Background
Tau PET positivity (T+) is recommended in Alzheimer’s disease (AD) trials involving preclinical and prodromal AD. As unbiased cut‐offs are still lacking, we established and validated ...data‐driven T+ PET cut‐offs for AD.
Method
Data were from ADNI (estimation cohort) and Geneva memory center (validation cohort). 18F‐Flortaucipir standardized uptake value ratios (SUVr) were computed for a global temporal meta‐ROI and for cortical regions corresponding to Braak‐based stages I‐VI in amyloid negative (Aβ−) cognitively normal (CN), Aβ+ CN, Aβ+ MCI and AD. For Tau PET data‐driven cut‐off estimation, Gaussian mixture model (GMM) was applied on the global and regional SUVr distributions in Aβ− CN and AD (n = 269). The GMM cut‐offs’ performance was compared with published 18F‐Flortaucipir cut‐offs (Mattsson et al., 2017) by assessing the percentage of T+ subjects within each diagnostic group.
Result
Cut‐offs were 1.36 for temporal meta‐ROI and ranged 1.20‐1.39 for stages. In the validation cohort, all Aβ− CN were tau negative (T−), while T+ percentage increased along the Aβ+ continuum (CN<MCI<AD) for temporal meta‐ROI (33<64<75) and stages I‐II (50<73<75), III (17<55<58), IV (17<57<75), V (0<18<50) and VI (0<5<33). Previously published cut‐offs reported a higher frequency of T+ in the AD spectrum and identified T+ subjects in the Aβ‐ CN group.
Conclusion
GMMs unbiased 18F‐Flortaucipir SUVr cut‐offs showed lower T+ percentage in Aβ− CN than published cut‐offs, possibly indicating lower false positive rates and suggesting that they might be useful for the in‐vivo assessment of participants eligibility in future preclinical and prodromal AD trials.
Purpose
Several
18
FFlortaucipir cutoffs have been proposed for tau PET positivity (T
+
) in Alzheimer’s disease (AD), but none were data-driven. The aim of this study was to establish and validate ...unsupervised T
+
cutoffs by applying Gaussian mixture models (GMM).
Methods
Amyloid negative (A
−
) cognitively normal (CN) and amyloid positive (A
+
) AD-related dementia (ADRD) subjects from ADNI (
n
=269) were included. ADNI (
n
=475) and Geneva Memory Clinic (GMC) cohorts (
n
=98) were used for validation. GMM-based cutoffs were extracted for the temporal meta-ROI, and validated against previously published cutoffs and visual rating.
Results
GMM-based cutoffs classified less subjects as T
+
, mainly in the A
−
CN (<3.4% vs >28.5%) and A
+
CN (<14.5% vs >42.9%) groups and showed higher agreement with visual rating (ICC=0.91 vs ICC<0.62) than published cutoffs.
Conclusion
We provided reliable data-driven
18
FFlortaucipir cutoffs for in vivo T
+
detection in AD. These cutoffs might be useful to select participants in clinical and research studies.
Background
The identification of unbiased cut‐off for amyloid and tau positivity is fundamental to early AD classification. While cut‐offs for amyloid markers are relatively established, tau markers ...cut‐off definition is controversial as they are influenced by the reference population. Moreover, several not modifiable risk factors (i.e., Apolipoprotein E ε4 allele APOE4, age, and sex) may affect tau pathology. The aim of the present study is to define data‐driven cut‐off values for cortical tau staging and to assess the effect of APOE4, age, and sex.
Method
Data were derived from the Alzheimer's Disease Neuroimaging Initiative consortium (ADNI). Amyloid‐PET (18‐F‐AV‐45) standardized uptake value ratio (SUVR) was used to classify subjects as amyloid positive (A+) or negative (A‐). Tau PET (18‐F‐AV1451) SUVR, APOE4, age, sex and clinical information were then collected. For 18‐F‐AV1451 SUVR, we applied a staging system according to Braak. Data‐driven stage‐specific 18‐F‐AV1451 cut‐offs were computed by applying Gaussian mixture model (GMM) to the subsample including A‐ cognitively normal (CN‐A‐) and AD dementia (AD‐A+) (n=194). We also investigated the effect of age, APOE4 status, and sex on 18‐F‐AV1451 SUVR distribution and cutoff extraction applying the GMM to 18‐F‐AV1451 SUVR distribution adjusted for these covariates. Finally, the cut‐offs sensitivity was assessed in preclinical AD (CN‐A+; n=45), prodromal AD (MCI‐A+; n=22), and AD‐A+ (n=19) subjects.
