Autoregressive Moving Average(ARMA) Model Applied to Quantification of Cerebral Blood Flow Using Dynamic Susceptibility Contrast-enhanced Magnetic Resonance Imaging
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概要
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Purpose: To investigate the feasibility of the autoregressive moving average (ARMA) model for quantification of cerebral blood flow (CBF) with dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI) in comparison with deconvolution analysis based on singular value decomposition (DA-SVD). 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 CBFs, cerebral blood volumes and signal-to-noise ratios (SNRs) for three different types of residue function (exponential, triangular, and box-shaped). We also considered the effects of delay and dispersion in AIF. The ARMA model and DA-SVD were used to estimate CBF values from the simulated concentration-time curves in the VOI and AIFs, and the estimated values were compared with the assumed values. Results: We found that the CBF value estimated by the ARMA model was more sensitive to the SNR and the delay in AIF than that obtained by DA-SVD. Although the ARMA model considerably overestimated CBF at low SNRs, it estimated the CBF more accurately than did DA-SVD at high SNRs for the exponential or triangular residue function. Conclusion: We believe this study will contribute to an understanding of the usefulness and limitations of the ARMA model when applied to quantification of CBF with DSC-MRI.
- 日本磁気共鳴医学会の論文
- 2003-07-01
著者
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MURASE Kenya
Department of Medical Engineering, Division of Allied Health Sciences, Osaka University Medical Scho
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Shinohara Masaaki
Department Of Medical Engineering Division Of Allied Health Sciences Osaka University Medical School
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YAMAZAKI Youichi
Department of Medical Engineering, Division of Allied Health Sciences, Osaka University Medical Scho
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Murase Kenya
Department Of Medical Engineering Division Of Allied Health Sciences Osaka University Medical School
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Yamazaki Youichi
Department Of Medical Engineering Division Of Allied Health Sciences Osaka University Medical School
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Murase Kenya
Department Of Allied Health Sciences Osaka University Graduate School Of Medicine
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