In vivo detection of microstructural correlates of brain pathology in preclinical and early Alzheimer Disease with magnetic resonance imaging

Abstract

Background: Alzheimer disease (AD) affects at least 5 million individuals in the USA alone stimulating an intense search for disease prevention and treatment therapies as well as for diagnostic techniques allowing early identification of AD during a long pre-symptomatic period that can be used for the initiation of prevention trials of disease-modifying therapies in asymptomatic individuals.

Methods: Our approach to developing such techniques is based on the Gradient Echo Plural Contrast Imaging (GEPCI) technique that provides quantitative in vivo measurements of several brain-tissue-specific characteristics of the gradient echo MRI signal (GEPCI metrics) that depend on the integrity of brain tissue cellular structure. Preliminary data were obtained from 34 participants selected from the studies of aging and dementia at the Knight Alzheimer's Disease Research Center at Washington University in St. Louis. Cognitive status was operationalized with the Clinical Dementia Rating (CDR) scale. The participants, assessed as cognitively normal (CDR=0; n=23) or with mild AD dementia (CDR=0.5 or 1; n=11) underwent GEPCI MRI, a collection of cognitive performance tests and CSF amyloid (Aβ) biomarker Aβ42. A subset of 19 participants also underwent PET PiB studies to assess their brain Aβ burden. According to the Aβ status, cognitively normal participants were divided into normal (Aβ negative; n=13) and preclinical (Aβ positive; n=10) groups.

Results: GEPCI quantitative measurements demonstrated significant differences between all the groups: normal and preclinical, normal and mild AD, and preclinical and mild AD. GEPCI quantitative metrics characterizing tissue cellular integrity in the hippocampus demonstrated much stronger correlations with psychometric tests than the hippocampal atrophy. Importantly, GEPCI-determined changes in the hippocampal tissue cellular integrity were detected even in the hippocampal areas not affected by the atrophy. Our studies also uncovered strong correlations between GEPCI brain tissue metrics and beta-amyloid (Aβ) burden defined by positron emission tomography (PET) - the current in vivo gold standard for detection of cortical Aβ, thus supporting GEPCI as a potential surrogate marker for Aβ imaging - a known biomarker of early AD. Remarkably, the data show significant correlations not only in the areas of high Aβ accumulation (e.g. precuneus) but also in some areas of medial temporal lobe (e.g. parahippocampal cortex), where Aβ accumulation is relatively low.

Conclusion: We have demonstrated that GEPCI provides a new approach for the in vivo evaluation of AD-related tissue pathology in the preclinical and early symptomatic stages of AD. Since MRI is a widely available technology, the GEPCI surrogate markers of AD pathology have a potential for improving the quality of AD diagnostic, and the evaluation of new disease-modifying therapies.

Keywords: Alzheimer's disease; Beta-amyloid; GEPCI; MRI; PET; Pathology.

Copyright © 2017 Elsevier Inc. All rights reserved.

Figures

Figure 1

Correlation between PET PiB Aβ SUVR (dimensionless) and R2* (s−1) relaxation rate constant obtained in 19 participants. Plots show examples of correlation in several brain regions. Each point represents a single participant. Shaded areas represent 95% confidence intervals of the linear fits (solid lines). Pearson correlation coefficients (r) and p values (corrected for multiple comparison using false discovery rate over all cortical regions) are shown in the left upper corners. The surface maps on the right represent r values in all cortical areas. The image segmentation is based on the FreeSurfer software (55). The data show significant correlations not only in the areas of high Aβ accumulation (e.g. precuneus) but also in the areas of MTL, such as the parahippocampal cortex and the fusiform cortex. Remarkably, the strongest and most significant correlation exists in the parahippocampal cortex – the area of low Aβ accumulation.

Figure 2

Upper row represents the surface maps of the slopes (units of sec) of linear regression (coefficient k in Eq. [4]) between regional PET-measured Aβ SUVR and parahippocampal R2* across 19 participants. All regional slopes are positive. The coefficients of the linear regressions are listed in Table 1. The second and the last rows represent the averaged cortical mean values of R2* and Aβ SUVR across the same 19 participants. White matter, deep gray matter and ventricles were excluded. The image segmentation is based on the FreeSurfer software (55).

Figure 3

Group comparison based on the R2* measurements in the parahippocampal cortex. The bar graph on the left shows significant differences between all participants (independent of CDR) with negative (n = 15, R2* = 16.79 ± 1.40 s−1) and positive (n = 19, R2* = 18.20 ± 1.08 s−1) Aβ status (see definition in the Methods). The bar graph on the right shows significant differences between normal group (CDR = 0, Aβ negative, n=13, R2* = 16.77 ± 1.51 s−1) and preclinical group (CDR = 0, Aβ positive, n = 10, R2* = 18.41 ± 0.84 s−1).

Figure 4

Correlation between cognitive tests performance and hippocampal R2t*. Cognitive measures included Free and Cued Selective Reminding Test (Srtfree), Animal Naming (ANIMALS), and Trail making Test Part A completion time (Tma). Note that higher scores on Tma indicate worse performance. Correlations with hippocampal volume are also presented for comparison. Each point represents a single participant (n = 34). Shaded areas represent 95% confidence intervals of linear fits (solid lines). Pearson correlation coefficients (r) and p values are shown in the left upper corners.

Figure 5

Examples of images obtained from three participants – 69 year old female representing control group (upper row), 72 year old male representing preclinical AD group (second row) and 69 year old male representing mild AD (CDR = 0.5) group. Thin yellow contours outline hippocampal area determined by FreeSurfer segmentation. In all cases, MPRAGE and GEPCI T1w images show small atrophy progressing from healthy to AD group. Gradually decreased GEPCI R2t* suggest altered tissue integrity even in the preserved hippocampal area.

Figure 6

Bar graphs show the data obtained in the hippocampus of 34 participants. Bars represent mean values and error bars are standard deviations. Data are separated into three groups: Normal, preclinical AD, and mild AD (CDR 0.5 or 1). GEPCI R2t*, and volumes are shown. Also shown is the parameter TCI (tissue content index, Eq.[5]). While R2t* can serve as a surrogate marker of neuronal density/integrity, the TCI can serve as a surrogate marker characterizing a change in the total neuronal content. The results are summarized in Table 2.