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

Cerebral glucose metabolic prediction from amnestic mild cognitive impairment to Alzheimer's dementia: a meta-analysis

Brain ¹⁸F-fluorodeoxyglucose positron emission tomography (FDG-PET) has been utilized to monitor disease conversion from amnestic mild cognitive impairment (aMCI) to Alzheimer’s dementia (AD). However, the conversion patterns of FDG-PET metabolism across studies are not conclusive. We conducted a voxel-wise meta-analysis using Seed-based d Mapping that included 10 baseline voxel-wise FDG-PET comparisons between 93 aMCI converters and 129 aMCI non-converters from nine longitudinal studies. The most robust and reliable metabolic alterations that predicted conversion from aMCI to AD were localized in the left posterior cingulate cortex (PCC)/precuneus. Furthermore, meta-regression analyses indicated that baseline mean age and severity of cognitive impairment, and follow-up duration were significant moderators for metabolic alterations in aMCI converters. Our study revealed hypometabolism in the left PCC/precuneus as an early feature in the development of AD. This finding has important implications in understanding the neural substrates for AD conversion and could serve as a potential imaging biomarker for early detection of AD as well as for tracking disease progression at the predementia stage.

Cerebral Hemodynamics in Mild Cognitive Impairment: A Systematic Review

BACKGROUND

The incidence of dementia is projected to rise over the coming decades, but with no sensitive diagnostic tests available. Vascular pathology precedes the deposition of amyloid and is an attractive early target.

OBJECTIVE

The aim of this review was to investigate the use of cerebral hemodynamics and oxygenation as a novel biomarker for mild cognitive impairment (MCI), focusing on transcranial Doppler ultrasonography (TCD) and near-infrared spectroscopy (NIRS).

METHODS

2,698 articles were identified from Medline, Embase, PsychINFO, and Web of Science databases. 306 articles were screened and quality assessed independently by two reviewers; 26 met the inclusion criteria. Meta-analyses were performed for each marker with two or more studies and limited heterogeneity.

RESULTS

Eleven studies were TCD, 8 NIRS, 5 magnetic resonance imaging, and 2 positron/single photon emission tomography. Meta-analyses showed reduced tissue oxygenation index, cerebral blood flow and velocity, with higher pulsatility index, phase and cerebrovascular resistance in MCI compared to controls. The majority of studies found reduced CO2 reactivity in MCI, with mixed findings in neuroactivation studies.

CONCLUSION

Despite small sample sizes and heterogeneity, meta-analyses demonstrate clear abnormalities in cerebral hemodynamic and oxygenation parameters, even at an early stage of cognitive decline. Further work is required to investigate the use of cerebral hemodynamic and oxygenation parameters as a sensitive biomarker for dementia.

Predicting progression of amnesic MCI: The integration of episodic memory impairment with perfusion SPECT

The present study aimed at assessing if the ability to predict progression from amnesic Mild Cognitive Impairment (aMCI) to dementia is improved by considering the presence at the baseline of Single Photon Emission Computed Tomography (SPECT) perfusion abnormalities in addition to a defect of long term memory. The Episodic Memory Score (EMS), a global index which integrates results obtained in subtests of the Rey's Verbal Learning Test and the Rey-Osterrieth Figure recall, were taken into account to evaluate defects of long term memory. The study sample consisted of 42 subjects affected by aMCI, who were followed-up during a two-year period. At the final follow-up 15 subjects progressed to AD. The EMS predicted progression from aMCI to dementia with a high level of sensitivity and a lower level of specificity, but the association of neuropsychological (EMS) and SPECT data (hypoperfusion in the Posterior Cingulate Cortex) increased the accuracy in predicting conversion from aMCI to AD. The association of results obtained by aMCI patients on memory tests and perfusion SPECT may improve the accuracy in detecting subjects who will progress to dementia. The use of currently available and low-cost investigations could be advantageous in terms of public health policies.

FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort

Background/aims

In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimer's disease (AD) dementia and non-AD dementias.

Methods

We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as "typical-AD", "atypical-AD" (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), "non-AD" (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or "negative" patterns. To perform the statistical analyses, the individual patterns were grouped either as "AD dementia vs. non-AD dementia (all diseases)" or as "FTD vs. non-FTD (all diseases)". Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated.

Results

The multivariate logistic model identified FDG-PET "AD" SPM classification (Expβ = 19.35, 95% C.I. 4.8-77.8, p < 0.001) and CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64-25.43, p < 0.05) as the best predictors of conversion from MCI to AD dementia. The "FTD" SPM pattern significantly predicted conversion to FTD dementias at follow-up (Expβ = 14, 95% C.I. 3.1-63, p < 0.001). Overall, FDG-PET-SPM classification was the most accurate biomarker, able to correctly differentiate either the MCI subjects who converted to AD or FTD dementias, and those who remained stable or reverted to normal cognition (Expβ = 17.9, 95% C.I. 4.55-70.46, p < 0.001).

Conclusions

Our results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.

Quantitative MRI Brain Studies in Mild Cognitive Impairment and Alzheimer's Disease: A Methodological Review

Classifying and predicting Alzheimer's disease (AD) in individuals with memory disorders through clinical and psychometric assessment is challenging, especially in mild cognitive impairment (MCI) subjects. Quantitative structural magnetic resonance imaging acquisition methods in combination with computer-aided diagnosis are currently being used for the assessment of AD. These acquisitions methods include voxel-based morphometry, volumetric measurements in specific regions of interest (ROIs), cortical thickness measurements, shape analysis, and texture analysis. This review evaluates the aforementioned methods in the classification of cases into one of the following three groups: normal controls, MCI, and AD subjects. Furthermore, the performance of the methods is assessed on the prediction of conversion from MCI to AD. In parallel, it is also assessed which ROIs are preferred in both classification and prognosis through the different states of the disease. Structural changes in the early stages of the disease are more pronounced in the medial temporal lobe, especially in the entorhinal cortex, whereas with disease progression, both entorhinal cortex and hippocampus offer similar discriminative power. However, for the conversion from MCI subjects to AD, entorhinal cortex provides better predictive accuracies rather than other structures, such as the hippocampus.

