Multicenter standardized 18F-FDG PET diagnosis of mild cognitive impairment, Alzheimer's disease, and other dementias

PET/CT in diagnosis of dementia

Clinical use of positron emission tomography (PET) is now well established in neurodegenerative disorders, especially in the diagnosis of dementia. Measurement of cerebral glucose metabolism is of significant value, and it facilitates early diagnosis, appropriate differential diagnosis, and the evaluation of drug treatment in patients with dementia. In addition, tracers offer new perspectives for studying the neuropathology of underlying dementia, such as the accumulation of amyloid proteins, tau-proteins, or the presence of neuroinflammation. Finally, PET tracer studies of different neurotransmitter systems in dementia may not only increase the understanding of pathophysiologic mechanisms of the different disorders, but also improve diagnostic accuracy. In conclusion, PET imaging with different tracers offers reliable biomarkers in dementia, which can assist clinicians in the diagnosis of different dementing disorders, especially in the situation of overlapping phenotypes.

The role of dopaminergic imaging in patients with symptoms of dopaminergic system neurodegeneration

Diagnosis of neurological and psychiatric conditions associated with disturbances of dopaminergic functioning can be challenging, especially in the early stages, and may be assisted with biomarkers such as dopamine system imaging. Distinguishing between Alzheimer's disease and dementia with Lewy bodies is a major diagnostic challenge. Clinical diagnosis of Parkinson's disease is straightforward with classic presentation, but accurate distinction among Parkinsonian variants may be difficult; non-Parkinson's disease conditions are commonly misdiagnosed as Parkinson's disease, and ~20% of patients with Parkinson's disease are not clinically diagnosed despite coming to medical attention. Early and accurate diagnosis is desirable to improve management. Imaging of the dopamine transporter using single-photon emission computed tomography may be of particular utility in this regard. Abnormal imaging indicates underlying nigrostriatal neurodegeneration, supportive of a diagnosis of Parkinson's disease, atypical parkinsonism or dementia with Lewy bodies, and identifies patient groups in whom dopaminergic therapy may be beneficial. Normal imaging supports diagnosis of a condition not involving nigrostriatal neurodegeneration such as Alzheimer's disease, essential tremor or drug-induced parkinsonism and hence a different therapeutic approach. In patients in whom there was diagnostic uncertainty between degenerative parkinsonism and non-degenerative tremor disorders, baseline imaging with the dopamine transporter ligand [(123)I]ioflupane (DaTscan™) has shown 78% sensitivity and 97% specificity with reference to clinical diagnosis at 3 years, versus 93% and 46%, respectively, for baseline clinical diagnosis. In a Phase III trial of [(123)I]ioflupane in patients with initial clinical diagnosis of probable or possible dementia with Lewy bodies or non-Lewy body dementia, mean specificity for excluding non-Lewy body dementia (predominantly Alzheimer's disease) was 90.4%. Using clinical diagnosis as a reference against which to assess sensitivity and specificity of dopamine transporter imaging is a limitation, but definitive diagnosis via pathological confirmation is generally not feasible. In a series of patients with post-mortem brain examination, imaging using [(123)I]ioflupane has demonstrated higher sensitivity (88%) and specificity (100%) for differentiating dementia with Lewy bodies from non-Lewy body dementia than clinical diagnosis (75% and 42%, respectively). Dopaminergic system imaging may be particularly valuable in patients with clinically inconclusive parkinsonism or a clinical diagnosis of possible dementia with Lewy bodies; it is not helpful in differentiating between Parkinson's disease and atypical parkinsonism, although postsynaptic dopaminergic imaging may be of utility. Other potential uses of dopamine transporter imaging include identification of patients with premotor Parkinson's disease, monitoring disease progression in testing novel therapeutics, and as an inclusion criterion for entry into clinical trials.

Noninvasive brain stimulation in Alzheimer's disease: systematic review and perspectives for the future

BACKGROUND

A number of studies have applied transcranial magnetic stimulation (TMS) to physiologically characterize Alzheimer's disease (AD) and to monitor effects of pharmacological agents, while others have begun to therapeutically use TMS and transcranial direct current stimulation (tDCS) to improve cognitive function in AD. These applications are still very early in development, but offer the opportunity of learning from them for future development.

METHODS

We performed a systematic search of all studies using noninvasive stimulation in AD and reviewed all 29 identified articles. Twenty-four focused on measures of motor cortical reactivity and (local) plasticity and functional connectivity, with eight of these studies assessing also effects of pharmacological agents. Five studies focused on the enhancement of cognitive function in AD.

RESULTS

Short-latency afferent inhibition (SAI) and resting motor threshold are significantly reduced in AD patients as compared to healthy elders. Results on other measures of cortical reactivity, e.g. intracortical inhibition (ICI), are more divergent. Acetylcholine-esterase inhibitors and dopaminergic drugs may increase SAI and ICI in AD. Motor cortical plasticity and connectivity are impaired in AD. TMS/tDCS can induce acute and short-duration beneficial effects on cognitive function, but the therapeutic clinical significance in AD is unclear. Safety of TMS/tDCS is supported by studies to date.

CONCLUSIONS

TMS/tDCS appears safe in AD, but longer-term risks have been insufficiently considered. TMS holds promise as a physiologic biomarker in AD to identify therapeutic targets and monitor pharmacologic effects. In addition, TMS/tDCS may have therapeutic utility in AD, though the evidence is still very preliminary and cautious interpretation is warranted.

An overview of biomarkers in Alzheimer's disease

Alzheimer’s disease (AD) is the commonest progressive, dementing neurodegenerative disease in elderly, which affects innumerable people each year, and these numbers are likely to further increase as the population ages. In addition to the financial burden of AD on health care system, the disease has powerful emotional impact on caregivers and families of those afflicted. In this advancing era of AD research, with the availability of new treatment strategies having disease-modifying effects, there is growing need for the early diagnosis in AD, often hampered by paucity of biomarkers of AD. Various candidate biomarkers for AD have been developed that can detect patients with AD at an early stage. In the recent years, the search for an ideal biomarker has undergone a rapid evolution. Novel technologies in proteomics, genomics, and imaging techniques further expand the role of a biomarker not only in early diagnosis, but also in monitoring the response to various treatments. However, the availability of sensitive and specific biomarkers requires the method to be standardized so as to be able to compare the results across studies. Inspite of tremendous advances in this field the quest for an “ideal biomarker” still continues. In this review, we will discuss the various candidate markers in five spheres namely biochemical, neuroanatomical, metabolic, genetic and neuropsychological, and their current status and limitations in AD diagnosis.

