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© 2017 The Authors Objective: Because curcumin's anti-inflammatory properties may protect the brain from neurodegeneration, we studied its effect on memory in non-demented adults and explored its impact on brain amyloid and tau accumulation using 2-(1-{6-[(2-[F-18]fluoroethyl)(methyl)amino]-2-naphthyl}ethylidene)malononitrile positron emission tomography (FDDNP-PET). Methods: Forty subjects (age 51–84 years) were randomized to a bioavailable form of curcumin (Theracurmin® containing 90 mg of curcumin twice daily [N = 21]) or placebo (N = 19) for 18 months. Primary outcomes were verbal (Buschke Selective Reminding Test [SRT]) and visual (Brief Visual Memory Test-Revised [BVMT-R]) memory, and attention (Trail Making A) was a secondary outcome. FDDNP-PET signals (15 curcumin, 15 placebo) were determined in amygdala, hypothalamus, medial and lateral temporal, posterior cingulate, parietal, frontal, and motor (reference) regions. Mixed effects general linear models controlling for age and education, and effect sizes (ES; Cohen's d) were estimated. Results: SRT Consistent Long-Term Retrieval improved with curcumin (ES = 0.63, p = 0.002) but not with placebo (ES = 0.06, p = 0.8; between-group: ES = 0.68, p = 0.05). Curcumin also improved SRT Total (ES = 0.53, p = 0.002), visual memory (BVMT-R Recall: ES = 0.50, p = 0.01; BVMT-R Delay: ES = 0.51, p = 0.006), and attention (ES = 0.96, p < 0.0001) compared with placebo (ES = 0.28, p = 0.1; between-group: ES = 0.67, p = 0.04). FDDNP binding decreased significantly in the amygdala with curcumin (ES = −0.41, p = 0.04) compared with placebo (ES = 0.08, p = 0.6; between-group: ES = 0.48, p = 0.07). In the hypothalamus, FDDNP binding did not change with curcumin (ES = −0.30, p = 0.2), but increased with placebo (ES = 0.26, p = 0.05; between-group: ES = 0.55, p = 0.02). Conclusions: Daily oral Theracurmin may lead to improved memory and attention in non-demented adults. The FDDNP-PET findings suggest that symptom benefits are associated with decreases in amyloid and tau accumulation in brain regions modulating mood and memory.

Currently, only presumptive diagnosis of chronic traumatic encephalopathy (CTE) can be made in living patients. We present a modality that may be instrumental to the definitive diagnosis of CTE in living patients based on brain autopsy confirmation of [F-18]FDDNP-PET findings in an American football player with CTE. [F-18]FDDNP-PET imaging was performed 52 mo before the subject's death. Relative distribution volume parametric images and binding values were determined for cortical and subcortical regions of interest. Upon death, the brain was examined to identify the topographic distribution of neurodegenerative changes. Correlation between neuropathology and [F-18]FDDNP-PET binding patterns was performed using Spearman rank-order correlation. Mood, behavioral, motor, and cognitive changes were consistent with chronic traumatic myeloencephalopathy with a 22-yr lifetime risk exposure to American football. There were tau, amyloid, and TDP-43 neuropathological substrates in the brain with a differential topographically selective distribution. [F-18]FDDNP-PET binding levels correlated with brain tau deposition (r(s) = 0.59, P = .02), with highest relative distribution volumes in the parasagittal and paraventricular regions of the brain and the brain stem. No correlation with amyloid or TDP-43 deposition was observed. [F-18]FDDNP-PET signals may be consistent with neuropathological patterns of tau deposition in CTE, involving areas that receive the maximal shearing, angular–rotational acceleration–deceleration forces in American football players, consistent with distinctive and differential topographic vulnerability and selectivity of CTE beyond brain cortices, also involving midbrain and limbic areas. Future studies are warranted to determine whether differential and selective [F-18]FDDNP-PET may be useful in establishing a diagnosis of CTE in at-risk patients.

