title: Accuracy of deconvolution analysis based on singular value decomposition for quantification of cerebral blood flow using dynamic susceptibility contrast-enhanced magnetic resonance imaging.
abstract: Deconvolution analysis (DA) based on singular value decomposition (SVD) has been widely accepted for quantification of cerebral blood flow (CBF) using dynamic susceptibility contrast-enhanced magnetic resonance imaging (DSC-MRI). When using this method, the elements in the diagonal matrix obtained by SVD are set to zero when they are smaller than the threshold value given beforehand. In the present study, we investigated the effect of the threshold value on the accuracy of the CBF values obtained by this method using computer simulations. We also investigated the threshold value giving the CBF closest to the assumed value (optimal threshold value) under various conditions. The CBF values obtained by this method largely depended on the threshold value. Both the mean and the standard deviation of the estimated CBF values decreased with increasing threshold value. The optimal threshold value decreased with increasing signal-to-noise ratio and CBF, and increased with increasing cerebral blood volume. Although delay and dispersion in the arterial input function also affected the relationship between the estimated CBF and threshold values, the optimal threshold value tended to be nearly constant. In conclusion, our results suggest that the threshold value should be carefully considered when quantifying CBF in terms of absolute values using DSC-MRI for DA based on SVD. We believe that this study will be helpful in selecting the threshold value in SVD.
authors.affiliation: Department of Medical Engineering, Division of Allied Health Sciences, Osaka University Medical School, Suita, Japan. murase@sahs.med.osaka-u.ac.jp
authors.forename: K
authors.initials: K
authors.lastname: Murase
authors.forename: M
authors.initials: M
authors.lastname: Shinohara
authors.forename: Y
authors.initials: Y
authors.lastname: Yamazaki
mesh_terms: D000465:Algorithms; D001783:Blood Flow Velocity / Q000502:physiology; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008962:Models, Theoretical; D012039:Regional Blood Flow / Q000502:physiology*; D013687:Telencephalon / Q000098:blood supply*; D013997:Time Factors