EANM procedure guidelines for PET brain imaging using [18F]FDG, version 2

These guidelines summarize the current views of the European Association of Nuclear Medicine Neuroimaging Committee (ENC). The purpose of the guidelines is to assist nuclear medicine practitioners in making recommendations, performing, interpreting, and reporting the results of fluorine-18 fluoro-2-deoxyglucose ([(18)F]FDG) PET imaging of the brain. The aim is to help achieve a high standard of FDG imaging, which will increase the diagnostic impact of this technique in neurological and psychiatric practice. The present document replaces a former version of the guidelines that were published in 2002 [1] and includes an update in the light of advances in PET technology, the introduction of hybrid PET/CT systems and the broadening clinical indications for FDG brain imaging. These guidelines are intended to present information specifically adapted for European practice. The information provided should be taken in the context of local conditions and regulations.

FDG- and amyloid-PET in Alzheimer's disease: is the whole greater than the sum of the parts?

The development of prevention therapies for Alzheimer's disease (AD) would greatly benefit from biomarkers that are sensitive to subtle brain changes occurring prior to the onset of clinical symptoms, when the potential for preservation of function is at the greatest. In vivo brain imaging is a promising tool for the early detection of AD through visualization of abnormalities in brain structure, function and histopathology. Currently, positron emission tomography (PET) imaging with amyloid-beta (Aβ) tracers and 2-[(18)F]fluoro-2-Deoxy-D-glucose (FDG) is largely utilized in the diagnosis of AD. This paper reviews brain Aβ- and FDG-PET studies in AD patients as well as in non-demented individuals at risk for AD. We then discuss the potential of combining symptoms-sensitive FDG-PET measures with pathology-specific Aβ-PET to improve the early detection of AD.

Brain functional network in Alzheimer's disease: diagnostic markers for diagnosis and monitoring

Alzheimer's disease (AD) is the most common type of dementia that is clinically characterized by the presence of memory impairment and later by impairment in other cognitive domains. The clinical diagnosis is based on interviews with the patient and his/her relatives and on neuropsychological assessment, which are also used to monitor cognitive decline over time. Several biomarkers have been proposed for detecting AD in its earliest stages, that is, in the predementia stage. In an attempt to find noninvasive biomarkers, researchers have investigated the feasibility of neuroimaging tools, such as MR, SPECT, and FDG-PET imaging, as well as neurophysiological measurements using EEG. In this paper, we investigate the brain functional networks in AD, focusing on main neurophysiological techniques, integrating with most relevant functional brain imaging findings.

Should mild cognitive impairment be subtyped?

PURPOSE OF REVIEW

To review evidence on the validity and utility of recent approaches to subtyping late-life mild cognitive impairment.

RECENT FINDINGS

There is growing evidence that amnestic mild cognitive impairment is associated with biomarkers for Alzheimer's disease, while nonamnestic mild cognitive impairment maps more closely to cerebrovascular disease. The former is more likely to progress to dementia than the latter. Mild impairment in multiple cognitive domains appears to represent a more advanced disease state than single-domain impairment, and is more likely to progress to dementia. The cognitive subtypes have imprecise boundaries and have limited ecological validity. Approaches to subtyping that also incorporate biomarkers increase diagnostic specificity and have greater predictive value. However, these approaches have yet to be validated outside specialized memory clinic populations.

SUMMARY

Mild cognitive impairment as currently defined is still etiologically and prognostically heterogeneous, particularly outside specialty clinical settings. The objective of further subtyping is to delineate subgroups that are more clinically homogeneous. The current cognitive subtypes have some validity and utility but additional approaches should be explored so as to enhance these properties.

Maternal age affects brain metabolism in adult children of mothers affected by Alzheimer's disease

Cognitively normal (NL) individuals with a maternal history of late-onset Alzheimer's disease (MH) show reduced brain glucose metabolism on FDG-PET as compared to those with a paternal history (PH) and those with negative family history (NH) of Alzheimer's disease (AD). This FDG-PET study investigates whether metabolic deficits in NL MH are associated with advancing maternal age at birth. Ninety-six NL individuals with FDG-PET were examined, including 36 MH, 24 PH, and 36 NH. Regional-to-whole brain gray matter standardized FDG uptake value ratios were examined for associations with parental age across groups using automated regions-of-interest and statistical parametric mapping. Groups were comparable for clinical and neuropsychological measures. Brain metabolism in AD-vulnerable regions was lower in MH compared to NH and PH, and negatively correlated with maternal age at birth only in MH. There were no associations between paternal age and metabolism in any group. Evidence for a maternally inherited, maternal age-related mechanism provides further insight on risk factors and genetic transmission in late-onset AD.

Typical cerebral metabolic patterns in neurodegenerative brain diseases

The differential diagnosis of neurodegenerative brain diseases on clinical grounds is difficult, especially at an early disease stage. Several studies have found specific regional differences of brain metabolism applying [(18)F]-fluoro-deoxyglucose positron emission tomography (FDG-PET), suggesting that this method can assist in early differential diagnosis of neurodegenerative brain diseases.We have studied patients who had an FDG-PET scan on clinical grounds at an early disease stage and included those with a retrospectively confirmed diagnosis according to strictly defined clinical research criteria. Ninety-six patients could be included of which 20 patients with Parkinson's disease (PD), 21 multiple system atrophy (MSA), 17 progressive supranuclear palsy (PSP), 10 corticobasal degeneration (CBD), 6 dementia with Lewy bodies (DLB), 15 Alzheimer's disease (AD), and 7 frontotemporal dementia (FTD). FDG PET images of each patient group were analyzed and compared to18 healthy controls using Statistical Parametric Mapping (SPM5).Disease-specific patterns of relatively decreased metabolic activity were found in PD (contralateral parietooccipital and frontal regions), MSA (bilateral putamen and cerebellar hemispheres), PSP (prefrontal cortex and caudate nucleus, thalamus, and mesencephalon), CBD (contralateral cortical regions), DLB (occipital and parietotemporal regions), AD (parietotemporal regions), and FTD (frontotemporal regions).The integrated method addressing a spectrum of various neurodegenerative brain diseases provided means to discriminate patient groups also at early disease stages. Clinical follow-up enabled appropriate patient inclusion. This implies that an early diagnosis in individual patients can be made by comparing each subject's metabolic findings with a complete database of specific disease related patterns.

Application of silicon photomultipliers to positron emission tomography

Historically, positron emission tomography (PET) systems have been based on scintillation crystals coupled to photomultipliers tubes (PMTs). However, the limited quantum efficiency, bulkiness, and relatively high cost per unit surface area of PMTs, along with the growth of new applications for PET, offers opportunities for other photodetectors. Among these, small-animal scanners, hybrid PET/MRI systems, and incorporation of time-of-flight information are of particular interest and require low-cost, compact, fast, and magnetic field compatible photodetectors. With high quantum efficiency and compact structure, avalanche photodiodes (APDs) overcome several of the drawbacks of PMTs, but this is offset by degraded signal-to-noise and timing properties. Silicon photomultipliers (SiPMs) offer an alternative solution, combining many of the advantages of PMTs and APDs. They have high gain, excellent timing properties and are insensitive to magnetic fields. At the present time, SiPM technology is rapidly developing and therefore an investigation into optimal design and operating conditions is underway together with detailed characterization of SiPM-based PET detectors. Published data are extremely promising and show good energy and timing resolution, as well as the ability to decode small scintillator arrays. SiPMs clearly have the potential to be the photodetector of choice for some, or even perhaps most, PET systems.