Clinical validity of medial temporal atrophy as a biomarker for Alzheimer's disease in the context of a structured 5-phase development framework

Research criteria for Alzheimer's disease recommend the use of biomarkers for diagnosis, but whether biomarkers improve the diagnosis in clinical routine has not been systematically assessed. The aim is to evaluate the evidence for use of medial temporal lobe atrophy (MTA) as a biomarker for Alzheimer's disease at the mild cognitive impairment stage in routine clinical practice, with an adapted version of the 5-phase oncology framework for biomarker development. A literature review on visual assessment of MTA and hippocampal volumetry was conducted with other biomarkers addressed in parallel reviews. Ample evidence is available for phase 1 (rationale for use) and phase 2 (discriminative ability between diseased and control subjects). Phase 3 (early detection ability) is partly achieved: most evidence is derived from research cohorts or clinical populations with short follow-up, but validation in clinical mild cognitive impairment cohorts is required. In phase 4, only the practical feasibility has been addressed for visual rating of MTA. The rest of phase 4 and phase 5 have not yet been addressed.

The evaluation of brain perfusion SPECT using an easy Z-score imaging system in the mild cognitive impairment subjects with brain amyloid-β deposition

OBJECTIVE

The analysis of ⁹⁹mTc-ECD single-photon emission computed tomography (SPECT) images using the easy Z-score imaging system (eZIS) program is useful for the diagnosis of early AD in daily medical practice. However, it remains unclear whether eZIS analysis can identify the amnestic mild cognitive impairment (MCI) subjects with brain amyloid-β deposition. The aim of this study was to evaluate the usefulness of an eZIS analysis for predicting amnestic MCI subjects with brain amyloid β deposition.

PATIENTS AND METHODS

Twenty-three subjects with MCI (10 men and 13 women, mean age; 74.2 years) underwent brain perfusion SPECT and ¹¹C-Pittsburgh Compound B positron emission tomography (PiB-PET). MCI subjects were divided into PiB-positive and PiB-negative subgroups. SPECT data was analyzed using the Specific Volume of interest Analysis of the eZIS program. Three indicators (severity, extent, and ratio) were calculated automatically and compared between the two subgroups.

RESULTS

Five of 12 (41.7%) subjects in the PiB-positive subgroup and three of 11 (27.3%) subjects in the PiB-negative subgroup showed the abnormal value for each indicator. The frequency of subjects with abnormal ratio values was significantly higher in the PiB-positive subgroup compared to the PiB-negative subgroup (p=0.02), whereas that of subjects with abnormal values in severity and extent did not differ among the two subgroups. In particular, all subjects in the PiB-negative subgroup showed normal ratio values. Moreover, the subjects with abnormal values on two indicators, including ratio, or on all three indicators, showed PiB-positive.

CONCLUSION

The analysis of brain perfusion SPECT using an eZIS program cannot identify the amnestic MCI subjects with brain amyloid-β deposition. However, abnormal three indicators or normal ratio values may be helpful SPECT findings for predicting the results of PiB-PET in the amnestic MCI subjects.

Mild Cognitive Impairment

Mild cognitive impairment (MCI) occurs along a continuum from normal cognition to dementia. A roadblock to earlier diagnosis and potential treatment is the lack of consistency with screening for MCI. Universal screening would be ideal, but is limited. Once a diagnosis of MCI is made, it is important for the clinician to evaluate for reversible causes. At present time, there are no pharmacologic treatments proven to slow or cure progression of MCI to dementia; nonetheless, there is evidence that lifestyle modifications including diet, exercise, and cognitive stimulation may be effective.

PET Imaging for Early Detection of Alzheimer's Disease: From Pathologic to Physiologic Biomarkers

This article describes the application of various PET imaging agents in the investigation and diagnosis of Alzheimer's disease (AD), including radiotracers for pathologic biomarkers of AD such as β-amyloid deposits and tau protein aggregates, and the neuroinflammation biomarker 18 kDa translocator protein, as well as physiologic biomarkers, such as cholinergic receptors, glucose metabolism, and the synaptic density biomarker synaptic vesicle glycoprotein 2A. Potential of these biomarkers for early AD diagnosis is also assessed.

The Role of Neuroimaging in the Assessment of the Cognitively Impaired Elderly

This article reviews the current diagnostic tools that are available for structural, functional, and molecular imaging of the brain, summarizing some of the key findings that have been reported in individuals diagnosed with Alzheimer disease, mild cognitive impairment, prodromal AD, or other prevalent dementias. Given recent advances in the development of amyloid PET tracers, current guidelines for the use of amyloid PET imaging in patients with cognitive complaints are reviewed. In addition, data addressing the potential value of amyloid PET imaging in the clinical setting are highlighted.

