Brain FDG PET study of normal aging in Japanese: effect of atrophy correction

Structural and Molecular Imaging of Aging Brain: A Focus on MR Imaging and PET Modalities

The process of aging in the brain is reflective of various factors including the environment, lifestyle, genetics, and management of concurrent chronic conditions. Aging in the brain leads to observable structural changes on neuroimaging, such as brain volume reduction, neuronal atrophy, and synaptic loss, which affect higher cognitive functions. Positron emission tomography imaging can help visualize these changes earlier before structural changes even take place and the associated decline in brain function, revealing important insights into how the brain ages and the impact on neural connectivity and cognitive abilities.

Lower brain glucose metabolism in normal ageing is predominantly frontal and temporal: A systematic review and pooled effect size and activation likelihood estimates meta-analyses

This review provides a qualitative and quantitative analysis of cerebral glucose metabolism in ageing. We undertook a systematic literature review followed by pooled effect size and activation likelihood estimates (ALE) meta-analyses. Studies were retrieved from PubMed following the PRISMA guidelines. After reviewing 635 records, 21 studies with 22 independent samples (n = 911 participants) were included in the pooled effect size analyses. Eight studies with eleven separate samples (n = 713 participants) were included in the ALE analyses. Pooled effect sizes showed significantly lower cerebral metabolic rates of glucose for older versus younger adults for the whole brain, as well as for the frontal, temporal, parietal, and occipital lobes. Among the sub-cortical structures, the caudate showed a lower metabolic rate among older adults. In sub-group analyses controlling for changes in brain volume or partial volume effects, the lower glucose metabolism among older adults in the frontal lobe remained significant, whereas confidence intervals crossed zero for the other lobes and structures. The ALE identified nine clusters of lower glucose metabolism among older adults, ranging from 200 to 2640 mm³ . The two largest clusters were in the left and right inferior frontal and superior temporal gyri and the insula. Clusters were also found in the inferior temporal junction, the anterior cingulate and caudate. Taken together, the results are consistent with research showing less efficient glucose metabolism in the ageing brain. The findings are discussed in the context of theories of cognitive ageing and are compared to those found in neurodegenerative disease.

Mitochondria, energy, and metabolism in neuronal health and disease

Mitochondria are associated with various cellular activities critical to homeostasis, particularly in the nervous system. The plastic architecture of the mitochondrial network and its dynamic structure play crucial roles in ensuring that varying energetic demands are rapidly met to maintain neuronal and axonal energy homeostasis. Recent evidence associates ageing and neurodegeneration with anomalous neuronal metabolism, as age-dependent alterations of neuronal metabolism are now believed to occur prior to neurodegeneration. The brain has a high energy demand, which makes it particularly sensitive to mitochondrial dysfunction. Distinct cellular events causing oxidative stress or disruption of metabolism and mitochondrial homeostasis can trigger a neuropathology. This review explores the bioenergetic hypothesis for the neurodegenerative pathomechanisms, discussing factors leading to age-related brain hypometabolism and its contribution to cognitive decline. Recent research on the mitochondrial network in healthy nervous system cells, its response to stress and how it is affected by pathology, as well as current contributions to novel therapeutic approaches will be highlighted.

Connectivity and Patterns of Regional Cerebral Blood Flow, Cerebral Glucose Uptake, and Aβ-Amyloid Deposition in Alzheimer's Disease (Early and Late-Onset) Compared to Normal Ageing

PURPOSE

The aim of this study was to investigate the differences in early (EOAD) and late (LOAD) onset of Alzheimer´s disease, as well as glucose uptake, regional cerebral blood flow (R1), amyloid depositions, and functional brain connectivity between normal young (YC) and Old Controls (OC).

METHODOLOGY

The study included 22 YC (37 ± 5 y), 22 OC (73 ± 5.9 y), 18 patients with EOAD (63 ± 9.5 y), and 18 with LOAD (70.6 ± 7.1 y). Patients underwent FDG and PIB PET/CT. R1 images were obtained from the compartmental analysis of the dynamic PIB acquisitions. Images were analyzed by a voxel-wise and a VOI-based approach. Functional connectivity was studied from the R1 and glucose uptake images.

RESULTS

OC had a significant reduction of R1 and glucose uptake compared to YC, predominantly at the dorsolateral and mesial frontal cortex. EOAD and LOAD vs. OC showed a decreased R1 and glucose uptake at the posterior parietal cortex, precuneus, and posterior cingulum. EOAD vs. LOAD showed a reduction in glucose uptake and R1 at the occipital and parietal cortex and an increased at the mesial frontal and temporal cortex. There was a mild increase in an amyloid deposition at the frontal cortex in LOAD vs. EOAD. YC presented higher connectivity than OC in R1 but lower connectivity considering glucose uptake. Moreover, EOAD and LOAD showed a decreased connectivity compared to controls that were more pronounced in glucose uptake than R1.

CONCLUSION

Our results demonstrated differences in amyloid deposition and functional imaging between groups and a differential pattern of functional connectivity in R1 and glucose uptake in each clinical condition. These findings provide new insights into the pathophysiological processes of AD and may have an impact on patient diagnostic evaluation.

Fully automated identification of brain abnormality from whole-body FDG-PET imaging using deep learning-based brain extraction and statistical parametric mapping

BACKGROUND

The whole brain is often covered in [18F]Fluorodeoxyglucose positron emission tomography ([18F]FDG-PET) in oncology patients, but the covered brain abnormality is typically screened by visual interpretation without quantitative analysis in clinical practice. In this study, we aimed to develop a fully automated quantitative interpretation pipeline of brain volume from an oncology PET image.

METHOD

We retrospectively collected 500 oncologic [18F]FDG-PET scans for training and validation of the automated brain extractor. We trained the model for extracting brain volume with two manually drawn bounding boxes on maximal intensity projection images. ResNet-50, a 2-D convolutional neural network (CNN), was used for the model training. The brain volume was automatically extracted using the CNN model and spatially normalized. For validation of the trained model and an application of this automated analytic method, we enrolled 24 subjects with small cell lung cancer (SCLC) and performed voxel-wise two-sample T test for automatic detection of metastatic lesions.

RESULT

The deep learning-based brain extractor successfully identified the existence of whole-brain volume, with an accuracy of 98% for the validation set. The performance of extracting the brain measured by the intersection-over-union of 3-D bounding boxes was 72.9 ± 12.5% for the validation set. As an example of the application to automatically identify brain abnormality, this approach successfully identified the metastatic lesions in three of the four cases of SCLC patients with brain metastasis.

CONCLUSION

Based on the deep learning-based model, extraction of the brain volume from whole-body PET was successfully performed. We suggest this fully automated approach could be used for the quantitative analysis of brain metabolic patterns to identify abnormalities during clinical interpretation of oncologic PET studies.

