Non-parametric deconvolution using Bézier curves for quantification of cerebral perfusion in dynamic susceptibility contrast MRI

• Objective Deconvolution is an ill-posed inverse problem that tends to yield non-physiological residue functions R(t) indynamic susceptibility contrast magnetic resonance imaging (DSC-MRI). In this study, the use of Bézier curves is proposedfor obtaining physiologically reasonable residue functions in perfusion MRI.Materials and methods Cubic Bézier curves were employed, ensuring R(0)=1, bounded-input, bounded-output stability anda non-negative monotonically decreasing solution, resulting in 5 parameters to be optimized. Bézier deconvolution (BzD),implemented in a Bayesian framework, was tested by simulation under realistic conditions, including efects of arterial delayand dispersion. BzD was also applied to DSC-MRI data from a healthy volunteer.Results Bézier deconvolution showed robustness to diferent underlying residue function shapes. Accurate perfusion estimates were observed, except for boxcar residue functions at low signal-to-noise ratio. BzD involving corrections for delay,dispersion, and delay with dispersion generally returned accurate results, except for some degree of cerebral blood fow(CBF) overestimation at low levels of each efect. Maps of mean transit time and delay were markedly diferent betweenBzD and block-circulant singular value decomposition (oSVD) deconvolution.Discussion A novel DSC-MRI deconvolution method based on Bézier curves was implemented and evaluated. BzD produced physiologically plausible impulse response, without spurious oscillations, with generally less CBF underestimationthan oSVD.

Ämnesord

MEDICIN OCH HÄLSOVETENSKAP  -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)

MEDICAL AND HEALTH SCIENCES  -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)

NATURVETENSKAP  -- Fysik -- Annan fysik (hsv//swe)

NATURAL SCIENCES  -- Physical Sciences -- Other Physics Topics (hsv//eng)

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