18F PET with flutemetamol for the early diagnosis of Alzheimer's disease dementia and other dementias in people with mild cognitive impairment (MCI).
Ontology highlight
ABSTRACT:
SUBMITTER: Martinez G
PROVIDER: S-EPMC6486287 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:This multicenter study examined (18)F-FDG PET measures in the differential diagnosis of Alzheimer's disease (AD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB) from normal aging and from each other and the relation of disease-specific patterns to mild cognitive impairment (MCI).We examined the (18)F-FDG PET scans of 548 subjects, including 110 healthy elderly individuals ("normals" or NLs), 114 MCI, 199 AD, 98 FTD, and 27 DLB patients, collected at 7 participating centers. Individual PET scans were Z scored using automated voxel-based comparison with generation of disease-specific patterns of cortical and hippocampal (18)F-FDG uptake that were then applied to characterize MCI.Standardized disease-specific PET patterns were developed that correctly classified 95% AD, 92% DLB, 94% FTD, and 94% NL. MCI patients showed primarily posterior cingulate cortex and hippocampal hypometabolism (81%), whereas neocortical abnormalities varied according to neuropsychological profiles. An AD PET pattern was observed in 79% MCI with deficits in multiple cognitive domains and 31% amnesic MCI. (18)F-FDG PET heterogeneity in MCI with nonmemory deficits ranged from absent hypometabolism to FTD and DLB PET patterns.Standardized automated analysis of (18)F-FDG PET scans may provide an objective and sensitive support to the clinical diagnosis in early dementia.
| S-EPMC3703818 | biostudies-literature
Project description:BACKGROUND:A previous Cochrane systematic review concluded there is insufficient evidence to support the routine use of 18F-FDG PET in clinical practice in people with mild cognitive impairment (MCI). OBJECTIVES:To update the evidence and reassess the accuracy of 18F-FDG-PET for detecting people with MCI at baseline who would clinically convert to Alzheimer's disease (AD) dementia at follow-up. METHODS:A systematic review including comprehensive search of electronic databases from January 2013 to July 2017, to update original searches (1999 to 2013). All key review steps, including quality assessment using QUADAS 2, were performed independently and blindly by two review authors. Meta-analysis could not be conducted due to heterogeneity across studies. RESULTS:When all included studies were examined across all semi-quantitative and quantitative metrics, exploratory analysis for conversion of MCI to AD dementia (n = 24) showed highly variable accuracy; half the studies failed to meet four or more of the seven sets of QUADAS 2 criteria. Variable accuracy for all metrics was also found across eleven newly included studies published in the last 5 years (range: sensitivity 56-100%, specificity 24-100%). The most consistently high sensitivity and specificity values (approximately ?80%) were reported for the sc-SPM (single case statistical parametric mapping) metric in 6 out of 8 studies. CONCLUSION:Systematic and comprehensive assessment of studies of 18FDG-PET for prediction of conversion from MCI to AD dementia reveals many studies have methodological limitations according to Cochrane diagnostic test accuracy gold standards, and shows accuracy remains highly variable, including in the most recent studies. There is some evidence, however, of higher and more consistent accuracy in studies using computer aided metrics, such as sc-SPM, in specialized clinical settings. Robust, methodologically sound prospective longitudinal cohort studies with long (?5 years) follow-up, larger consecutive samples, and defined baseline threshold(s) are needed to test these promising results. Further evidence of the clinical validity and utility of 18F-FDG PET in people with MCI is needed.