Evaluation of Age and Sex-Related Metabolic Changes in Healthy Subjects: An Italian Brain 18F-FDG PET Study

Background: 18F-fluorodeoxyglucose (18F-FDG) positron-emission-tomography (PET) allows detection of cerebral metabolic alterations in neurological diseases vs. normal aging. We assess age- and sex-related brain metabolic changes in healthy subjects, exploring impact of activity normalization methods. Methods: brain scans of Italian Association of Nuclear Medicine normative database (151 subjects, 67 Males, 84 Females, aged 20–84) were selected. Global mean, white matter, and pons activity were explored as normalization reference. We performed voxel-based and ROI analyses using SPM12 and IBM-SPSS software. Results: SPM proved a negative correlation between age and brain glucose metabolism involving frontal lobes, anterior-cingulate and insular cortices bilaterally. Narrower clusters were detected in lateral parietal lobes, precuneus, temporal pole and medial areas bilaterally. Normalizing on pons activity, we found a more significant negative correlation and no positive one. ROIs analysis confirmed SPM results. Moreover, a significant age × sex interaction effect was revealed, with worse metabolic reduction in posterior-cingulate cortices in females than males, especially in post-menopausal age. Conclusions: this study demonstrated an age-related metabolic reduction in frontal lobes and in some parieto-temporal areas more evident in females. Results suggested pons as the most appropriate normalization reference. Knowledge of age- and sex-related cerebral metabolic changes is critical to correctly interpreting brain 18F-FDG PET imaging.

Aging-Related Modular Architectural Reorganization of the Metabolic Brain Network

Background: Modules in brain network represent groups of brain regions that are collectively involved in one or more cognitive domains. Exploring aging-related reorganization of the brain modular architecture using metabolic brain network could further our understanding about aging-related neuromechanism and neurodegenerations. Materials and Methods: In this study, 432 subjects who performed ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET) were enrolled and divided into young and old adult groups, as well as female and male groups. The modular architecture was detected, and the connector and hub nodes were identified to explore the topological role of the brain regions based on the metabolic brain network. Results: This study revealed that human metabolic brain network was modular and could be clustered into three modules. The modular architecture was reorganized from young to old ages with regions related to sensorimotor function clustered into the same module; and the number of connector nodes was reduced and most connector nodes were localized in temporo-occipital areas related to visual and auditory functions in old ages. The major gender difference is that the metabolic brain network was delineated into four modules in old female group with the nodes related to sensorimotor function split into two modules. Discussion: Those findings suggest aging is associated with reorganized brain modular architecture. Clinical Trial Registration number: ChiCTR2000036842.

Cortical hypometabolism reflects local atrophy and tau pathology in symptomatic Alzheimer's disease

Posterior cortical hypometabolism measured with [18F]-Fluorodeoxyglucose (FDG)-PET is a well-known marker of Alzheimer's disease-related neurodegeneration, but its associations with underlying neuropathological processes are unclear. We assessed cross-sectionally the relative contributions of three potential mechanisms causing hypometabolism in the retrosplenial and inferior parietal cortices: local molecular (amyloid and tau) pathology and atrophy, distant factors including contributions from the degenerating medial temporal lobe or molecular pathology in functionally connected regions, and the presence of the apolipoprotein E (APOE) ε4 allele. Two hundred and thirty-two amyloid-positive cognitively impaired patients from two cohorts (University of California, San Francisco, UCSF, and Alzheimer's Disease Neuroimaging Initiative, ADNI) underwent MRI and PET with FDG, amyloid-PET using [11C]-Pittsburgh Compound B, [18F]-Florbetapir, or [18F]-Florbetaben, and [18F]-Flortaucipir tau-PET within one year. Standard uptake value ratios (SUVR) were calculated using tracer-specific reference regions. Regression analyses were run within cohorts to identify variables associated with retrosplenial or inferior parietal FDG SUVR. On average, ADNI patients were older and were less impaired than UCSF patients. Regional patterns of hypometabolism were similar between cohorts, though there were cohort differences in regional gray matter atrophy. Local cortical thickness and tau-PET (but not amyloid-PET) were independently associated with both retrosplenial and inferior parietal FDG SUVR (ΔR2 = .09 to .21) across cohorts in models that also included age and disease severity (local model). Including medial temporal lobe volume improved the retrosplenial FDG model in ADNI (ΔR2 = .04, p = .008) but not UCSF (ΔR2 < .01, p = .52), and did not improve the inferior parietal models (ΔR2s < .01, ps > .37). Interaction analyses revealed that medial temporal volume was more strongly associated with retrosplenial FDG SUVR at earlier disease stages (p = .06 in UCSF, p = .046 in ADNI). Exploratory analyses across the cortex confirmed overall associations between hypometabolism and local tau pathology and thickness and revealed associations between medial temporal degeneration and hypometabolism in retrosplenial, orbitofrontal, and anterior cingulate cortices. Finally, our data did not support hypotheses of a detrimental effect of pathology in connected regions or of an effect of the APOE ε4 allele in impaired participants. Overall, in two independent groups of patients at symptomatic stages of Alzheimer's disease, cortical hypometabolism mainly reflected structural neurodegeneration and tau, but not amyloid, pathology.

The pons as reference region for intensity normalization in semi-quantitative analysis of brain 18FDG PET: application to metabolic changes related to ageing in conventional and digital control databases

Background

The objective of the study is to define the most appropriate region for intensity normalization in brain ¹⁸FDG PET semi-quantitative analysis. The best option could be based on previous absolute quantification studies, which showed that the metabolic changes related to ageing affect the quasi-totality of brain regions in healthy subjects. Consequently, brain metabolic changes related to ageing were evaluated in two populations of healthy controls who underwent conventional (n = 56) or digital (n = 78) ¹⁸FDG PET/CT. The median correlation coefficients between age and the metabolism of each 120 atlas brain region were reported for 120 distinct intensity normalizations (according to the 120 regions). SPM linear regression analyses with age were performed on most significant normalizations (FWE, p < 0.05).

Results

The cerebellum and pons were the two sole regions showing median coefficients of correlation with age less than − 0.5. With SPM, the intensity normalization by the pons provided at least 1.7- and 2.5-fold more significant cluster volumes than other normalizations for conventional and digital PET, respectively.

Conclusions

The pons is the most appropriate area for brain ¹⁸FDG PET intensity normalization for examining the metabolic changes through ageing.

Mitochondrial Dysfunction in Alzheimer's Disease: A Biomarker of the Future?

