High <i>b</i>‐Value <i>q</i>‐Space Analyzed Diffusion‐Weighted MRI Using 1.5 Tesla Clinical Scanner; Determination of Displacement Parameters in the Brains of Normal versus Multiple Sclerosis and Low‐Grade Glioma Subjects

Fatima, Zareen; Hori, Masaaki; Ishigame, Keiichi; Onodera, Tatsuhiro; Yagi, Kazuo; Araki, Tsutomu

doi:10.1111/j.1552-6569.2011.00596.x

Cited by 9 publications

(4 citation statements)

References 23 publications

(35 reference statements)

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“…18,21 However, for q-space analysis, QSI-analyzer was introduced for calculating the FWHM of the PDF and the mean displacement of water molecules. 22,26,30,31 For diŠusional kurtosis analysis, diffusion kurtosis estimator (DKE) 29,32 and the combination of dTV¿FZR (http://www.ut-radiology. umin.jp/people/masutani/dTV.htm) and VOLUME-ONE software (http://www.volume-one.org/) have been introduced in the literature 33,34 (Fig.…”

Section: Software For Calculating Non-gaussian Metricsmentioning

confidence: 99%

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Hori

Fukunaga

Masutani

et al. 2012

MRMS

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104

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Recently, non-Gaussian diŠusion-weighted imaging (DWI) techniques, including qspace imaging (QSI) and diŠusional kurtosis imaging (DKI), have emerged as advanced methods to evaluate tissue microstructure in vivo using water diŠusion. QSI and DKI have shown promising results in clinical applications, such as in the evaluation of brain tumors (e.g., grading gliomas), degenerative diseases (e.g., speciˆc diagnosis of Parkinson disease), demyelinating diseases (e.g., assessment of normal-appearing tissue of multiple sclerosis), and cerebrovascular diseases (e.g., assessment of the microstructural environment of fresh infarctions). Representative metrics in clinical use are the full width at half maximum, also known as the mean displacement of the probability density function curve, which is derived from QSI, and diŠusional kurtosis, which is derived from DKI. These new metrics may provide information on tissue structure in addition to that provided by conventional Gaussian DWI investigations that use the apparent diŠusion coe‹cient and fractional anisotropy, recognized indices for evaluating disease and normal development in the brain and spine. In some clinical situations, sensitivity for detecting pathological conditions is higher using QSI and DKI than conventional DWI and diŠusion tensor imaging (DTI) because DWI and DTI calculations are based on the assumption that water molecules follow a Gaussian distribution, whereas hindrance of the distribution of water molecules by complex and restricted structures in actual neural tissues produces distributions that are far from Gaussian. We review the technical aspects and clinical applications of QSI and DKI, focusing on clinical use and in vivo studies and highlighting diŠerences from conventional diŠusional metrics.

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Section: Software For Calculating Non-gaussian Metricsmentioning

confidence: 99%

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Hori

Fukunaga

Masutani

et al. 2012

MRMS

Self Cite

104

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“…All QSI data were transferred to an independent PC, and MDP maps were obtained for each MPG axis by using software (QSI-analyzer; 25,27,28) applying the theory of q-space analysis (24,25). All conventional DWI images were transferred to an independent workstation, and ADC maps were obtained.…”

Section: Methodsmentioning

confidence: 99%

Mean displacement map of spine and spinal cord disorders using high b-value q-space imaging-feasibility study

et al. 2011

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“…2 ). 15 , 16 In general, the advantage of QSI compared to DTI is its ability to detect pathologic conditions with higher sensitivity. 17 , 18 Moreover, QSI-based myelin imaging was introduced to monitor demyelination and remyelination in MS patients.…”

Section: Q-space Imagingmentioning

confidence: 99%

Advanced Diffusion MR Imaging for Multiple Sclerosis in the Brain and Spinal Cord

Hori

Maekawa

Kamiya

et al. 2022

MRMS

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Diffusion tensor imaging (DTI) has been established its usefulness in evaluating normal-appearing white matter (NAWM) and other lesions that are difficult to evaluate with routine clinical MRI in the evaluation of the brain and spinal cord lesions in multiple sclerosis (MS), a demyelinating disease. With the recent advances in the software and hardware of MRI systems, increasingly complex and sophisticated MRI and analysis methods, such as q-space imaging, diffusional kurtosis imaging, neurite orientation dispersion and density imaging, white matter tract integrity, and multiple diffusion encoding, referred to as advanced diffusion MRI, have been proposed. These are capable of capturing in vivo microstructural changes in the brain and spinal cord in normal and pathological states in greater detail than DTI.This paper reviews the current status of recent advanced diffusion MRI for assessing MS in vivo as part of an issue celebrating two decades of magnetic resonance in medical sciences (MRMS), an official journal of the Japanese Society of Magnetic Resonance in Medicine.

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High b‐Value q‐Space Analyzed Diffusion‐Weighted MRI Using 1.5 Tesla Clinical Scanner; Determination of Displacement Parameters in the Brains of Normal versus Multiple Sclerosis and Low‐Grade Glioma Subjects

Abstract: We propose that the relative values of MD obtained by QSI in control and diseased tissues can be useful for diagnosing various WM abnormalities.

Cited by 9 publications

References 23 publications

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Visualizing Non-Gaussian Diffusion: Clinical Application of q-Space Imaging and Diffusional Kurtosis Imaging of the Brain and Spine

Mean displacement map of spine and spinal cord disorders using high b-value q-space imaging-feasibility study

Advanced Diffusion MR Imaging for Multiple Sclerosis in the Brain and Spinal Cord

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