Cerebral blood flow MRI in the nondemented elderly is not predictive of post-operative delirium but is correlated with cognitive performance

Three-dimensional Arterial Spin Labeling (ASL) MRI was performed before surgery in a cohort of 146 prospectively enrolled subjects ≥ 70 years old scheduled to undergo elective surgery. We investigated the prospective association between ASL-derived measures of cerebral blood flow (CBF) before surgery with postoperative delirium incidence and severity using whole-brain and globally normalized voxel-wise analysis. We also investigated the cross-sectional association of CBF with patients' baseline performance on specific neuropsychological tests, and with a composite general cognitive performance measure (GCP). Out of 146 subjects, 32 (22%) developed delirium. We found no significant association between global and voxel-wise CBF with delirium incidence or severity. We found the most significant positive associations between CBF of the posterior cingulate and precuneus and the Hopkins Verbal Learning Test - Revised total score, Visual Search and Attention Test (VSAT) score and the GCP composite. VSAT score was also strongly associated with right parietal lobe CBF. ASL can be employed in a large, well-characterized older cohort to examine associations between CBF and age-related cognitive performance. Although ASL CBF measures in regions previously associated with preclinical Alzheimer's Disease were correlated with cognition, they were not found to be indicators of baseline pathology that may increase risk for delirium.

Structural MRI and Amyloid PET Imaging for Prediction of Conversion to Alzheimer's Disease in Patients with Mild Cognitive Impairment: A Meta-Analysis

OBJECTIVE

The aim of this study was to explore the prognostic values of biomarkers of neurodegeneration as measured by magnetic resonance imaging (MRI) and amyloid burden as measured by amyloid positron emission tomography (PET) in predicting conversion to Alzheimer's disease (AD) in patients with mild cognitive impairment (MCI).

METHODS

PubMed and EMBASE databases were searched for structural MRI or amyloid PET imaging studies published between January 2000 and July 2014 that reported conversion to AD in patients with MCI. Means and standard deviations or individual numbers of biomarkers with positive or negative status at baseline and corresponding numbers of patients who had progressed to AD at follow-up were retrieved from each study. The effect size of each biomarker was expressed as Hedges's g.

RESULTS

Twenty-four MRI studies and 8 amyloid PET imaging studies were retrieved. 674 of the 1741 participants (39%) developed AD. The effect size for predicting conversion to AD was 0.770 [95% confidence interval (CI) 0.607-0.934] for across MRI and 1.316 (95% CI 0.920-1.412) for amyloid PET imaging (p<0.001). The effect size was 1.256 (95% CI 0.902-1.609) for entorhinal cortex volume from MRI.

CONCLUSION

Our study suggests that volumetric MRI measurement may be useful for the early detection of AD.

Prediction of Mild Cognitive Impairment Conversion Using a Combination of Independent Component Analysis and the Cox Model

Mild cognitive impairment (MCI) represents a transitional stage from normal aging to Alzheimer’s disease (AD) and corresponds to a higher risk of developing AD. Thus, it is necessary to explore and predict the onset of AD in MCI stage. In this study, we propose a combination of independent component analysis (ICA) and the multivariate Cox proportional hazards regression model to investigate promising risk factors associated with MCI conversion among 126 MCI converters and 108 MCI non-converters from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Using structural magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data, we extracted brain networks from AD and normal control groups via ICA and then constructed Cox models that included network-based neuroimaging factors for the MCI group. We carried out five separate Cox analyses and the two-modality neuroimaging Cox model identified three significant network-based risk factors with higher prediction performance (accuracy = 73.50%) than those in either single-modality model (accuracy = 68.80%). Additionally, the results of the comprehensive Cox model, including significant neuroimaging factors and clinical variables, demonstrated that MCI individuals with reduced gray matter volume in a temporal lobe-related network of structural MRI [hazard ratio (HR) = 8.29E-05 (95% confidence interval (CI), 5.10E- 07 ~ 0.013)], low glucose metabolism in the posterior default mode network based on FDG-PET [HR = 0.066 (95% CI, 4.63E-03 ~ 0.928)], positive apolipoprotein E ε4-status [HR = 1. 988 (95% CI, 1.531 ~ 2.581)], increased Alzheimer’s Disease Assessment Scale-Cognitive Subscale scores [HR = 1.100 (95% CI, 1.059 ~ 1.144)] and Sum of Boxes of Clinical Dementia Rating scores [HR = 1.622 (95% CI, 1.364 ~ 1.930)] were more likely to convert to AD within 36 months after baselines. These significant risk factors in such comprehensive Cox model had the best prediction ability (accuracy = 84.62%, sensitivity = 86.51%, specificity = 82.41%) compared to either neuroimaging factors or clinical variables alone. These results suggested that a combination of ICA and Cox model analyses could be used successfully in survival analysis and provide a network-based perspective of MCI progression or AD-related studies.

Utility of Molecular and Structural Brain Imaging to Predict Progression from Mild Cognitive Impairment to Dementia

This project compares three neuroimaging biomarkers to predict progression to dementia in subjects with mild cognitive impairment (MCI). Eighty-eight subjects with MCI and 40 healthy controls (HCs) were recruited. Subjects had a 3T magnetic resonance imaging (MRI) scan, and two positron emission tomography (PET) scans, one with Pittsburgh compound B ([11C]PIB) and one with fluorodeoxyglucose ([18F]FDG). MCI subjects were followed for up to 4 y and progression to dementia was assessed on an annual basis. MCI subjects had higher [11C]PIB binding potential (BPND) than HCs in multiple brain regions, and lower hippocampus volumes. [11C]PIB BPND, [18F]FDG standard uptake value ratio (SUVR), and hippocampus volume were associated with time to progression to dementia using a Cox proportional hazards model. [18F]FDG SUVR demonstrated the most statistically significant association with progression, followed by [11C]PIB BPND and then hippocampus volume. [11C]PIB BPND and [18F]FDG SUVR were independently predictive, suggesting that combining these measures is useful to increase accuracy in the prediction of progression to dementia. Hippocampus volume also had independent predictive properties to [11C]PIB BPND, but did not add predictive power when combined with the [18F]FDG SUVR data. This work suggests that PET imaging with both [11C]PIB and [18F]FDG may help to determine which MCI subjects are likely to progress to AD, possibly directing future treatment options.