Result
In tau stage regions I–VI, 18‐F‐AV1451 cut‐off values for positivity ranged between 1.21‐1.35. The cut‐offs sensitivity increased from CN‐A+ to MCI‐A+ and AD‐A+ in all tau stages regions: from 20% to 64% and 90% for tau stage I‐II, from 16% to 46% to 90% for tau stage III, from 11% to 46and 90% for tau stage IV, from 0% to 18% and 53% for tau stage V, and from 0% for CN‐A+ and MCI‐A+ to 32% for tau stage VI. A similar sensitivity progressive pattern was detected within each tau stage region. Finally, APOE4, age, and sex significantly impacted 18‐F‐AV1451 regional SUVR of each tau stage.
Conclusion
Data‐driven 18‐F‐AV1451 SUVR cut‐offs for in‐vivo tau staging could be useful to index regional tau deposition. The impact of APOE4, age, and sex should be also considered.
Background
Deep learning approaches for classification have the advantage of automatically learning the relevant features but require large amount of data for training. We test the efficacy of deep ...learning approach for prediction of risk factor for prodromal Alzheimer’s disease from whole brain MRI scans segmented into grey/white matter and CSF images.
Method
Longitudinal MPRAGE images were acquired from 146 participants in six month intervals over a period of two years as part of PharmaCog Consortium. Whole brain structural scans were segmented using FreeSurfer pipeline into grey matter (GM), white matter (WM) and cerebrospinal fluid (CSF) images. We used a convolutional neural network architecture with 11 layers to classify individuals with high and low risk based on 3‐dimensional MRI data. The model consisted of 3 convolution layers that performed slice wise convolutions in 2‐dimensions, 3 batch normalization layers, 1 max pooling layer, 1 flatten layer, 2 dense layers and 1 rectified linear unit (ReLU) activation layer. Hyperparameter tuning for the model was done using various combinations of kernel size (2,3,4), strides (1,2,3), batch size (5,10,15,20), epochs (10,15,20) and number of neurons in the dense layer (16,32,64) to identify the optimized parameters for the model.
Result
Out of the 146 subjects available, we chose 97 subjects randomly. The cross‐sectional MRI data at various timestamps was considered for training the model. The rest of the data was considered as the test set. After this separation, we had training size and test size of 436 and 168 images respectively. The training and test sets did not have any common subjects and thus provided relevant results for subject wise classification for unseen subjects.
We trained and tested our model with all possible combinations of segmented images separately (GM, WM, CSF, GM+WM, WM+CSF, GM+CSF, GM+WM+CSF). Out of all the combinations, we attained best results using Grey mask (GM) data, with training and test accuracies of 93.62% and 72.02% respectively.
Conclusion
We presented a deep learning framework for risk prediction of cross‐sectional whole brain MRI data for unseen subjects. This work combined with classification approaches on longitudinal data can prove effective in early diagnosis of Alzheimer’s disease.
Background
The ε4 allele of the Apolipoprotein E gene (APOE) is a well‐established risk factor for Alzheimer’s disease (AD), ε4 carriers showing earlier onset and more severe memory impairment than ...non‐carriers. Neuroimaging evidence suggests that APOEε4 may modulate neural activity in AD since early stages. The purpose of this study was to determine whether APOEε4 influences brain activity in the memory circuit in older cognitively unimpaired individuals.
Method
Thirty cognitively unimpaired participants (n = 10 APOEε4 heterozygous carriers, age = 65± 5 years, 50% females, MMSE score = 29±1; n = 20 APOEε4 non‐carriers, age = 68±5 years, 35% females, MMSE score = 30±1) were recruited and underwent multidomain (i.e., memory, visuospatial abilities, language, attention) neuropsychological exams and functional MRI scan during an associative memory task, which consisted of two phases: (i) encoding of face‐name associations; (ii) recognition of the name associated to each face. Image preprocessing and voxel‐wise comparisons were conducted using the Statistical Parametric Mapping (SPM, v12). Clusters were considered significant at an uncorrected threshold of p<0.001.
Result
Participants were comparable for demographic and cognitive features (p>0.10) and performed similarly on the in‐scanner face‐name association memory task (p>0.10). Compared to ε4 non‐carriers, carriers showed (i) greater activation during the encoding task in the left temporo‐occipital cortex/fusiform gyrus, (ii) greater activation during the recognition task in the middle temporal gyrus/temporo‐occipital cortex bilaterally and in the right cerebellum, and (iii) lower activation during the recognition task in the medial supplementary motor area.
Conclusion
These preliminary results confirm that the APOE ε4 allele is associated with a different pattern of brain functional activity during an associative memory task in cognitively unimpaired older. Given the similar cognitive performance between groups, higher activation in temporo‐occipital regions might reflect a compensatory process in regions vulnerable to AD pathology.