Alzheimer's disease (AD) is the most common cause of dementia worldwide and is characterised pathologically by the accumulation of amyloid beta and tau protein aggregates. Currently, there are no approved disease modifying therapies for clearance of either of these proteins from the brain of people with AD. As well as abnormalities in protein aggregation, other pathological changes are seen in this condition. The function of mitochondria in both the nervous system and rest of the body is altered early in this disease, and both amyloid and tau have detrimental effects on mitochondrial function. In this review article, we describe how the function and structure of mitochondria change in AD. This review summarises current imaging techniques that use surrogate markers of mitochondrial function in both research and clinical practice, but also how mitochondrial functions such as ATP production, calcium homeostasis, mitophagy and reactive oxygen species production are affected in AD mitochondria. The evidence reviewed suggests that the measurement of mitochondrial function may be developed into a future biomarker for early AD. Further work with larger cohorts of patients is needed before mitochondrial functional biomarkers are ready for clinical use.

Selection of the optimal intensity normalization region for FDG-PET studies of normal aging and Alzheimer's disease

The primary method for measuring brain metabolism in humans is positron emission tomography (PET) imaging using the tracer 18F-fluorodeoxyglucose (FDG). Standardized uptake value ratios (SUVR) are commonly calculated from FDG-PET images to examine intra- and inter-subject effects. Various reference regions are used in the literature of FDG-PET studies of normal aging, making comparison between studies difficult. Our primary objective was to determine the optimal SUVR reference region in the context of healthy aging, using partial volume effect (PVE) and non-PVE corrected data. We calculated quantitative cerebral metabolic rates of glucose (CMRg) from PVE-corrected and non-corrected images from young and older adults. We also investigated regional atrophy using magnetic resonance (MR) images. FreeSurfer 6.0 atlases were used to explore possible reference regions of interest (ROI). Multiple regression was used to predict CMRg data, in each FreeSurfer ROI, with age and sex as predictors. Age had the least effect in predicting CMRg for PVE corrected data in the pons (r2 = 2.83 × 10-3, p = 0.67). For non-PVE corrected data age also had the least effect in predicting CMRg in the pons (r2 = 3.12 × 10-3, p = 0.67). We compared the effects of using the whole brain or the pons as a reference region in PVE corrected data in two regions susceptible to hypometabolism in Alzheimer's disease, the posterior cingulate and precuneus. Using the whole brain as a reference region resulted in non-significant group differences in the posterior cingulate while there were significant differences between all three groups in the precuneus (all p < 0.004). When using the pons as a reference region there was significant differences between all groups for both the posterior cingulate and the precuneus (all p < 0.001). Therefore, the use of the pons as a reference region is more sensitive to hypometabism changes associated with Alzheimer's disease than the whole brain.

Aging-Related Hypometabolism in the Anterior Cingulate Cortex of Cognitively Intact, Amyloid-Negative Seniors at Rest Mediates the Relationship between Age and Executive Function but Not Memory

The anterior cingulate cortex (ACC) shows the most aging-related brain metabolic dysfunction that correlates with decreasing executive processing in otherwise healthy, cognitively intact volunteers. Here, data from ADNI are used to elucidate potential pathophysiological mechanisms involved in cognitive aging, that is, age-related decline in cognitive performance in the absence of known neurodegenerative disease. Amyloid-negative volunteers showed statistically significant mediation of ACC metabolism in the relationship between age and verbal fluency. A nonlinguistic task of executive function, Trails B, showed also negative correlation between performance and age, albeit weaker, but was not significant in the mediation analysis. Recall of story items, minimizing attentional demands compared with learning of word lists, did not correlate with age. ADNI subjects selected for low vascular risks also showed correlation between age and declining ACC metabolism. In the whole-brain amyloid-negative subset, ACC amyloid was not correlated with age. As expected, the metabolism in an arbitrary region such as motor cortex that was not expected to decline with cognitive aging showed no correlation with age or ACC metabolism suggesting regional specificity. These findings motivate the search for the pathophysiology of aging-related ACC dysfunction to prevent, diagnose, and treat the decline in executive function associated with cognitive aging.

Alzheimer's disease and type 2 diabetes mellitus are distinct diseases with potential overlapping metabolic dysfunction upstream of observed cognitive decline

Alzheimer's disease (AD) and type 2 diabetes mellitus (T2DM) are highly prevalent aging-related diseases associated with significant morbidity and mortality. Some findings in human and animal models have linked T2DM to AD-type dementia. Despite epidemiological associations between the T2DM and cognitive impairment, the interrelational mechanisms are unclear. The preponderance of evidence in longitudinal studies with autopsy confirmation have indicated that vascular mechanisms, rather than classic AD-type pathologies, underlie the cognitive decline often seen in self-reported T2DM. T2DM is associated with cardiovascular and cerebrovascular disease (CVD), and is associated with increased risk of infarcts and small vessel disease in the brain and other organs. Neuropathological examinations of post-mortem brains demonstrated evidence of cerebrovascular disease and little to no correlation between T2DM and β-amyloid deposits or neurofibrillary tangles. Nevertheless, the mechanisms upstream of early AD-specific pathology remain obscure. In this regard, there may indeed be overlap between the pathologic mechanisms of T2DM/"metabolic syndrome," and AD. More specifically, cerebral insulin processing, glucose metabolism, mitochondrial function, and/or lipid metabolism could be altered in patients in early AD and directly influence symptomatology and/or neuropathology.

Enhancement of Partial Volume Correction in MR-Guided PET Image Reconstruction by Using MRI Voxel Sizes

Positron emission tomography (PET) suffers from poor spatial resolution which results in quantitative bias when evaluating the radiotracer uptake in small anatomical regions, such as the striatum in the brain which is of importance in this paper of neurodegenerative diseases. These partial volume effects need to be compensated for by employing partial volume correction (PVC) methods in order to achieve quantitatively accurate images. Two important PVC methods applied during the reconstruction are resolution modeling, which suffers from Gibbs artifacts, and penalized likelihood using anatomical priors. The introduction of clinical simultaneous PET-MR scanners has attracted new attention for the latter methods and brought new opportunities to use MRI information to assist PET image reconstruction in order to improve image quality. In this context, MR images are usually down-sampled to the PET resolution before being used in MR-guided PET reconstruction. However, the reconstruction of PET images using the MRI voxel size could achieve a better utilization of the high resolution anatomical information and improve the PVC obtained with these methods. In this paper, we evaluate the importance of the use of MRI voxel sizes when reconstructing PET images with MR-guided maximum a posteriori (MAP) methods, specifically the modified Bowsher method. We also propose a method to avoid the artifacts that arise when PET reconstructions are performed in a higher resolution matrix than the standard for a given scanner. The MR-guided MAP reconstructions were implemented with a modified Lange prior that included anatomical information with the Bowsher method. The methods were evaluated with and without resolution modeling for simulated and real brain data. We show that the use of the MRI voxel sizes when reconstructing PET images with MR-guided MAP enhances PVC by improving the contrast and reducing the bias in six different regions of the brain using regional metrics for a single simulated data set and ensemble metrics for ten noise realizations. Similar results were obtained for real data, where a good enhancement of the contrast was achieved. The combination of MR-guided MAP reconstruction with point-spread function modeling and MRI voxel sizes proved to be an attractive method to achieve considerable enhancement of PVC, while reducing and controlling the noise level and Gibbs artifacts.

