Fluorodeoxyglucose-positron-emission tomography, single-photon emission tomography, and structural MR imaging for prediction of rapid conversion to Alzheimer disease in patients with mild cognitive impairment: a meta-analysis

Clinical applications of neuroimaging in patients with Alzheimer's disease: a review from the Fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia 2012

In May 2012, the Fourth Canadian Consensus Conference on the Diagnosis and Treatment of Dementia brought together in Montreal experts from around Canada to update Canadian recommendations for the diagnosis and management of patients with neurodegenerative conditions associated with deterioration of cognition. Multiple topics were discussed. The present paper is a highly condensed version of those recommendations that were produced to support discussions in the field of neuroimaging for clinical diagnosis of those conditions.

Sensitivity and specificity of diagnostic accuracy in Alzheimer's disease: a synthesis of existing evidence

PURPOSE OF THE STUDY

This report synthesizes existing evidence to compare the accuracy of various Alzheimer's disease (AD) diagnostic approaches.

DESIGN AND METHODS

Meta-analyses and reviews of diagnostic accuracy of AD were identified through a search of the PubMed and Cochrane Library databases using the keyword combinations of "sensitivity specificity Alzheimer's disease diagnosis" and "accuracy of Alzheimer's disease diagnosis."

RESULTS

From 507 abstracts initially identified, 41 systematic reviews or meta-analyses were selected. Cerebrospinal fluid-tau demonstrated variable sensitivity (range 73.3%-100%) and specificity (range 70.0%-92.4%) in diagnosing AD when compared to neuropathological verification of clinical criteria for AD. Various positron emission tomography approaches showed a similar range of sensitivity (range 80.0%-100%) and specificity (range 62.0%-90%) as diagnostic protocols.

IMPLICATIONS

Issues that remain in the study of AD diagnosis include the need to determine the comparative effectiveness of diagnostic approaches. Variations in study quality make empirically derived conclusions about the diagnostic accuracy of existing approaches tenuous.

Using Pittsburgh Compound B for in vivo PET imaging of fibrillar amyloid-beta

The development of Aβ-PET imaging agents has allowed for detection of fibrillar Aβ deposition in vivo and marks a major advancement in understanding the role of Aβ in Alzheimer's disease (AD). Imaging Aβ thus has many potential clinical benefits: early or perhaps preclinical detection of disease and accurately distinguishing AD from dementias of other non-Aβ causes in patients presenting with mild or atypical symptoms or confounding comorbidities (in which the distinction is difficult to make clinically). From a research perspective, imaging Aβ allows us to study relationships between amyloid pathology and changes in cognition, brain structure, and function across the continuum from normal aging to mild cognitive impairment (MCI) to AD; and to monitor the effectiveness of anti-Aβ drugs and relate them to neurodegeneration and clinical symptoms. Here, we will discuss the application of one of the most broadly studied and widely used Aβ imaging agents, Pittsburgh Compound-B (PiB).

The diagnosis and evaluation of dementia and mild cognitive impairment with emphasis on SPECT perfusion neuroimaging

As the world population ages, the incidence of dementing illnesses will dramatically increase. The number of people afflicted with dementia is expected to quadruple in the next 50 years. Since the neuropathology of the dementias precedes clinical symptoms often by several years, earlier detection and intervention could be key steps to mitigating the progression and burden of these diseases. This review will explore methods of evaluating, differentiating, and diagnosing the multiple forms of dementia. Particular emphasis will be placed on the diagnosis of mild cognitive impairment-the precursor to dementia. Anatomical imaging; cerebrospinal fluid markers; functional neuroimaging, such as positron emission tomography and single photon emission tomography; and molecular imaging, such as amyloid marker imaging, will be assessed in terms of sensitivity and specificity. Cost will also be a consideration, as the growing population afflicted with dementia represents an increasingly large financial encumbrance to the healthcare systems of every nation. In the face of expensive new markers and limited availability of cyclotrons, single photon emission computer tomography (SPECT) provides relatively high sensitivity and specificity at a comparatively low overall cost.

