title: Fast nonlinear regression method for CT brain perfusion analysis.
abstract: Although computed tomography (CT) perfusion (CTP) imaging enables rapid diagnosis and prognosis of ischemic stroke, current CTP analysis methods have several shortcomings. We propose a fast nonlinear regression method with a box-shaped model (boxNLR) that has important advantages over the current state-of-the-art method, block-circulant singular value decomposition (bSVD). These advantages include improved robustness to attenuation curve truncation, extensibility, and unified estimation of perfusion parameters. The method is compared with bSVD and with a commercial SVD-based method. The three methods were quantitatively evaluated by means of a digital perfusion phantom, described by Kudo et al. and qualitatively with the aid of 50 clinical CTP scans. All three methods yielded high Pearson correlation coefficients ([Formula: see text]) with the ground truth in the phantom. The boxNLR perfusion maps of the clinical scans showed higher correlation with bSVD than the perfusion maps from the commercial method. Furthermore, it was shown that boxNLR estimates are robust to noise, truncation, and tracer delay. The proposed method provides a fast and reliable way of estimating perfusion parameters from CTP scans. This suggests it could be a viable alternative to current commercial and academic methods.
authors.affiliation: University Medical Center Utrecht, Department of Radiology, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands; University Medical Center Utrecht, Image Sciences Institute, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands.
authors.forename: Edwin
authors.initials: E
authors.lastname: Bennink
authors.affiliation: University Medical Center Utrecht, Department of Radiology, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands; University Medical Center Utrecht, Image Sciences Institute, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands.
authors.forename: Jaap
authors.initials: J
authors.lastname: Oosterbroek
authors.affiliation: Hokkaido University Hospital , Department of Diagnostic and Interventional Radiology, N14 W5, Kita-ku, Sapporo 060-8648, Japan.
authors.forename: Kohsuke
authors.initials: K
authors.lastname: Kudo
authors.affiliation: University Medical Center Utrecht , Image Sciences Institute, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands.
authors.forename: Max A
authors.initials: MA
authors.lastname: Viergever
authors.affiliation: University Medical Center Utrecht , Department of Radiology, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands.
authors.forename: Birgitta K
authors.initials: BK
authors.lastname: Velthuis
authors.affiliation: University Medical Center Utrecht, Department of Radiology, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands; University Medical Center Utrecht, Image Sciences Institute, Heidelberglaan 100, 3584CX, Utrecht, The Netherlands.
authors.forename: Hugo W A M
authors.initials: HW
authors.lastname: de Jong
keywords: CT perfusion; brain; deconvolution; model; nonlinear regression; stroke