Structural MRI biomarkers for preclinical and mild Alzheimer's disease

Abstract

Noninvasive MRI biomarkers for Alzheimer's disease (AD) may enable earlier clinical diagnosis and the monitoring of therapeutic effectiveness. To assess potential neuroimaging biomarkers, the Alzheimer's Disease Neuroimaging Initiative is following normal controls (NC) and individuals with mild cognitive impairment (MCI) or AD. We applied high-throughput image analyses procedures to these data to demonstrate the feasibility of detecting subtle structural changes in prodromal AD. Raw DICOM scans (139 NC, 175 MCI, and 84 AD) were downloaded for analysis. Volumetric segmentation and cortical surface reconstruction produced continuous cortical surface maps and region-of-interest (ROI) measures. The MCI cohort was subdivided into single-(SMCI) and multipledomain MCI (MMCI) based on neuropsychological performance. Repeated measures analyses of covariance were used to examine group and hemispheric effects while controlling for age, sex, and, for volumetric measures, intracranial vault. ROI analyses showed group differences for ventricular, temporal, posterior and rostral anterior cingulate, posterior parietal, and frontal regions. SMCI and NC differed within temporal, rostral posterior cingulate, inferior parietal, precuneus, and caudal midfrontal regions. With MMCI and AD, greater differences were evident in these regions and additional frontal and retrosplenial cortices; evidence for non-AD pathology in MMCI also was suggested. Mesial temporal right-dominant asymmetries were evident and did not interact with diagnosis. Our findings demonstrate that high-throughput methods provide numerous measures to detect subtle effects of prodromal AD, suggesting early and later stages of the preclinical state in this cross-sectional sample. These methods will enable a more complete longitudinal characterization and allow us to identify changes that are predictive of conversion to AD.

Relative Capability of MR Imaging and FDG PET to Depict Changes Associated with Prodromal and Early Alzheimer Disease

“…Manual delineation of ROIs on MR imaging data can overcome some of these problems, although such methods are labor intensive, requiring high inter-and intrarater reliability, and are thus prohibitive in large-scale studies and routine clinical use. We developed high-throughput analytic methods that provide sensitive measurements of morphologic change in AD ( 10 ) and that are predictive of clinical decline in MCI ( 11 ). These methods can be used to obtain quantitative estimates of FDG PET metabolism within subject-specifi c, anatomic ROIs derived from MR images in each subject.…”

“…The averaged FDG PET images were registered to the subject's distortion-corrected and signal intensity-normalized baseline MR imaging volume. FDG PET ROIs were derived for each subcortical and cortical region, as defi ned on the basis of each subject's MR images, by means of the cerebral segmentation and cortical in detail elsewhere ( 10,11 ). Briefl y, MR images were corrected for gradient nonlinearities ( 14 ) and intensity nonuniformity by using methods developed within the Biomedical Informatics Research…”

On the early diagnosis of Alzheimer's Disease from multimodal signals: A survey

“…Some remarkable works have resulted from this database, allowing to increase our understanding about the disease. For example, thanks to ADNI, it is currently known that AD starts to develop many years before symptoms are manifested [305,306], as well as the order in which biomarkers become abnormal [307,308] or the order in which atrophy of the brain occurs [309,310]. Identification of new biomarkers (in blood [311], ˛-Synuclein [312],.…”

Classification of Mild Cognitive Impairment and Alzheimer Disease Using Model-Based MR and Magnetization Transfer Imaging

“…The candidate volumes were selected on the basis of previous MR imaging and FDG-PET findings. [26][27][28] To project these regions from a reference data template (Fig 1) in Montreal Neurological Institute space (SPM Anatomy toolbox, colin27T1; http:// www2.fz-juelich.de/inm/index.php?indexϭ194) into the individual brains, the SPM5 (Wellcome Department of Imaging Neuroscience, London, UK) warping algorithms and matrices were used. Details of the segmentation procedure and data extraction are provided as supplementary material (On-line Appendix).…”