High b‐value q‐space diffusion‐weighted MRI of the human cervical spinal cord in vivo: Feasibility and application to multiple sclerosis

Abstract

Q-space analysis is an alternative analysis technique for diffusion-weighted imaging (DWI) data in which the probability density function (PDF) for molecular diffusion is estimated without the need to assume a Gaussian shape. Although used in the human brain, q-space DWI has not yet been applied to study the human spinal cord in vivo. Here we demonstrate the feasibility of performing q-space imaging in the cervical spinal cord of eight healthy volunteers and four patients with multiple sclerosis. The PDF was computed and water displacement and zerodisplacement probability maps were calculated from the width and height of the PDF, respectively. In the dorsal column white matter, q-space contrasts showed a significant (P < 0.01) increase in the width and a decrease in the height of the PDF in lesions, the result of increased diffusion. These q-space contrasts, which are sensitive to the slow diffusion component, exhibited improved detection of abnormal diffusion compared to perpendicular apparent diffusion constant measurements. In white matter (WM) the axonal membrane and myelin sheath present barriers to water displacement, resulting in anisotropic diffusion (1-4). WM damage is known to affect tissue microstructure and diffusion-weighted MRI (DWI) has been used to measure changes in diffusion properties (both parallel and perpendicular to WM fiber bundles) in a number of WM diseases in humans (5) as well as animal models of myelin deficiency (6,7). In general, however, conclusive assignment of diffusion changes observed with DWI to axonal and/or myelin damage is not straightforward, in part because the biophysics of diffusion in vivo is not fully understood and because axonal and myelin loss are histopathologically related. Additionally, the technique selected to analyze diffusion-weighted images (DWIs) is an important consideration and has an impact on the quantitative interpretation of diffusion experiments. DWIs are typically analyzed with a monoexponential tensor model that characterizes the observed signal decay according to the Stejskal-Tanner equation (8):where S/S 0 is the normalized signal intensity, ␥ is the proton gyromagnetic ratio, ␦, G, and ⌬ are the duration, magnitude, and leading edge separation time of the diffusion weighting gradient vector, respectively, and D is the diffusion tensor. Diffusion tensor imaging (DTI) has been applied in the brain (5,9 -12) and spinal cord (10,(13)(14)(15) and is typically performed in the low b-value (Ͻ1500 s/mm 2 ) regime where the signal decay is, to a reasonable approximation, monoexponential. The degree to which diffusion is reduced in the CNS, compared to free water, is the result of microstructural barriers, which generally includes multiple compartments in vivo and the diffusion time that molecules have to explore their environment. If restrictions between compartments are sufficiently large so that exchange is slow on the MR timescale, the signal attenuation will become non-monoexponential. This effect becomes apparent at higher b-values (Ͼ1500 s/mm 2 )...

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

“…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.…”

“…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.…”

“…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.…”

“…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. 25 This method is theoretically superior to conventional Gaussian diŠusion analysis, but few reports apply it to human studies 21,26 because QSI is timeconsuming for daily clinical use, generally taking a minimum of 10 min.…”

“…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.…”