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Review
. 2018 Oct 30;10(1):112.
doi: 10.1186/s13195-018-0438-z.

Secondary prevention of Alzheimer's dementia: neuroimaging contributions

Affiliations
Review

Secondary prevention of Alzheimer's dementia: neuroimaging contributions

Mara Ten Kate et al. Alzheimers Res Ther. .

Abstract

Background: In Alzheimer's disease (AD), pathological changes may arise up to 20 years before the onset of dementia. This pre-dementia window provides a unique opportunity for secondary prevention. However, exposing non-demented subjects to putative therapies requires reliable biomarkers for subject selection, stratification, and monitoring of treatment. Neuroimaging allows the detection of early pathological changes, and longitudinal imaging can assess the effect of interventions on markers of molecular pathology and rates of neurodegeneration. This is of particular importance in pre-dementia AD trials, where clinical outcomes have a limited ability to detect treatment effects within the typical time frame of a clinical trial. We review available evidence for the use of neuroimaging in clinical trials in pre-dementia AD. We appraise currently available imaging markers for subject selection, stratification, outcome measures, and safety in the context of such populations.

Main body: Amyloid positron emission tomography (PET) is a validated in-vivo marker of fibrillar amyloid plaques. It is appropriate for inclusion in trials targeting the amyloid pathway, as well as to monitor treatment target engagement. Amyloid PET, however, has limited ability to stage the disease and does not perform well as a prognostic marker within the time frame of a pre-dementia AD trial. Structural magnetic resonance imaging (MRI), providing markers of neurodegeneration, can improve the identification of subjects at risk of imminent decline and hence play a role in subject inclusion. Atrophy rates (either hippocampal or whole brain), which can be reliably derived from structural MRI, are useful in tracking disease progression and have the potential to serve as outcome measures. MRI can also be used to assess comorbid vascular pathology and define homogeneous groups for inclusion or for subject stratification. Finally, MRI also plays an important role in trial safety monitoring, particularly the identification of amyloid-related imaging abnormalities (ARIA). Tau PET to measure neurofibrillary tangle burden is currently under development. Evidence to support the use of advanced MRI markers such as resting-state functional MRI, arterial spin labelling, and diffusion tensor imaging in pre-dementia AD is preliminary and requires further validation.

Conclusion: We propose a strategy for longitudinal imaging to track early signs of AD including quantitative amyloid PET and yearly multiparametric MRI.

Keywords: Alzheimer’s disease; Clinical trials; Neuroimaging; Secondary prevention.

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Conflict of interest statement

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

AJS is a full-time employee of Takeda Pharmaceuticals. MCI is a stock-holding employee of Eli Lilly and Company. Florbetapir F18 is owned and marketed by Avid/Lilly. Flortaucipir (18F-AV-1451) is an investigational agent under development by Avid/Lilly. DH is a full-time employee and stockholder of IXICO plc. ME is a full-time employee of Janssen Pharmaceutica. CF is a full-time employee of GE Healthcare. The remaining authors declare that they have no competing interests.

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Figures

Fig. 1
Fig. 1
PET imaging biomarkers. Examples of normal (top) and abnormal (bottom) positron emission tomography (PET) imaging markers in three different subjects. For all images, the warmer the colour, the more tracer binding. Left: amyloid PET with [18F]-flutemetamol. In the abnormal scan, diffuse tracer binding to fibrillary amyloid can be observed. Middle: tau PET with [18F]-AV-1451. In the abnormal scan, tracer binding to tau can be observed in the temporal lobes. Right: Fluorodeoxyglucose (FDG)-PET scan. In the abnormal scan, there is hypometabolism of the parietal lobes
Fig. 2
Fig. 2
MRI imaging biomarkers. Left: T1-weighted MRI (top) showing severe hippocampal atrophy and example of diffusion tensor imaging (DTI) (bottom). Middle: example of functional imaging markers with arterial spin labelling (ASL) (top) and resting state functional magnetic resonance imaging (rs-fMRI) (bottom). Right: imaging of vascular pathology with thalamus lacune on T2 (top; arrow) and white matter hyper-intensities on fluid attenuated inversion recovery (FLAIR) (bottom)
Fig. 3
Fig. 3
Step-wise approach for subject inclusion and testing. Information from clinical measurements (and, in the near future, possibly also plasma) may be used to select subjects with an increased risk of amyloid pathology (screening). Provided there are no exclusion criteria, molecular measurements of amyloid (or tau, depending on the treatment target) can be used to screen-in subjects for clinical trials. Finally, imaging measures predicting imminent cognitive decline may be used for additionally enrichment. APOE apolipoprotein E, CSF cerebrospinal fluid, MRI magnetic resonance imaging, PET positron emission tomography
Fig. 4
Fig. 4
Amyloid-related imaging abnormalities. Example of ARIA-E on FLAIR with sulcal effusion (left) and ARIA-H with multiple microbleeds (middle) and superficial siderosis (right) on T2* images

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