
- Issue Sort Value:
- 2016-0075-0002-0000
- Page Start:
- 852
- Page End:
- 858
- Publication Date:
- 2015-03-30
- Subjects:
- diffusion tensor imaging -- signal‐to‐noise ratio -- denoising
Nuclear magnetic resonance -- Periodicals
Electron paramagnetic resonance -- Periodicals
616.07548 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1522-2594 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1002/mrm.25691 ↗
- Languages:
- English
- ISSNs:
- 0740-3194
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5337.798000
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