title: Differentiation of sCJD and vCJD forms by automated analysis of basal ganglia intensity distribution in multisequence MRI of the brain--definition and evaluation of new MRI-based ratios.
abstract: We present a method for the analysis of basal ganglia (including the thalamus) for accurate detection of human spongiform encephalopathy in multisequence magnetic resonance imaging (MRI) of the brain. One common feature of most forms of prion protein diseases is the appearance of hyperintensities in the deep grey matter area of the brain in T2-weighted magnetic resonance (MR) images. We employ T1, T2, and Flair-T2 MR sequences for the detection of intensity deviations in the internal nuclei. First, the MR data are registered to a probabilistic atlas and normalized in intensity. Then smoothing is applied with edge enhancement. The segmentation of hyperintensities is performed using a model of the human visual system. For more accurate results, a priori anatomical data from a segmented atlas are employed to refine the registration and remove false positives. The results are robust over the patient data and in accordance with the clinical ground truth. Our method further allows the quantification of intensity distributions in basal ganglia. The caudate nuclei are highlighted as main areas of diagnosis of sporadic Creutzfeldt-Jakob Disease (sCJD), in agreement with the histological data. The algorithm permitted the classification of the intensities of abnormal signals in sCJD patient FLAIR images with a higher hypersignal in caudate nuclei (10/10) and putamen (6/10) than in thalami. Defining normalized MRI measures of the intensity relations between the internal grey nuclei of patients, we robustly differentiate sCJD and variant CJD (vCJD) patients, in an attempt to create an automatic classification tool of human spongiform encephalopathies.
authors.affiliation: Epidaure/Asclepios Research Group--INRIA, Sophia Antipolis, France. mglin@deas.harvard.edu
authors.forename: Marius George
authors.initials: MG
authors.lastname: Linguraru
authors.forename: Nicholas
authors.initials: N
authors.lastname: Ayache
authors.forename: Eric
authors.initials: E
authors.lastname: Bardinet
authors.forename: Miguel Angel González
authors.initials: MA
authors.lastname: Ballester
authors.forename: Damien
authors.initials: D
authors.lastname: Galanaud
authors.forename: Stéphane
authors.initials: S
authors.lastname: Haïk
authors.forename: Baptiste
authors.initials: B
authors.lastname: Faucheux
authors.forename: Jean-Jacques
authors.initials: JJ
authors.lastname: Hauw
authors.forename: Patrick
authors.initials: P
authors.lastname: Cozzone
authors.forename: Didier
authors.initials: D
authors.lastname: Dormont
authors.forename: Jean-Philippe
authors.initials: JP
authors.lastname: Brandel
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D001479:Basal Ganglia / Q000473:pathology*; D003198:Computer Simulation; D007562:Creutzfeldt-Jakob Syndrome / Q000145:classification / Q000175:diagnosis*; D003937:Diagnosis, Differential; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008954:Models, Biological; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique