Use of a clinical MRI scanner for preclinical research on rats

Abstract

This study evaluated the feasibility of imaging rat brains using a human whole-body 3-T magnetic resonance imaging (MRI) scanner with specially developed transmit-and-receive radiofrequency coils. The T₁- and T₂-weighted images obtained showed reasonable contrast. Acquired contrast-free time-of-flight magnetic resonance angiography images clearly showed the cortical middle cerebral artery (MCA) branches, and interhemispheric differences could be observed. Dynamic susceptibility contrast MRI at 1.17 mm³ voxel resolution, performed three times following administration of gadolinium diethylenetriamine pentaacetic acid (Gd-DTPA, 0.1 mmol/kg), demonstrated that the arterial input function (AIF) can be obtained from the MCA region, yielding cerebral blood flow (CBF), cerebral blood volume, and mean transit time (MTT) maps. The hypothalamus (HT) to parietal cortex (Pt) CBF ratio was 45.11 ± 2.85%, and the MTT was 1.29 ± 0.40 s in the Pt region and 2.32 ± 0.17 s in the HT region. A single dose of Gd-DTPA enabled the assessment of AIF within MCA territory and of quantitative CBF in rats.

Appendix: Calculation of functional mapping images from DSC-MRI

The observed TIC S(t) was converted to a time-versus-concentration curve (TCC) C(t) by the following equation [16, 36]:

$$ C(t) = k\cdot\Updelta R2^*(t) = - k\cdot {\rm In}\left({S(0)/S(t)} \right)/{\rm TE}, $$

(1)

where ΔR2* is the change in the T₂* relaxation rate and k is a constant. In this study, it was assumed that k = 1. S(0) is the pre-contrast (baseline) signal and S(t) is the measured signal at time t. The next step was to fit this first-pass period of TCC to a gamma variate function:

$$ C(t) = a\left( {t - b} \right)^{c} \exp \left( { - (t - b)/d} \right), $$

(2)

where a, b, c, and d were determined by nonlinear least-squares fitting. To minimize the effects of the recirculation of the contrast agent, data were neglected in the fit if these concentrations were less than 50% of the maximum after the peak of the TCC.

The fitted tissue TCC Ct(t) was deconvolved by the fitted AIF C _AIF(t) by using singular value decomposition with a block-circulant deconvolution matrix (b-SVD) method [28] according to the equation

$$ {\rm CBF}\cdot R(t) = Ct(t) \otimes^{- 1} C_{\rm AIF} (t), $$

(3)

where ⊗⁻¹ represents the deconvolution operator and R(t) is a residue function representing the tissue response to an instantaneous bolus. CBF·R(t) was estimated by deconvolving Ct(t) by C _AIF(t) using b-SVD, and then CBF was determined as the maximum value of the obtained CBF·R(t).

The CBV was calculated as follows:

$$ {\text{CBV}} = {{\int\limits_{0}^{\infty } {Ct(t){\text{d}}t} } \mathord{\left/ {\vphantom {{\int\limits_{0}^{\infty } {Ct(t){\text{d}}t} } {\int\limits_{0}^{\infty } {C_{\text{AIF}} (t){\text{d}}t} }}} \right. \kern-\nulldelimiterspace} {\int\limits_{0}^{\infty } {C_{\text{AIF}} (t){\text{d}}t} }}. $$

(4)

Lastly, the MTT is calculated from CBF and CBV by applying the central volume principle [32]:

$$ {\text{MTT}} = {\text{CBV}}/{\text{CBF}}. $$

(5)