title: Based on the Network Degeneration Hypothesis: Separating Individual Patients with Different Neurodegenerative Syndromes in a Preliminary Hybrid PET/MR Study.
abstract: The network degeneration hypothesis (NDH) of neurodegenerative syndromes suggests that pathologic brain changes distribute primarily along distinct brain networks, which are characteristic for different syndromes. Brain changes of neurodegenerative syndromes can be characterized in vivo by different imaging modalities. Our aim was to test the hypothesis whether multimodal imaging based on the NDH separates individual patients with different neurodegenerative syndromes.
  
  
  METHODS
  Twenty patients with Alzheimer disease (AD) and 20 patients with frontotemporal lobar degeneration (behavioral variant frontotemporal dementia [bvFTD, n = 11], semantic dementia [SD, n = 4], or progressive nonfluent aphasia [PNFA, n = 5]) underwent simultaneous MRI and (18)F-FDG PET in a hybrid PET/MR scanner. The 3 outcome measures were voxelwise values of degree centrality as a surrogate for regional functional connectivity, glucose metabolism as a surrogate for regional metabolism, and volumetric-based morphometry as a surrogate for regional gray matter volume. Outcome measures were derived from predefined core regions of 4 intrinsic networks based on the NDH, which have been demonstrated to be characteristic for AD, bvFTD, SD, and PNFA, respectively. Subsequently, we applied support vector machine to classify individual patients via combined imaging measures, and results were evaluated by leave-one-out cross-validation.
  
  
  RESULTS
  On the basis of multimodal voxelwise regional patterns, classification accuracies for separating patients with different neurodegenerative syndromes were 77.5% for AD versus others, 82.5% for bvFTD versus others, 97.5% for SD versus others, and 87.5% for PNFA versus others. Multimodal classification results were significantly superior to unimodal approaches.
  
  
  CONCLUSIONS
  Our finding provides initial evidence that the combination of regional metabolism, functional connectivity, and gray matter volume, which were derived from disease characteristic networks, separates individual patients with different neurodegenerative syndromes. Preliminary results suggest that employing multimodal imaging guided by the NDH may generate promising biomarkers of neurodegenerative syndromes.
authors.affiliation: Department of Neuroradiology, Technische Universität München, Munich, Germany Department of Nuclear Medicine, Technische Universität München, Munich, Germany TUM-Neuroimaging Center (TUM-NIC), Technische Universität München, Munich, Germany Sleep Disorders Research Center, Kermanshah University of Medical Science (KUMS), Kermanshah, Iran Department of Neurology, University Hospital Cologne, Cologne, Germany Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany masoud.tahmasian@uk-koeln.de.
authors.forename: Masoud
authors.initials: M
authors.lastname: Tahmasian
authors.affiliation: School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China Big Data Research Center, University of Electronic Science and Technology of China, Chengdu, China Center for Information in BioMedicine, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Junming
authors.initials: J
authors.lastname: Shao
authors.affiliation: Department of Neuroradiology, Technische Universität München, Munich, Germany TUM-Neuroimaging Center (TUM-NIC), Technische Universität München, Munich, Germany.
authors.forename: Chun
authors.initials: C
authors.lastname: Meng
authors.affiliation: Department of Psychiatry and Psychotherapy, Technische Universität München, Munich, Germany; and.
authors.forename: Timo
authors.initials: T
authors.lastname: Grimmer
authors.affiliation: Department of Psychiatry and Psychotherapy, Technische Universität München, Munich, Germany; and.
authors.forename: Janine
authors.initials: J
authors.lastname: Diehl-Schmid
authors.affiliation: Department of Nuclear Medicine, Technische Universität München, Munich, Germany Radiopharmacy of Klinikum Rechts der Isar, Technische Universität München, Munich, Germany.
authors.forename: Behrooz H
authors.initials: BH
authors.lastname: Yousefi
authors.affiliation: Department of Nuclear Medicine, Technische Universität München, Munich, Germany TUM-Neuroimaging Center (TUM-NIC), Technische Universität München, Munich, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Förster
authors.affiliation: Department of Neuroradiology, Technische Universität München, Munich, Germany Department of Nuclear Medicine, Technische Universität München, Munich, Germany TUM-Neuroimaging Center (TUM-NIC), Technische Universität München, Munich, Germany.
authors.forename: Valentin
authors.initials: V
authors.lastname: Riedl
authors.affiliation: Department of Nuclear Medicine, Technische Universität München, Munich, Germany Department of Nuclear Medicine, University Hospital Cologne, Cologne, Germany.
authors.forename: Alexander
authors.initials: A
authors.lastname: Drzezga
authors.affiliation: Department of Neuroradiology, Technische Universität München, Munich, Germany Department of Nuclear Medicine, Technische Universität München, Munich, Germany TUM-Neuroimaging Center (TUM-NIC), Technische Universität München, Munich, Germany Department of Psychiatry and Psychotherapy, Technische Universität München, Munich, Germany; and.
authors.forename: Christian
authors.initials: C
authors.lastname: Sorg
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000175:diagnosis / Q000000981:diagnostic imaging; D001039:Aphasia, Broca / Q000175:diagnosis / Q000000981:diagnostic imaging; D003937:Diagnosis, Differential; D005260:Female; D019788:Fluorodeoxyglucose F18; D057174:Frontotemporal Lobar Degeneration / Q000175:diagnosis / Q000000981:diagnostic imaging; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging; D008297:Male; D064847:Multimodal Imaging; D009415:Nerve Net / Q000000981:diagnostic imaging*; D019636:Neurodegenerative Diseases / Q000175:diagnosis* / Q000000981:diagnostic imaging; D049268:Positron-Emission Tomography; D011237:Predictive Value of Tests; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18
keywords: Alzheimer’s disease; frontotemporal lobar degeneration; hybrid PET/MR; network degeneration hypothesis; neurodegenerative syndromes