Research On Cerebral Blood Volume Based On Dynamic Contrast-enhanced Magnetic Resonance Imaging

Dynamic contrast-enhanced magnetic resonance imaging(MRI)is a kind of magnetic resonance perfusion imaging technology,which is used to study the hemodynamic parameters of the test site.It evaluates the perfusion status and the microcirculation blood flow of the corresponding tissues or organs effectively by the comparison of the parameter values in order to realize the diagnosis of disease.As the first choice for the diagnosis of certain brain diseases,the study on the hemodynamic parameters of cerebral blood volume(CBV)is of great importance.Firstly,the research background and development of the dynamic contrast enhanced MRI technique are overviewed in detail.Secondly,the improved adaptive algorithm method based on the least mean square(LMS)is studied and applied to simulate CBV.Factors such as signal to noise ratio(SNR),residue functions and tracer delay are discussed as well.The simulation results show that the improved adaptive algorithm based on LMS is more accurate than the Fourier transform algorithm based on minimum mean square error(MMSE).The former is not affected by the ratio of signal to noise ratio and the delay of tracer,but the latter is influenced by the signal to noise ratio.Then,the singular value decomposition(SVD)method based on the Hankel matrix is proposed to estimate the cerebral blood volume.Compared with the traditional SVD method,it can calculate the CBV more objectively.Finally,the color-coded CBV maps are achieved from Dynamic contrast-enhanced MRI images by the improved adaptive algorithm based on LMS and the SVD method based on the Hankel matrix.The color-coded images can reflect the brain structure clearly,and estimate the distribution of CBV.It provides an objective basis for the clinical diagnosis of the lesion location and lesion type.