The neurobiology of Alzheimer disease defined by neuroimaging

PURPOSE OF REVIEW

In 2011, a new set of new guidelines for the research diagnosis of three stages of Alzheimer disease was promulgated by the US National Institute of Aging and the Alzheimer Association. For the first time, they include the diagnosis of presymptomatic Alzheimer disease, recognizing that the disease process begins years before cognitive impairment develops. Awareness of this fact has largely been driven by neuroimaging, and particularly by imaging amyloid β (abeta) deposition in the brain, a procedure approved by the US Food and Drug Administration for clinical use in April 2012.

RECENT FINDINGS

In Alzheimer disease, abeta deposition antecedes, probably by decades, the onset of cognitive impairment. In brain regions with greatest abeta deposition, synaptic dysfunction can be imaged beginning at preclinical stages. In regions that are not identical with the ones with greatest abeta deposition but heavily connected with them, regional atrophy and loss of white-matter anisotropy can be detected later in the course of the disease, near the time when mild cognitive impairment supervenes. Together with neuropsychological testing, imaging can improve the prediction of worsening to Alzheimer disease among patients with mild cognitive impairment.

SUMMARY

These findings have huge implications for research on therapeutic approaches to Alzheimer disease. For instance, while so far only patients with the clinical diagnosis have been treated with immunotherapy targeting abeta removal, a consensus is building that to be effective, this therapy should be given in the preclinical stages of the disease, which are assessed most advantageously by means of neuroimaging.

Prediction of Alzheimer's disease in subjects with mild cognitive impairment from the ADNI cohort using patterns of cortical thinning

Predicting Alzheimer's disease (AD) in individuals with some symptoms of cognitive decline may have great influence on treatment choice and disease progression. Structural magnetic resonance imaging (MRI) has the potential of revealing early signs of neurodegeneration in the human brain and may thus aid in predicting and diagnosing AD. Surface-based cortical thickness measurements from T1-weighted MRI have demonstrated high sensitivity to cortical gray matter changes. In this study we investigated the possibility for using patterns of cortical thickness measurements for predicting AD in subjects with mild cognitive impairment (MCI). We used a novel technique for identifying cortical regions potentially discriminative for separating individuals with MCI who progress to probable AD, from individuals with MCI who do not progress to probable AD. Specific patterns of atrophy were identified at four time periods before diagnosis of probable AD and features were selected as regions of interest within these patterns. The selected regions were used for cortical thickness measurements and applied in a classifier for testing the ability to predict AD at the four stages. In the validation, the test subjects were excluded from the feature selection to obtain unbiased results. The accuracy of the prediction improved as the time to conversion from MCI to AD decreased, from 70% at 3 years before the clinical criteria for AD was met, to 76% at 6 months before AD. By inclusion of test subjects in the feature selection process, the prediction accuracies were artificially inflated to a range of 73% to 81%. Two important results emerge from this study. First, prediction accuracies of conversion from MCI to AD can be improved by learning the atrophy patterns that are specific to the different stages of disease progression. This has the potential to guide the further development of imaging biomarkers in AD. Second, the results show that one needs to be careful when designing training, testing and validation schemes to ensure that datasets used to build the predictive models are not used in testing and validation.

Regional cerebral blood flow differences in patients with mild cognitive impairment between those who did and did not develop Alzheimer's disease

