scholarly journals Diffusion MRI Indices and their Relation to Cognitive Impairment in Brain Aging: The updated multi-protocol approach in ADNI3

2018 ◽  
Author(s):  
Artemis Zavaliangos-Petropulu ◽  
Talia M. Nir ◽  
Sophia I. Thomopoulos ◽  
Robert I. Reid ◽  
Matt A. Bernstein ◽  
...  

AbstractBrain imaging with diffusion-weighted MRI (dMRI) is sensitive to microstructural white matter changes associated with brain aging and neurodegeneration. In its third phase, the Alzheimer’s Disease Neuroimaging Initiative (ADNI3) is collecting data across multiple sites and scanners using different dMRI acquisition protocols, to better understand disease effects. It is vital to understand when data can be pooled across scanners, and how the choice of dMRI protocol affects the sensitivity of extracted measures to differences in clinical impairment. Here, we analyzed ADNI3 data from 317 participants (mean age: 75.4±7.9 years; 143 men/174 women), who were each scanned at one of 47 sites with one of six dMRI protocols using scanners from three different manufacturers. We computed four standard diffusion tensor imaging (DTI) indices including fractional anisotropy (FADTI) and mean, radial, and axial diffusivity, and one FA index based on the tensor distribution function (FATDF), in 24 bilaterally averaged white matter regions of interest. We found that protocol differences significantly affected dMRI indices, in particular FADTI. We ranked the diffusion indices for their strength of association with four clinical assessments. In addition to diagnosis, we evaluated cognitive impairment as indexed by three commonly used screening tools for detecting dementia and Alzheimer’s disease: the Alzheimer’s Disease Assessment Scale (ADAS-cog), the Mini-Mental State Examination (MMSE), and the Clinical Dementia Rating scale sum-of-boxes (CDR-sob). Using a nested random-effects model to account for protocol and site, we found that across all dMRI indices and clinical measures, the hippocampal-cingulum and fornix (crus) / stria terminalis regions most consistently showed strong associations with clinical impairment. Overall, the greatest effect sizes were detected in the hippocampal-cingulum and uncinate fasciculus for associations between axial or mean diffusivity and CDR-sob. FATDF detected robust widespread associations with clinical measures, while FADTI was the weakest of the five indices for detecting associations. Ultimately, we were able to successfully pool dMRI data from multiple acquisition protocols from ADNI3 and detect consistent and robust associations with clinical impairment and age.

2018 ◽  
Vol 15 (12) ◽  
pp. 1151-1160 ◽  
Author(s):  
Zihan Jiang ◽  
Huilin Yang ◽  
Xiaoying Tang

Objective: In this study, we investigated the influence that the pathology of Alzheimer’s disease (AD) exerts upon the corpus callosum (CC) using a total of 325 mild cognitive impairment (MCI) subjects, 155 AD subjects, and 185 healthy control (HC) subjects. Method: Regionally-specific morphological CC abnormalities, as induced by AD, were quantified using a large deformation diffeomorphic metric curve mapping based statistical shape analysis pipeline. We also quantified the association between the CC shape phenotype and two cognitive measures; the Mini Mental State Examination (MMSE) and the Alzheimer’s Disease Assessment Scale-Cognitive Behavior Section (ADAS-cog). To identify AD-relevant areas, CC was sub-divided into three subregions; the genu, body, and splenium (gCC, bCC, and sCC). Results: We observed significant shape compressions in AD relative to that in HC, mainly concentrated on the superior part of CC, across all three sub-regions. The HC-vs-MCI shape abnormalities were also concentrated on the superior part, but mainly occurred on bCC and sCC. The significant MCI-vs-AD shape differences, however, were only detected in part of sCC. In the shape-cognition association, significant negative correlations to ADAS-cog were detected for shape deformations at regions belonging to gCC and sCC and significant positive correlations to MMSE at regions mainly belonging to sCC. Conclusion: Our results suggest that the callosal shape deformation patterns, especially those of sCC, linked tightly to the cognitive decline in AD, and are potentially a powerful biomarker for monitoring the progression of AD.