| S-EPMC6218118 | biostudies-other
Project description:BackgroundWith the more widespread use of 18F-radioligand-based amyloid-β (Aβ) PET-CT imaging, we evaluated Aβ binding and the utility of neocortical 18F-Flutemetamol standardized uptake value ratio (SUVR) as a biomarker.Objective18F-Flutemetamol SUVR was used to differentiate 1) mild cognitive impairment (MCI) from Alzheimer's disease (AD), and 2) MCI from other non-AD dementias (OD).Methods109 patients consecutively recruited from a University memory clinic underwent clinical evaluation, neuropsychological test, MRI and 18F-Flutemetamol PET-CT. The diagnosis was made by consensus of a panel consisting of 1 neuroradiologist and 2 geriatricians. The final cohort included 13 subjective cognitive decline (SCD), 22 AD, 39 MCI, and 35 OD. Quantitative analysis of 16 region-of-interests made by Cortex ID software (GE Healthcare).ResultsThe global mean 18F-Flutemetamol SUVR in SCD, MCI, AD, and OD were 0.50 (SD-0.08), 0.53 (SD-0.16), 0.76 (SD-0.10), and 0.56 (SD-0.16), respectively, with SUVR in SCD and MCI and OD being significantly lower than AD. Aβ binding in SCD, MCI, and OD was heterogeneous, being 23%, 38.5%, and 42.9% respectively, as compared to 100% amyloid positivity in AD. Using global SUVR, ROC analysis showed AUC of 0.868 and 0.588 in differentiating MCI from AD and MCI from OD respectively.Conclusion18F-Flutemetamol SUVR differentiated MCI from AD with high efficacy (high negative predictive value), but much lower efficacy from OD. The major benefit of the test was to differentiate cognitively impaired patients (either SCD, MCI, or OD) without AD-related-amyloid-pathology from AD in the clinical setting, which was under-emphasized in the current guidelines proposed by Amyloid Imaging Task Force.
| S-EPMC7902948 | biostudies-literature
Project description:The advent of tau-targeted PET tracers such as flortaucipir (18F) (flortaucipir, also known as 18F-AV-1451 or 18F-T807) have made it possible to investigate the sequence of development of tau in relationship to age, amyloid-β, and to the development of cognitive impairment due to Alzheimer's disease. Here we report a multicentre longitudinal evaluation of the relationships between baseline tau, tau change and cognitive change, using flortaucipir PET imaging. A total of 202 participants 50 years old or older, including 57 cognitively normal subjects, 97 clinically defined mild cognitive impairment and 48 possible or probable Alzheimer's disease dementia patients, received flortaucipir PET scans of 20 min in duration beginning 80 min after intravenous administration of 370 MBq flortaucipir (18F). On separate days, subjects also received florbetapir amyloid PET imaging, and underwent a neuropsychological test battery. Follow-up flortaucipir scans and neuropsychological battery assessments were also performed at 9 and 18 months. Fifty-five amyloid-β+ and 90 amyloid-β- subjects completed the baseline and 18-month study visits and had valid quantifiable flortaucipir scans at both time points. There was a statistically significant increase in the global estimate of cortical tau burden as measured by standardized uptake value ratio (SUVr) from baseline to 18 months in amyloid-β+ but not amyloid-β- subjects (least squared mean change in flortaucipir SUVr : 0.0524 ± 0.0085, P < 0.0001 and 0.0007 ± 0.0024 P = 0.7850, respectively), and a significant association between magnitude of SUVr increase and baseline tau burden. Voxel-wise evaluations further suggested that the regional pattern of change in flortaucipir PET SUVr over the 18-month study period (i.e. which regions exhibited the greatest change) also varied as a function of baseline global estimate of tau burden. In subjects with lower global SUVr, temporal lobe regions showed the greatest flortaucipir retention, whereas in subjects with higher baseline SUVr, parietal and frontal regions were increasingly affected. Finally, baseline flortaucipir and change in flortaucipir SUVr were both significantly (P < 0.0001) associated with changes in cognitive performance. Taken together, these results provide a preliminary characterization of the longitudinal spread of tau in Alzheimer's disease and suggest that the amount and location of tau may have implications both for the spread of tau and the cognitive deterioration that may occur over an 18-month period.
