https://scholars.lib.ntu.edu.tw/handle/123456789/611805
標題: | A control point interpolation method for the non-parametric quantification of cerebral haemodynamics from dynamic susceptibility contrast MRI | 作者: | Mehndiratta A. MacIntosh B.J. Crane D.E. Payne S.J. Chappell M.A. STEPHEN JOHN PAYNE |
關鍵字: | accuracy;algorithm;article;brain blood flow;brain function;brain hemodynamics;brain infarction;brain tissue;controlled study;hemodynamics;human;human tissue;nonparametric test;parenchyma;priority journal;simulation;susceptibility weighted imaging;Algorithms;Blood Flow Velocity;Cerebrovascular Circulation;Cerebrovascular Disorders;Computer Simulation;Contrast Media;Gadolinium DTPA;Humans;Image Interpretation, Computer-Assisted;Magnetic Resonance Imaging;Models, Cardiovascular;Numerical Analysis, Computer-Assisted;Reproducibility of Results;Sensitivity and Specificity | 公開日期: | 2013 | 卷: | 64 | 期: | 1 | 起(迄)頁: | 560-570 | 來源出版物: | NeuroImage | 摘要: | DSC-MRI analysis is based on tracer kinetic theory and typically involves the deconvolution of the MRI signal in tissue with an arterial input function (AIF), which is an ill-posed inverse problem. The current standard singular value decomposition (SVD) method typically underestimates perfusion and introduces non-physiological oscillations in the resulting residue function. An alternative vascular model (VM) based approach permits only a restricted family of shapes for the residue function, which might not be appropriate in pathologies like stroke. In this work a novel deconvolution algorithm is presented that can estimate both perfusion and residue function shape accurately without requiring the latter to belong to a specific class of functional shapes. A control point interpolation (CPI) method is proposed that represents the residue function by a number of control points (CPs), each having two degrees of freedom (in amplitude and time). A complete residue function shape is then generated from the CPs using a cubic spline interpolation. The CPI method is shown in simulation to be able to estimate cerebral blood flow (CBF) with greater accuracy giving a regression coefficient between true and estimated CBF of 0.96 compared to 0.83 for VM and 0.71 for the circular SVD (oSVD) method. The CPI method was able to accurately estimate the residue function over a wide range of simulated conditions. The CPI method has also been demonstrated on clinical data where a marked difference was observed between the residue function of normally appearing brain parenchyma and infarcted tissue. The CPI method could serve as a viable means to examine the residue function shape under pathological variations. ? 2012 Elsevier Inc. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867605238&doi=10.1016%2fj.neuroimage.2012.08.083&partnerID=40&md5=a7580b4cb7f0509a5158070c76a157c2 https://scholars.lib.ntu.edu.tw/handle/123456789/611805 |
DOI: | 10.1016/j.neuroimage.2012.08.083 |
顯示於: | 應用力學研究所 |
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