Volumetric q-space imaging by 3D diffusion-weighted MRI

Hikishima, Keigo; Yagi, Kazuo; Numano, Tomokazu; Homma, Kazuhiro; Nitta, Naotaka; Nakatani, Tetsu; Hyodo, Koji

doi:10.1016/j.mri.2007.09.001

Cited by 15 publications

(19 citation statements)

References 12 publications

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“…Skeletal muscle cells are currently classiˆed by staining but may be classiˆed in the future by MR imaging using the l 3 value and q-space imaging. [27][28][29] …”

Section: Discussionmentioning

confidence: 99%

Diffusion Fractional Anisotropy-based Transformation in Skeletal Muscle Caused by Pressure

Hata¹,

Yagi

Hikishima³

et al. 2012

magn reson med sci

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Purpose: We used diŠusion tensor imaging (DTI) to evaluate anisotropic changes in skeletal muscle cells under external pressure.Materials and Methods: In 6 healthy volunteers, we compared DTI of the tibialis anterior (TA) and soleus (SOL) muscles under pressure. We performed imaging using a 1.5-tesla magnetic resonance (MR) scanner and diŠusion-weighted stimulated-echo echo-planar pulse sequences optimized for skeletal muscle. We calculated diŠusion tensor eigenvalues (l), apparent diŠusion coe‹cients, and fractional anisotropy (FA) values in a series of axially acquired DTI and compared them between the pressurized and nonpressurized lower limbs. We also measured a cross-sectional area of skeletal muscle.Results: We observed clear diŠerences in FA and l 3 between pressurized muscles and the nonpressurized muscles we used as controls. Conclusion: Anisotropy changed markedly on pressurizing the lower limb based on the correlation of the cross-sectional area and l 3 suggested marked changed in anisotropy following application of pressure to the lower limb. If compression of the cross-sectional area is assumed to represent compression of the cell, change in l 3 re‰ected the change in the size of muscle cells.

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“…Skeletal muscle cells are currently classiˆed by staining but may be classiˆed in the future by MR imaging using the l 3 value and q-space imaging. [27][28][29] …”

Section: Discussionmentioning

confidence: 99%

Diffusion Fractional Anisotropy-based Transformation in Skeletal Muscle Caused by Pressure

Hata¹,

Yagi

Hikishima³

et al. 2012

magn reson med sci

Self Cite

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show abstract

“…A non-Gaussian diŠusion analysis using multiple b-values, including high b-values, has been introduced to estimate real structural information [16][17][18][19][20][21][22][23] ; this is called``q-space imaging.'' The main principle in q-space analysis is that a Fourier transformation of the signal intensity with respect to q, Et dif (q), provides the PDF, Ps(R, t dif ), for the water diŠusion: Ps(R, t dif )＝FTs E tdif (q)t , 21 where R＝the distance a spin diŠuses during the allowed diŠusion time; t dif ＝D-d/3, the eŠective diŠusion time; D＝ the time between MPG pulses; and d＝the length of the MPG pulse.…”

Section: Q-space Analysismentioning

confidence: 99%

“…1). The MDP or root mean square displacement value at each MPG axis can be calculated using the following equation 21,23 : MDP value ＝0.425×FWHM. The normal MDP in the white matter and grey matter is reported to be 3.3±0.8 and 7-9, 19 3.8±0.2 and 5-9, 24 6.6±0.2 and 8.44± 0.41, 22 9 and 11.9 mm.…”

Section: Q-space Analysismentioning

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

105

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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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“…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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Volumetric q-space imaging by 3D diffusion-weighted MRI

Cited by 15 publications

References 12 publications

Diffusion Fractional Anisotropy-based Transformation in Skeletal Muscle Caused by Pressure

Diffusion Fractional Anisotropy-based Transformation in Skeletal Muscle Caused by Pressure

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

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