Dataset Information

Whole Brain Voxel-Wise Analysis of Cerebral Retention of Beta-Amyloid in Cognitively Normal Older Adults Using 18F-Florbetaben.

ABSTRACT: Objective:Recently developed 18F-labelled amyloid beta (A?) positron emission tomography (PET) tracers have demonstrated potentials to enable more prevalent application of amyloid imaging in the clinical setting. The aim of this study is to demonstrate cerebral retention of A? in cognitively normal older adults, by implementing voxel-based analysis on images acquired from 18F-Florbetaben amyloid PET. Methods:Fifty cognitive normal elderly subjects were recruited and included in the study. Demographic data and cognitive measurements were collected. Magnetic resonance imaging (MRI) and 18F-Florbetaben PET data were obtained followed by whole brain voxel-based analysis. Results:Compared to the florbetaben (FBB) (-) counterpart, FBB (+) showed significantly higher A? deposition in the brain regions comprising anterior cingulate, middle cingulate, posterior cingulate and precuneus (family wise error corrected p<0.05). There was no significant correlation between amyloid retention and cognitive functions. Conclusion:Our results confirms previous results regarding A? deposition by using 18F-Florbetaben, demonstrating potentials in application of 18F-Florbetaben PET imaging in clinical settings.

SUBMITTER: Um YH

PROVIDER: S-EPMC5714734 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

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Whole Brain Voxel-Wise Analysis of Cerebral Retention of Beta-Amyloid in Cognitively Normal Older Adults Using <sup>18</sup>F-Florbetaben.

Um Yoo Hyun YH Choi Woo Hee WH Jung Won Sang WS Park Young Ha YH Lee Chang-Uk CU Lim Hyun Kook HK

Psychiatry investigation 20171107 6

<h4>Objective</h4>Recently developed 18F-labelled amyloid beta (Aβ) positron emission tomography (PET) tracers have demonstrated potentials to enable more prevalent application of amyloid imaging in the clinical setting. The aim of this study is to demonstrate cerebral retention of Aβ in cognitively normal older adults, by implementing voxel-based analysis on images acquired from <sup>18</sup>F-Florbetaben amyloid PET.<h4>Methods</h4>Fifty cognitive normal elderly subjects were recruited and inc ...[more]

PMID: 29209396

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Project description:BACKGROUND:Florbetaben, a 18F-labeled stilbene derivative (Neuraceq®, formerly known as BAY-949172), is a diagnostic radiopharmaceutical developed to visualize ?-amyloid plaques in the brain. Here, we report a pilot study evaluating patients with suspected cardiac amyloidosis for systemic extent of disease. METHODS:We prospectively enrolled nine patients, 61-86 year old (mean?±?SD 69.4?±?8.6), referred from the cardiac amyloid clinic. First, dynamic imaging of the heart was acquired immediately after injection of 222-318.2 MBq (mean?±?SD 270.1?±?33.3) of 18F-florbetaben using the GE SIGNA PET/MRI. This was followed by a whole-body PET/MRI scan 60-146.4 min (mean?±?SD 98?±?33.4) after injection. Cardiac MRI sequences included ECG-triggered cine SSFP, T2-weighted, and late gadolinium-enhanced imaging. Whole-body MRI sequences included MRAC and axial T1-weighted imaging. RESULTS:High early uptake and delayed high uptake in the left ventricle correlated with amyloid deposition in five patients, while low uptake on early and delayed cardiac imaging was noted in four patients. Cardiac function measurements were successfully obtained in all participants. Areas of increased abnormal 18F-florbetaben accumulation were noted on delayed whole-body imaging in the bone marrow (seven patients), stomach (diffuse in five patients and focal in one patient), brain (five patients), salivary glands (three patients), tongue (three patients), spleen (three patients), skeletal muscles (three patients), ocular muscles (two patients), thyroid (two patients), pleura (two patients), kidneys (two patients), and lungs (two patients). CONCLUSIONS:Whole-body 18F-florbetaben PET/MRI is promising for localization of systemic amyloid deposition. This technique may provide important structural and functional information regarding the organs involved by disease, with potential to guide biopsy and evaluate response to treatment. TRIAL REGISTRATION:Clinicaltrials.gov registration: NCT03119558 .

