Multimodal MRI ‐based imputation of the A β + in early mild cognitive impairment

Abstract

Objective To identify brain atrophy from structural-MRI and cerebral blood flow(CBF) patterns from arterial spin labeling perfusion-MRI that are best predictors of the Aβ-burden, measured as composite 18F-AV45-PET uptake, in individuals with early mild cognitive impairment(MCI). Furthermore, to assess the relative importance of imaging modalities in classification of Aβ+/Aβ− early mild cognitive impairment. Methods Sixty-seven ADNI-GO/2 participants with early-MCI were included. Voxel-wise anatomical shape variation measures were computed by estimating the initial diffeomorphic mapping momenta from an unbiased control template. CBF measures normalized to average motor cortex CBF were mapped onto the template space. Using partial least squares regression, we identified the structural and CBF signatures of Aβ after accounting for normal cofounding effects of age, sex, and education. Results 18F-AV45-positive early-MCIs could be identified with 83% classification accuracy, 87% positive predictive value, and 84% negative predictive value by multidisciplinary classifiers combining demographics data, ApoE ε4-genotype, and a multimodal MRI-based Aβ score. Interpretation Multimodal-MRI can be used to predict the amyloid status of early-MCI individuals. MRI is a very attractive candidate for the identification of inexpensive and non-invasive surrogate biomarkers of Aβ deposition. Our approach is expected to have value for the identification of individuals likely to be Aβ+ in circumstances where cost or logistical problems prevent Aβ detection using cerebrospinal fluid analysis or Aβ-PET. This can also be used in clinical settings and clinical trials, aiding subject recruitment and evaluation of treatment efficacy. Imputation of the Aβ-positivity status could also complement Aβ-PET by identifying individuals who would benefit the most from this assessment.

Relationship of Hippocampal Volume to Amyloid Burden across Diagnostic Stages of Alzheimer's Disease

“…In the same cohort, however, advanced quantitation methods using whole-brain anatomical shape variation derived from vMRI demonstrated a better predictive performance with AUCs of 0.70 ± 0.05 for the vMRI brain shape alone and 0.88 ± 0.03 for vMRI combined with the ApoE genotype [45]. A similar analysis of an EMCI population resulted in a classification accuracy of 0.83 ± 0.03 for the vMRI shape change score (not just hippocampus) when combined with demographics and the ApoE genotype [46]. However, the size and deformity of hippocampi using vMRI shape analysis in PiB-positive AD dementia cases were similar to those found in PiB-negative subcortical vascular dementia [22], raising questions about specificity.…”

“…Data using the ADNI may not be as generalizable to a broader community population where other physiologies and comorbidities as potential confounders are more common. Our work focused on one particular measure, HV, whereas other vMRI measurements, such as whole-brain voxel-based methods in combination with HV or other brain regions, might yield better prediction of amyloid status, as recently reported in MCI using advanced quantitative methods not clinically available [45,46]. …”

Magnetic resonance imaging in Alzheimer's Disease Neuroimaging Initiative 2

“…The performance of hippocampal volume as an independent predictor of brain amyloidosis in MCI was only marginally better than random chance (56% classification accuracy). Aβ-positive early-MCIs could be identified with 83% classification accuracy, 87% positive predictive value, and 84% negative predictive value by multidisciplinary classifiers combining demographics data, APOE 4-genotype, and a multimodal MRI-based Aβ score combining structural and perfusion signatures of brain amyloidosis [87, 88]. …”

Molecular and cellular pathophysiology of preclinical Alzheimer’s disease

“…Findings indicate that loss of hippocampal volume and the ratio of CSF Aβ 42 to total tau or phospho-tau are predictive of longitudinal changes in cognitive measures [121-124]. Arterial spin labeling MRI is used to examine the influence of changes in resting cerebral blood flow as well as blood oxygenation level dependent signal response in relation to PET-derived regional amyloid load [125, 126] or to memory encoding in the MTL [127]. It has become increasingly clear that imaging radioligands, alone or in combination with other AD biomarkers will be critical for the earliest detection of AD pathology and timely initiation of therapy.…”