Dissociation of Tau Deposits and Brain Atrophy in Early Alzheimer's Disease: A Combined Positron Emission Tomography/Magnetic Resonance Imaging Study

The recent advent of tau-specific positron emission tomography (PET) has enabled in vivo assessment of tau pathology in Alzheimer’s disease (AD). However, because PET scanners have limited spatial resolution, the measured signals of small brain structures or atrophied areas are underestimated by partial volume effects (PVEs). The aim of this study was to determine whether partial volume correction (PVC) improves the precision of measures of tau deposits in early AD. We investigated tau deposits in 18 patients with amyloid-positive early AD and in 36 amyloid-negative healthy controls using ¹⁸F-THK5351 PET. For PVC, we applied the SPM toolbox PETPVE12. The PET images were then spatially normalized and subjected to voxel-based group analysis using SPM12 for comparison between the early AD patients and healthy controls. We also compared these two groups in terms of brain atrophy using voxel-based morphometry of MRI. We found widespread neocortical tracer retention predominantly in the posterior cingulate and precuneus areas, but also in the inferior temporal lobes, inferior parietal lobes, frontal lobes, and occipital lobes in the AD patients compared with the controls. The pattern of tracer retention was similar between before and after PVC, suggesting that PVC had little effect on the precision of tau load measures. Gray matter atrophy was detected in the medial/lateral temporal lobes and basal frontal lobes in the AD patients. Interestingly, only a few associations were found between atrophy and tau deposits, even after PVC. In conclusion, PVC did not significantly affect ¹⁸F-THK5351 PET measures of tau deposits. This discrepancy between tau deposits and atrophy suggests that tau load precedes atrophy.

Predicting Aging of Brain Metabolic Topography Using Variational Autoencoder

Predicting future brain topography can give insight into neural correlates of aging and neurodegeneration. Due to variability in the aging process, it has been challenging to precisely estimate brain topographical change according to aging. Here, we predict age-related brain metabolic change by generating future brain ¹⁸F-Fluorodeoxyglucose PET. A cross-sectional PET dataset of cognitively normal subjects with different age was used to develop a generative model. The model generated PET images using age information and characteristic individual features. Predicted regional metabolic changes were correlated with the real changes obtained by follow-up data. This model was applied to produce a brain metabolism aging movie by generating PET at different ages. Normal population distribution of brain metabolic topography at each age was estimated as well. In addition, a generative model using APOE4 status as well as age as inputs revealed a significant effect of APOE4 status on age-related metabolic changes particularly in the calcarine, lingual cortex, hippocampus, and amygdala. It suggested APOE4 could be a factor affecting individual variability in age-related metabolic degeneration in normal elderly. This predictive model may not only be extended to understanding the cognitive aging process, but apply to the development of a preclinical biomarker for various brain disorders.

Biomarkers for Early Diagnosis of Alzheimer's Disease in the Oldest Old: Yes or No?

In recent years, many efforts have been spent to identify sensitive biomarkers able to improve the accuracy of Alzheimer's disease (AD) diagnosis. Two different workgroups (NIA-AA and IWG) included cerebrospinal fluid (CSF) and neuroimaging findings in their sets of criteria in order to improve diagnostic accuracy as well as early diagnosis. The number of subjects with cognitive impairment increases with aging but the oldest old (≥85 years of age), the fastest growing age group, is still the most unknown from a biological point of view. For this reason, the aim of our narrative mini-review is to evaluate the pertinence of the new criteria for AD diagnosis in the oldest old. Moreover, since different subgroups of oldest old have been described in scientific literature (escapers, delayers, survivors), we want to outline the clinical profile of the oldest old who could really benefit from the use of biomarkers for early diagnosis. Reviewing the literature on biomarkers included in the diagnostic criteria, we did not find a high degree of evidence for their use in the oldest old, although CSF biomarkers seem to be still the most useful for excluding AD diagnosis in the "fit" subgroup of oldest old subjects, due to the high negative predictive value maintained in this age group.

Multimodal Discrimination between Normal Aging, Mild Cognitive Impairment and Alzheimer's Disease and Prediction of Cognitive Decline

Alzheimer’s Disease (AD) and mild cognitive impairment (MCI) are associated with widespread changes in brain structure and function, as indicated by magnetic resonance imaging (MRI) morphometry and 18-fluorodeoxyglucose position emission tomography (FDG PET) metabolism. Nevertheless, the ability to differentiate between AD, MCI and normal aging groups can be difficult. Thus, the goal of this study was to identify the combination of cerebrospinal fluid (CSF) biomarkers, MRI morphometry, FDG PET metabolism and neuropsychological test scores to that best differentiate between a sample of normal aging subjects and those with MCI and AD from the Alzheimer’s Disease Neuroimaging Initiative. The secondary goal was to determine the neuroimaging variables from MRI, FDG PET and CSF biomarkers that can predict future cognitive decline within each group. To achieve these aims, a series of multivariate stepwise logistic and linear regression models were generated. Combining all neuroimaging modalities and cognitive test scores significantly improved the index of discrimination, especially at the earliest stages of the disease, whereas MRI gray matter morphometry variables best predicted future cognitive decline compared to other neuroimaging variables. Overall these findings demonstrate that a multimodal approach using MRI morphometry, FDG PET metabolism, neuropsychological test scores and CSF biomarkers may provide significantly better discrimination than any modality alone.

PET/MR Imaging: New Frontier in Alzheimer's Disease and Other Dementias

Alzheimer's disease (AD) is the most common form of dementia; a progressive neurodegenerative disease that currently lacks an effective treatment option. Early and accurate diagnosis, in addition to quick elimination of differential diagnosis, allows us to provide timely treatments that delay the progression of AD. Imaging plays an important role for the early diagnosis of AD. The newly emerging PET/MR imaging strategies integrate the advantages of PET and MR to diagnose and monitor AD. This review introduces the development of PET/MR imaging systems, technical considerations of PET/MR imaging, special considerations of PET/MR in AD, and the system's potential clinical applications and future perspectives in AD.

Phantom criteria for qualification of brain FDG and amyloid PET across different cameras

Background

While fluorodeoxyglucose (FDG) and amyloid PET is valuable for patient management, research, and clinical trial of therapeutics on Alzheimer’s disease, the specific details of the PET scanning method including the PET camera model type influence the image quality, which may further affect the interpretation of images and quantitative capabilities. To make multicenter PET data reliable and to establish PET scanning as a universal diagnostic technique and a verified biomarker, we have proposed phantom test procedures and criteria for optimizing image quality across different PET cameras.