Allocentric Spatial Memory Testing Predicts Conversion from Mild Cognitive Impairment to Dementia: An Initial Proof-of-Concept Study

The hippocampus is one of the first regions to exhibit neurodegeneration in Alzheimer's disease (AD), and knowledge of its role in allocentric spatial memory may therefore aid early diagnosis of AD. The 4 Mountains Test (4MT) is a short and easily administered test of spatial memory based on the cognitive map theory of hippocampal function as derived from rodent single cell and behavioral studies. The 4MT has been shown in previous cross-sectional studies to be sensitive and specific for mild cognitive impairment (MCI) due to AD. This report describes the initial results of a longitudinal study testing the hypothesis that allocentric spatial memory is predictive of conversion from MCI to dementia. Fifteen patients with MCI underwent baseline testing on the 4MT in addition to CSF amyloid/tau biomarker studies, volumetric MRI and neuropsychological assessment including the Rey Auditory Verbal Learning Test (RAVLT) and Trail Making Test "B" (TMT-B). At 24 months, 9/15 patients had converted to AD dementia. The 4MT predicted conversion to AD with 93% accuracy (Cohen's d = 2.52). The predictive accuracies of the comparator measures were as follows: CSF tau/β-amyloid_1-42 ratio 92% (d = 1.81), RAVLT 64% (d = 0.41), TMT-B 78% (d = 1.56), and hippocampal volume 77% (d = 0.65). CSF tau levels were strongly negatively correlated with 4MT scores (r = -0.71). This proof-of-concept study provides initial support for the hypothesis that allocentric spatial memory testing is a predictive cognitive marker of hippocampal neurodegeneration in pre-dementia AD. The 4MT is a brief, non-invasive, straightforward spatial memory test and is therefore ideally suited for use in routine clinical diagnostic practice. This is of particular importance given the current unmet need for simple accurate diagnostic tests for early AD and the ongoing development of potential disease-modifying therapeutic agents, which may be more efficacious when given earlier in the disease course. By applying a test based on studies of hippocampal function in rodents to patient populations, this work represents the first step in the development of translatable biomarkers of hippocampal involvement in early AD for use in both animal models and human subjects.

Clinical Amyloid Imaging

Amyloid plaques, along with neurofibrillary tangles, are a neuropathologic hallmark of Alzheimer disease (AD). Recently, amyloid PET radiotracers have been developed and approved for clinical use in the evaluation of suspected neurodegenerative disorders. In both research and clinical settings, amyloid PET imaging has provided important diagnostic and prognostic information for the management of patients with possible AD, mild cognitive impairment (MCI), and other challenging diagnostic presentations. Although the overall impact of amyloid imaging is still being evaluated, the Society of Nuclear Medicine and Molecular Imaging and Alzheimer's Association Amyloid Imaging Task Force have created appropriate use criteria for the standard clinical use of amyloid PET imaging. By the appropriate use criteria, amyloid imaging is appropriate for patients with (1) persistent or unexplained MCI, (2) AD as a possible but still uncertain diagnosis after expert evaluation and (3) atypically early-age-onset progressive dementia. To better understand the clinical and economic effect of amyloid imaging, the Imaging Dementia-Evidence for Amyloid Scanning (IDEAS) study is an ongoing large multicenter study in the United States, which is evaluating how amyloid imaging affects diagnosis, management, and outcomes for cognitively impaired patients who cannot be completely evaluated by clinical assessment alone. Multiple other large-scale studies are evaluating the prognostic role of amyloid PET imaging for predicting MCI progression to AD in general and high-risk populations. At the same time, amyloid imaging is an important tool for evaluating potential disease-modifying therapies for AD. Overall, the increased use of amyloid PET imaging has led to a better understanding of the strengths and limitations of this imaging modality and how it may best be used with other clinical, molecular, and imaging assessment techniques for the diagnosis and management of neurodegenerative disorders.

Brain fluorodeoxyglucose (FDG) PET in dementia

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

Alzheimer's Disease Cerebrospinal Fluid and Neuroimaging Biomarkers: Diagnostic Accuracy and Relationship to Drug Efficacy

Widely researched Alzheimer's disease (AD) biomarkers include in vivo brain imaging with PET and MRI, imaging of amyloid plaques, and biochemical assays of Aβ 1 - 42, total tau, and phosphorylated tau (p-tau-181) in cerebrospinal fluid (CSF). In this review, we critically evaluate these biomarkers and discuss their clinical utility for the differential diagnosis of AD. Current AD biomarker tests are either highly invasive (requiring CSF collection) or expensive and labor-intensive (neuroimaging), making them unsuitable for use in the primary care, clinical office-based setting, or to assess drug efficacy in clinical trials. In addition, CSF and neuroimaging biomarkers continue to face challenges in achieving required sensitivity and specificity and minimizing center-to-center variability (for CSF-Aβ 1 - 42 biomarkers CV = 26.5% ; http://www.alzforum.org/news/conference-coverage/paris-standardization-hurdle-spinal-fluid-imaging-markers). Although potentially useful for selecting patient populations for inclusion in AD clinical trials, the utility of CSF biomarkers and neuroimaging techniques as surrogate endpoints of drug efficacy needs to be validated. Recent trials of β- and γ-secretase inhibitors and Aβ immunization-based therapies in AD showed no significant cognitive improvements, despite changes in CSF and neuroimaging biomarkers. As we learn more about the dysfunctional cellular and molecular signaling processes that occur in AD, and how these processes are manifested in tissues outside of the brain, new peripheral biomarkers may also be validated as non-invasive tests to diagnose preclinical and clinical AD.