Head movement during a dynamic brain PET/CT imaging results in mismatch between CT and dynamic PET images. It can cause artifacts in CT-based attenuation corrected PET images, thus affecting both the qualitative and quantitative aspects of the dynamic PET images and the derived parametric images. In this study, we developed an automated retrospective image-based movement correction (MC) procedure. The MC method first registered the CT image to each dynamic PET frames, then re-reconstructed the PET frames with CT-based attenuation correction, and finally re-aligned all the PET frames to the same position. We evaluated the MC method's performance on the Hoffman phantom and dynamic FDDNP and FDG PET/CT images of patients with neurodegenerative disease or with poor compliance. Dynamic FDDNP PET/CT images (65 min) were obtained from 12 patients and dynamic FDG PET/CT images (60 min) were obtained from 6 patients. Logan analysis with cerebellum as the reference region was used to generate regional distribution volume ratio (DVR) for FDDNP scan before and after MC. For FDG studies, the image derived input function was used to generate parametric image of FDG uptake constant (Ki) before and after MC. Phantom study showed high accuracy of registration between PET and CT and improved PET images after MC. In patient study, head movement was observed in all subjects, especially in late PET frames with an average displacement of 6.92 mm. The z-direction translation (average maximum = 5.32 mm) and x-axis rotation (average maximum = 5.19 degrees) occurred most frequently. Image artifacts were significantly diminished after MC. There were significant differences (P

This work is aimed at correlating pre-mortem [18F]FDDNP positron emission tomography (PET) scan results in a patient with dementia with Lewy bodies (DLB), with cortical neuropathology distribution determined postmortem in three physical dimensions in whole brain coronal sections. Analysis of total amyloid-β (Aβ) distribution in frontal cortex and posterior cingulate gyrus confirmed its statistically significant correlation with cortical [18F]FDDNP PET binding values (distribution volume ratios, DVR) (p < 0.001, R = 0.97, R2 = 0.94). Neurofibrillary tangle (NFT) distribution correlated significantly with cortical [18F]FDDNP PET DVR in the temporal lobe (p < 0.001, R = 0.87, R2 = 0.76). Linear combination of Aβ and NFT densities was highly predictive of [18F]FDDNP PET DVR through all analyzed regions of interest (p < 0.0001, R = 0.92, R2 = 0.85), and both densities contributed significantly to the model. Lewy bodies were present at a much lower level than either Aβ or NFTs and did not significantly contribute to the in vivo signal. [18F]FDG PET scan results in this patient were consistent with the distinctive DLB pattern of hypometabolism. This work offers a mapping brain model applicable to all imaging probes for verification of imaging results with Aβ and/or tau neuropathology brain distribution using immunohistochemistry, fluorescence microscopy, and autoradiography.

Many tumor cells have elevated rates of glucose uptake that can be measured quantitatively, noninvasively and repeatedly by positron emission tomography (PET) with 2-deoxy-2-[ 18 F]-fluoro-D-glucose ( 18 F-FDG). Clinical imaging with 18 F-FDG PET has been used for detection and staging of primary and metastatic tumors. High-resolution microPET scanning and murine cancer models make it possible to analyze longitudinally glucose metabolism during the appearance, development and progression of individual experimental tumors. In this study, we used 18 F-FDG microPET and micro computerized tomography (microCT) to investigate glucose uptake in the DMBA/TPA chemically-induced multistage mouse skin carcinogenesis model. 18 F-FDG uptake is significantly higher in all papillomas than in surrounding skin. Elevated 18 F-FDG uptake is observed when tumors can be identified morphologically, but not before. Although 18 F-FDG uptake is high in all fully invasive, malignant skin squamous cell carcinomas, uptake in papillomas and microinvasive malignant squamous cell carcinomas is variable and does not exhibit any correlation with tumor stage.