| S-EPMC6536847 | biostudies-literature
Project description:BACKGROUND:A long dynamic scanning protocol may be required to accurately measure longitudinal changes in amyloid load. However, such a protocol results in a lower patient comfort and scanning efficiency compared to static scans. A compromise can be achieved by implementing dual-time-window protocols. This study aimed to optimize these protocols for quantitative [18F]flutemetamol and [18F]florbetaben studies. METHODS:Rate constants for subjects across the Alzheimer's disease spectrum (i.e., non-displaceable binding potential (BPND) in the range 0.02-0.77 and 0.02-1.04 for [18F]flutemetamol and [18F]florbetaben, respectively) were established based on clinical [18F]flutemetamol (N?=?6) and [18F]florbetaben (N?=?20) data, and used to simulate tissue time-activity curves (TACs) of 110?min using a reference tissue and plasma input model. Next, noise was added (N?=?50) and data points corresponding to different intervals were removed from the TACs, ranging from 0 (i.e., 90-90?=?full-kinetic curve) to 80 (i.e., 10-90) minutes, creating a dual-time-window. Resulting TACs were fitted using the simplified reference tissue method (SRTM) to estimate the BPND, outliers (??1.5?×?BPND max) were removed and the bias was assessed using the distribution volume ratio (DVR?=?BPND?+?1). To this end, acceptability curves, which display the fraction of data below a certain bias threshold, were generated and the area under those curves were calculated. RESULTS:[18F]Flutemetamol and [18F]florbetaben data demonstrated an increased bias in amyloid estimate for larger intervals and higher noise levels. An acceptable bias (??3.1%) in DVR could be obtained with all except the 10-90 and 20-90-min intervals. Furthermore, a reduced fraction of acceptable data and most outliers were present for these two largest intervals (maximum percentage outliers 48 and 32 for [18F]flutemetamol and [18F]florbetaben, respectively). CONCLUSIONS:The length of the interval inversely correlates with the accuracy of the BPND estimates. Consequently, a dual-time-window protocol of 0-30 and 90-110?min (=maximum of 60?min interval) allows for accurate estimation of BPND values for both tracers. [18F]flutemetamol: EudraCT 2007-000784-19, registered 8 February 2007, [18F]florbetaben: EudraCT 2006-003882-15, registered 2006.
| S-EPMC6437225 | biostudies-literature
Project description:BACKGROUND:Although amyloid beta (A?) imaging is widely used for diagnosing and monitoring Alzheimer's disease in clinical fields, paralleling comparison between 18F-flutemetamol and 18F-florbetaben was rarely attempted in AD mouse model. We performed a comparison of A? PET images between 18F-flutemetamol and 18F-florbetaben in a recently developed APPswe mouse model, C57BL/6-Tg (NSE-hAPPsw) Korl. RESULTS:After an injection (0.23 mCi) of 18F-flutemetamol and 18F-florbetaben at a time interval of 2-3 days, we compared group difference of SUVR and kinetic parameters between the AD (n?=?7) and control (n?=?7) mice, as well as between 18F-flutemetamol and 18F-florbetaben image. In addition, bio-distribution and histopathology were conducted. With visual image and VOI-based SUVR analysis, the AD group presented more prominent uptake than did the control group in both the 18F-florbetaben and 18F-flutemetamol images. With kinetic analysis, the 18F-florbetaben images showed differences in K1 and k4 between the AD and control groups, although 18F-flutemetamol images did not show significant difference. 18F-florbetaben images showed more prominent cortical uptake and matched well to the thioflavin S staining images than did the 18F-flutemetamol image. In contrast, 18F-flutemetamol images presented higher K1, k4, K1/k2 values than those of 18F-florbetaben images. Also, 18F-flutemetamol images presented prominent uptake in the bowel and bladder, consistent with higher bio-distribution in kidney, lung, blood and heart. CONCLUSIONS:Compared with 18F-flutemetamol images, 18F-florbetaben images showed prominent visual uptake intensity, SUVR, and higher correlations with the pathology. In contrast, 18F-flutemetamol was more actively metabolized than was 18F-florbetaben (Son et al. in J Nucl Med 58(Suppl 1):S278, 2017].
| S-EPMC6063010 | biostudies-literature
Project description:The Centiloid (CL) is a method for standardizing amyloid beta (A?) quantification through different ligands and methods. To find the most appropriate reference region to reduce the variance in the A? CL unit between 18F-florbetaben (FBB) and 18F-flutemetamol (FMM), we conducted head-to-head comparisons from 56 participants using the direct comparison of FBB-FMM CL (dcCL) method with four reference regions: cerebellar gray (CG), whole cerebellum (WC), WC with brainstem (WC?+?B), and pons. The FBB and FMM dcCL units were highly correlated in four reference regions: WC (R2?=?0.97), WC?+?B (R2?=?0.98), CG (R2?=?0.92), and pons (R2?=?0.98). WC showed the largest effect size in both FBB and FMM. Comparison of the variance of the dcCL values within the young control group showed that with FBB, WC?+?B had the smallest variance and with FMM, the WC had the smallest variance. Additionally, WC?+?B showed the smallest absolute difference between FBB and FMM, followed by the WC, pons, and CG. We found that it would be reasonable to use the WC or WC?+?B as the reference region when converting FBB and FMM SUVRs into dcCL, which can increase the accuracy of standardizing FBB and FMM PET results.
