Federico Massa, Dario Arnaldi, Bart N.M. van Berckel, Samantha Galluzzi, Rik Ossenkoppele, Eric Guedj, Matteo Grazzini, Marco Pagani, Gianmario Sambuceti, Andrea Chincarini, Cathrine Jonsson, S. Morbelli, Mira Didic, Matteo Bauckneht, Fabrizio De Carli, Patrizia Mecocci, Matteo Pardinia, Alexander Drzezga, Giovanni B. Frisoni, Flavio Nobili, Massimo E. Dottorini, Robert Perneczky, Andrea Brugnolo, Radiology and nuclear medicine, Amsterdam Neuroscience - Neurodegeneration, Neurology, VU University medical center, Institute of Bioimaging and Molecular Physiology [Germaneto], National Research Council [Italy] (CNR), Universita degli studi di Genova, Neuroimaging and Telemedicine (LENITEM), IRCCS Fatebenefratelli - Brescia, University Hospital of the Ludwig-Maximilian-University Munich, Medizinische Klinik â€' Innenstadt, Lehrstuhl für Endokrinologie/Diabetologie, Department of Nuclear Medicine [Cologne], University Hospital of Cologne [Cologne], Service de neurologie et de neuropsychologie, Université de la Méditerranée - Aix-Marseille 2-Assistance Publique - Hôpitaux de Marseille (APHM)- Hôpital de la Timone [CHU - APHM] (TIMONE), Service Central de Biophysique et de Médecine Nucléaire, Hôpital de la Timone [CHU - APHM] (TIMONE), Imagerie MOléculaire pour applications THéranostiques personnalisées (IMOTHEP), Institut FRESNEL (FRESNEL), Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-École Centrale de Marseille (ECM)-Centre National de la Recherche Scientifique (CNRS)- Hôpital de la Timone [CHU - APHM] (TIMONE), DINOGMI Genoa, Physiopathologie du système nerveux central - Institut François Magendie, Université Bordeaux Segalen - Bordeaux 2-IFR8-Institut National de la Santé et de la Recherche Médicale (INSERM), German Aerospace Center (DLR), Institute of Gerontology and Geriatrics, Università degli Studi di Perugia (UNIPG), Clinical Neurophysiology Service, Dept of Endocrinological and Metabolic Sciences, University of Ge, Imperial College London, Centre de résonance magnétique biologique et médicale (CRMBM), Assistance Publique - Hôpitaux de Marseille (APHM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS)-École Centrale de Marseille (ECM)-Aix Marseille Université (AMU)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Marseille (ECM)-Aix Marseille Université (AMU)- Hôpital de la Timone [CHU - APHM] (TIMONE), Dipartimento di Neuroscienze, riabilitazione, oftalmologia, genetica e scienze materno-infantili [Genova] (DINOGMI), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-Centre National de la Recherche Scientifique (CNRS), Università degli studi di Genova = University of Genoa (UniGe), Centre Européen de Recherche en Imagerie médicale (CERIMED), Aix Marseille Université (AMU)-Assistance Publique - Hôpitaux de Marseille (APHM)-École Centrale de Marseille (ECM)-Institut Paoli-Calmettes, Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Fédération nationale des Centres de lutte contre le Cancer (FNCLCC)-Centre National de la Recherche Scientifique (CNRS), and Università degli Studi di Perugia = University of Perugia (UNIPG)
Background: Several automatic tools have been implemented for semi-quantitative assessment of brain [ 18 ]F-FDG-PET. Objective: We aimed to head-to-head compare the diagnostic performance among three statistical parametric mapping (SPM)-based approaches, another voxel-based tool (i.e., PALZ), and a volumetric region of interest (VROI-SVM)-based approach, in distinguishing patients with prodromal Alzheimer's disease (pAD) from controls. Methods: Sixty-two pAD patients (MMSE score = 27.0±1.6) and one hundred-nine healthy subjects (CTR) (MMSE score = 29.2±1.2) were enrolled in five centers of the European Alzheimer's Disease Consortium. The three SPM-based methods, based on different rationales, included 1) a cluster identified through the correlation analysis between [ 18 ]F-FDG-PET and a verbal memory test (VROI-1), 2) a VROI derived from the comparison between pAD and CTR (VROI-2), and 3) visual analysis of individual maps obtained by the comparison between each subject and CTR (SPM-Maps). The VROI-SVM approach was based on 6 VROI plus 6 VROI asymmetry values derived from the pAD versus CTR comparison thanks to support vector machine (SVM). Results: The areas under the ROC curves between pAD and CTR were 0.84 for VROI-1, 0.83 for VROI-2, 0.79 for SPM maps, 0.87 for PALZ, and 0.95 for VROI-SVM. Pairwise comparisons of Youden index did not show statistically significant differences in diagnostic performance between VROI-1, VROI-2, SPM-Maps, and PALZ score whereas VROI-SVM performed significantly (p < 0.005) better than any of the other methods. Conclusion: The study confirms the good accuracy of [ 18 ]F-FDG-PET in discriminating healthy subjects from pAD and highlights that a non-linear, automatic VROI classifier based on SVM performs better than the voxel-based methods.