Application of silicon photomultipliers to positron emission tomography

Historically, positron emission tomography (PET) systems have been based on scintillation crystals coupled to photomultipliers tubes (PMTs). However, the limited quantum efficiency, bulkiness, and relatively high cost per unit surface area of PMTs, along with the growth of new applications for PET, offers opportunities for other photodetectors. Among these, small-animal scanners, hybrid PET/MRI systems, and incorporation of time-of-flight information are of particular interest and require low-cost, compact, fast, and magnetic field compatible photodetectors. With high quantum efficiency and compact structure, avalanche photodiodes (APDs) overcome several of the drawbacks of PMTs, but this is offset by degraded signal-to-noise and timing properties. Silicon photomultipliers (SiPMs) offer an alternative solution, combining many of the advantages of PMTs and APDs. They have high gain, excellent timing properties and are insensitive to magnetic fields. At the present time, SiPM technology is rapidly developing and therefore an investigation into optimal design and operating conditions is underway together with detailed characterization of SiPM-based PET detectors. Published data are extremely promising and show good energy and timing resolution, as well as the ability to decode small scintillator arrays. SiPMs clearly have the potential to be the photodetector of choice for some, or even perhaps most, PET systems.

Feature selection using factor analysis for Alzheimer's diagnosis using 18F-FDG PET images

PURPOSE

This article presents a computer-aided diagnosis technique for improving the accuracy of the early diagnosis of Alzheimer's disease (AD). Two hundred and ten 18F-FDG PET images from the ADNI initiative [52 normal controls (NC), 114 mild cognitive impairment (MCI), and 53 AD subjects] are studied.

METHODS

The proposed methodology is based on the selection of voxels of interest using the t-test and a posterior reduction of the feature dimension using factor analysis. Factor loadings are used as features for three different classifiers: Two multivariate Gaussian mixture model, with linear and quadratic discriminant function, and a support vector machine with linear kernel.

RESULTS

An accuracy rate up to 95% when NC and AD are considered and an accuracy rate up to 88% and 86% for NC-MCI and NC-MCI,AD, respectively, are obtained using SVM with linear kernel.

CONCLUSIONS

Results are compared to the voxel-as-features and a PCA- based approach and the proposed methodology achieves better classification performance.

Diagnosis and biomarkers of predementia in Alzheimer's disease

In view of the growing prevalence of Alzheimer's disease (AD) worldwide, there is an urgent need for the development of better diagnostic tools and more effective therapeutic interventions. At the earliest stages of AD, no significant cognitive or functional impairment is detected by conventional clinical methods. However, new technologies based on structural and functional neuroimaging, and on the biochemical analysis of cerebrospinal fluid (CSF) may reveal correlates of intracerebral pathology in individuals with mild, predementia symptoms. These putative correlates are commonly referred to as AD-related biomarkers. The relevance of the early diagnosis of AD relies on the hypothesis that pharmacological interventions with disease-modifying compounds are likely to produce clinically relevant benefits if started early enough in the continuum towards dementia. Here we review the clinical characteristics of the prodromal and transitional states from normal cognitive ageing to dementia in AD. We further address recent developments in biomarker research to support the early diagnosis and prediction of dementia, and point out the challenges and perspectives for the translation of research data into clinical practice.

(99m)Tc hexamethyl-propylene-aminoxime single-photon emission computed tomography prediction of conversion from mild cognitive impairment to Alzheimer disease

OBJECTIVE

To examine the utility of single-photon emission computed tomography (SPECT) to predict conversion from mild cognitive impairment (MCI) to Alzheimer disease (AD).

DESIGN

Longitudinal, prospective study.

SETTING

University-based memory disorders clinic.

PARTICIPANTS

One hundred twenty seven patients with MCI and 59 healthy comparison subjects followed up for 1-9 years.

MEASUREMENTS

Diagnostic evaluation, neuropsychological tests, social/cognitive function, olfactory identification, apolipoprotein E genotype, magnetic resonance imaging, and brain Tc hexamethyl-propylene-aminoxime SPECT scan with visual ratings, and region of interest (ROI) analyses were done.

RESULTS

Visual ratings of SPECT temporal and parietal blood flow did not distinguish eventual MCI converters to AD (N = 31) from nonconverters (N = 96), but the global rating predicted conversion (41.9% sensitivity and 82.3% specificity, Fisher's exact test p = 0.013). Blood flow in each ROI was not predictive, but when dichotomized at the median value of the patients with MCI, low flow increased the hazard of conversion to AD for parietal (hazard ratio: 2.96, 95% confidence interval: 1.16-7.53, p = 0.023) and medial temporal regions (hazard ratio: 3.12, 95% confidence interval: 1.14-8.56, p = 0.027). In the 3-year follow-up sample, low parietal (p <0.05) and medial temporal (p <0.01) flow predicted conversion to AD, with or without controlling for age, Mini-Mental State Examination, and apolipoprotein E ε4 genotype. These measures lost significance when other strong predictors were included in logistic regression analyses: verbal memory, social/cognitive functioning, olfactory identification deficits, hippocampal, and entorhinal cortex volumes.

CONCLUSIONS

SPECT visual ratings showed limited utility in predicting MCI conversion to AD. The modest predictive utility of quantified low parietal and medial temporal flow using SPECT may decrease when other stronger predictors are available.

Scaled subprofile modeling of resting state imaging data in Parkinson's disease: methodological issues

Consistent functional brain abnormalities in Parkinson's disease (PD) are difficult to pinpoint because differences from the normal state are often subtle. In this regard, the application of multivariate methods of analysis has been successful but not devoid of misinterpretation and controversy. The Scaled Subprofile Model (SSM), a principal components analysis (PCA)-based spatial covariance method, has yielded critical information regarding the characteristic abnormalities of functional brain organization that underlie PD and other neurodegenerative disorders. However, the relevance of disease-related spatial covariance patterns (metabolic brain networks) and the most effective methods for their derivation has been a subject of debate. We address these issues here and discuss the inherent advantages of proper application as well as the effects of the misapplication of this methodology. We show that ratio pre-normalization using the mean global metabolic rate (GMR) or regional values from a "reference" brain region (e.g. cerebellum) that may be required in univariate analytical approaches is obviated in SSM. We discuss deviations of the methodology that may yield erroneous or confounding factors.