PET imaging in neurology: Alzheimer's and Parkinson's diseases

PET studies play an important role in the early detection of Alzheimer's and Parkinson's diseases (AD and PD). Fluorine-18 fluorodeoxyglucose (F-FDG) PET imaging of regional cerebral glucose metabolism and PET amyloid imaging are the two major PET studies for AD. F-FDG PET is highly sensitive for the early diagnosis of AD, in predicting conversion from mild cognitive impairment to AD, and in differentiating AD from other dementias. PET amyloid imaging is positive in the majority of patients with AD. Negative amyloid PET reduces the likelihood of AD. The main limitations of PET amyloid imaging is its high positivity in the normal elderly population and in other medical conditions with amyloid pathologies. Various PET tracers are available to assess motor and cognitive dysfunctions in PD. PET tracers targeting presynaptic dopaminergic function (F-DOPA, radiolabeled PET tracers assessing the availability of dopamine transporters and vesicular monoamine transporters) and postsynaptic dopamine receptors are used to assess motor dysfunction in PD. PET tracers, particularly dopamine transporters, are highly sensitive in the early diagnosis of PD. Uptake of PET tracers in the striatum is inversely correlated with disease severity. PET is valuable in differentiating PD from other movement disorders. PET studies, particularly F-FDG PET, help to evaluate cortical metabolism in PD patients with cognitive dysfunction and dementia.

Neuroimaging of hippocampal atrophy in early recognition of Alzheimer's disease--a critical appraisal after two decades of research

As a characteristic feature of Alzheimer's disease (AD) hippocampal atrophy (HA) can be demonstrated in the majority of patients by using neuroimaging techniques in particular magnetic resonance imaging (MRI). Hippocampal atrophy is associated with declarative memory deficits and can also be associated with changes of adjacent medial temporal substructures such as the parahippocampal gyrus or the the entorhinal cortex. Similar findings are present in patients with mild cognitive impairment (MCI) albeit to a lesser extent. While these finding facilitate the diagnostic process in patients with clinical suspicious AD, the metric properties of hippocampal atrophy for delineating healthy aging from MCI and mild AD still appear to be rather limited; as such it is not sufficient to establish the diagnosis of AD (and even more so of MCI). This limitation partly refers to methodological issues and partly to the fact that hippocampal tissue integrity is subject to various pathogenetic influences other than AD. Moreover,the effects of hippocampal atrophy on the behavioral level (e.g. cognitive deficits) are modulated by the individual's cognitive reserve. From a clinical standpoint these observations are in line with the hypothesis that the onset and course of AD is influenced by a number of peristatic factors which are partly conceptualized in the concepts of brain and/or cognitive reserve. These complex interactions have to be considered when using the presence of hippocampal atrophy in the routine diagnostic procedure of AD.

Genetic and degenerative disorders primarily causing dementia

Neuroimaging comprises a powerful set of instruments to diagnose the different causes of dementia, clarify their neurobiology, and monitor their treatment. Magnetic resonance imaging (MRI) depicts volume changes with neurodegeneration and inflammation, as well as abnormalities in functional and structural connectivity. MRI arterial spin labeling allows for the quantification of regional cerebral blood flow, characteristically altered in Alzheimer's disease, diffuse Lewy-body disease, and the frontotemporal dementias. Positron emission tomography allows for the determination of regional metabolism, with similar abnormalities as flow, and for the measurement of β-amyloid and abnormal tau deposition in the brain, as well as regional inflammation. These instruments allow for the quantification in vivo of most of the pathologic features observed in disorders causing dementia. Importantly, they allow for the longitudinal study of these abnormalities, having revealed, for instance, that the deposition of β-amyloid in the brain can antecede by decades the onset of dementia. Thus, a therapeutic window has been opened and the efficacy of immunotherapies directed at removing β-amyloid from the brain of asymptomatic individuals is currently being tested. Tau and inflammation imaging, still in their infancy, combined with genomics, should provide powerful insights into these disorders and facilitate their treatment.

Brain PET in the diagnosis of Alzheimer's disease

OBJECTIVES

The aim of this article was to review the current role of brain PET in the diagnosis of Alzheimer dementia. The characteristic patterns of glucose metabolism on brain FDG-PET can help in differentiating Alzheimer's disease from other causes of dementia such as frontotemporal dementia and dementia of Lewy body. Amyloid brain PET may exclude significant amyloid deposition and thus Alzheimer's disease in appropriate clinical setting.

CONCLUSIONS

FDG-PET and amyloid PET imaging are valuable in the assessment of patients with Alzheimer's disease.

Multimodal imaging in Alzheimer's disease: validity and usefulness for early detection

Alzheimer's disease is a progressive neurodegenerative disease that typically manifests clinically as an isolated amnestic deficit that progresses to a characteristic dementia syndrome. Advances in neuroimaging research have enabled mapping of diverse molecular, functional, and structural aspects of Alzheimer's disease pathology in ever increasing temporal and regional detail. Accumulating evidence suggests that distinct types of imaging abnormalities related to Alzheimer's disease follow a consistent trajectory during pathogenesis of the disease, and that the first changes can be detected years before the disease manifests clinically. These findings have fuelled clinical interest in the use of specific imaging markers for Alzheimer's disease to predict future development of dementia in patients who are at risk. The potential clinical usefulness of single or multimodal imaging markers is being investigated in selected patient samples from clinical expert centres, but additional research is needed before these promising imaging markers can be successfully translated from research into clinical practice in routine care.