Project description:BackgroundMagnetic resonance imaging (MRI) has unveiled specific alterations at different stages of Alzheimer's disease (AD) pathophysiologic continuum constituting what has been established as "AD signature". To what extent MRI can detect amyloid-related cerebral changes from structural MRI in cognitively unimpaired individuals is still an area open for exploration.MethodLongitudinal 3D-T1 MRI scans were acquired from a subset of the ADNI cohort comprising 403 subjects: 79 controls (Ctrls), 50 preclinical AD (PreAD), and 274 MCI and dementia due to AD (MCI/AD). Amyloid CSF was used as gold-standard measure with established cutoffs (<?192?pg/mL) to establish diagnostic categories. Cognitively unimpaired individuals were defined as Ctrls if were amyloid negative and PreAD otherwise. The MCI/AD group was amyloid positive. Only subjects with the same diagnostic category at baseline and follow-up visits were considered for the study. Longitudinal morphometric analysis was performed using SPM12 to calculate Jacobian determinant maps. Statistical analysis was carried out on these Jacobian maps to identify structural changes that were significantly different between diagnostic categories. A machine learning classifier was applied on Jacobian determinant maps to predict the presence of abnormal amyloid levels in cognitively unimpaired individuals. The performance of this classifier was evaluated using receiver operating characteristic curve analysis and as a function of the follow-up time between MRI scans. We applied a cost function to assess the benefit of using this classifier in the triaging of individuals in a clinical trial-recruitment setting.ResultsThe optimal follow-up time for classification of Ctrls vs PreAD was ?t?>?2.5?years, and hence, only subjects within this temporal span are used for evaluation (15 Ctrls, 10 PreAD). The longitudinal voxel-based classifier achieved an AUC?=?0.87 (95%CI 0.72-0.97). The brain regions that showed the highest discriminative power to detect amyloid abnormalities were the medial, inferior, and lateral temporal lobes; precuneus; caudate heads; basal forebrain; and lateral ventricles.ConclusionsOur work supports that machine learning applied to longitudinal brain volumetric changes can be used to predict, with high precision, the presence of amyloid abnormalities in cognitively unimpaired subjects. Used as a triaging method to identify a fixed number of amyloid-positive individuals, this longitudinal voxel-wise classifier is expected to avoid 55% of unnecessary CSF and/or PET scans and reduce economic cost by 40%.

Project description:Background: Little is known about the relation between dietary intake and cerebral amyloid accumulation in aging.Objective: We assessed the association of dietary glycemic measures with cerebral amyloid burden and cognitive performance in cognitively normal older adults.Design: We performed cross-sectional analyses relating dietary glycemic measures [adherence to a high-glycemic-load diet (HGLDiet) pattern, intakes of sugar and carbohydrates, and glycemic load] with cerebral amyloid burden (measured by florbetapir F-18 positron emission tomography) and cognitive performance in 128 cognitively normal older adults who provided eligibility screening data for the University of Kansas's Alzheimer's Prevention through Exercise (APEX) Study. The study began in November 2013 and is currently ongoing.Results: Amyloid was elevated in 26% (n = 33) of participants. HGLDiet pattern adherence (P = 0.01), sugar intake (P = 0.03), and carbohydrate intake (P = 0.05) were significantly higher in participants with elevated amyloid burden. The HGLDiet pattern was positively associated with amyloid burden both globally and in all regions of interest independently of age, sex, and education (all P ? 0.001). Individual dietary glycemic measures (sugar intake, carbohydrate intake, and glycemic load) were also positively associated with global amyloid load and nearly all regions of interest independently of age, sex, and educational level (P ? 0.05). Cognitive performance was associated only with daily sugar intake, with higher sugar consumption associated with poorer global cognitive performance (global composite measure and Mini-Mental State Examination) and performance on subtests of Digit Symbol, Trail Making Test B, and Block Design, controlling for age, sex, and education.Conclusion: A high-glycemic diet was associated with greater cerebral amyloid burden, which suggests diet as a potential modifiable behavior for cerebral amyloid accumulation and subsequent Alzheimer disease risk. This trial was registered at clinicaltrials.gov as NCT02000583.

Dataset Information

Whole Brain Voxel-Wise Analysis of Cerebral Retention of Beta-Amyloid in Cognitively Normal Older Adults Using 18F-Florbetaben.

Publications

Whole Brain Voxel-Wise Analysis of Cerebral Retention of Beta-Amyloid in Cognitively Normal Older Adults Using <sup>18</sup>F-Florbetaben.

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