Results

As the method, four physical parameters (resolution, gray-white contrast, uniformity, and image noise) were selected as essential to image quality for brain FDG and amyloid PET and were measured with a Hoffman 3D brain phantom and a uniform cylindrical phantom on a total of 12 currently used PET models. The phantom radioactivity and acquisition time were determined based on the standard scanning protocol for each PET drug (FDG, ¹¹C-PiB, ¹⁸F-florbetapir, and ¹⁸F-flutemetamol). Reconstruction parameters were either determined based on the methods adopted in ADNI, J-ADNI, and other research and clinical trials or optimized based on measured phantom image parameters under various reconstruction conditions.

As the result, phantom test criteria were proposed as follows: (i) 8 mm FWHM or better resolution and (ii) gray/white %contrast ≥55 % with the Hoffman 3D brain phantom and (iii) SD of 51 small region of interests (ROIs) ≤0.0249 (equivalent to 5 % variation) for uniformity and (iv) image noise (SD/mean) ≤15 % for a large ROI with the uniform cylindrical phantom. These criteria provided image quality conforming to those multicenter clinical studies and were also achievable with most of the PET cameras that are currently used.

Conclusions

The proposed phantom test criteria facilitate standardization and qualification of brain FDG and amyloid PET images and deserve further evaluation by future multicenter clinical studies.

Data-driven identification of intensity normalization region based on longitudinal coherency of 18F-FDG metabolism in the healthy brain

OBJECTIVES

In brain ¹⁸F-FDG PET data intensity normalization is usually applied to control for unwanted factors confounding brain metabolism. However, it can be difficult to determine a proper intensity normalization region as a reference for the identification of abnormal metabolism in diseased brains. In neurodegenerative disorders, differentiating disease-related changes in brain metabolism from age-associated natural changes remains challenging. This study proposes a new data-driven method to identify proper intensity normalization regions in order to improve separation of age-associated natural changes from disease related changes in brain metabolism.

METHODS

127 female and 128 male healthy subjects (age: 20 to 79) with brain¹⁸F-FDG PET/CT in the course of a whole body cancer screening were included. Brain PET images were processed using SPM8 and were parcellated into 116 anatomical regions according to the AAL template. It is assumed that normal brain ¹⁸F-FDG metabolism has longitudinal coherency and this coherency leads to better model fitting. The coefficient of determination R² was proposed as the coherence coefficient, and the total coherence coefficient (overall fitting quality) was employed as an index to assess proper intensity normalization strategies on single subjects and age-cohort averaged data. Age-associated longitudinal changes of normal subjects were derived using the identified intensity normalization method correspondingly. In addition, 15 subjects with clinically diagnosed Parkinson's disease were assessed to evaluate the clinical potential of the proposed new method.

RESULTS

Intensity normalizations by paracentral lobule and cerebellar tonsil, both regions derived from the new data-driven coherency method, showed significantly better coherence coefficients than other intensity normalization regions, and especially better than the most widely used global mean normalization. Intensity normalization by paracentral lobule was the most consistent method within both analysis strategies (subject-based and age-cohort averaging). In addition, the proposed new intensity normalization method using the paracentral lobule generates significantly higher differentiation from the age-associated changes than other intensity normalization methods.

CONCLUSION

Proper intensity normalization can enhance the longitudinal coherency of normal brain glucose metabolism. The paracentral lobule followed by the cerebellar tonsil are shown to be the two most stable intensity normalization regions concerning age-dependent brain metabolism. This may provide the potential to better differentiate disease-related changes from age-related changes in brain metabolism, which is of relevance in the diagnosis of neurodegenerative disorders.

Brain fluorodeoxyglucose (FDG) PET in dementia

The purpose of this article is to present a selective and concise summary of fluorodeoxyglucose (FDG) positron emission tomography (PET) in dementia imaging. FDG PET is used to visualize a downstream topographical marker that indicates the distribution of neural injury or synaptic dysfunction, and can identify distinct phenotypes of dementia due to Alzheimer's disease (AD), Lewy bodies, and frontotemporal lobar degeneration. AD dementia shows hypometabolism in the parietotemporal association area, posterior cingulate, and precuneus. Hypometabolism in the inferior parietal lobe and posterior cingulate/precuneus is a predictor of cognitive decline from mild cognitive impairment (MCI) to AD dementia. FDG PET may also predict conversion of cognitively normal individuals to those with MCI. Age-related hypometabolism is observed mainly in the anterior cingulate and anterior temporal lobe, along with regional atrophy. Voxel-based statistical analyses, such as statistical parametric mapping or three-dimensional stereotactic surface projection, improve the diagnostic performance of imaging of dementias. The potential of FDG PET in future clinical and methodological studies should be exploited further.

Different partial volume correction methods lead to different conclusions: An (18)F-FDG-PET study of aging

A cross-sectional group study of the effects of aging on brain metabolism as measured with (18)F-FDG-PET was performed using several different partial volume correction (PVC) methods: no correction (NoPVC), Meltzer (MZ), Müller-Gärtner (MG), and the symmetric geometric transfer matrix (SGTM) using 99 subjects aged 65-87years from the Harvard Aging Brain study. Sensitivity to parameter selection was tested for MZ and MG. The various methods and parameter settings resulted in an extremely wide range of conclusions as to the effects of age on metabolism, from almost no changes to virtually all of cortical regions showing a decrease with age. Simulations showed that NoPVC had significant bias that made the age effect on metabolism appear to be much larger and more significant than it is. MZ was found to be the same as NoPVC for liberal brain masks; for conservative brain masks, MZ showed few areas correlated with age. MG and SGTM were found to be similar; however, MG was sensitive to a thresholding parameter that can result in data loss. CSF uptake was surprisingly high at about 15% of that in gray matter. The exclusion of CSF from SGTM and MG models, which is almost universally done, caused a substantial loss in the power to detect age-related changes. This diversity of results reflects the literature on the metabolism of aging and suggests that extreme care should be taken when applying PVC or interpreting results that have been corrected for partial volume effects. Using the SGTM, significant age-related changes of about 7% per decade were found in frontal and cingulate cortices as well as primary visual and insular cortices.

Integrated (18)F-fluorodeoxyglucose positron emission tomography magnetic resonance imaging ((18)F-FDG PET/MRI), a multimodality approach for comprehensive evaluation of dementia patients: A pictorial essay

Dementia, caused by irreversible neurodegenerative disorders such as Alzheimer's disease or reversible non-degenerative conditions, is rapidly becoming one of the most alarming health problems in our aging society. This cognitive disorder associated with a multitude of clinical differentials with overlapping clinical, pathological, and imaging features is difficult to diagnose and treat, as it often presents late after significant neuronal damage has already occurred. Novel disease-modifying treatments being developed will have to be corroborated with innovative imaging biomarkers so that earlier reliable diagnosis can be made and treatment initiated upon. Along with new specific PET radiotracers, integrated PET/MRI with combined methodological advantage and simultaneously acquired structural-cum-functional information may help achieve this goal. The present pictorial essay details our experiences with PET/MRI in dementing disorders, along with reviewing recent advances and future scope.

