title: Signal-to-noise ratio-enhancing joint reconstruction for improved diffusion imaging of mouse spinal cord white matter injury.
abstract: OBJECTIVE
  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.
  
  
  CONCLUSIONS
  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.
authors.affiliation: Department of Radiology, Washington University, St. Louis, Missouri, USA.
authors.forename: Joong Hee
authors.initials: JH
authors.lastname: Kim
authors.affiliation: Department of Radiology, Washington University, St. Louis, Missouri, USA.
authors.forename: Sheng-Kwei
authors.initials: SK
authors.lastname: Song
authors.affiliation: Departments of Electrical Engineering and Biomedical Engineering, University of Southern California, Los Angeles, California, USA.
authors.forename: Justin P
authors.initials: JP
authors.lastname: Haldar
mesh_terms: D000818:Animals; D016880:Anisotropy; D056324:Diffusion Tensor Imaging / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods; D051379:Mice; D059629:Signal-To-Noise Ratio; D013119:Spinal Cord Injuries / Q000175:diagnosis*; D066127:White Matter / Q000293:injuries*
keywords: denoising; diffusion tensor imaging; signal-to-noise ratio
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