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A new automated method for analysis of rCBF-SPECT images based on the active-shape algorithm: normal values
Authors:Hägerström Douglas  Jakobsson David  Stomrud Erik  Andersson Ann-Margret  Ryding Erik  Londos Elisabet  Minthon Lennart  Rosén Ingmar  Edenbrandt Lars
Affiliation:Clinical Neurophysiology Unit, Department of Clinical Sciences, Lund University, Sweden. Douglas.Hagerstrom@skane.se
Abstract:Most nuclear medicine clinicians use only visual assessment when interpreting regional cerebral blood flow (rCBF) from single-photon emission computed tomography (SPECT) images in clinical practice. The aims of this study were to develop a new, easy to use, automated method for quantification of rCBF-SPECT and to create normal values by using the method on a normal population. We developed a 3-dimensional method based on a brain-shaped model and the active-shape algorithm. The method defines the surface shape of the brain and then projects the maximum counts 0-1.5 cm deep for designated surface points. These surface projection values are divided into cortical regions representing the different lobes and presented relative to the whole cortex, cerebellum or cerebellar maximum. (99m) Tc-hexa methyl propylene amine oxime (HMPAO) SPECT was performed on 30 healthy volunteers with a mean age of 74 years (range 64-98). The ability of the active-shape algorithm to define the shape of the brain was satisfactory when visually scrutinized. The results of the quantification show rCBF values in the frontal, temporal and parietal lobes of 87-88% using cerebellum as the reference. There were no significant differences in normal rCBF values between male and female subjects and only a weak relation between rCBF and age. In conclusion, our new automated method was able to quantify rCBF-SPECT images and create normal values in ranges as expected. Further studies are needed to assess the clinical value of this method and the normal values.
Keywords:active shape  image processing  normal values  quantification  radionuclide imaging  regional cerebral blood flow  single‐photon emission computed tomography
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