Brain Metabolism of Less-Educated Patients With Alzheimer Dementia Studied by Positron Emission Tomography

Alzheimer dementia (AD) is the commonest form of dementia. Although illiteracy is associated with high prevalence of dementia of the Alzheimer type (DAT), their relationship is still unclear. Nevertheless, mild DAT in illiterate participants seems to be due to brain atrophy.In this study, we compared the impact of brain metabolism efficiency in healthy participants and less-educated patients with mild DAT using 2-fluoro-2-deoxy-D-glucose (F-FDG-PET) positron emission tomography. Out of 43 eligible less-educated participants with dementia, only 23 (14 women and 9 men) met Diagnostic and Statistical Manual (DSM)-III-R or DSM-IV criteria for DAT and AD and were included. Participants with intracranial insults were excluded by brain magnetic resonance imaging and participants with metabolic or systemic conditions were excluded by blood sampling. In addition, 16 cognitively normal elderly (age >70 years), including 7 women and 9 men, were enrolled in the sham group. The PET imaging data were analyzed using statistical parametric mapping (SPM8) to determine reliability and specificity.Glucose metabolic rate was low in the DAT group, especially in the middle temporal gyrus, middle frontal gyrus, superior frontal gyrus, inferior frontal gyrus, posterior cingulate gyrus, angular gyrus, parahippocampal gyrus, middle occipital gyrus, rectal gyrus, and lingual gyrus.Our results showed that DAT patients with less education not only have prominent clinical signs and symptoms related to dementia but also decreased gray matter metabolism.

Recommendations for the use of PET imaging biomarkers in the diagnosis of neurodegenerative conditions associated with dementia: SEMNIM and SEN consensus

The new diagnostic criteria for Alzheimer's disease (AD) acknowledges the interest given to biomarkers to improve the specificity in subjects with dementia and to facilitate an early diagnosis of the pathophysiological process of AD in the prodromal or pre-dementia stage. The current availability of PET imaging biomarkers of synaptic dysfunction (PET-FDG) and beta amyloid deposition using amyloid-PET provides clinicians with the opportunity to apply the new criteria and improve diagnostic accuracy in their clinical practice. Therefore, it seems essential for the scientific societies involved to use the new clinical diagnostic support tools to establish clear, evidence-based and agreed set of recommendations for their appropriate use. The present work includes a systematic review of the literature on the utility of FDG-PET and amyloid-PET for the diagnosis of AD and related neurodegenerative diseases that occur with dementia. Thus, we propose a series of recommendations agreed on by the Spanish Society of Nuclear Medicine and Spanish Society of Neurology as a consensus statement on the appropriate use of PET imaging biomarkers.

Is quality and completeness of reporting of systematic reviews and meta-analyses published in high impact radiology journals associated with citation rates?

PURPOSE

The purpose of this study is to determine whether study quality and completeness of reporting of systematic reviews (SR) and meta-analyses (MA) published in high impact factor (IF) radiology journals is associated with citation rates.

METHODS

All SR and MA published in English between Jan 2007-Dec 2011, in radiology journals with an IF >2.75, were identified on Ovid MEDLINE. The Assessing the Methodologic Quality of Systematic Reviews (AMSTAR) checklist for study quality, and the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist for study completeness, was applied to each SR & MA. Each SR & MA was then searched in Google Scholar to yield a citation rate. Spearman correlation coefficients were used to assess the relationship between AMSTAR and PRISMA results with citation rate. Multivariate analyses were performed to account for the effect of journal IF and journal 5-year IF on correlation with citation rate. Values were reported as medians with interquartile range (IQR) provided.

RESULTS

129 studies from 11 journals were included (50 SR and 79 MA). Median AMSTAR result was 8.0/11 (IQR: 5-9) and median PRISMA result was 23.0/27 (IQR: 21-25). The median citation rate for SR & MA was 0.73 citations/month post-publication (IQR: 0.40-1.17). There was a positive correlation between both AMSTAR and PRISMA results and SR & MA citation rate; ρ=0.323 (P=0.0002) and ρ=0.327 (P=0.0002) respectively. Positive correlation persisted for AMSTAR and PRISMA results after journal IF was partialed out; ρ=0.243 (P=0.006) and ρ=0.256 (P=0.004), and after journal 5-year IF was partialed out; ρ=0.235 (P=0.008) and ρ=0.243 (P=0.006) respectively.

CONCLUSION

There is a positive correlation between the quality and the completeness of a reported SR or MA with citation rate which persists when adjusted for journal IF and journal 5-year IF.

Using structural and diffusion magnetic resonance imaging to differentiate the dementias

Dementia is one of the major causes of personal, societal and financial dependence in older people and in today's ageing society there is a pressing need for early and accurate markers of cognitive decline. There are several subtypes of dementia but the four most common are Alzheimer's disease, Lewy body dementia, vascular dementia and frontotemporal dementia. These disorders can only be diagnosed at autopsy, and ante-mortem assessments of "probable dementia (e.g. of Alzheimer type)" are traditionally driven by clinical symptoms of cognitive or behavioural deficits. However, owing to the overlapping nature of symptoms and age of onset, a significant proportion of dementia cases remain incorrectly diagnosed. Misdiagnosis can have an extensive impact, both at the level of the individual, who may not be offered the appropriate treatment, and on a wider scale, by influencing the entry of patients into relevant clinical trials. Magnetic resonance imaging (MRI) may help to improve diagnosis by providing non-invasive and detailed disease-specific markers of cognitive decline. MRI-derived measurements of grey and white matter structural integrity are potential surrogate markers of disease progression, and may also provide valuable diagnostic information. This review summarises the latest evidence on the use of structural and diffusion MRI in differentiating between the four major dementia subtypes.

