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or more. It is not yet clear what triggers the decline to dementia in individuals with amyloid pathology, or whether cognitively healthy individuals with amyloid pathology are destined to develop AD if they live long enough. Amyloid burden does not show a strong relation with cognitive ability in healthy individuals, nor is it a strong predictor of cognitive decline. However, presence of amyloid pathology in patients with amnestic MCI is associated with higher risk of developing dementia. Biomarkers of neuronal injury include

elevated levels of tau and phosphorylated tau proteins in the CSF, posterior hypometabolism on fluorodeoxyglucose


 Although there are no treatments to prevent or cure AD, early diagnosis is important for ensuring optimal care

(FDG) PET, and atrophy on structural magnetic resonance images (MRIs). These biomarkers, which reflect the presence of neuronal injury, are more closely associated with cognitive impairment and progressive clinical decline than are biomarkers of amyloid pathology. CSF and MRI measures are more

likely to be of clinical use in early detection of AD than FDG-PET due to their lower cost and more widespread availability. A recent study from our group demonstrated that to a large extent, the hypometabolism observed in MCI and early AD could be accounted for by atrophy, and that measures of regional atrophy from structural MRIs were as sensitive to MCI and AD as were FDG-PET measures of hypometabolism. In contrast, several studies have shown that CSF biomarkers provide complementary information to MRI measures.

 Figure 2: Example NeuroQuant TM (CorTechs Labs Inc, La Jolla, CA). report from an MCI patient scanned

longitudinally for two years as a volunteer in the Alzheimer’s Disease Neuroimaging Initiative. Ten scans (two per timepoint) were analyzed. Axial, coronal and sagittal MR images with a color overlay of the segmentation results are shown above a table reporting the raw volume, volume as percent of intracranial volume, and the volume’s percentile score based on the normative database for bilateral hippocampus, lateral ventricle, and temporal horn of the lateral ventricle (inferior lateral ventricle). Normative graphs plot the patient’s hippocampal and inferior lateral ventricle volume relative to the expected range (in white). For this patient, the baseline hippocampal volume was more than two standard deviations below that expected for age and continued to atrophy at a rate faster than would be expected in normal aging. The patient was diagnosed with AD at the 24 month study visit. From McEvoy, Brewer, (2010). Quantitative structural MRI for early detection of Alzheimer’s disease. Expert Rev Neurother, 10(11), 1675-1688.


STRUCTURAL MRI FOR EARLY DETECTION OFAD AD is associated with prominent atrophy of the medial temporal lobe structures associated with memory, the entorhinal cortex and hippocampus. This atrophy is visible on high resolution MRIs and visual ratings have shown good sensitivity to AD. However, quantification of cortical thickness or volumes in individual patients provides a more sensitive measure of atrophy, and application of semi-automated methods for quantifying thickness across the brain has demonstrated that atrophy is widespread, even in the MCI stage. In prior work, we found a pattern of regional atrophy that was able to differentiate AD from healthy control data with high cross-validated sensitivity (83%) and specificity (93%). We recently showed that the degree to which this atrophy pattern was expressed in patients with MCI was predictive of their risk of developing dementia within the next year. In the 317 MCI patients from the Alzheimer’s Disease Neuroimaging Initiative that we analyzed, the risk of developing AD based on degree of regional atrophy on a baseline MRI ranged from 3% to 40%. MCI patients who showed the least amount of atrophy had a risk level similar to that of healthy older individuals without memory impairment. In contrast, MCI patients with the highest degree of atrophy had double the risk of developing dementia than that expected from the diagnosis of MCI alone. Since AD is a progressive disorder, the

rate of atrophy from a follow-up MRI is also informative of the risk of developing dementia. When information on annual rate of atrophy from a 1-year follow-up MRI was included in the prediction model, we were able to identify a subgroup of MCI patients at very high risk of developing AD within the next year, with risk as high

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