Target-specific PET probes for neurodegenerative disorders related to dementia

Dementia is a highly prevalent problem causing considerable disability and mortality and exacting great costs to individuals, their families, and society. The 4 most common neurodegenerative disorders that cause dementia-Alzheimer disease, frontotemporal dementia, dementia with Lewy bodies, and dementia in Parkinson disease-have different underlying etiologies and pathogenetic mechanisms. There is a great need for early diagnostic markers; functional brain imaging may therefore assist in the detection and differential diagnosis of dementia due to neurodegenerative diseases. Functional imaging such as PET allows in vivo imaging of functional brain activity indicating cerebral blood flow and cerebral glucose metabolism, and PET allows imaging of neurotransmitter activity, including that of the cholinergic, dopaminergic, and serotonergic systems. New PET neuroimaging tracers are being developed for detecting pathologic parameters such as amyloid plaque and microglial activity. The development of molecular imaging is important for early diagnosis of dementia, selection of patients for therapies, and evaluation of therapies.

Education attenuates the effect of medial temporal lobe atrophy on cognitive function in Alzheimer's disease: the MIRAGE study

Functional imaging and neuropathological studies suggest that individuals with higher education have better cognitive performance at the same level of brain pathology than less educated subjects. No in vivo studies are available that directly test how education modifies the effect of structural pathology on cognition in Alzheimer's disease (AD). The present study therefore aimed to measure this effect using data from a large multi-center study. 270 patients with AD underwent cognitive testing using the Mini Mental State Examination (MMSE), apolipoprotein E (APOE) genotyping, and cerebral magnetic resonance imaging. A linear regression analysis was used to examine the relation of medial temporal lobe atrophy (MTA), as a proxy of AD pathology, to MMSE score, adjusting for age, gender, APOE, cerebrovascular disease, ethnicity, education, and disease duration. An interaction term for MTA and education was introduced to test the hypothesis that education modifies the effect of MTA on cognition. There was a significant inverse association between MTA and cognition. Most interestingly, the interaction term between education and MTA was significant suggesting that education modifies the relation of MTA to cognition. At any level of pathology, cognition remained higher for better educated individuals.

Early Detection of Brain Pathology Suggestive of Early AD Using Objective Evaluation of FDG-PET Scans

The need for early detection of AD becomes critical as disease-modifying agents near the marketplace. Here, we present results from a study focused on improvement in detection of metabolic deficits related to neurodegenerative changes consistent with possible early AD with statistical evaluation of FDG-PET brain images. We followed 31 subjects at high risk or diagnosed with MCI/AD for 3 years. 15 met criteria for diagnosis of MCI, and five met criteria for AD. FDG-PET scans were completed at initiation and termination of the study. PET scans were read clinically and also evaluated objectively using Statistical Parametric Mapping (SPM). Using standard clinical evaluation of the FDG-PET scans, 11 subjects were detected, while 18 were detected using SPM evaluation. These preliminary results indicate that objective analyses may improve detection; however, early detection in at-risk normal subjects remains tentative. Several FDA-approved software packages are available that use objective analyses, thus the capacity exists for wider use of this method for MCI/AD.

Pre-clinical detection of Alzheimer's disease using FDG-PET, with or without amyloid imaging

The development of prevention therapies for Alzheimer's disease (AD) would greatly benefit from biomarkers that are sensitive to subtle brain changes occurring in the preclinical stage of the disease. Early diagnostics is necessary to identify and treat at risk individuals before irreversible neuronal loss occurs. In vivo imaging has long been used to evaluate brain structural and functional abnormalities as predictors of future AD in non-demented persons. Prior to development of amyloid-beta (Abeta) tracers for positron emission tomography (PET), the most widely utilized PET tracer in AD was 2-[18F]fluoro-2-Deoxy-D-glucose (FDG) PET. For over 20 years, FDG-PET has been used to measure cerebral metabolic rates of glucose (CMRglc), a proxy for neuronal activity, in AD. Many studies have shown that CMRglc reductions occur early in AD, correlate with disease progression, and predict histopathological diagnosis. This paper reviews reports of clinical and preclinical CMRglc reductions observed in association with genetic and non-genetic risk factors for AD. We then briefly review brain Abeta PET imaging studies in AD and discuss the potential of combining symptoms-sensitive FDG-PET measures with pathology-specific Abeta-PET to improve the early detection of AD.

Pittsburgh compound B (11C-PIB) and fluorodeoxyglucose (18 F-FDG) PET in patients with Alzheimer disease, mild cognitive impairment, and healthy controls

Amyloid load in the brain using Pittsburgh compound B ((11)C-PIB) positron emission tomography (PET) and cerebral glucose metabolism using fluorodeoxyglucose ((18)F-FDG) PET were evaluated in patients with mild Alzheimer disease (AD, n = 18), mild cognitive impairment (MCI, n = 24), and controls (CTR, n = 18). ( 11)C-PIB binding potential (BP(ND)) was higher in prefrontal cortex, cingulate, parietal cortex, and precuneus in AD compared to CTR or MCI and in prefrontal cortex for MCI compared to CTR. For (18)F-FDG, regional cerebral metabolic rate for glucose (rCMRGlu) was decreased in precuneus and parietal cortex in AD compared to CTR and MCI, with no MCI-CTR differences. For the AD-CTR comparison, precuneus BP(ND) area under the receiver operating characteristic (ROC) curve (AUC) was 0.938 and parietal cortex rCMRGlu AUC was 0.915; for the combination, AUC was 0.989. ( 11)C-PIB PET BP(ND) clearly distinguished diagnostic groups and combined with (18)F-FDG PET rCMRGlu, this effect was stronger. These PET techniques provide complementary information in strongly distinguishing diagnostic groups in cross-sectional comparisons that need testing in longitudinal studies.

Diffuse occipital hypometabolism on [18 F]-FDG PET scans in patients with idiopathic REM sleep behavior disorder: prodromal dementia with Lewy bodies?

BACKGROUND

Previous longitudinal studies have revealed that specific patterns on [(18) F]-fluoro-d-glucose (FDG) positron emission tomography (PET) scans in patients with amnesic mild cognitive impairment can predict Alzheimer's disease (AD). However, the significance of particular patterns on [(18) F]-FDG PET scans in prodromal patients with dementia with Lewy bodies (DLB) remains unclear.

METHODS

Based on the prevailing evidence that rapid eye movement (REM) sleep behavior disorder (RBD) often precedes the onset of DLB, [(18) F]-FDG PET scans of nine non-demented patients reporting recurrent nocturnal dream-enactment behavior in our memory clinic were compared with the normative database using three-dimensional stereotactic surface projection (3D-SSP) images. All patients underwent clinical and neuropsychological examinations as well as cardiac [(123) I]-metaiodobenzylguanidine ([(123) I]-MIBG) scintigraphy.

RESULTS

Four patients were found to have diffuse areas of reduced cerebral metabolic rate of glucose (CMRglc), predominantly in the occipital lobe, which is the preferentially affected region in DLB patients. In contrast, five patients showed no such occipital hypometabolism; instead, these five patients showed hypometabolism in the left anterior cingulate gyrus (Broadmann area (BA) 24), right frontal lobe (BA 32) and right anterior temporal lobe (BA 38), which are the preferentially affected regions in Parkinson's disease rather than DLB. The extent of the reduction in CMRglc in the left occipital lobe was correlated with scores on the Bender Gestalt Test, which reflects visuospatial ability, but not with global cognitive measures. All patients showed reduced cardiac [(123) I]-MIBG levels, consistent with underlying Lewy body disease.