2018 ◽  
Vol 15 (5) ◽  
pp. 429-442 ◽  
Author(s):  
Nishant Verma ◽  
S. Natasha Beretvas ◽  
Belen Pascual ◽  
Joseph C. Masdeu ◽  
Mia K. Markey ◽  
...  

Background: Combining optimized cognitive (Alzheimer's Disease Assessment Scale- Cognitive subscale, ADAS-Cog) and atrophy markers of Alzheimer's disease for tracking progression in clinical trials may provide greater sensitivity than currently used methods, which have yielded negative results in multiple recent trials. Furthermore, it is critical to clarify the relationship among the subcomponents yielded by cognitive and imaging testing, to address the symptomatic and anatomical variability of Alzheimer's disease. Method: Using latent variable analysis, we thoroughly investigated the relationship between cognitive impairment, as assessed on the ADAS-Cog, and cerebral atrophy. A biomarker was developed for Alzheimer's clinical trials that combines cognitive and atrophy markers. Results: Atrophy within specific brain regions was found to be closely related with impairment in cognitive domains of memory, language, and praxis. The proposed biomarker showed significantly better sensitivity in tracking progression of cognitive impairment than the ADAS-Cog in simulated trials and a real world problem. The biomarker also improved the selection of MCI patients (78.8±4.9% specificity at 80% sensitivity) that will evolve to Alzheimer's disease for clinical trials. Conclusion: The proposed biomarker provides a boost to the efficacy of clinical trials focused in the mild cognitive impairment (MCI) stage by significantly improving the sensitivity to detect treatment effects and improving the selection of MCI patients that will evolve to Alzheimer’s disease.


Author(s):  
Zahra Ayati ◽  
Guoyan Yang ◽  
Mohammad Hossein Ayati ◽  
Seyed Ahmad Emami ◽  
Dennis Chang

Abstract Background Saffron (stigma of Crocus sativus L.) from Iridaceae family is a well-known traditional herbal medicine that has been used for hundreds of years to treat several diseases such as depressive mood, cancer and cardiovascular disorders. Recently, anti-dementia property of saffron has been indicated. However, the effects of saffron for the management of dementia remain controversial. The aim of the present study is to explore the effectiveness and safety of saffron in treating mild cognitive impairment and dementia. Methods An electronic database search of some major English and Chinese databases was conducted until 31st May 2019 to identify relevant randomised clinical trials (RCT). The primary outcome was cognitive function and the secondary outcomes included daily living function, global clinical assessment, quality of life (QoL), psychiatric assessment and safety. Rev-Man 5.3 software was applied to perform the meta-analyses. Results A total of four RCTs were included in this review. The analysis revealed that saffron significantly improves cognitive function measured by the Alzheimer’s Disease Assessment Scale-cognitive subscale (ADAS-cog) and Clinical Dementia Rating Scale-Sums of Boxes (CDR-SB), compared to placebo groups. In addition, there was no significant difference between saffron and conventional medicine, as measured by cognitive scales such as ADAS-cog and CDR-SB. Saffron improved daily living function, but the changes were not statistically significant. No serious adverse events were reported in the included studies. Conclusions Saffron may have the potential to improve cognitive function and activities of daily living in patients with Alzheimer’s disease and mild cognitive impairment (MCI). However, due to limited high-quality studies there is insufficient evidence to make any recommendations for clinical use. Further clinical trials on larger sample sizes are warranted to shed more light on its efficacy and safety.


Stroke ◽  
2015 ◽  
Vol 46 (suppl_1) ◽  
Author(s):  
Jonathan Graff-Radford ◽  
Rosebud Roberts ◽  
Malini Madhavan ◽  
Alejandro Rabinstein ◽  
Ruth Cha ◽  
...  