Mild cognitive impairment (MCI) is a heterogeneous condition associated with increased risk of Alzheimer's disease (AD) and other dementias. This study aimed to identify areas of initial hypoperfusion in MCI conversion to AD using technetium (Tc-99m) hexamethylpropyleneamine oxime (TC-99m HMPAO) single photon emission computed tomography (SPECT) to compare baseline cerebral hypoperfusion in converted MCI and non-converted MCI patients and normal controls. Forty-nine MCI patients were recruited for brain magnetic resonance imaging (MRI), detailed neuropsychological testing, Tc-99m HMPAO SPECT, and 1- to 2-year periodic follow-up to monitor progression to dementia status. We processed SPECT images with Statistical Parametric Mapping 8 (SPM8) software and performed voxel-based statistical parametric mapping analysis. Thirty-nine of 49 MCI patients were included in our analysis. Nine patients were diagnosed with conversion to AD, on average 19.0±6.6 months after initial assessment. Compared with normal controls, converted MCI patients demonstrated perfusion deficits in both parahippocampal gyri and right precuneus, and non-converted MCI patients demonstrated hypoperfusion in the left parahippocampal gyrus. Compared with non-converted MCI patients, converted MCI patients demonstrated significant hypoperfusion in both cingulate gyri and right precuneus. Our study suggests that using brain SPECT to identify initial hypoperfusion in patients with MCI may be helpful for predicting MCI patients likely to develop AD.

Diagnostic accuracy of 18 F-FDG and 11 C-PIB-PET for prediction of short-term conversion to Alzheimer's disease in subjects with mild cognitive impairment

In recent years, the role of PET imaging in the prediction of mild cognitive impairment (MCI) to Alzheimer's disease (AD) conversion has been the subject of many longitudinal studies. The purpose of this study was to perform a meta-analysis to estimate the diagnostic accuracy of (18) F-fluoro-2-deoxyglucose-positron emission tomography (FDG-PET) and (11) C-Pittsburgh Compound B-positron emission tomography (PIB-PET) for prediction of short-term conversion to AD in patients with MCI. The MEDLINE and EMBASE databases were systematically searched for relevant studies. Methodological quality of the included studies was assessed. Sensitivities and specificities of PET in individual studies were calculated and meta-analysis was undertaken with a random-effects model. A summary receiver operating characteristic (SROC) curve was constructed with the Moses-Shapiro-Littenberg method. Heterogeneity was tested, and the presence of publication bias was assessed. Potential sources for heterogeneity were explored by assessing whether or not certain covariates significantly influenced the relative diagnostic odds ratio (DOR). Pooled estimates of sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), DOR and the SROC curve of each PET imaging were determined. A total of 13 research studies (seven FDG-PET and six PIB-PET) met inclusion criteria and had sufficient data for statistical analysis. FDG-PET pooled estimates had 78.7% sensitivity (95% CI, 68.7-86.6%),74.0% specificity (95% CI, 67.0-80.3%), 18.1 LR+(95% CI, 7.3-45.0) and 0.32 LR-(95% CI, 0.16-0.61); and PIB-PET pooled estimates had 93.5% sensitivity (95%CI, 71.3-99.9%), 56.2% specificity (95% CI, 47.2-64.8%), 2.01 LR+ (95% CI, 1.57-2.58) and 0.17 LR-(95% CI, 0.08-0.36). Overall DOR was 17.3 (95% CI, 5.08-59.2) for FDG-PET and 12.8 (95% CI, 5.35-30.54) for PIB-PET. Area under the SROC curve was 0.88 ± 0.05 for FDG-PET and 0.85 ± 0.04 for PIB-PET. The data from FDG-PET research studies had high heterogeneity and funnel plot suggested a publication bias. The diagnostic accuracy determined for both FDG-PET and PIB-PET in this meta-analysis suggests that they are potentially valuable techniques for prediction of progression in patients with MCI. Both have their advantages and their combined use is a promising option for prediction purposes depending on availability and experience.

Asymmetric cerebral blood flow in patients with mild cognitive impairment: possible relationship to further cognitive deterioration

Aim

To explore patterns of cerebral blood flow in patients with mild cognitive impairment (MCI), who (1) eventually deteriorate into overt dementia, with no particular focus on the type of dementia, or (2) do not appear to further deteriorate in their cognitive functions.