Background Many biological factors of 2-[18 F]fluoro-2-deoxy-d-glucose (18 F-FDG) in blood can affect 18 F-FDG uptake in tumors. In this study, longitudinal 18 F-FDG positron emission tomography (PET) studies were performed on tumor-bearing mice to investigate the effect of blood glucose level and tumor size on 18 F-FDG uptake in tumors. Methods Six- to eight-week-old severe combined immunodeficiency mice were implanted with glioblastoma U87 (n = 8) or adenocarcinoma MDA-MB-231 (MDA) (n = 11) in the shoulder. When the tumor diameter was approximately 2.5 mm, a 60-min dynamic 18 F-FDG PET scan was performed weekly until the tumor diameter reached 10 mm. Regions of interests were defined in major organs and tumor. A plasma curve was derived based on a modeling method that utilizes the early heart time-activity curve and a late-time blood sample. The 18 F-FDG uptake constant K i was calculated using Patlak analysis on the tumors without an apparent necrotic center shown in the PET images. For each tumor type, the measured K i was corrected for partial volume (PV), and multivariate regression analysis was performed to examine the effects of blood glucose level ([Glc]) and tumor growth. Corrected Akaike's information criterion was used to determine the best model. Results The regression model that best fit the PV-corrected K i for U87 data was K i /RC = (1/[Glc]) × (0.27 ± 0.027) mL/min/mL (where [Glc] is in mmol/L), and for MDA, it was K i /RC = (0.04 ± 0.005) mL/min/mL, where K i /RC denotes the PV-corrected K i using an individual recovery coefficient (RC). The results indicated that 18 F-FDG K i /RC for U87 was inversely related to [Glc], while [Glc] had no effect on 18 F-FDG K i /RC of MDA. After the effects of PV and [Glc] were accounted for, the data did not support any increase of 18 F-FDG K i as the tumor (of either type) grew larger in size. Conclusions The effect of [Glc] on the tumor 18 F-FDG K i was tumor-dependent. PV- and [Glc]-corrected 18 F-FDG K i did not show significant increase as the tumor of either type grew in size.

Purpose Subcortical white matter is known to be relatively unaffected by amyloid deposition in Alzheimer’s disease (AD). We investigated the use of subcortical white matter as a reference region to quantify [18F]FDDNP binding in the human brain. Methods Dynamic [18F]FDDNP PET studies were performed on 7 control subjects and 12 AD patients. Population efflux rate constants (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {k\prime_2} $$\end{document}) from subcortical white matter (centrum semiovale) and cerebellar cortex were derived by a simplified reference tissue modeling approach incorporating physiological constraints. Regional distribution volume ratio (DVR) estimates were derived using Logan and simplified reference tissue approaches, with either subcortical white matter or cerebellum as reference input. Discriminant analysis with cross-validation was performed to classify control subjects and AD patients. Results The population estimates of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {k\prime_2} $$\end{document} in subcortical white matter did not differ significantly between control subjects and AD patients but the variability of individual estimates of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$ {k\prime_2} $$\end{document} determined in white matter was lower than that in cerebellum. Logan DVR showed dependence on the efflux rate constant in white matter. The DVR estimates in the frontal, parietal, posterior cingulate, and temporal cortices were significantly higher in the AD group (p

Traumatic brain injury (TBI) is a major cause of mortality and morbidity, placing a significant financial burden on the healthcare system worldwide. Non-invasive neuroimaging technologies have been playing a pivotal role in the study of TBI, providing important information for surgical planning and patient management. Advances in understanding the basic mechanisms and pathophysiology of the brain following TBI are hindered by a lack of reliable image analysis methods for accurate quantitative assessment of TBI-induced structural and pathophysiological changes seen on anatomical and functional images obtained from multiple imaging modalities. Conventional region-of-interest (ROI) analysis based on manual labeling of brain regions is time-consuming and the results could be inconsistent within and among investigators. In this study, we propose a workflow solution framework that combined the use of non-linear spatial normalization of structural brain images and template-based anatomical labeling to automate the ROI analysis process. The proposed workflow solution is applied to dynamic PET scanning with 15O-water (0–10 min) and 18F-FDDNP (0–6 min) for measuring cerebral blood flow in patients with TBI.