The objective of this study was to investigate the cross-sectional associations of atrial fibrillation with neuroimaging measures of cerebrovascular disease and Alzheimer’s disease-related pathology, and their interaction with cognitive impairment. MRI scans of non-demented individuals (n=1044) from the population-based Mayo Clinic Study of Aging were analyzed for infarctions, total grey matter, hippocampal and white matter hyperintensity volumes. A subset of 496 individuals underwent FDG and C-11 Pittsburgh compound B (PiB) PET scans. We assessed the associations of atrial fibrillation with i) categorical MRI measures (cortical and subcortical infarctions) using multivariable logistic regression models, and with ii) continuous MRI measures ( hippocampal, total grey matter, and white matter hyperintensity volumes) and FDG-PET and PiB-PET measures using multivariable linear regression models, and adjusting for confounders. Among participants who underwent MRI (median age, 77.8, 51.6% male), 13.5% had atrial fibrillation. Presence of atrial fibrillation was associated with subcortical infarctions (odds ratio [OR], 1.83; p=0.002), cortical infarctions (OR, 1.91; p=0.03), total grey matter volume (Beta [β], -.025, p<.0001) after controlling for age, education, gender, APOE e4 carrier status, coronary artery disease, diabetes, history of clinical stroke, and hypertension. However, atrial fibrillation was not associated with white matter hyperintensity volume, hippocampal volume, Alzheimer’s pattern of FDG hypometabolism or PiB uptake. There was a significant interaction of cortical infarction (p for interaction=0.004) and subcortical infarction (p for interaction =0.015) with atrial fibrillation with regards to odds of mild cognitive impairment (MCI). Using subjects with no atrial fibrillation and no infarction as the reference, the OR (95% confidence intervals [CI]) for MCI was 2.98 (1.66, 5.35;p = 0.0002) among participants with atrial fibrillation and any infarction, 0.69 (0.36, 1.33;p= 0.27) for atrial fibrillation and no infarction, and 1.50 (0.96, 2.32;p = 0.07) for no atrial fibrillation and any infarction. These data highlight that atrial fibrillation is associated with MCI in the presence of infarctions.


CNS Spectrums ◽  
2004 ◽  
Vol 9 (S5) ◽  
pp. 20-23 ◽  
Author(s):  
Gary W. Small

AbstractThe prevalence of Alzheimer's disease (AD) and dementia continues to rise. However, a significant number of patients are undiagnosed or untreated. Given the complexities of detecting cognitive impairment and the early signs of AD, this review discusses how advances in brain imaging can help assist in improving overall management. Imaging techniques and surrogate markers may provide unique opportunities to diagnose accurately AD in presymptomatic stages with practical consequences for patients, caregivers, and physicians. The possible outcomes for using imaging and surrogate markers as adjuncts to clinical examination and as screening tools for AD, as well as tangible and intangible advantages to early diagnosis and treatment, will be discussed. The specific value of using advanced serial imaging in patients with a genetic disposition to AD will be evaluated. If neurons can be protected from neurodegenerative damage in early stages, this may preserve patient cognition, function, and quality of life, and may confer considerable societal healthcare benefits.


2020 ◽  
Author(s):  
Sang Won Seo ◽  
Seung Joo Kim ◽  
Sook-Young Woo ◽  
Young Ju Kim ◽  
Yeshin Kim ◽  
...  

