Data used in the provision of this paper were extracted from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). The ADNI was funded in 2003 as a public-private partnership, led by Michael W. Weiner, MD. The primary goal was to test that weather the combination of serial magnetic resonance imaging (MRI), positron emission tomography (PET), other biological markers, and clinical and neuropsychological assessment could be used to measure the progression of mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). We entered a population of subjects consists of 29 AD,76 MCI and 39 cognitively healthy. We enrolled all subjects which all required variables were available. According to the Stroke–Alzheimer’s Disease and Related Disorders Association and National Institute of Neurological and Communicative Disorders Clinical Dementia Rating and MMSE scores are the factors for considering subjects as MCI, AD or CN (13).
Plasma NFL measurement
Analysis of plasma neurofilamentlight (NFL) on ADNI-1 samples performed by Blennow K in clinical neurochemistry laboratory of Gothenburg University, Sweden. He used single molecule array (Simoa) technique. The assay uses a combination of purified bovine NFL , monoclonal antibodies as a calibrator. All samples were measured in duplicate, except for one (due to technical reasons). Analytical sensitivity was <1.0 pg/mL, and plasma level of NFL wasn't below the limit of detection in any sample.
Apoe genotyping and CSF biomarkers assessment
Results for Apoe genotyping are available at ADNI. Careers are participants with at least one £4 allele. CSF collected samples were acquired by lumbar puncture and concentration of CSF biomarkers consist of T-tau, P-tau181 and Aβ1-42 have been measured by the micro-bead-based multiplex immunoassay, the INNO-BIA AlzBio3 RUO test (Fujirebio, Ghent, Belgium) (14), on the Luminex platform. All the details about CSF specimen collection and analytic measurement, are available at ADNI http://adni.loni.usc.edu/methods/documents/.)
The center for imaging of neurodegenerative disease (CIND) processing pipeline for Arterial Spine Label (ASL) imaging, provides perfusion-weighted images (PW1) and figures a quantitative map of cerebral blood flow (CBF) and a regional analysis. It is necessary to implant multiple instruments from the public domain to achieve the quantification of CBF and discrepancy to high-resolution anatomical MRI data such as various FSL tools, EPI nonlinear geometric distortion correction (15), SPM8, Insight Toolkit (ITK) (16), Free Surfer and in house MATLAB scripts.
The pipeline consummates 1) motion correction of the ASL frames, 2)computation of the PWI by subtracting the mean of tagged from untagged ASL data sets, 3) adjustment of ASL and structural MRI data, 4) geometric distortion correction, 5) partial volume correction, 6) and CBF quantification in physical units by normalizing ASL to an estimated blood water density signal.
At the end ultimately there are two achievements consists of the PWI and a CBF image which both of them corrected for EPI distortion in two representations: 1) in native perfusion MRI space, 2) in the subject-specific space of the corresponding structural MRI data. Each achievement suggests users a manifold of options for more processing and analysis of the data.
Upon the interest to know the details you can visit the ADNI (http://adni.loni.usc.edu/methods)
Cognitive condition of subjects estimated by Mini-Mental State Exam (MMSE), which is a common test to assess the cognitive function in the aged individuals . Language, memory, orientation, attention and visual-spatial are the skills that MMSE test measures. Each patient's MMSE score acquired from ADNI Mini-Mental examination.
Statistical analysis carried out using SPSS16. Non normal distributed variables log transformed for using parametric analysis. Demographical variables and rCBF difference between groups assessed by one way ANOVA. For comparison results we used Benjamini Hochberg correction for addressing type I error due to multiple comparisons. In the next step for investigation the linear relation between CSF or plasma biomarkers with rCBF, once among all subject and then within each group, we implemented the Pearson’s correlation models by entering CSF or plasma biomarkers, and rCBF in each region as variables, adjusted for age, sex and APOE genotype as covariates. Bootstrapping method were used due to multiple comparisons in correlation models.