CONCLUSION

These variations in [(18) F]-FDG PET scans raise the possibility that the specific pattern of CMRglc reduction may predict developing DLB in patients with idiopathic RBD. Further follow-up studies are needed, particularly on patients with diffuse occipital hypometabolism.

Hypometabolism in Alzheimer-affected brain regions in cognitively healthy Latino individuals carrying the apolipoprotein E epsilon4 allele

OBJECTIVE

To investigate with fluorodeoxyglucose positron emission tomography whether regional reductions in the cerebral metabolic rate for glucose (CMRgl) previously found in cognitively healthy late-middle-aged apolipoprotein E (APOE) epsilon4 carriers extend to members of the Latino Mexican American community.

DESIGN

Prospective cohort study.

SETTING

Banner Alzheimer's Institute, Phoenix, Arizona.

PATIENTS OR OTHER PARTICIPANTS

Eleven APOE epsilon4 carriers and 16 noncarriers from Arizona's Latino community (mean [SD] age, 54.6 [6.4] years) matched for sex, mean age, and educational level and who were predominantly of self-designated Mexican origin.

MAIN OUTCOME MEASURE

A brain mapping algorithm was used to compare cross-sectional regional CMRgl in Latino APOE epsilon4 carriers vs noncarriers.

RESULTS

Participant groups had similar distributions for age, sex, education, family history of dementia, clinical ratings, and neuropsychological test scores. Latino APOE epsilon4 carriers had lower CMRgl than the noncarriers in the posterior cingulate, precuneus, and parietal regions previously found to be preferentially affected in patients with Alzheimer disease (AD) and cognitively healthy non-Latino APOE epsilon4 carriers. Additionally, the Latino APOE epsilon4 carriers had lower CMRgl in the middle and anterior cingulate cortex, hippocampus, and thalamus.

CONCLUSIONS

This study provides support for the relationship between APOE epsilon4 and risk of AD in Latino individuals. It illustrates the role of positron emission tomography as a presymptomatic endophenotype for the assessment of AD risk factors and supports the inclusion of Latino APOE epsilon4 carriers in proof-of-concept studies using fluorodeoxyglucose PET to evaluate promising presymptomatic treatments in cognitively healthy carriers of this common AD susceptibility gene.

Comparing fludeoxyglucose F18-PET assessment of regional cerebral glucose metabolism and [11C]dihydrotetrabenazine-PET in evaluation of early dementia and mild cognitive impairment

OBJECTIVE

To compare assessment of regional cerebral metabolic changes with [(11)C]dihydrotetrabenazine (DTBZ)-positron emission tomography (PET) measurement of regional cerebral blood flow (K(1)) and fludeoxyglucose F18 (FDG)-PET measurement of regional cerebral glucose uptake (CMR(glc)) in a clinically representative sample of subjects with mild dementia and mild cognitive impairment (MCI).

DESIGN

[(11)C]Dihydrotetrabenazine-PET K(1) and FDG-PET CMR(glc) measurements were performed.

SETTING

University-based cognitive disorders clinic.

PARTICIPANTS

Fifty subjects with either mild dementia (Mini-Mental State Examination score > or = 18) or MCI. Their results were compared with those of 80 normal control subjects.

MAIN OUTCOME MEASURES

The DTBZ-PET regional K(1) and FDG-PET CMR(glc) measurements were compared with standard correlation analysis. The overall patterns of DTBZ-PET K(1) and FDG-PET CMR(glc) deficits were assessed with stereotaxic surface projections (SSPs) of parametric images.

RESULTS

The DTBZ-PET regional K(1) and FDG-PET CMR(glc) measurements were highly correlated, both within and between subjects. The SSP maps of deficits in DTBZ-PET regional K(1) and FDG-PET CMR(glc) measurements were markedly similar. The DTBZ-PET K(1) SSP maps exhibited a mild decrease in sensitivity relative to FDG-PET CMR(glc) maps.

CONCLUSIONS

Both DTBZ-PET K(1) and FDG-PET CMR(glc) measurements provide comparable information in assessment of regional cerebral metabolic deficits in mild dementia and MCI. Blood flow measures can assess regional cerebral metabolism deficits accurately in mild dementia and MCI. Blood flow assessments of regional cerebral metabolic deficits can be combined with tracer binding results to improve utility of PET imaging in mild dementia and MCI.

Diagnostic power of default mode network resting state fMRI in the detection of Alzheimer's disease

Functional magnetic resonance imaging (fMRI) of default mode network (DMN) brain activity during resting is recently gaining attention as a potential noninvasive biomarker to diagnose incipient Alzheimer's disease. The aim of this study was to determine which method of data processing provides highest diagnostic power and to define metrics to further optimize the diagnostic value. fMRI was acquired in 21 healthy subjects, 17 subjects with mild cognitive impairment and 15 patients with Alzheimer's disease (AD) and data evaluated both with volumes of interest (VOI)-based signal time course evaluations and independent component analyses (ICA). The first approach determines the amount of DMN region interconnectivity (as expressed with correlation coefficients); the second method determines the magnitude of DMN coactivation. Apolipoprotein E (ApoE) genotyping was available in 41 of the subjects examined. Diagnostic power (expressed as accuracy) of data of a single DMN region in independent component analyses was 64%, that of a single correlation of time courses between 2 DMN regions was 71%, respectively. With multivariate analyses combining both methods of analysis and data from various regions, accuracy could be increased to 97% (sensitivity 100%, specificity 95%). In nondemented subjects, no significant differences in activity within DMN could be detected comparing ApoE ε4 allele carriers and ApoE ε4 allele noncarriers. However, there were some indications that fMRI might yield useful information given a larger sample. Time course correlation analyses seem to outperform independent component analyses in the identification of patients with Alzheimer's disease. However, multivariate analyses combining both methods of analysis by considering the activity of various parts of the DMN as well as the interconnectivity between these regions are required to achieve optimal and clinically acceptable diagnostic power.

Decline in mitochondrial bioenergetics and shift to ketogenic profile in brain during reproductive senescence

BACKGROUND

We have previously demonstrated that mitochondrial bioenergetic deficits precede Alzheimer's pathology in the female triple transgenic Alzheimer's (3xTgAD) mouse model. Herein, we sought to determine the impact of reproductive senescence on mitochondrial function in the normal non-transgenic (nonTg) and 3xTgAD female mouse model of AD.

METHODS

Both nonTg and 3xTgAD female mice at 3, 6, 9, and 12 months of age were sacrificed and mitochondrial bioenergetic profile as well as oxidative stress markers were analyzed.

