Magnetic Resonance in Medical Sciences
Online ISSN : 1880-2206
Print ISSN : 1347-3182
ISSN-L : 1347-3182
3 巻, 4 号
選択された号の論文の10件中1~10を表示しています
Major Papers
  • Michihiro TAKEUCHI, Masaki SEKINO, Norio IRIGUCHI, Shoogo UENO
    2004 年 3 巻 4 号 p. 153-157
    発行日: 2004年
    公開日: 2005/07/05
    ジャーナル オープンアクセス
    In this study, we investigated the effect of structural differences in collagen fibers in relation to the spin-spin (T2) relaxation time of surrounding water molecules. We propose a simple experimental model of the magic angle effect based on magnetically oriented collagen gels. Experiments were performed with a 4.7T magnetic resonance imaging (MRI) system with a quadrature radio frequency coil operated at 200 MHz for 1H resonance. Collagen gels were polymerized from collagen solutions exposed to a 4.7T magnetic field for 120 min. The T2 relaxation time was measured with the Carr-Purcell-Meiboom-Gill (CPMG) sequence. The apparent diffusion coefficient (ADC) was measured with the stimulated echo acquisition mode (STEAM) sequence with a motion-probing gradient (MPG). Orienting the collagen fibers at an angle of about 55 degrees to the main magnetic field caused an increase in the T2 relaxation times of water molecules in the collagen gels. The ADC in the direction parallel to the fibers was larger than that in the direction perpendicular to the fibers. The increase in the T2 relaxation time and ADC are attributed to a change in the magnetic interaction between the water molecules and collagen fibers.
  • Tomohisa HATADA, Masaki SEKINO, Shoogo UENO
    2004 年 3 巻 4 号 p. 159-163
    発行日: 2004年
    公開日: 2005/07/05
    ジャーナル オープンアクセス
    Detection of weak magnetic fields induced by neuronal electrical activities with magnetic resonance imaging (MRI) is a potentially effective method for functional imaging of the brain. In this study, we compared the theoretical and practical limits of sensitivity for detecting weak magnetic fields with a columnar phantom. The theoretical limit of sensitivity was estimated from signal and noise intensities in magnetic resonance images. The theoretical limit of sensitivity was approximately 10-8T. The practical limit was 10 times the theoretical limit. The dependence of the theoretical limit of sensitivity on acquisition parameters, such as the repetition time (TR), echo time (TE), number of pixels, and spectral width, was quantitatively evaluated. The results indicated the existence of an optimal value in TE/T2*.
  • Kenya MURASE, Youichi YAMAZAKI, Shohei MIYAZAKI
    2004 年 3 巻 4 号 p. 165-175
    発行日: 2004年
    公開日: 2005/07/05
    ジャーナル オープンアクセス
    Purpose: To present an implementation of generalized cross validation (GCV) for automatically determining the regularization parameter—i.e., the threshold value in deconvolution analysis based on truncated singular value decomposition (TSVD) of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data—and to investigate the usefulness of this approach in comparison with TSVD with a fixed threshold value (TSVD-F).
    Methods: Using computer simulations, we generated a time-dependent concentration of the contrast agent in the volume of interest (VOI) from the arterial input function (AIF) modeled as a gamma-variate function under various cerebral blood flows (CBFs), cerebral blood volumes (CBVs), and signal-to-noise ratios (SNRs) for three different types of residue functions (exponential, triangular, and box-shaped). We also considered the effects of delay and dispersion in AIF. The TSVD with GCV (TSVD-G) and TSVD-F with a fixed threshold value of 0.2 were used to estimate CBF values from the simulated concentration-time curves in the VOI and AIF, and the estimated values were compared with the assumed values. Additionally, the optimal threshold value was determined from the threshold value in TSVD-F giving the mean CBF value closest to the assumed value and was compared with the threshold value determined with TSVD-G.
    Results: With TSVD-G, the CBF estimation was substantially improved over a wide range of CBFs for all types of residue functions at the cost of more noise than was seen with TSVD-F. The dependency of the threshold value determined with TSVD-G on the CBF, CBV, and SNR was similar to that of the optimal threshold value, with some discrepancy being observed for the box-shaped residue function, although they did not always agree in terms of absolute value.
    Conclusion: Given an improved SNR, TSVD-G is useful for quantification of CBF with deconvolution analysis of DCE-MRI data.
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