Brain: normal variations and benign findings in fluorodeoxyglucose-PET/computed tomography imaging

Brain 18F-fluorodeoxyglucose (18F-FDG) PET allows the in vivo study of cerebral glucose metabolism, reflecting neuronal and synaptic activity. 18F-FDG-PET has been extensively used to detect metabolic alterations in several neurologic diseases compared with normal aging. However, healthy subjects have variants of 18F-FDG distribution, especially as associated with aging. This article focuses on 18F-FDG-PET findings in so-called normal brain aging, and in particular on metabolic differences occurring with aging and as a function of people’s gender. The effect of different substances, medications, and therapy procedures are discussed, as well as common artifacts.

When structure affects function--the need for partial volume effect correction in functional and resting state magnetic resonance imaging studies

Both functional and also more recently resting state magnetic resonance imaging have become established tools to investigate functional brain networks. Most studies use these tools to compare different populations without controlling for potential differences in underlying brain structure which might affect the functional measurements of interest. Here, we adapt a simulation approach combined with evaluation of real resting state magnetic resonance imaging data to investigate the potential impact of partial volume effects on established functional and resting state magnetic resonance imaging analyses. We demonstrate that differences in the underlying structure lead to a significant increase in detected functional differences in both types of analyses. Largest increases in functional differences are observed for highest signal-to-noise ratios and when signal with the lowest amount of partial volume effects is compared to any other partial volume effect constellation. In real data, structural information explains about 25% of within-subject variance observed in degree centrality – an established resting state connectivity measurement. Controlling this measurement for structural information can substantially alter correlational maps obtained in group analyses. Our results question current approaches of evaluating these measurements in diseased population with known structural changes without controlling for potential differences in these measurements.

Glucose hypometabolism is highly localized, but lower cortical thickness and brain atrophy are widespread in cognitively normal older adults

Several studies have suggested that glucose hypometabolism may be present in specific brain regions in cognitively normal older adults and could contribute to the risk of subsequent cognitive decline. However, certain methodological shortcomings, including a lack of partial volume effect (PVE) correction or insufficient cognitive testing, confound the interpretation of most studies on this topic. We combined [(18)F]fluorodeoxyglucose ([(18)F]FDG) positron emission tomography (PET) and magnetic resonance (MR) imaging to quantify cerebral metabolic rate of glucose (CMRg) as well as cortical volume and thickness in 43 anatomically defined brain regions from a group of cognitively normal younger (25 ± 3 yr old; n = 25) and older adults (71 ± 9 yr old; n = 31). After correcting for PVE, we observed 11-17% lower CMRg in three specific brain regions of the older group: the superior frontal cortex, the caudal middle frontal cortex, and the caudate (P ≤ 0.01 false discovery rate-corrected). In the older group, cortical volumes and cortical thickness were 13-33 and 7-18% lower, respectively, in multiple brain regions (P ≤ 0.01 FDR correction). There were no differences in CMRg between individuals who were or were not prescribed antihypertensive medication. There were no significant correlations between CMRg and cognitive performance or metabolic parameters measured in fasting plasma. We conclude that highly localized glucose hypometabolism and widespread cortical thinning and atrophy can be present in older adults who are cognitively normal, as assessed using age-normed neuropsychological testing measures.

Potential Clinical Applications of PET/MR Imaging in Neurodegenerative Diseases

Neurodegenerative disorders such as Alzheimer disease are among today's most alarming health problems in our aging society. The clinical assessment of neurodegenerative disorders benefits from recent innovations in the field of imaging technology. These innovations include emerging tracers for molecular imaging of neurodegenerative pathology and the introduction of novel integrated PET/MR imaging instruments. Because both PET and MR imaging procedures have shown critical value in the diagnostic work-up of neurodegenerative disorders, the combination of both imaging modalities in the form of an integrated PET/MR imaging system may be of value. This combination includes practical methodologic advantages and an improved workflow facilitated by the combined acquisition of dual-modality data. It offers clinical advantages because of the systematic combination of complementary information, potentially allowing the creation of novel integrated imaging biomarkers. The effectiveness of new disease-modifying treatments may depend on the timely initiation of therapy before irreversible neuronal damage in slowly progressive neurodegenerative disorders. Integrated PET/MR imaging may be able to improve such early diagnosis through both structural and functional information.

18F-fluorodeoxyglucose positron emission tomography, aging, and apolipoprotein E genotype in cognitively normal persons

Our objective was to examine associations between glucose metabolism, as measured by (18)F-fluorodeoxyglucose positron emission tomography (FDG PET), and age and to evaluate the impact of carriage of an apolipoprotein E (APOE) ε4 allele on glucose metabolism and on the associations between glucose metabolism and age. We studied 806 cognitively normal (CN) and 70 amyloid-imaging-positive cognitively impaired participants (35 with mild cognitive impairment and 35 with Alzheimer's disease [AD] dementia) from the Mayo Clinic Study of Aging, Mayo Alzheimer's Disease Research Center and an ancillary study who had undergone structural MRI, FDG PET, and (11)C-Pittsburgh compound B (PiB) PET. Using partial volume corrected and uncorrected FDG PET glucose uptake ratios, we evaluated associations of regional FDG ratios with age and carriage of an APOE ε4 allele in CN participants between the ages of 30 and 95 years, and compared those findings with the cognitively impaired participants. In region-of-interest (ROI) analyses, we found modest but statistically significant declines in FDG ratio in most cortical and subcortical regions as a function of age. We also found a main effect of APOE ε4 genotype on FDG ratio, with greater uptake in ε4 noncarriers compared with carriers but only in the posterior cingulate and/or precuneus, lateral parietal, and AD-signature meta-ROI. The latter consisted of voxels from posterior cingulate and/or precuneus, lateral parietal, and inferior temporal. In age- and sex-matched CN participants the magnitude of the difference in partial volume corrected FDG ratio in the AD-signature meta-ROI for APOE ε4 carriers compared with noncarriers was about 4 times smaller than the magnitude of the difference between age- and sex-matched elderly APOE ε4 carrier CN compared with AD dementia participants. In an analysis in participants older than 70 years (31.3% of whom had elevated PiB), there was no interaction between PiB status and APOE ε4 genotype with respect to glucose metabolism. Glucose metabolism declines with age in many brain regions. Carriage of an APOE ε4 allele was associated with reductions in FDG ratio in the posterior cingulate and/or precuneus, lateral parietal, and AD-signature ROIs, and there was no interaction between age and APOE ε4 status. The posterior cingulate and/or precuneus and lateral parietal regions have a unique vulnerability to reductions in glucose metabolic rate as a function both of age and carriage of an APOE ε4 allele.