Methods

Thirty-seven MCI patients, with or without vascular pathology, were studied prospectively. The patients underwent ^99mTc-HMPAO SPECT analysis at baseline. Possible clinical conversion into dementia within a 2-year period was assessed.

Results

Nineteen patients had progressive MCI (PMCI), while 18 patients were considered clinically stable (SMCI). PMCI patients had more often abnormally low cerebral blood flow in at least one of the frontal, temporal, parietal or occipital lobes compared to SMCI patients (12/19 vs. 5/18; p = 0.049). At least one of the temporal regions was found to be abnormal in 9 PMCI patients in contrast to only 1 SMCI patient (p = 0.008). More specifically, blood flow in the medial portion of the left temporal region was abnormal in 8 PMCI patients, a pattern seen in 1 SMCI patient only (p = 0.019).

Conclusion

The results suggest that blood flow reductions particularly in the left medial temporal region indicate an elevated risk of further cognitive decline in MCI patients.

Structural MRI changes detectable up to ten years before clinical Alzheimer's disease

Structural brain changes have been described in both mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, less is known about whether structural changes are detectable earlier, in the asymptomatic phase. Using voxel-based morphometry (VBM) and shape analyses of magnetic resonance imaging (MRI) data, we investigated structural brain differences between groups of healthy subjects, stratified by subsequent diagnoses of MCI or AD during a 10-year follow-up. Images taken at baseline, at least 4 years before any cognitive symptoms, showed that subjects with future cognitive impairment (preclinical AD and MCI) had reduced brain volume in medial temporal lobes, posterior cingulate/precuneus, and orbitofrontal cortex, compared with matched subjects who remained cognitively healthy for 10 years (HC). For only those subjects later diagnosed as AD, significantly greater atrophy at baseline was detected in the right medial temporal lobe, which was also confirmed by shape analysis of the right hippocampus in these subjects. Our results demonstrate that structural brain changes occur years before clinical cognitive decline in AD and are localized to regions affected by AD neuropathology.

Biomarkers in Alzheimer's disease

Alzheimer's disease (AD) is the most common form of dementia in the elderly, and it is characterized by progressive impairment in multiple cognitive domains of sufficient severity to interfere with individuals' daily living activities. Historically, the diagnosis of AD has been based on the identification of a clinical syndrome, and accuracy studies of the current clinical criteria conducted in referral clinics have shown high sensitivity for AD. However, the identification of the disease is still not perfect, and there is growing evidence that the use of biomarkers will increase our ability to better indentify the underlying biology of AD, especially in its early stages. These biomarkers will improve the detection of the patients suitable for research studies and drug trials, and they will contribute to a better management of the disease in the clinical practice. In this review, we discuss the most studied biomarkers in AD: cerebrospinal fluid proteins, structural magnetic resonance imaging, functional neuroimaging techniques, and amyloid imaging.

Cerebrospinal fluid and blood flow in mild cognitive impairment and Alzheimer's disease: a differential diagnosis from idiopathic normal pressure hydrocephalus

Background

Phase-contrast magnetic resonance imaging (PC-MRI) enables quantification of cerebrospinal fluid (CSF) flow and total cerebral blood (tCBF) flow and may be of value for the etiological diagnosis of neurodegenerative diseases. This investigation aimed to study CSF flow and intracerebral vascular flow in patients with Alzheimer's disease (AD) and patients with amnesic mild cognitive impairment (a-MCI) and to compare the results with patients with idiopathic normal pressure hydrocephalus (NPH) and with healthy elderly volunteers (HEV).

Methods

Ten a-MCI and 9 mild AD patients were identified in a comprehensive neurological and neuropsychological assessment. They underwent brain MRI; PC-MRI pulse sequence was performed with the following parameters: two views per segment; flip angle: 25° for vascular flow and 20° for CSF flow; field-of-view (FOV): 14 × 14 mm²; matrix: 256 × 128; slice thickness: 5 mm; with one excitation for exams on the 3 T machine, and 2 excitations for the 1.5 T machine exams. Velocity (encoding) sensitization was set to 80 cm/s for the vessels at the cervical level, 10 or 20 cm/s for the aqueduct and 5 cm/s for the cervical subarachnoid space (SAS). Dynamic flow images were analyzed with in-house processing software. The patients' results were compared with those obtained for HEVs (n = 12), and for NPH patients (n = 13), using multivariate analysis.