Abstract
Background
Non‐cognitive deficits (e.g., sleep‐cycle and neuroendocrine alterations) are commonly observed in Alzheimer’s disease (AD) and are suggestive of hypothalamic (HPT) dysfunctions ...(Ishii and Iadecola., 2015). However, studies on the HPT involvement in the early stages of the disease are limited. Here, we compared the volumes of HPT and its subunits in cognitively unimpaired (CU), mild cognitive impairment (MCI), and AD.
Method
Twenty‐nine cognitively unimpaired (CU), 21 MCI, and 21 AD participants were enrolled and underwent 3T MRI and neuropsychological exams. 3D T1‐weighted images were processed using the standard FreeSurfer v7.2 pipeline, and the newly released tool for the automated segmentation of HPT and its subunits (Billot et al., 2020). After normalization to the total intracranial volume, whole and subunits HTP volumes were compared among groups using the Kruskall‐Wallis test with Dunn‐Bonferroni correction.
Result
MCI and AD showed lower left (
p
<.001) and right (
p
= .013) whole HPT volume than CU. Furthermore, lower volumes were detected in both the hemisphere for the anterior (
p
<.011) and posterior (
p
<.001) subunits in AD, and for right anterior posterior (
p
= .025) and for the superior tubular (
p
= .045) subunits in MCI, as compared with CU. No HPT differences were observed between AD and MCI patients.
Conclusion
Posterior HPT subunit atrophy was detectable since MCI stage and increased according to the disease progression. These results suggest a possible involvement of hypothalamus in early AD phases.
Background
Increasing evidence suggests that neuroinflammation and astrogliosis have a prominent role in the spread of pathology and the development of cognitive impairment in Alzheimer’s disease ...(AD). Circulating plasma markers of neuroinflammation, such as the glial fibrillary acid protein (GFAP), have recently become available, and early observations suggest a robust association with brain pathology. Positron emission tomography (PET) is a molecular imaging technique that allows visualisation and quantification of AD pathology in vivo. The aim of this study was to evaluate the association between GFAP and AD pathology, and its interaction with cognitive decline.
Method
121 subjects from the Geneva Memory Centre underwent amyloid and tau PET, blood collection, and mini‐mental state examination (MMSE). Amyloid uptake was calculated as centiloid whereas tau was quantified as standardised uptake value ratio. Association of centiloid and tau with GFAP was assessed using a multivariate linear regression model, corrected for age, gender, and MMSE. Mediation analysis described the mediating effect of GFAP on the association between centiloid and tau. Ninety‐four subjects had a follow‐up MMSE after at least 12 months. Linear regression was used to assess the effect of GFAP on the annual rate of change of MMSE (corrected for centiloid, global tau, age, and gender). Mediation analysis was used to test whether the relationship between rate of MMSE change and tau could be explained by a mediation of GFAP.
Result
The mean (SD) age of the participants was 72.6 (7.6) years, and 61 of 121 subjects were men. GFAP was significantly associated with increased tau, but not with centiloid. GFAP partially mediated the effect of centiloid on global tau (mediated proportion = 14%, p = 0.03). The rate of MMSE change was significantly associated with GFAP, and global tau, but not with centiloid. Moreover, GFAP partially mediated the effect between global tau SUVR and change of MMSE scores (52%, p<0.01).
Conclusion
Elevated GFAP is associated with tau. GFAP also partially explains the effect of amyloid pathology on tau accumulation and of tau pathology on subsequent cognitive decline. These results support neuroinflammation and astrogliosis as a relevant contributor to AD pathology, which can be monitored in blood.
Background
The e4 allele of the Apolipoprotein E gene (APOE) is a well‐established risk factor for Alzheimer’s disease (AD), e4 carriers showing earlier onset and more severe memory impairment than ...non‐carriers. Neuroimaging evidence suggests that APOEe4 may modulate neural activity in AD since early stages. The purpose of this study was to determine whether APOEe4 influences brain activity in the memory circuit in older cognitively unimpaired individuals.
Method
Thirty cognitively unimpaired participants (n = 10 APOEe4 heterozygous carriers, age = 65± 5 years, 50% females, MMSE score = 29±1; n = 20 APOEe4 non‐carriers, age = 68±5 years, 35% females, MMSE score = 30±1) were recruited and underwent multidomain (i.e., memory, visuospatial abilities, language, attention) neuropsychological exams and functional MRI scan during an associative memory task, which consisted of two phases: (i) encoding of face‐name associations; (ii) recognition of the name associated to each face. Image preprocessing and voxel‐wise comparisons were conducted using the Statistical Parametric Mapping (SPM, v12). Clusters were considered significant at an uncorrected threshold of p<0.001.
