title: Application of a MRI based index to longitudinal atrophy change in Alzheimer disease, mild cognitive impairment and healthy older individuals in the AddNeuroMed cohort.
abstract: Cross sectional studies of patients at risk of developing Alzheimer disease (AD) have identified several brain regions known to be prone to degeneration suitable as biomarkers, including hippocampal, ventricular, and whole brain volume. The aim of this study was to longitudinally evaluate an index based on morphometric measures derived from MRI data that could be used for classification of AD and healthy control subjects, as well as prediction of conversion from mild cognitive impairment (MCI) to AD. Patients originated from the AddNeuroMed project at baseline (119 AD, 119 MCI, 110 controls (CTL)) and 1-year follow-up (62 AD, 73 MCI, 79 CTL). Data consisted of 3D T1-weighted MR images, demographics, MMSE, ADAS-Cog, CERAD and CDR scores, and APOE e4 status. We computed an index using a multivariate classification model (AD vs. CTL), using orthogonal partial least squares to latent structures (OPLS). Sensitivity, specificity and AUC were determined. Performance of the classifier (AD vs. CTL) was high at baseline (10-fold cross-validation, 84% sensitivity, 91% specificity, 0.93 AUC) and at 1-year follow-up (92% sensitivity, 74% specificity, 0.93 AUC). Predictions of conversion from MCI to AD were good at baseline (77% of MCI converters) and at follow-up (91% of MCI converters). MCI carriers of the APOE e4 allele manifested more atrophy and presented a faster cognitive decline when compared to non-carriers. The derived index demonstrated a steady increase in atrophy over time, yielding higher accuracy in prediction at the time of clinical conversion. Neuropsychological tests appeared less sensitive to changes over time. However, taking the average of the two time points yielded better correlation between the index and cognitive scores as opposed to using cross-sectional data only. Thus, multivariate classification seemed to detect patterns of AD changes before conversion from MCI to AD and including longitudinal information is of great importance.
authors: Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet Stockholm, Sweden.
authors: Carlos
authors: C
authors: Aguilar
authors: Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet Stockholm, Sweden ; Department of Neuroimaging and Department of Old Age Psychiatry, Institute of Psychiatry, King's College London London, UK.
authors: J-Sebastian
authors: JS
authors: Muehlboeck
authors: Institute of Gerontology and Geriatrics, University of Perugia Perugia, Italy.
authors: Patrizia
authors: P
authors: Mecocci
authors: INSERM U 558, University of Toulouse Toulouse, France.
authors: Bruno
authors: B
authors: Vellas
authors: Department of Classics, Aristotle University of Thessaloniki Thessaloniki, Greece.
authors: Magda
authors: M
authors: Tsolaki
authors: Department of Old Age Psychiatry and Psychotic Disorders, Medical University of Lodz Lodz, Poland.
authors: Iwona
authors: I
authors: Kloszewska
authors: Department of Neurology, University and University Hospital of Kuopio Finland.
authors: Hilkka
authors: H
authors: Soininen
authors: Department of Neuroimaging and Department of Old Age Psychiatry, Institute of Psychiatry, King's College London London, UK ; NIHR Biomedical Research Centre for Mental Health and NIHR Biomedical Research Unit for Dementia London, UK.
authors: Simon
authors: S
authors: Lovestone
authors: Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet Stockholm, Sweden.
authors: Lars-Olof
authors: LO
authors: Wahlund
authors: Department of Neuroimaging and Department of Old Age Psychiatry, Institute of Psychiatry, King's College London London, UK ; NIHR Biomedical Research Centre for Mental Health and NIHR Biomedical Research Unit for Dementia London, UK.
authors: Andrew
authors: A
authors: Simmons
authors: Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet Stockholm, Sweden.
authors: Eric
authors: E
authors: Westman
keywords: APOE4; Alzheimer disease; MCI; MRI; OPLS; multivariate statistics