Diagnostic tools for alzheimer's disease dementia and other dementias: an overview of diagnostic test accuracy (DTA) systematic reviews

BACKGROUND

Dementia includes a group of neurodegenerative disorders characterized by progressive loss of cognitive function and a decrease in the ability to perform activities of daily living. Systematic reviews of diagnostic test accuracy (DTA) focus on how well the index test detects patients with the disease in terms of figures such as sensitivity and specificity. Although DTA reviews about dementia are essential, at present there is no information about their quantity and quality.

METHODS

We searched for DTA reviews in MEDLINE (1966-2013), EMBASE (1980-2013), The Cochrane Library (from its inception until December 2013) and the Database of Abstracts of Reviews of Effects (DARE). Two reviewers independently assessed the methodological quality of the reviews using the AMSTAR measurement tool, and the quality of the reporting using the PRISMA checklist. We describe the main characteristics of these reviews, including basic characteristics, type of dementia, and diagnostic test evaluated, and we summarize the AMSTAR and PRISMA scores.

RESULTS

We selected 24 DTA systematic reviews. Only 10 reviews (41.6%), assessed the bias of included studies and few (33%) used this information to report the review results or to develop their conclusions Only one review (4%) reported all methodological items suggested by the PRISMA tool. Assessing methodology quality by means of the AMSTAR tool, we found that six DTA reviews (25%) pooled primary data with the aid of methods that are used for intervention reviews, such as Mantel-Haenszel and separate random-effects models (25%), while five reviews (20.8%) assessed publication bias by means of funnel plots and/or Egger's Test.

CONCLUSIONS

Our assessment of these DTA reviews reveals that their quality, both in terms of methodology and reporting, is far from optimal. Assessing the quality of diagnostic evidence is fundamental to determining the validity of the operating characteristics of the index test and its usefulness in specific settings. The development of high quality DTA systematic reviews about dementia continues to be a challenge.

The link between cardiovascular risk, Alzheimer's disease, and mild cognitive impairment: support from recent functional neuroimaging studies

OBJECTIVE

To review functional neuroimaging studies about the relationship between cardiovascular risk factors (CVRFs), Alzheimer's disease (AD), and mild cognitive impairment (MCI).

METHODS

We performed a comprehensive literature search to identify articles in the neuroimaging field addressing CVRF in AD and MCI. We included studies that used positron emission tomography (PET), single photon emission computerized tomography (SPECT), or functional magnetic resonance imaging (fMRI).

RESULTS

CVRFs have been considered risk factors for cognitive decline, MCI, and AD. Patterns of AD-like changes in brain function have been found in association with several CVRFs (both regarding individual risk factors and also composite CVRF measures). In vivo assessment of AD-related pathology with amyloid imaging techniques provided further evidence linking CVRFs and AD, but there is still limited information resulting from this new technology.

CONCLUSION

There is a large body of evidence from functional neuroimaging studies supporting the hypothesis that CVRFs may play a causal role in the pathophysiology of AD. A major limitation of most studies is their cross-sectional design; future longitudinal studies using multiple imaging modalities are expected to better document changes in CVRF-related brain function patterns and provide a clearer picture of the complex relationship between aging, CVRFs, and AD.

A comparison of FDG-PET and blood flow SPECT in the diagnosis of neurodegenerative dementias: a systematic review

OBJECTIVE

Perfusion single photon emission computed tomography (SPECT) and 18F fluorodeoxyglucose positron emission tomography (FDG-PET) both have clinical utility for the differential diagnosis of dementia. Although PET is often viewed by some as more accurate and therefore preferential, the extent to which published evidence supports this is not clear. The aim of this review was to address the question by reviewing studies of SPECT and PET imaging in dementia diagnosis, with a particular focus on all published head-to-head studies.

DESIGN

A MEDLINE search was carried out using the following keywords: "PET" and "SPECT" and "dementia" or "Mild Cognitive Impairment," together with "alzheimers" or "DLB" or "lewy body" or "frontotemporal" or "FTD" or "Picks." Articles were included up to February 2013, limited to human studies and in English language.

RESULTS

Published studies of SPECT accuracy show that it is a useful tool for differential diagnosis, with sensitivities of 65-85% for diagnosing Alzheimer's disease (AD) and specificities (for other neurodegenerative dementias) of 72-87%. PET studies generally report higher accuracy, with sensitivities of 75-99% for AD and specificities of 71-93%. However, there have been few direct head-to-head comparisons, with some indicating SPECT and PET to be equally useful in dementia diagnosis and others favouring PET. Many of these studies are limited with respect to numbers and methodically with poorly matched control groups.

CONCLUSIONS

Overall, although studies suggest superiority of PET over SPECT, the evidence base for this is actually quite limited. We suggest that further direct comparative studies, including health economic and patient preference evaluations, are needed to help direct future service provision.