RESULTS

In both nonTg and 3xTgAD mice, reproductive senescence paralleled a significant decline in PDH, and Complex IV cytochrome c oxidase activity and mitochondrial respiration. During the reproductive senescence transition, both nonTg and 3xTgAD mice exhibited greater individual variability in bioenergetic parameters suggestive of divergent bioenergetic phenotypes. Following transition through reproductive senescence, enzymes required for long-chain fatty acid (HADHA) and ketone body (SCOT) metabolism were significantly increased and variability in cytochrome c oxidase (Complex IV) collapsed to cluster at a approximately 40% decline in both the nonTg and 3xTgAD brain which was indicative of alternative fuel generation with concomitant decline in ATP generation.

CONCLUSIONS

These data indicate that reproductive senescence in the normal nonTg female brain parallels the shift to ketogenic/fatty acid substrate phenotype with concomitant decline in mitochondrial function and exacerbation of bioenergetic deficits in the 3xTgAD brain.

GENERAL SIGNIFICANCE

These findings provide a plausible mechanism for increased life-time risk of AD in postmenopausal women and suggest an optimal window of opportunity to prevent or delay decline in bioenergetics during reproductive senescence.

White matter integrity in mild cognitive impairment: a tract-based spatial statistics study

Mild cognitive impairment (MCI) as a clinical diagnosis has limited specificity, and identifying imaging biomarkers may improve its predictive validity as a pre-dementia syndrome. This study used diffusion tensor imaging (DTI) to detect white matter (WM) structural alterations in MCI and its subtypes, and aimed to examine if DTI can serve as a potential imaging marker of MCI. We studied 96 amnestic MCI (aMCI), 69 non-amnestic MCI (naMCI), and 252 cognitively normal (CN) controls. DTI was performed to measure fractional anisotropy (FA), and tract-based spatial statistics (TBSS) were applied to investigate the characteristics of WM changes in aMCI and naMCI. The diagnostic utility of DTI in distinguishing MCI from CN was further evaluated by using a binary logistic regression model. We found that FA was significantly reduced in aMCI and naMCI when compared with CN. For aMCI subjects, decreased FA was seen in the frontal, temporal, parietal, and occipital WM, together with several commissural, association, and projection fibres. The best discrimination between aMCI and controls was achieved by combining FA measures of the splenium of corpus callosum and crus of fornix, with accuracy of 74.8% (sensitivity 71.0%, specificity 76.2%). For naMCI subjects, WM abnormality was more anatomically widespread, but the temporal lobe WM was relatively spared. These results suggest that aMCI is best characterized by pathology consistent with early Alzheimer's disease, whereas underlying pathology in naMCI is more heterogeneous, and DTI analysis of white matter structural integrity can serve as a potential biomarker of MCI and its subtypes.

The value of PET in mild cognitive impairment, typical and atypical/unclear dementias: A retrospective memory clinic study

This retrospective study examined the role of [(18)F]fluorodeoxyglucose positron emission tomography (FDG-PET) in the diagnosis of atypical/unclear dementias in a memory clinic setting. A total of 94 patients with a diagnosis of mild cognitive impairment (MCI) or dementia, who had a PET study within 2 months of their diagnosis, were reevaluated at 5 and 18 months. Results showed that PET was associated with a change in diagnosis in 29% of patients and a 64% increase in the use of cholinesterase inhibitors (ChEIs). PET significantly lowered the number of atypical/unclear diagnoses from 39.4% to 16% and nearly 30% of these were found to have a typical Alzheimer's disease (AD) pattern of hypometabolism. In conclusion, the addition of PET to the investigation of atypical/unclear cases of dementia helped generating a more accurate diagnosis and initiating earlier treatment. PET was of limited contribution to typical AD and frontotemporal dementia (FTD) cases. This study provides guiding evidence about the true value of PET imaging in the day-to-day challenge of dementia diagnosis.

Fluorodeoxyglucose positron emission tomography of mild cognitive impairment with clinical follow-up at 3 years

BACKGROUND

Alzheimer's disease (AD) is the most common dementing illness. Development of effective treatments directed at AD requires an early diagnosis. Mild cognitive impairment (MCI) often heralds AD. Thus, characterizing MCI is fundamental to the early diagnosis of AD.

METHODS

19 MCI patients referred from a memory loss clinic and 27 healthy subjects, all followed up for 3 years. Metabolism scans (MCI minus controls) were compared voxel-wise after anatomic normalization and were examined both visually and with a computerized classifier.

RESULTS

Agreement between raters as to whether the individual scans were normal or abnormal was high. Agreement between raters of the eventual clinical diagnosis and baseline metabolic pattern was poor. A computerized classifier was unsuccessful at classifying MCI from normal; however, its performance improved when using only prototypic AD-like MCI scans, indicating the classifier worked well when shared patterns existed in the data. Outcomes on follow-up were nine of 19 AD, five of 19 remained MCI, and five of 19 developed dementias other than AD. Both MCI cases of early Lewy body dementia (LBD) showed an AD-like metabolic pattern.

CONCLUSIONS

Visual inspection proved reliable in determining normal from abnormal scans, but it proved unreliable at predicting diagnosis on follow-up. Computerized classification of MCI by using an AD-like metabolic template (such as derived from the averaged MCI images) showed potential to identify patients who will develop AD. However, the metabolic pattern in early LBD did not differ from that in AD.

Construction of a (18)F-FDG PET normative database of Japanese healthy elderly subjects and its application to demented and mild cognitive impairment patients

OBJECTIVE

To construct a (18)F-FDG PET normative database of Japanese healthy elderly subjects and to apply it to demented and mild cognitive impairment (MCI) patients.

METHODS

Seventy-seven Japanese normal volunteers from 41 to 84 years of age (36 males and 41 females) who underwent clinical, neuropsychological, and MRI examinations were selected. In these subjects, (18)F-FDG PET/CT scans were performed, (18)F-FDG PET images were analyzed using the 3D-SSP program, and a normative database for cerebral glucose metabolism was constructed. Then, (18)F-FDG PET images from 14 demented and MCI patients were evaluated based on the normative database.

RESULTS

The 77 healthy elderly subjects were divided into three groups according to their age. In these subjects, the difference in glucose metabolism between males and females was minimal in contrast, glucose metabolism showed a weak reciprocal correlation with aging in several cerebral regions. The 3D-SSP images of 14 demented and MCI patients based on the age-matched (18)F-FDG PET normative database showed decreased patterns of glucose metabolism similar to those of previous studies on dementia diseases and MCI.

CONCLUSIONS

An age-matched normative database can be applied to the evaluation of single subjects, and the application of a mixed database of males and females is viable. Normative databases are useful for detecting dementia diseases and their MCI.

Early detection of Alzheimer's disease with PET imaging

Preclinical diagnosis of Alzheimer's disease (AD) is one of the major challenges for the prevention of AD. AD biomarkers are needed not only to reveal preclinical pathologic changes, but also to monitor progression and therapeutics. PET neuroimaging can reliably assess aspects of the molecular biology and neuropathology of AD. The aim of this article is to review the use of FDG-PET and amyloid PET imaging in the early detection of AD.

