Single-Channel Blind Estimation of Arterial Input Function and Tissue Impulse Response in DCE-MRI

• Published in: IEEE transactions on biomedical engineering 2012-04, Vol.59 (4), p.1012-1021
• Main Authors: Taxt, Torfinn, Jirík, Radovan, Rygh, Cecilie Brekke, Gruner, Renate, Bartos, Michal, Andersen, Erling, Curry, Fitz-Roy, Reed, Rolf K.
• Format: Article
• Language: English
• Subjects: Algorithms; Animals; Applied sciences; Arterial input function (AIF); Arteries - physiology; Biological and medical sciences; blind deconvolution; Blood Flow Velocity - physiology; Computer Simulation; Computerized, statistical medical data processing and models in biomedicine; Contrast Media - pharmacokinetics; Convolution; Deconvolution; Delay; Detection, estimation, filtering, equalization, prediction; dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI); Exact sciences and technology; Extrapolation; Female; Gadolinium DTPA - pharmacokinetics; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Information, signal and communications theory; Magnetic Resonance Angiography - methods; Medical management aid. Diagnosis aid; Medical sciences; Mice; Mice, Inbred C57BL; Models, Biological; Models, Statistical; multichannel; Muscle, Skeletal - blood supply; Muscle, Skeletal - physiology; perfusion; Reproducibility of Results; Sensitivity and Specificity; Signal and communications theory; Signal to noise ratio; Signal, noise; single channel; Telecommunications and information theory
• ISSN: 0018-9294; 1558-2531
• DOI: 10.1109/TBME.2011.2182195

Multipass dynamic MRI and pharmacokinetic modeling are used to estimate perfusion parameters of leaky capillaries. Curve fitting and nonblind deconvolution are the established methods to derive the perfusion estimates from the observed arterial input function (AIF) and tissue tracer concentration function. These nonblind methods are sensitive to errors in the AIF, measured in some nearby artery or estimated by multichannel blind deconvolution. Here, a single-channel blind deconvolution algorithm is presented, which only uses a single tissue tracer concentration function to estimate the corresponding AIF and tissue impulse response function. That way, many errors affecting these functions are reduced. The validity of the algorithm is supported by simulations and tests on real data from mouse. The corresponding nonblind and multichannel methods are also presented.