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Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla.

Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla. Research Abstract Details 

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  • Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla. Abstract Text:

    siamak ardekaniSiamak Ardekani,luis selvaLuis Selva,james sayreJames Sayre,usha sinhaUsha Sinha,siamak ardekaniSiamak Ardekani,luis selvaLuis Selva,james sayreJames Sayre,usha sinhaUsha Sinha,

    OBJECTIVES: Single-shot echo-planar based diffusion tensor imaging is prone to geometric and intensity distortions. Parallel imaging is a means of reducing these distortions while preserving spatial resolution. A quantitative comparison at 3 T of parallel imaging for diffusion tensor images (DTI) using k-space (generalized auto-calibrating partially parallel acquisitions; GRAPPA) and image domain (sensitivity encoding; SENSE) reconstructions at different acceleration factors, R, is reported here. MATERIALS AND METHODS: Images were evaluated using 8 human subjects with repeated scans for 2 subjects to estimate reproducibility. Mutual information (MI) was used to assess the global changes in geometric distortions. The effects of parallel imaging techniques on random noise and reconstruction artifacts were evaluated by placing 26 regions of interest and computing the standard deviation of apparent diffusion coefficient and fractional anisotropy along with the error of fitting the data to the diffusion model (residual error). RESULTS: The larger positive values in mutual information index with increasing R values confirmed the anticipated decrease in distortions. Further, the MI index of GRAPPA sequences for a given R factor was larger than the corresponding mSENSE images. The residual error was lowest in the images acquired without parallel imaging and among the parallel reconstruction methods, the R = 2 acquisitions had the least error. The standard deviation, accuracy, and reproducibility of the apparent diffusion coefficient and fractional anisotropy in homogenous tissue regions showed that GRAPPA acquired with R = 2 had the least amount of systematic and random noise and of these, significant differences with mSENSE, R = 2 were found only for the fractional anisotropy index. CONCLUSION: Evaluation of the current implementation of parallel reconstruction algorithms identified GRAPPA acquired with R = 2 as optimal for diffusion tensor imaging.

    Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla. Publishing Authors By Initials

    s ardekaniS Ardekani,l selvaL Selva,j sayreJ Sayre,u sinhaU Sinha,s ardekaniS Ardekani,l selvaL Selva,j sayreJ Sayre,u sinhaU Sinha,

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    Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla. Journal Published:

    PUBLICATION TYPE: Research Support, N.I.H., Extr

    Journal: Investigative radiology

    VOLUME: 41

    Page Numbers: 806-14

    Journal Abbreviation:

    ISSN: 0020-9996

    DAY: 12

    MONTH: Nov

    YEAR: 2006

    Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla. Information

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    LANGUAGE: eng

    NlmUniqueID: 45377

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    Grant and Affiliation Information for Quantitative metrics for evaluating parallel acquisition techniques in diffusion tensor imaging at 3 Tesla.

    AFFILIATION: Center for Cardiovascular Bioinformatics and Modeling, Johns Hopkins University, Maryland, USA.

    Country: United States

    United States Research PublicationUnited States Research Publication

    AGENCY: United States NIBIB

    GRANT: P01-EB00216

    ACRONYM: EB

    MEDLINETA: Invest Radiol

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