Protein targets of oxidative damage in human neurodegenerative diseases with abnormal protein aggregates

Human neurodegenerative diseases with abnormal protein aggregates are associated with aberrant post-translational modifications, solubility, aggregation and fibril formation of selected proteins which cannot be degraded by cytosolic proteases, ubiquitin-protesome system and autophagy, and, therefore, accumulate in cells and extracellular compartments as residual debris. In addition to the accumulation of "primary" proteins, several other mechanisms are involved in the degenerative process and probably may explain crucial aspects such as the timing, selective cellular vulnerability and progression of the disease in particular individuals. One of these mechanisms is oxidative stress, which occurs in the vast majority of, if not all, degenerative diseases of the nervous system. The present review covers most of the protein targets that have been recognized as modified proteins mainly using bidimensional gel electrophoresis, Western blotting with oxidative and nitrosative markers, and identified by mass spectrometry in Alzheimer disease; certain tauopathies such as progressive supranuclear palsy, Pick disease, argyrophilic grain disease and frontotemporal lobar degeneration linked to mutations in tau protein, for example, FTLD-tau, Parkinson disease and related alpha-synucleinopathies; Huntington disease; and amyotrophic lateral sclerosis, together with related animal and cellular models. Vulnerable proteins can be mostly grouped in defined metabolic pathways covering glycolysis and energy metabolism, cytoskeletal, chaperoning, cellular stress responses, and members of the ubiquitin-proteasome system. Available information points to the fact that vital metabolic pathways are hampered by protein oxidative damage in several human degenerative diseases and that oxidative damage occurs at very early stages of the disease. Yet parallel functional studies are limited and further work is needed to document whether protein oxidation results in loss of activity and impaired performance. A better understanding of proteins susceptible to oxidation and nitration may serve to define damaged metabolic networks at early stages of disease and to advance therapeutic interventions to attenuate disease progression.

Alzheimer’s disease detection with objective statistical evaluation of FDG-PET brain scans: essential methodology for early identification

The anticipated introduction of disease-modifying agents for the treatment of Alzheimer’s disease (AD) highlights the need for its early and accurate detection. This article provides an overview of the objective statistical voxel-based image processing and analyses technology that make early detection of AD with 18F-fluorodeoxyglucose (FDG)-PET possible. Our report demonstrates that the comparison of a single FDG-PET scan with a group of control scans provides an objective statistical map that is useful for the detection of early stages of AD, augmenting visual inspection of the PET image itself. The need for early detection of AD, together with the power of voxel-based statistical analyses, provides an impetus for agencies to re-evaluate FDG-PET as an approved methodology for the early diagnosis of AD. The expected approval of disease-modifying agents for the treatment of AD places more emphasis on the need for earlier diagnosis of this common and devastating disorder.

Metabolic alterations associated with impaired clock drawing in Lewy body dementia

The clock drawing test (CDT) is a widely used dementia screening instrument that assesses executive and visuospatial abilities; studies in patients with Alzheimer's disease (AD) suggest frontoposterior networks to be involved in clock drawing. Clock drawing errors are also often observed in dementia with Lewy bodies (DLB), but the functional neuroanatomical substrate of impaired clock drawing has not been firmly established in this disorder. The present study was designed to provide initial evidence for brain metabolic alterations associated with CDT performance in DLB. Twenty-one patients with DLB were enrolled. CDT ratings were correlated with the regional cerebral metabolic rate of glucose (rCMRglc) measured by (18)F-fluoro-2-deoxy-glucose positron emission tomography ((18)F-FDG PET) in the statistical parametric mapping software package SPM5, controlling for overall cognitive impairment as measured by the Mini-Mental-State Examination (MMSE) score. There was a significant negative association between test scores and rCMRglc in a left-hemispheric posterofrontal network including the temporoparietal and dorsal pre-motor cortices and the precuneus. The present study provides evidence for a direct association between frontoparietal dysfunction and impaired CDT performance in DLB. These findings also suggest that the CDT is an appropriate screening instrument for this disorder and that metabolic dysfunction, and therefore disease severity, is mirrored by performance on the test.

Combining MR imaging, positron-emission tomography, and CSF biomarkers in the diagnosis and prognosis of Alzheimer disease

BACKGROUND AND PURPOSE

Different biomarkers for AD may potentially be complementary in diagnosis and prognosis of AD. Our aim was to combine MR imaging, FDG-PET, and CSF biomarkers in the diagnostic classification and 2-year prognosis of MCI and AD, by examining the following: 1) which measures are most sensitive to diagnostic status, 2) to what extent the methods provide unique information in diagnostic classification, and 3) which measures are most predictive of clinical decline.

MATERIALS AND METHODS

ADNI baseline MR imaging, FDG-PET, and CSF data from 42 controls, 73 patients with MCI, and 38 patients with AD; and 2-year clinical follow-up data for 36 controls, 51 patients with MCI, and 25 patients with AD were analyzed. The hippocampus and entorhinal, parahippocampal, retrosplenial, precuneus, inferior parietal, supramarginal, middle temporal, lateral, and medial orbitofrontal cortices were used as regions of interest. CSF variables included Abeta42, t-tau, p-tau, and ratios of t-tau/Abeta42 and p-tau/Abeta42. Regression analyses were performed to determine the sensitivity of measures to diagnostic status as well as 2-year change in CDR-SB, MMSE, and delayed logical memory in MCI.

RESULTS

Hippocampal volume, retrosplenial thickness, and t-tau/Abeta42 uniquely predicted diagnostic group. Change in CDR-SB was best predicted by retrosplenial thickness; MMSE, by retrosplenial metabolism and thickness; and delayed logical memory, by hippocampal volume.

CONCLUSIONS

All biomarkers were sensitive to the diagnostic group. Combining MR imaging morphometry and CSF biomarkers improved diagnostic classification (controls versus AD). MR imaging morphometry and PET were largely overlapping in value for discrimination. Baseline MR imaging and PET measures were more predictive of clinical change in MCI than were CSF measures.

Performance of FDG PET for detection of Alzheimer's disease in two independent multicentre samples (NEST-DD and ADNI)

AIM

We investigated the performance of FDG PET using an automated procedure for discrimination between Alzheimer's disease (AD) and controls, and studied the influence of demographic and technical factors.

METHODS

FDG PET data were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) [102 controls (76.0 +/- 4.9 years) and 89 AD patients (75.7 +/- 7.6 years, MMSE 23.5 +/- 2.1) and the Network for Standardisation of Dementia Diagnosis (NEST-DD) [36 controls (62.2 +/- 5.0 years) and 237 AD patients (70.8 +/- 8.3 years, MMSE 20.9 +/- 4.4). The procedure created t-maps of abnormal voxels. The sum of t-values in predefined areas that are typically affected by AD (AD t-sum) provided a measure of scan abnormality associated with a preset threshold for discrimination between patients and controls.