Characterizing the normative profile of 18F-FDG PET brain imaging: sex difference, aging effect, and cognitive reserve

The aim of this study was to investigate findings of positron emission tomography with 18F-fluorodeoxyglucose (18F-FDG PET) in normal subjects to clarify the effects of sex differences, aging, and cognitive reserve on cerebral glucose metabolism. Participants comprised 123 normal adults who underwent 18F-FDG PET and a neuropsychological battery. We used statistical parametric mapping (SPM8) to investigate sex differences, and aging effects. The effects of cognitive reserve on 18F-FDG uptake were investigated using years of education as a proxy. Finally, we studied the effect of cognitive reserve on the recruitment of glucose metabolism in a memory task by dichotomizing the data according to educational level. Our results showed that the overall cerebral glucose metabolism in females was higher than that in males, whereas male participants had higher glucose metabolism in the bilateral inferior temporal gyri and cerebellum than females. Age-related hypometabolism was found in anterior regions, including the anterior cingulate gyrus. These areas are part of the attentional system, which may decline with aging even in healthy elderly individuals. Highly educated subjects revealed focal hypermetabolism in the right hemisphere and lower recruitment of glucose metabolism in memory tasks. This phenomenon is likely a candidate for a neural substrate of cognitive reserve.

Cortical surface-based analysis reduces bias and variance in kinetic modeling of brain PET data

Exploratory (i.e., voxelwise) spatial methods are commonly used in neuroimaging to identify areas that show an effect when a region-of-interest (ROI) analysis cannot be performed because no strong a priori anatomical hypothesis exists. However, noise at a single voxel is much higher than noise in a ROI making noise management critical to successful exploratory analysis. This work explores how preprocessing choices affect the bias and variability of voxelwise kinetic modeling analysis of brain positron emission tomography (PET) data. These choices include the use of volume- or cortical surface-based smoothing, level of smoothing, use of voxelwise partial volume correction (PVC), and PVC masking threshold. PVC was implemented using the Muller-Gartner method with the masking out of voxels with low gray matter (GM) partial volume fraction. Dynamic PET scans of an antagonist serotonin-4 receptor radioligand ([(11)C]SB207145) were collected on sixteen healthy subjects using a Siemens HRRT PET scanner. Kinetic modeling was used to compute maps of non-displaceable binding potential (BPND) after preprocessing. The results showed a complicated interaction between smoothing, PVC, and masking on BPND estimates. Volume-based smoothing resulted in large bias and intersubject variance because it smears signal across tissue types. In some cases, PVC with volume smoothing paradoxically caused the estimated BPND to be less than when no PVC was used at all. When applied in the absence of PVC, cortical surface-based smoothing resulted in dramatically less bias and the least variance of the methods tested for smoothing levels 5mm and higher. When used in combination with PVC, surface-based smoothing minimized the bias without significantly increasing the variance. Surface-based smoothing resulted in 2-4 times less intersubject variance than when volume smoothing was used. This translates into more than 4 times fewer subjects needed in a group analysis to achieve similarly powered statistical tests. Surface-based smoothing has less bias and variance because it respects cortical geometry by smoothing the PET data only along the cortical ribbon and so does not contaminate the GM signal with that of white matter and cerebrospinal fluid. The use of surface-based analysis in PET should result in substantial improvements in the reliability and detectability of effects in exploratory PET analysis, with or without PVC.

Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease

The failure of current strategies to provide an explanation for controversial findings on the pattern of pathophysiological changes in Alzheimer's Disease (AD) motivates the necessity to develop new integrative approaches based on multi-modal neuroimaging data that captures various aspects of disease pathology. Previous studies using [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and structural magnetic resonance imaging (sMRI) report controversial results about time-line, spatial extent and magnitude of glucose hypometabolism and atrophy in AD that depend on clinical and demographic characteristics of the studied populations. Here, we provide and validate at a group level a generative anatomical model of glucose hypo-metabolism and atrophy progression in AD based on FDG-PET and sMRI data of 80 patients and 79 healthy controls to describe expected age and symptom severity related changes in AD relative to a baseline provided by healthy aging. We demonstrate a high level of anatomical accuracy for both modalities yielding strongly age- and symptom-severity- dependant glucose hypometabolism in temporal, parietal and precuneal regions and a more extensive network of atrophy in hippocampal, temporal, parietal, occipital and posterior caudate regions. The model suggests greater and more consistent changes in FDG-PET compared to sMRI at earlier and the inversion of this pattern at more advanced AD stages. Our model describes, integrates and predicts characteristic patterns of AD related pathology, uncontaminated by normal age effects, derived from multi-modal data. It further provides an integrative explanation for findings suggesting a dissociation between early- and late-onset AD. The generative model offers a basis for further development of individualized biomarkers allowing accurate early diagnosis and treatment evaluation.

Introduction to the analysis of PET data in oncology

Several reviews on specific topics related to positron emission tomography (PET) ranging in complexity from introductory to highly technical have already been published. This introduction to the analysis of PET data was written as a simple guide of the different phases of analysis of a given PET dataset, from acquisition to preprocessing, to the final data analysis. Although sometimes issues specific to PET in neuroimaging will be mentioned for comparison, most of the examples and applications provided will refer to oncology. Due to the limitations of space we couldn't address each issue comprehensively but, rather, we provided a general overview of each topic together with the references that the interested reader should consult. We will assume a familiarity with the basic principles of PET imaging.

The relationship between cerebral glucose metabolism and age: report of a large brain PET data set

Cerebral glucose metabolism is a reliable index of neural activity and may provide evidence for brain function in healthy adults. We studied the correlation between cerebral glucose metabolism and age under the resting-state in both sexes with position emission tomography. Statistical test of age effect on cerebral glucose metabolism was performed using the statistical parametric mapping software with a voxel-by-voxel approach (p=0.05 family wise error corrected, 100-voxel threshold). The subjects consisted of 108 females (mean ± S.D. = 45 ± 10 years) and 126 males (mean ± S.D. = 49 ± 11 years). We showed here that brain activity in the frontal and temporal lobes in both sexes decreased significantly with normal aging. The glucose metabolism in the caudate bilaterally showed a negative correlation with age in males, but not in females. Few regions in males were shown with an increased glucose metabolism with age. Although the mechanisms of brain aging are still unknown, a map of brain areas susceptible to age was described in this report.