Results

Arterial tCBF and the calculated pulsatility index were significantly greater in a-MCI patients than in HEVs. In contrast, vascular parameters were lower in NPH patients. Cervical CSF flow analysis yielded similar values for all four populations. Aqueductal CSF stroke volumes (in μl per cardiac cycle) were similar in HEVs (34 ± 17) and AD patients (39 ± 18). In contrast, the aqueductal CSF was hyperdynamic in a-MCI patients (73 ± 33) and even more so in NPH patients (167 ± 89).

Conclusion

Our preliminary data show that a-MCI patients present with high systolic arterial peak flows, which are associated with higher mean total cerebral arterial flows. Aqueductal CSF oscillations are within normal range in AD and higher than normal in NPH. This study provides an original dynamic vision of cerebral neurodegenerative diseases, consistent with the vascular theory for AD, and supporting primary flow disturbances different from those observed in NPH.

Biomarkers of Alzheimer's disease: from central nervous system to periphery?

Alzheimer's Disease (AD) is the most frequent form of dementia and represents one of the main causes of disability among older subjects. Up to now, the diagnosis of AD has been made according to clinical criteria. However, the use of such criteria does not allow an early diagnosis, as pathological alterations may be apparent many years before the clear-cut clinical picture. An early diagnosis is even more valuable to develop new treatments, potentially interfering with the pathogenetic process. During the last decade, several neuroimaging and cerebrospinal fluid (CSF) parameters have been introduced to allow an early and accurate detection of AD patients, and, recently, they have been included among research criteria for AD diagnosis. However, their use in clinical practice suffers from limitations both in accuracy and availability. The increasing amount of knowledge about peripheral biomarkers will possibly allow the future identification of reliable and easily available diagnostic tests.

(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.

Role of structural MRI in Alzheimer's disease

Atrophy measured on structural magnetic resonance imaging (sMRI) is a powerful biomarker of the stage and intensity of the neurodegenerative aspect of Alzheimer's disease (AD) pathology. In this review, we will discuss the role of sMRI as an AD biomarker by summarizing (a) the most commonly used methods to extract information from sMRI images, (b) the different roles in which sMRI can be used as an AD biomarker, and (c) comparisons of sMRI with other major AD biomarkers.

Automated MRI measures predict progression to Alzheimer's disease

The prediction of individuals with mild cognitive impairment (MCI) destined to develop Alzheimer's disease (AD) is of increasing clinical importance. In this study, using baseline T1-weighted MRI scans of 324 MCI individuals from two cohorts and automated software tools, we employed factor analyses and Cox proportional hazards models to identify a set of neuroanatomic measures that best predicted the time to progress from MCI to AD. For comparison, cerebrospinal fluid (CSF) assessments of cellular pathology and positron emission tomography (PET) measures of metabolic activity were additionally examined. By 3 years follow-up, 60 MCI individuals from the first cohort and 58 MCI individuals from the second cohort had progressed to a diagnosis of AD. Cox models on the first cohort demonstrated significant effects for the medial temporal factor [Hazards Ratio (HR) = 0.43{95% confidence interval (CI), 0.32-0.55}, p < 0.0001], the fronto-parietoccipital factor [HR = 0.59{95% CI, 0.48-0.80}, p < 0.001], and the lateral temporal factor [HR = 0.67 {95% CI, 0.52-0.87}, p < 0.01]. When applied to the second cohort, these Cox models showed significant effects for the medial temporal factor [HR = 0.44 {0.32-0.61}, p < 0.001] and lateral temporal factor [HR = 0.49 {0.38-0.62}, p < 0.001]. In a combined Cox model, consisting of individual CSF, PET, and MRI measures that best predicted disease progression, only the medial temporal factor [HR = 0.53 {95% CI, 0.34-0.81}, p < 0.001] demonstrated a significant effect. These findings illustrate that automated MRI measures of the medial temporal cortex accurately and reliably predict time to disease progression, outperform cellular and metabolic measures as predictors of clinical decline, and can potentially serve as a predictive marker for AD.