Result
Participants were comparable for demographic and cognitive features (p>0.10) and performed similarly on the in‐scanner face‐name association memory task (p>0.10). Compared to e4 non‐carriers, carriers showed (i) greater activation during the encoding task in the left temporo‐occipital cortex/fusiform gyrus, (ii) greater activation during the recognition task in the middle temporal gyrus/temporo‐occipital cortex bilaterally and in the right cerebellum, and (iii) lower activation during the recognition task in the medial supplementary motor area.
Conclusion
These preliminary results confirm that the APOE e4 allele is associated with a different pattern of brain functional activity during an associative memory task in cognitively unimpaired older. Given the similar cognitive performance between groups, higher activation in temporo‐occipital regions might reflect a compensatory process in regions vulnerable to AD pathology.
The amygdala and the hippocampus are two limbic structures that play a critical role in cognition and behavior, however their manual segmentation and that of their smaller nuclei/subfields in ...multicenter datasets is time consuming and difficult due to the low contrast of standard MRI. Here, we assessed the reliability of the automated segmentation of amygdalar nuclei and hippocampal subfields across sites and vendors using FreeSurfer in two independent cohorts of older and younger healthy adults.
Sixty-five healthy older (cohort 1) and 68 younger subjects (cohort 2), from the PharmaCog and CoRR consortia, underwent repeated 3D-T1 MRI (interval 1–90 days). Segmentation was performed using FreeSurfer v6.0. Reliability was assessed using volume reproducibility error (ε) and spatial overlapping coefficient (DICE) between test and retest session.
Significant MRI site and vendor effects (p < .05) were found in a few subfields/nuclei for the ε, while extensive effects were found for the DICE score of most subfields/nuclei. Reliability was strongly influenced by volume, as ε correlated negatively and DICE correlated positively with volume size of structures (absolute value of Spearman’s r correlations >0.43, p < 1.39E-36). In particular, volumes larger than 200 mm3 (for amygdalar nuclei) and 300 mm3 (for hippocampal subfields, except for molecular layer) had the best test-retest reproducibility (ε < 5% and DICE > 0.80).
Our results support the use of volumetric measures of larger amygdalar nuclei and hippocampal subfields in multisite MRI studies. These measures could be useful for disease tracking and assessment of efficacy in drug trials.
•Differences in MRI site/vendor had a limited effect on volume reproducibility.•Differences in MRI site/vendor had an extensive effect on spatial accuracy.•Reliability is good for larger amygdalar and hippocampal structures.•Automated volumetry is reliable in multicenter MRI studies.
Large-scale longitudinal multi-site MRI brain morphometry studies are becoming increasingly crucial to characterize both normal and clinical population groups using fully automated segmentation ...tools. The testaretest reproducibility of morphometry data acquired across multiple scanning sessions, and for different MR vendors, is an important reliability indicator since it defines the sensitivity of a protocol to detect longitudinal effects in a consortium. There is very limited knowledge about how across-session reliability of morphometry estimates might be affected by different 3 T MRI systems. Moreover, there is a need for optimal acquisition and analysis protocols in order to reduce sample sizes. A recent study has shown that the longitudinal FreeSurfer segmentation offers improved within session testaretest reproducibility relative to the cross-sectional segmentation at one 3 T site using a nonstandard multi-echo MPRAGE sequence. In this study we implement a multi-site 3 T MRI morphometry protocol based on vendor provided T1 structural sequences from different vendors (3D MPRAGE on Siemens and Philips, 3D IR-SPGR on GE) implemented in 8 sites located in 4 European countries. The protocols used mild acceleration factors (1.5a2) when possible. We acquired across-session testaretest structural data of a group of healthy elderly subjects (5 subjects per site) and compared the across-session reproducibility of two full-brain automated segmentation methods based on either longitudinal or cross-sectional FreeSurfer processing. The segmentations include cortical thickness, intracranial, ventricle and subcortical volumes. Reproducibility is evaluated as absolute changes relative to the mean (%), Dice coefficient for volume overlap and intraclass correlation coefficients across two sessions. We found that this acquisition and analysis protocol gives comparable reproducibility results to previous studies that used longer acquisitions without acceleration. We also show that the longitudinal processing is systematically more reliable across sites regardless of MRI system differences. The reproducibility errors of the longitudinal segmentations are on average approximately half of those obtained with the cross sectional analysis for all volume segmentations and for entorhinal cortical thickness. No significant differences in reliability are found between the segmentation methods for the other cortical thickness estimates. The average of two MPRAGE volumes acquired within each testaretest session did not systematically improve the across-session reproducibility of morphometry estimates. Our results extend those from previous studies that showed improved reliability of the longitudinal analysis at single sites and/or with non-standard acquisition methods. The multi-site acquisition and analysis protocol presented here is promising for clinical applications since it allows for smaller sample sizes per MRI site or shorter trials in studies evaluating the role of potential biomarkers to predict disease progression or treatment effects.
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