Abstract Background: Few studies have investigated cognitive trajectories or developed a prediction model for amyloid beta-positive (Aβ+) mild cognitive impairment (MCI) patients. We aimed to identify distinct cognitive trajectories in Aβ+ MCI patients based on longitudinal Alzheimer’s Disease Assessment Scale-Cognitive subscale (ADAS-cog) 13 scores. Furthermore, we aimed to develop and visualize a prediction model to predict trajectory groups using the demographic, genetic, and clinical biomarkers of Aβ+ MCI patients.Methods: We performed a retrospective analysis of the data in 238 Aβ+ MCI patients from the Alzheimer’s Disease Neuroimaging Initiative who underwent at least three rounds of annual neuropsychological testing to identify cognitive trajectories. A group-based trajectory model (GBTM) was used to classify distinct groups based on ADAS-cog 13 scores. The prediction model was estimated using multinomial logistic regression and visualized using a bar-based method for risk prediction. Results: Three distinct classes, namely slow decliners (18.5%), intermediate decliners (42.9%), and fast decliners (38.7%), were suggested. Intermediate decliners were associated with higher age (≥70 years) (odds ratio [OR] 2.72, 95% confidence interval [CI] 1.78-6.28), higher AV45 standardized uptake value ratios (SUVRs)*10 (OR 1.69, 95% CI 1.22-2.34), and lower fluorodeoxyglucose (FDG) SUVR*10 (OR 0.65, 95% CI 0.46-0.93) than slow decliners. Fast decliners were associated with higher age (≥70 years) (OR 3.76, 95% CI 1.40-10.10), greater likelihood of being an apolipoprotein E 4 carrier (OR 4.2, 95% CI 1.53-11.58), higher AV45 positron emission tomography SUVR*10 (OR 2.14, 95% CI 1.50-3.05), and lower FDG SUVR*10 (OR 0.31, 95% CI 0.20-0.48) than slow decliners. The predicted probability of being classified to a trajectory group according to the risk scores of predictors was visualized.Conclusions: Our GBTM analysis yielded novel insights into the heterogeneous cognitive trajectories among Aβ+ MCI patients, which further facilitates the effective stratification of Aβ+ MCI patients in Aβ-targeted clinical trials.


2021 ◽  
Vol 84 (6) ◽  
pp. 472-480
Author(s):  
Yulin Luo ◽  
Li Tan ◽  
Joseph Therriault ◽  
Hua Zhang ◽  
Ying Gao ◽  
...  

<b><i>Background:</i></b> Apolipoprotein E (<i>APOE</i>) ε4 is highly associated with mild cognitive impairment (MCI). However, the specific influence of <i>APOE</i> ε4 status on tau pathology and cognitive decline in early MCI (EMCI) and late MCI (LMCI) is poorly understood. Our goal was to evaluate the association of <i>APOE</i> ε4 with cerebrospinal fluid (CSF) tau levels and cognition in EMCI and LMCI patients in the Alzheimer’s Disease Neuroimaging Initiative database, and whether this association was mediated by amyloid-β (Aβ). <b><i>Methods:</i></b> Participants were 269 cognitively normal (CN), 262 EMCI, and 344 LMCI patients. They underwent CSF Aβ42 and tau detection, <i>APOE</i> ε4 genotyping, Mini-Mental State Examination, (MMSE), and Alzheimer’s disease assessment scale (ADAS)-cog assessments. Linear regressions were used to examine the relation of <i>APOE</i> ε4 and CSF tau levels and cognitive scores in persons with and without Aβ deposition (Aβ+ and Aβ−). <b><i>Results:</i></b> The prevalence of <i>APOE</i> ε4 is higher in EMCI and LMCI than in CN (<i>p</i> &#x3c; 0.001 for both), and in LMCI than in EMCI (<i>p</i> = 0.001). <i>APOE</i> ε4 allele was significantly higher in Aβ+ subjects than in Aβ− subjects (<i>p</i> &#x3c; 0.001). Subjects who had a lower CSF Aβ42 level and were <i>APOE</i> ε4-positive experienced higher levels of CSF tau and cognitive scores in EMCI and/or LMCI. <b><i>Conclusions:</i></b> An <i>APOE</i> ε4 allele is associated with increased CSF tau and worse cognition in both EMCI and LMCI, and this association may be mediated by Aβ. We conclude that <i>APOE</i> ε4 may be an important mediator of tau pathology and cognition in the early stages of AD.


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