title: Patient-specific detection of perfusion abnormalities combining within-subject and between-subject variances in Arterial Spin Labeling.
abstract: In this paper, patient-specific perfusion abnormalities in Arterial Spin Labeling (ASL) were identified by comparing a single patient to a group of healthy controls using a mixed-effect hierarchical General Linear Model (GLM). Two approaches are currently in use to solve hierarchical GLMs: (1) the homoscedastic approach assumes homogeneous variances across subjects and (2) the heteroscedastic approach is theoretically more efficient in the presence of heterogeneous variances but algorithmically more demanding. In practice, in functional magnetic resonance imaging studies, the superiority of the heteroscedastic approach is still under debate. Due to the low signal-to-noise ratio of ASL sequences, within-subject variances have a significant impact on the estimated perfusion maps and the heteroscedastic model might be better suited in this context. In this paper we studied how the homoscedastic and heteroscedastic approaches behave in terms of specificity and sensitivity in the detection of patient-specific ASL perfusion abnormalities. Validation was undertaken on a dataset of 25 patients diagnosed with brain tumors and 36 healthy volunteers. We showed evidence of heterogeneous within-subject variances in ASL and pointed out an increased false positive rate of the homoscedastic model. In the detection of patient-specific brain perfusion abnormalities with ASL, modeling heterogeneous variances increases the sensitivity at the same specificity level.
authors.affiliation: University of Rennes 1, Faculty of Medicine, F-35043 Rennes, France; INSERM, U746, F-35042 Rennes, France; CNRS, IRISA, UMR 6074, F-35042 Rennes, France; Inria, VISAGES Project-Team, F-35042 Rennes, France. Electronic address: contact@camillemaumet.com.
authors.forename: Camille
authors.initials: C
authors.lastname: Maumet
authors.affiliation: University of Rennes 1, Faculty of Medicine, F-35043 Rennes, France; INSERM, U746, F-35042 Rennes, France; CNRS, IRISA, UMR 6074, F-35042 Rennes, France; Inria, VISAGES Project-Team, F-35042 Rennes, France.
authors.forename: Pierre
authors.initials: P
authors.lastname: Maurel
authors.affiliation: University of Rennes 1, Faculty of Medicine, F-35043 Rennes, France; INSERM, U746, F-35042 Rennes, France; CNRS, IRISA, UMR 6074, F-35042 Rennes, France; Inria, VISAGES Project-Team, F-35042 Rennes, France; CHU Rennes, Department of Neuroradiology, F-35033 Rennes, France.
authors.forename: Jean-Christophe
authors.initials: JC
authors.lastname: Ferré
authors.affiliation: CHU Rennes, Department of Neuroradiology, F-35033 Rennes, France.
authors.forename: Béatrice
authors.initials: B
authors.lastname: Carsin
authors.affiliation: University of Rennes 1, Faculty of Medicine, F-35043 Rennes, France; INSERM, U746, F-35042 Rennes, France; CNRS, IRISA, UMR 6074, F-35042 Rennes, France; Inria, VISAGES Project-Team, F-35042 Rennes, France.
authors.forename: Christian
authors.initials: C
authors.lastname: Barillot
mesh_terms: D000328:Adult; D001921:Brain / Q000098:blood supply*; D001931:Brain Mapping / Q000379:methods*; D002560:Cerebrovascular Circulation / Q000502:physiology*; D005260:Female; D006801:Humans; D016014:Linear Models; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D013113:Spin Labels
chemical_list: D013113:Spin Labels
keywords: Arterial Spin Labeling; General Linear Model; Heteroscedasticity; Hyper-perfusion; Hypo-perfusion; Within-subject variance