RESULTS

AD patients had much higher AD t-sum scores compared to controls (p < 0.01), which were significantly related to dementia severity (ADNI: r = -0.62, p < 0.01; NEST-DD: r = -0.59, p < 0.01). Early-onset AD patients had significantly higher AD t-sum scores than late-onset AD patients (p < 0.01). Differences between databases were mainly due to different age distributions. The predefined AD t-sum threshold yielded a sensitivity and specificity of 83 and 78% in ADNI and 78 and 94% in NEST-DD, respectively.

CONCLUSION

The automated FDG PET analysis procedure provided good discrimination power, and was most accurate for early-onset AD.

Menopause and mitochondria: windows into estrogen effects on Alzheimer's disease risk and therapy

Metabolic derangements and oxidative stress are early events in Alzheimer's disease pathogenesis. Multi-faceted effects of estrogens include improved cerebral metabolic profile and reduced oxidative stress through actions on mitochondria, suggesting that a woman's endogenous and exogenous estrogen exposures during midlife and in the late post-menopause might favourably influence Alzheimer risk and symptoms. This prediction finds partial support in the clinical literature. As expected, early menopause induced by oophorectomy may increase cognitive vulnerability; however, there is no clear link between age at menopause and Alzheimer risk in other settings, or between natural menopause and memory loss. Further, among older post-menopausal women, initiating estrogen-containing hormone therapy increases dementia risk and probably does not improve Alzheimer's disease symptoms. As suggested by the 'critical window' or 'healthy cell' hypothesis, better outcomes might be expected from earlier estrogen exposures. Some observational results imply that effects of hormone therapy on Alzheimer risk are indeed modified by age at initiation, temporal proximity to menopause, or a woman's health. However, potential methodological biases warrant caution in interpreting observational findings. Anticipated results from large, ongoing clinical trials [Early Versus Late Intervention Trial with Estradiol (ELITE), Kronos Early Estrogen Prevention Study (KEEPS)] will help settle whether midlife estrogen therapy improves midlife cognitive skills but not whether midlife estrogen exposures modify late-life Alzheimer risk. Estrogen effects on mitochondria adumbrate the potential relevance of estrogens to Alzheimer's disease. However, laboratory models are inexact embodiments of Alzheimer pathogenesis and progression, making it difficult to surmise net effects of estrogen exposures. Research needs include better predictors of adverse cognitive outcomes, biomarkers for risks associated with hormone therapy, and tools for monitoring brain function and disease progression.

Evaluation of Early Dementia (Mild Cognitive Impairment)

Early diagnosis of Alzheimer disease (AD) is one of the major challenges for the prevention of this dementia. The pathologic lesions associated with AD develop many years before the clinical manifestations of the disease become evident, during a likely transitional period between normal aging and the appearance of first cognitive symptoms. AD biomarkers are needed not only to reveal these early pathologic changes but also to monitor progression in cognitive and behavioral decline and brain lesions. PET neuroimaging can reliably assess indirect and direct aspects of the molecular biology and neuropathology of AD. This article reviews the use of [18F] 2-fluoro-2-deoxy-D-glucose-PET and amyloid PET imaging in the early detection of AD.

Comparison of eight methods for the estimation of the image-derived input function in dynamic [(18)F]-FDG PET human brain studies

The aim of this study was to compare eight methods for the estimation of the image-derived input function (IDIF) in [(18)F]-FDG positron emission tomography (PET) dynamic brain studies. The methods were tested on two digital phantoms and on four healthy volunteers. Image-derived input functions obtained with each method were compared with the reference input functions, that is, the activity in the carotid labels of the phantoms and arterial blood samples for the volunteers, in terms of visual inspection, areas under the curve, cerebral metabolic rates of glucose (CMRglc), and individual rate constants. Blood-sample-free methods provided less reliable results as compared with those obtained using the methods that require the use of blood samples. For some of the blood-sample-free methods, CMRglc estimations considerably improved when the IDIF was calibrated with a single blood sample. Only one of the methods tested in this study, and only in phantom studies, allowed a reliable calculation of the individual rate constants. For the estimation of CMRglc values using an IDIF in [(18)F]-FDG PET brain studies, a reliable absolute blood-sample-free procedure is not available yet.

Differential effects of global and cerebellar normalization on detection and differentiation of dementia in FDG-PET studies

FDG-PET ([18F]fluorodeoxyglucose positron emission tomography) is frequently used to improve the differential diagnosis of dementia. However, a fundamental methodological issue of the reference area for the intensity normalization procedure is still unsolved. Here, we systematically compared the two most commonly used normalization methods to the cerebral and to the cerebellar metabolic rate for glucose with regard to detection and differentiation of dementia syndromes. FDG-PET imaging was performed on 19 subjects with early Alzheimer's disease, 13 subjects with early frontotemporal lobar degeneration and 10 subjects complaining of memory impairment, which had not been confirmed by comprehensive clinical testing. Images were normalized to either the cerebral or the cerebellar metabolic rate for glucose. Differences in relative regional glucose metabolism were assessed by voxelwise comparison. Analysis using the two normalization procedures revealed remarkable differential effects. Whereas cerebellar normalization was superior in identifying dementia patients in comparison to control subjects, cerebral normalization showed better results for differential diagnosis between types of dementia. These effects were shown for both, Alzheimer's disease and frontotemporal lobar degeneration. Relative hypermetabolism in comparison to the control group was only detected in both kinds of dementia using global normalization. The results indicate that normalization has a decisive impact on diagnostic accuracy in dementia. While cerebellar normalization seems to be more sensitive for early diagnosis, cerebral global normalization might be superior for differential diagnostic purposes in dementia syndromes.

Associations between cognitive, functional, and FDG-PET measures of decline in AD and MCI

The Functional Activities Questionnaire (FAQ) and Alzheimer's Disease Assessment Scale-cognitive subscale (ADAS-cog) are frequently used indices of cognitive decline in Alzheimer's disease (AD). The goal of this study was to compare FDG-PET and clinical measurements in a large sample of elderly subjects with memory disturbance. We examined relationships between glucose metabolism in FDG-PET regions of interest (FDG-ROIs), and ADAS-cog and FAQ scores in AD and mild cognitive impairment (MCI) patients enrolled in the Alzheimer's Disease Neuroimaging Initiative (ADNI). Low glucose metabolism at baseline predicted subsequent ADAS-cog and FAQ decline. In addition, longitudinal glucose metabolism decline was associated with concurrent ADAS-cog and FAQ decline. Finally, a power analysis revealed that FDG-ROI values have greater statistical power than ADAS-cog to detect attenuation of cognitive decline in AD and MCI patients. Glucose metabolism is a sensitive measure of change in cognition and functional ability in AD and MCI, and has value in predicting future cognitive decline.