Deconvolution Analysis of Dynamic Contrast-Enhanced Data Based on Singular Value Decomposition Optimized by Generalized Cross Validation
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概要
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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.
- 日本磁気共鳴医学会の論文
- 2005-03-31
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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Murase Kenya
Department Of Medical Physics And Engineering Division Of Medical Technology And Science Course Of H
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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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Murase Kenya
大阪大学大学院医学系研究科保健学専攻
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MIYAZAKI Shohei
Department of Medical Physics and Engineering, Division of Medical Technology and Science, Course of
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YAMAZAKI Youichi
大阪大学大学院医学系研究科保健学専攻
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Murase K
Department Of Medical Physics And Engineering Division Of Medical Technology And Science Course Of H
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Miyazaki Shohei
Department Of Medical Physics And Engineering Division Of Medical Technology And Science Course Of H
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Miyazaki Shohei
大阪大学大学院医学系研究科保健学専攻
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Yamazaki Youichi
Department Of Medical Engineering Division Of Allied Health Sciences Osaka University Medical School
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Miyazaki Shohei
Department Of Medical Physics And Engineering Division Of Medical Technology And Science Course Of H
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Murase Kenya
Department Of Medical Physics And Engineering Division Of Medical Technology And Science Course Of H
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Murase Kenya
Department Of Allied Health Sciences Osaka University Graduate School Of Medicine
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Murase Kenya
Department Of Medical Physics And Engineering Division Of Medical Technology And Science Course Of H
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