Differential levels of apolipoprotein E and butyrylcholinesterase show strong association with pathological signs of Alzheimer's disease in the brain in vivo

Recently, we reported that 3 of the known risk factors of Alzheimer's disease (AD), i.e., advanced age, apolipoprotein E (ApoE) ε4, and female gender, are associated with differential levels of ApoE proteins and butyrylcholinesterase (BuChE) in the cerebrospinal fluid (CSF) of AD patients. The ApoE ε4 allele and certain BuChE polymorphisms synergistically affect the conversion rate of mild cognitive impairment (MCI) to AD. Here, we investigated interrelationships between ApoE and BuChE levels, and pathological markers of AD in vivo. CSF from patients with probable AD, assessed for cerebral glucose metabolism (CMRglc; n = 50) and Pittsburgh compound B (PIB) retention (β-amyloid [Aβ] load, n = 29) by positron emission tomography (PET), was used for measurement of BuChE, ApoE, Aβ, tau, phosphorylated tau (P-tau) and interleukin-1β (IL-1β) levels. Levels of ApoE and BuChE strongly correlated with CMRglc (fluorodeoxyglucose [FDG]-PET, r = 0.54, p < 0.0001, n = 50), cerebral Aβ load (PIB retention, r = 0.73, p < 0.0001, n = 29), and CSF P-tau (r = 0.73, p < 0.0001, n = 33). High ApoE protein was tied to low CMRglc and high PIB retention and P-tau. BuChE levels had opposite relationships. Other CSF covariates were levels of interleukin-1β and Aβ(42) peptide. The pattern of the patients' cognitive Z-scores strongly supported these observations. High ApoE protein was also linked to changes in 3 of the biodynamic properties of BuChE. In vitro analysis indicated that high ApoE protein levels were related to an increased pool of dormant BuChE molecules with an abnormally high intrinsic catalytic rate in CSF, which was "turned on" by excess Aβ peptides. The findings suggest that abnormally high levels of ApoE may play a causative role in the pathological events of AD, particularly those involving the early cholinergic deficit in the AD brain, through modulation of cholinesterases activities, hence disturbing the acetylcholine-dependent activity of neurons and nonexcitable cells such as glial cells.

The clinical use of structural MRI in Alzheimer disease

Structural imaging based on magnetic resonance is an integral part of the clinical assessment of patients with suspected Alzheimer dementia. Prospective data on the natural history of change in structural markers from preclinical to overt stages of Alzheimer disease are radically changing how the disease is conceptualized, and will influence its future diagnosis and treatment. Atrophy of medial temporal structures is now considered to be a valid diagnostic marker at the mild cognitive impairment stage. Structural imaging is also included in diagnostic criteria for the most prevalent non-Alzheimer dementias, reflecting its value in differential diagnosis. In addition, rates of whole-brain and hippocampal atrophy are sensitive markers of neurodegeneration, and are increasingly used as outcome measures in trials of potentially disease-modifying therapies. Large multicenter studies are currently investigating the value of other imaging and nonimaging markers as adjuncts to clinical assessment in diagnosis and monitoring of progression. The utility of structural imaging and other markers will be increased by standardization of acquisition and analysis methods, and by development of robust algorithms for automated assessment.

Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade

Currently available evidence strongly supports the position that the initiating event in Alzheimer's disease (AD) is related to abnormal processing of beta-amyloid (Abeta) peptide, ultimately leading to formation of Abeta plaques in the brain. This process occurs while individuals are still cognitively normal. Biomarkers of brain beta-amyloidosis are reductions in CSF Abeta(42) and increased amyloid PET tracer retention. After a lag period, which varies from patient to patient, neuronal dysfunction and neurodegeneration become the dominant pathological processes. Biomarkers of neuronal injury and neurodegeneration are increased CSF tau and structural MRI measures of cerebral atrophy. Neurodegeneration is accompanied by synaptic dysfunction, which is indicated by decreased fluorodeoxyglucose uptake on PET. We propose a model that relates disease stage to AD biomarkers in which Abeta biomarkers become abnormal first, before neurodegenerative biomarkers and cognitive symptoms, and neurodegenerative biomarkers become abnormal later, and correlate with clinical symptom severity.

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.

Conversion of amyloid positive and negative MCI to AD over 3 years: an 11C-PIB PET study

BACKGROUND

Patients with amnestic mild cognitive impairment (MCI) represent an important clinical group as they are at increased risk of developing Alzheimer disease (AD). (11)C-PIB PET is an in vivo marker of brain amyloid load.

OBJECTIVE

To assess the rates of conversion of MCI to AD during a 3-year follow-up period and to compare levels of amyloid deposition between MCI converters and nonconverters.

METHODS

Thirty-one subjects with MCI with baseline (11)C-PIB PET, MRI, and neuropsychometry have been clinically followed up for 1 to 3 years (2.68 +/- 0.6 years). Raised cortical (11)C-PIB binding in subjects with MCI was detected with region of interest analysis and statistical parametric mapping.

RESULTS

Seventeen of 31 (55%) subjects with MCI had increased (11)C-PIB retention at baseline and 14 of these 17 (82%) clinically converted to AD during follow-up. Only one of the 14 PIB-negative MCI cases converted to AD. Of the PIB-positive subjects with MCI, half (47%) converted to AD within 1 year of baseline PIB PET, these faster converters having higher tracer-retention values than slower converters in the anterior cingulate (p = 0.027) and frontal cortex (p = 0.031). Seven of 17 (41%) subjects with MCI with known APOE status were epsilon4 allele carriers, this genotype being associated with faster conversion rates in PIB-positive subjects with MCI (p = 0.035).

CONCLUSIONS

PIB-positive subjects with mild cognitive impairment (MCI) are significantly more likely to convert to AD than PIB-negative patients, faster converters having higher PIB retention levels at baseline than slower converters. In vivo detection of amyloid deposition in MCI with PIB PET provides useful prognostic information.

Early marker for Alzheimer's disease: hippocampus T1rho (T(1rho)) estimation

PURPOSE

To evaluate the T1rho (T(1rho)) MRI relaxation time in hippocampus in the brain of Alzheimer's disease (AD), mild cognitive impairment (MCI), and control, and to determine whether the T(1rho) shows any significant difference between these cohorts.

MATERIALS AND METHODS

With informed consent, AD (n = 49), MCI (n = 48), and age-matched control (n = 31) underwent T(1rho) MRI on a Siemens 1.5T Scanner. T(1rho) values were automatically calculated from the left and right hippocampus region using in-house developed software. Bonferroni post-hoc multiple comparisons was performed to compare the T(1rho) value among the different cohorts.

RESULTS

Significantly higher T(1rho) values were observed both in AD (P = 0.000) and MCI (P = 0.037) cohorts compared to control; also, the T(1rho) in AD was significantly high over (P = 0.032) MCI. Hippocampus T(1rho) was 13% greater in the AD patients than control, while in MCI it was 7% greater than control. Hippocampus T(1rho) in AD patients was 6% greater than MCI.

CONCLUSION

Higher hippocampus T(1rho) values in the AD patients might be associated with the increased plaques burden. A follow-up study would help to determine the efficacy of T(1rho) values as a predictor of developing AD in the control and MCI individuals.