Blind Source Separation of Hemodynamics from Magnetic Resonance Perfusion Brain Images Using Independent Factor Analysis

Perfusion magnetic resonance brain imaging induces temporal signal changes on brain tissues, manifesting distinct blood-supply patterns for the profound analysis of cerebral hemodynamics. We employed independent factor analysis to blindly separate such dynamic images into different maps, that is, artery, gray matter, white matter, vein and sinus, and choroid plexus, in conjunction with corresponding signal-time curves. The averaged signal-time curve on the segmented arterial area was further used to calculate the relative cerebral blood volume (rCBV), relative cerebral blood flow (rCBF), and mean transit time (MTT). The averaged ratios for rCBV, rCBF, and MTT between gray and white matters for normal subjects were congruent with those in the literature.

[1]  Colin Fyfe,et al.  A Comparative Study of Two Neural Methods of Exploratory Projection Pursuit , 1997, Neural Networks.

[2]  K. Zierler.  Theoretical Basis of Indicator‐Dilution Methods For Measuring Flow and Volume , 1962 .

[3]  G. Cheon,et al.  Quantification of Regional Myocardial Blood Flow Using Dynamic H 2 15 O Pet and Factor Analysis , 2001 .

[4]  Hagai Attias,et al.  Independent Factor Analysis , 1999, Neural Computation.

[5]  B. Rosen,et al.  Perfusion imaging with NMR contrast agents , 1990, Magnetic resonance in medicine.

[6]  S. Klinke,et al.  Exploratory Projection Pursuit , 1995 .

[7]  T J Spinks,et al.  Generation of myocardial factor images directly from the dynamic oxygen-15-water scan without use of an oxygen-15-carbon monoxide blood-pool scan. , 1998, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[8]  David J. C. MacKay,et al.  Bayesian Interpolation , 1992, Neural Computation.

[9]  J. P. Bazin,et al.  Handling of Dynamic Sequences in Nuclear Medicine , 1982, IEEE Transactions on Nuclear Science.

[10]  Hagai Attias,et al.  A graphical model for estimating stimulus-evoked brain responses from magnetoencephalography data with large background brain activity , 2006, NeuroImage.

[11]  J C Froment,et al.  Perfusion‐based segmentation of the human brain using similarity mapping , 2001, Magnetic resonance in medicine.

[12]  B. Rosen,et al.  High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part I: Mathematical approach and statistical analysis , 1996, Magnetic resonance in medicine.

[13]  B. Rosen,et al.  High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part II: Experimental comparison and preliminary results , 1996, Magnetic resonance in medicine.

[14]  N. Otsu.  A threshold selection method from gray level histograms , 1979 .

[15]  A S Houston,et al.  The effect of apex-finding errors on factor images obtained from factor analysis and oblique transformation. , 1984, Physics in medicine and biology.

[16]  Richard Gran,et al.  On the Convergence of Random Search Algorithms In Continuous Time with Applications to Adaptive Control , 1970, IEEE Trans. Syst. Man Cybern..

[17]  N. Lassen,et al.  Tracer kinetic methods in medical physiology , 1979 .

[18]  T. Nagaoka,et al.  Moyamoya disease: evaluation with diffusion-weighted and perfusion echo-planar MR imaging. , 1999, Radiology.

[19]  G. Brix,et al.  Cerebral Blood Flow and Cerebrovascular Reserve Capacity: Estimation by Dynamic Magnetic Resonance Imaging , 1998, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[20]  W. J. Lorenz,et al.  Quantification of regional cerebral blood flow and volume with dynamic susceptibility contrast-enhanced MR imaging. , 1994, Radiology.

[21]  David L. Thomas,et al.  Measuring Cerebral Blood Flow Using Magnetic Resonance Imaging Techniques , 1999, Journal of cerebral blood flow and metabolism : official journal of the International Society of Cerebral Blood Flow and Metabolism.

[22]  D. Barber.  The use of principal components in the quantitative analysis of gamma camera dynamic studies. , 1980, Physics in medicine and biology.

[23]  Ralph W. Gerard,et al.  Methods in medical research , 1967 .

[24]  M. Knopp,et al.  Age dependency of the regional cerebral blood volume (rCBV) measured with dynamic susceptibility contrast MR imaging (DSC). , 1996, Magnetic resonance imaging.

[25]  Jeroen van der Grond,et al.  Model of the human vasculature for studying the influence of contrast injection speed on cerebral perfusion MRI , 2003, Magnetic resonance in medicine.

[26]  Yu-Te Wu,et al.  Classification of spatiotemporal hemodynamics from brain perfusion MR images using expectation‐maximization estimation with finite mixture of multivariate gaussian distributions , 2007, Magnetic resonance in medicine.

[27]  B. Rosen,et al.  Tracer arrival timing‐insensitive technique for estimating flow in MR perfusion‐weighted imaging using singular value decomposition with a block‐circulant deconvolution matrix , 2003, Magnetic resonance in medicine.

[28]  M A Goldberg,et al.  Cerebral toxoplasmosis and lymphoma in AIDS: perfusion MR imaging experience in 13 patients. , 1998, Radiology.

[29]  B R Rosen,et al.  Hyperacute stroke: simultaneous measurement of relative cerebral blood volume, relative cerebral blood flow, and mean tissue transit time. , 1999, Radiology.

[30]  Anne L. Martel,et al.  Extracting parametric images from dynamic contrast-enhanced MRI studies of the brain using factor analysis , 2001, Medical Image Anal..

[31]  M E Phelps,et al.  Factor analysis for extraction of blood time-activity curves in dynamic FDG-PET studies. , 1995, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[32]  B. Rosen,et al.  Echo-planar MR cerebral blood volume mapping of gliomas. Clinical utility. , 1996, Acta radiologica.

[33]  B. Rosen,et al.  Microscopic susceptibility variation and transverse relaxation: Theory and experiment , 1994, Magnetic resonance in medicine.

[34]  L. C. Hall,et al.  SPECT, magnetic resonance and angiographic features in a moyamoya patient before and after external-to-internal carotid artery bypass. , 1992, Journal of nuclear medicine : official publication, Society of Nuclear Medicine.

[35]  B. Rosen,et al.  Contrast agents in functional MR imaging , 1997, Journal of magnetic resonance imaging : JMRI.