| S-EPMC7486392 | biostudies-literature
Project description:BackgroundDiverse research approaches support the concept that a clinical diagnosis of Late-Onset Alzheimer's Disease (LOAD) does not distinguish between subpopulations with differing neuropathologies, including dementia patients with amyloid deposition and dementia patients without amyloid deposition but with cortical thinning. Mild cognitive impairment (MCI) is generally considered the prodromal phase for LOAD, however, while a number of studies have attempted to define plasma biomarkers for the conversion of MCI to LOAD, these studies have not taken into account the heterogeneity of patient cohorts within a clinical phenotype.MethodsStudies of MCI and LOAD in several laboratories have demonstrated decrements in ethanolamine plasmalogen levels in plasma and brain and increased levels of diacylglycerols in plasma and brain. To further extend these studies and to address the issue of heterogeneity in MCI and LOAD patient groups we investigated the levels of diacylglycerols and ethanolamine plasmalogens in larger cohorts of patients utilizing, high-resolution (0.2 to 2 ppm mass error) mass spectrometry.ResultsFor the first time, our lipidomics data clearly stratify both MCI and LOAD subjects into 3 different patient cohorts within each clinical diagnosis. These include i) patients with lower circulating ethanolamine plasmalogen levels; ii) patients with augmented plasma diacylglycerol levels; and iii) patients with neither of these lipid alterations.ConclusionsThese represent the first serum biochemical data to stratify MCI and LOAD patients, advancing efforts to biochemically define patient heterogeneity in cognitive disorders.General significanceLipidomics offers a new approach for identifying biomarkers and biological targets in cognitive disorders.
| S-EPMC4802395 | biostudies-literature
Project description:IntroductionTo date, there is no broadly accepted dementia risk score for use in individuals with mild cognitive impairment (MCI), partly because there are few large datasets available for model development. When evidence is limited, the knowledge and experience of experts becomes more crucial for risk stratification and providing MCI patients with prognosis. Structured expert elicitation (SEE) includes formal methods to quantify experts' beliefs and help experts to express their beliefs in a quantitative form, reducing biases in the process. This study proposes to (1) assess experts' beliefs about important predictors for 3-year dementia risk in persons with MCI through SEE methodology and (2) to integrate expert knowledge and patient data to derive dementia risk scores in persons with MCI using a Bayesian approach.Methods and analysisThis study will use a combination of SEE methodology, prospectively collected clinical data, and statistical modelling to derive a dementia risk score in persons with MCI . Clinical expert knowledge will be quantified using SEE methodology that involves the selection and training of the experts, administration of questionnaire for eliciting expert knowledge, discussion meetings and results aggregation. Patient data from the Prospective Registry for Persons with Memory Symptoms of the Cognitive Neurosciences Clinic at the University of Calgary; the Alzheimer's Disease Neuroimaging Initiative; and the National Alzheimer's Coordinating Center's Uniform Data Set will be used for model training and validation. Bayesian Cox models will be used to incorporate patient data and elicited data to predict 3-year dementia risk.DiscussionThis study will develop a robust dementia risk score that incorporates clinician expert knowledge with patient data for accurate risk stratification, prognosis and management of dementia.
| S-EPMC8587594 | biostudies-literature
Project description:In Alzheimer's disease (AD), neurodegenerative processes are ongoing for years prior to the time that cortical atrophy can be reliably detected using conventional neuroimaging techniques. Recent advances in diffusion-weighted imaging have provided new techniques to study neural microstructure, which may provide additional information regarding neurodegeneration. In this study, we used neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion model, in order to investigate cortical microstructure along the clinical continuum of mild cognitive impairment (MCI) and AD dementia. Using gray matter-based spatial statistics (GBSS), we demonstrated that neurite density index (NDI) was significantly lower throughout temporal and parietal cortical regions in MCI, while both NDI and orientation dispersion index (ODI) were lower throughout parietal, temporal, and frontal regions in AD dementia. In follow-up ROI analyses comparing microstructure and cortical thickness (derived from T1-weighted MRI) within the same brain regions, differences in NODDI metrics remained, even after controlling for cortical thickness. Moreover, for participants with MCI, gray matter NDI-but not cortical thickness-was lower in temporal, parietal, and posterior cingulate regions. Taken together, our results highlight the utility of NODDI metrics in detecting cortical microstructural degeneration that occurs prior to measurable macrostructural changes and overt clinical dementia.
| S-EPMC7197091 | biostudies-literature