The ketogenic diet increases brain glucose and ketone uptake in aged rats: a dual tracer PET and volumetric MRI study

Despite decades of study, it is still unclear whether regional brain glucose uptake is lower in the cognitively healthy elderly. Whether regional brain uptake of ketones (β-hydroxybutyrate and acetoacetate [AcAc]), the main alternative brain fuel to glucose, changes with age is unknown. We used a sequential, dual tracer positron emission tomography (PET) protocol to quantify brain (18)F-fluorodeoxyglucose ((18)F-FDG) and (11)C-AcAc uptake in two studies with healthy, male Sprague-Dawley rats: (i) Aged (21 months; 21M) versus young (4 months; 4M) rats, and (ii) The effect of a 14 day high-fat ketogenic diet (KD) on brain (18)F-FDG and (11)C-AcAc uptake in 24 month old rats (24M). Similar whole brain volumes assessed by magnetic resonance imaging, were observed in aged 21M versus 4M rats, but the lateral ventricles were 30% larger in the 21M rats (p=0.001). Whole brain cerebral metabolic rates of AcAc (CMR(AcAc)) and glucose (CMR(glc)) did not differ between 21M and 4M rats, but were 28% and 44% higher, respectively, in 24M-KD compared to 24M rats. The region-to-whole brain ratio of CMR(glc) was 37-41% lower in the cortex and 40-45% lower in the cerebellum compared to CMR(AcAc) in 4M and 21M rats. We conclude that a quantitative measure of uptake of the brain's two principal exogenous fuels was generally similar in healthy aged and young rats, that the % of distribution across brain regions differed between ketones and glucose, and that brain uptake of both fuels was stimulated by mild, experimental ketonemia.

Theory of Mind in normal ageing and neurodegenerative pathologies

This paper reviews findings in three subcomponents of social cognition (i.e., Theory of Mind, facial emotion recognition, empathy) during ageing. Changes over time in social cognition were evaluated in normal ageing and in patients with various neurodegenerative pathologies, such as Alzheimer's disease, mild cognitive impairment, frontal and temporal variants of frontotemporal lobar degeneration and Parkinson's disease. Findings suggest a decline in social cognition with normal ageing, a decline that is at least partially independent of a more general cognitive or executive decline. The investigation of neurodegenerative pathologies showing specific deficits in Theory of Mind in relation to damage to specific cerebral regions led us to suggest a neural network involved in Theory of Mind processes, namely a fronto-subcortical loop linking the basal ganglia to the regions of the frontal lobes.

Usefulness of extent analysis for statistical parametric mapping with asymmetry index using inter-ictal FGD-PET in mesial temporal lobe epilepsy

OBJECTIVE

Inter-ictal (18)F-2-fluoro-deoxy-D: -glucose-positron emission tomography (FDG-PET) is widely used for preoperative evaluation to identify epileptogenic zones in patients with temporal lobe epilepsy. In this study, we combined statistical parametric mapping (SPM) with the asymmetry index and volume-of-interest (VOI) based extent analysis employing preoperative FDG-PET in unilateral mesial temporal lobe epilepsy (MTLE) patients. We also evaluated the detection utility of these techniques for automated identification of abnormalities in the unilateral hippocampal area later confirmed to be epileptogenic zones by surgical treatment and subsequent good seizure control.

METHODS

FDG-PET scans of 17 patients (9 males, mean age 35 years, age range 16-60 years) were retrospectively analyzed. All patients had been preoperatively diagnosed with unilateral MTLE. The surgical outcomes of all patients were Engel class 1A or 1B with postoperative follow-up of 2 years. FDG-PET images were spatially normalized and smoothed. After two voxel-value adjustments, one employing the asymmetry index and the other global normalization, had been applied to the images separately, voxel-based statistical comparisons were performed with 20 controls. Peak analysis and extent analysis in the VOI in the parahippocampal gyrus were conducted for SPM. For the extent analysis, a receiver operating characteristic (ROC) curve was devised to calculate the area under the curve and to determine the optimal threshold of extent.

RESULTS

The accuracy of the method employing the asymmetry index was better than that of the global normalization method for both the peak and the extent analysis. The ROC analysis results, for the extent analysis, yielded an area under the curve of 0.971, such that the accuracy and optimal extent threshold of judgment were 92 and 32.9%, respectively.

CONCLUSION

Statistical z-score mapping with the asymmetry index was more sensitive for detecting regional glucose hypometabolism and more accurate for identifying the side harboring the epileptogenic zone using inter-ictal FDG-PET in unilateral MTLE than z-score mapping with global normalization. Moreover, the automated determination of the side with the epileptogenic zone in unilateral MTLE showed improved accuracy when the combination of SPM with the asymmetry index and extent analysis was applied based on the VOI in the parahippocampal gyrus.

Brain and systemic glucose metabolism in the healthy elderly following fish oil supplementation

Cerebral metabolic rate of glucose (CMRg) is lower in individuals affected by cognitive decline and dementia, especially in Alzheimer's disease. However, as yet there is no consensus as to whether CMRg decreases during healthy aging. Epidemiological studies show that weekly consumption of fish abundant in ω3 fatty acids has a protective effect on cognition during aging. Thus, the primary objective of this human study was to use positron emission tomography analysis with (18)F-fluorodeoxyglucose to evaluate whether supplementation with a fish oil rich in ω3 fatty acids increases cerebral glucose metabolism in young or elderly adults. Healthy young (23±5y old; n=5) and elderly (76±3y old; n=6) women and men were included in the study. Semi-quantitative expression of the data as 'standardized uptake values' showed that elderly participants had significantly lower cerebral glucose metabolism compared with the young group. However, when expressed quantitatively a CMRg, there was no effect of age or ω3 supplementation on glucose metabolism in any of the brains regions studied. Higher plasma triglyceride levels and higher plasma insulin levels were associated with lower CMRg in several regions, suggesting that a trend towards the metabolic syndrome may be associated with cerebral hypometabolism. We conclude that under these experimental conditions, ω3 supplementation did not affect brain glucose metabolism in the healthy elderly. Future studies in this area should address whether glucose intolerance or other conditions linked to the metabolic syndrome impact negatively on brain glucose metabolism and cognition.

Effects of brain amyloid deposition and reduced glucose metabolism on the default mode of brain function in normal aging

Brain β-amyloid (Aβ) deposition during normal aging is highlighted as an initial pathogenetic event in the development of Alzheimer's disease. Many recent brain imaging studies have focused on areas deactivated during cognitive tasks [the default mode network (DMN), i.e., medial frontal gyrus/anterior cingulate cortex and precuneus/posterior cingulate cortex], where the strength of functional coordination was more or less affected by cerebral Aβ deposits. In the present positron emission tomography study, to investigate whether regional glucose metabolic alterations and Aβ deposits seen in nondemented elderly human subjects (n = 22) are of pathophysiological importance in changes of brain hemodynamic coordination in DMN during normal aging, we measured cerebral glucose metabolism with [(18)F]FDG, Aβ deposits with [(11)C]PIB, and regional cerebral blood flow during control and working memory tasks by H(2)(15)O on the same day. Data were analyzed using both region of interest and statistical parametric mapping. Our results indicated that the amount of Aβ deposits was negatively correlated with hemodynamic similarity between medial frontal and medial posterior regions, and the lower similarity was associated with poorer working memory performance. In contrast, brain glucose metabolism was not related to this medial hemodynamic similarity. These findings suggest that traceable Aβ deposition, but not glucose hypometabolism, in the brain plays an important role in occurrence of neuronal discoordination in DMN along with poor working memory in healthy elderly people.