Evaluation of optimized b -value sampling schemas for diffusion kurtosis imaging with an application to stroke patient data

Abstract Diffusion kurtosis imaging (DKI) is a new method of magnetic resonance imaging (MRI) that provides non-Gaussian information that is not available in conventional diffusion tensor imaging (DTI). DKI requires data acquisition at multiple b -values for parameter estimation; this process is usu...

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Bibliographic Details
Published in:Computerized medical imaging and graphics 2013-06, Vol.37 (4), p.272-280
Main Authors: Yan, Xu, Zhou, Minxiong, Ying, Lingfang, Yin, Dazhi, Fan, Mingxia, Yang, Guang, Zhou, Yongdi, Song, Fan, Xu, Dongrong
Format: Article
Language:English
Subjects:
Aged
Algorithms
Applied sciences
Artificial intelligence
b-value sampling
Biological and medical sciences
Brain - pathology
Computer science
control theory
systems
Data Interpretation, Statistical
Data processing. List processing. Character string processing
Diffusion kurtosis imaging
Diffusion tensor imaging
Diffusion Tensor Imaging - methods
Exact sciences and technology
Female
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Internal Medicine
Investigative techniques, diagnostic techniques (general aspects)
Male
Medical sciences
Memory organisation. Data processing
Middle Aged
Nervous system
Neurology
Non-Gaussian diffusion
Optimized b-value
Other
Pattern recognition. Digital image processing. Computational geometry
Radiodiagnosis. Nmr imagery. Nmr spectrometry
Reproducibility of Results
Sample Size
Sensitivity and Specificity
Signal Processing, Computer-Assisted
Software
Stroke - pathology
Vascular diseases and vascular malformations of the nervous system
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Description
Summary:Abstract Diffusion kurtosis imaging (DKI) is a new method of magnetic resonance imaging (MRI) that provides non-Gaussian information that is not available in conventional diffusion tensor imaging (DTI). DKI requires data acquisition at multiple b -values for parameter estimation; this process is usually time-consuming. Therefore, fewer b -values are preferable to expedite acquisition. In this study, we carefully evaluated various acquisition schemas using different numbers and combinations of b -values. Acquisition schemas that sampled b -values that were distributed to two ends were optimized. Compared to conventional schemas using equally spaced b -values (ESB), optimized schemas require fewer b -values to minimize fitting errors in parameter estimation and may thus significantly reduce scanning time. Following a ranked list of optimized schemas resulted from the evaluation, we recommend the 3b schema based on its estimation accuracy and time efficiency, which needs data from only 3 b -values at 0, around 800 and around 2600 s/mm2 , respectively. Analyses using voxel-based analysis (VBA) and region-of-interest (ROI) analysis with human DKI datasets support the use of the optimized 3b (0, 1000, 2500 s/mm2 ) DKI schema in practical clinical applications.
ISSN:0895-6111
1879-0771
DOI:10.1016/j.compmedimag.2013.04.007