Systematic Comparison of the Performance of Integrated Whole-Body PET/MR Imaging to Conventional PET/CT for ¹⁸F-FDG Brain Imaging in Patients Examined for Suspected Dementia

Technologic specifications of recently introduced integrated PET/MR instrumentation, such as MR-based attenuation correction, may particularly affect brain imaging procedures. To evaluate the qualitative performance of PET/MR in clinical neuroimaging, we systematically compared results obtained with integrated PET/MR with conventional PET/CT in the same patients examined for assessment of cognitive impairment.

METHODS

Thirty patients underwent a single-injection ((18)F-FDG), dual-imaging protocol including PET/CT and integrated PET/MR imaging in randomized order. Attenuation and scatter correction were performed using low-dose CT for the PET/CT and segmented Dixon MR imaging data for the PET/MR. Differences between PET/MR and PET/CT were assessed via region-of-interest (ROI)-based and voxel-based statistical group comparison. Analyses involved attenuation-corrected (AC) and non-attenuation-corrected (NAC) data. Individual PET/MR and PET/CT datasets were compared versus a predefined independent control population, using 3-dimensional stereotactic surface projections.

RESULTS

Generally, lower measured PET signal values were obtained throughout the brain in ROI-based quantification of the PET signal for PET/MR as compared with PET/CT in AC and NAC data, independently of the scan order. After elimination of global effects, voxel-based and ROI-based group comparison still revealed significantly lower relative tracer signal in PET/MR images in frontoparietal portions of the neocortex but significantly higher relative signal in subcortical and basal regions of the brain than the corresponding PET/CT images of the AC data. In the corresponding NAC images, the discrepancies in frontoparietal portions of the neocortex were diminished, but the subcortical overestimation of tracer intensity by PET/MR persisted.

CONCLUSION

Considerable region-dependent differences were observed between brain imaging data acquired on the PET/MR, compared with corresponding PET/CT images, in patients evaluated for neurodegenerative disorders. These findings may only in part be explained by inconsistencies in the attenuation-correction procedures. The observed differences may interfere with semiquantitative evaluation and with individual qualitative clinical assessment and they need to be considered, for example, for clinical trials. Improved attenuation-correction algorithms and a PET/MR-specific healthy control database are recommended for reliable and consistent application of PET/MR for clinical neuroimaging.

Potential Clinical Applications of PET/MR Imaging in Neurodegenerative Diseases

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

Early detection of Alzheimer's disease using PiB and FDG PET

Use of biomarkers in the detection of early and preclinical Alzheimer's disease (AD) has become of central importance following publication of the NIA-Alzheimer's Association revised criteria for the diagnosis of AD, mild cognitive impairment (MCI) and preclinical AD. The use of in vivo amyloid imaging agents, such a Pittsburgh Compound-B and markers of neurodegeneration, such as fluoro-2-deoxy-D-glucose (FDG) is able to detect early AD pathological processes and subsequent neurodegeneration. Imaging with PiB and FDG thus has many potential clinical benefits: early or perhaps preclinical detection of disease and accurately distinguishing AD from dementias of other etiologies in patients presenting with mild or atypical symptoms or confounding comorbidities in which the diagnostic distinction is difficult to make clinically. From a research perspective, this allows us to study relationships between amyloid pathology and changes in cognition, brain structure, and function across the continuum from normal aging to MCI to AD. The present review focuses on use of PiB and FDG-PET and their relationship to one another.

A survey of FDG- and amyloid-PET imaging in dementia and GRADE analysis

PET based tools can improve the early diagnosis of Alzheimer's disease (AD) and differential diagnosis of dementia. The importance of identifying individuals at risk of developing dementia among people with subjective cognitive complaints or mild cognitive impairment has clinical, social, and therapeutic implications. Within the two major classes of AD biomarkers currently identified, that is, markers of pathology and neurodegeneration, amyloid- and FDG-PET imaging represent decisive tools for their measurement. As a consequence, the PET tools have been recognized to be of crucial value in the recent guidelines for the early diagnosis of AD and other dementia conditions. The references based recommendations, however, include large PET imaging literature based on visual methods that greatly reduces sensitivity and specificity and lacks a clear cut-off between normal and pathological findings. PET imaging can be assessed using parametric or voxel-wise analyses by comparing the subject's scan with a normative data set, significantly increasing the diagnostic accuracy. This paper is a survey of the relevant literature on FDG and amyloid-PET imaging aimed at providing the value of quantification for the early and differential diagnosis of AD. This allowed a meta-analysis and GRADE analysis revealing high values for PET imaging that might be useful in considering recommendations.

Imaging markers for Alzheimer disease: which vs how

Revised diagnostic criteria for Alzheimer disease (AD) acknowledge a key role of imaging biomarkers for early diagnosis. Diagnostic accuracy depends on which marker (i.e., amyloid imaging, ¹⁸F-fluorodeoxyglucose [FDG]-PET, SPECT, MRI) as well as how it is measured ("metric": visual, manual, semiautomated, or automated segmentation/computation). We evaluated diagnostic accuracy of marker vs metric in separating AD from healthy and prognostic accuracy to predict progression in mild cognitive impairment. The outcome measure was positive (negative) likelihood ratio, LR+ (LR-), defined as the ratio between the probability of positive (negative) test outcome in patients and the probability of positive (negative) test outcome in healthy controls. Diagnostic LR+ of markers was between 4.4 and 9.4 and LR- between 0.25 and 0.08, whereas prognostic LR+ and LR- were between 1.7 and 7.5, and 0.50 and 0.11, respectively. Within metrics, LRs varied up to 100-fold: LR+ from approximately 1 to 100; LR- from approximately 1.00 to 0.01. Markers accounted for 11% and 18% of diagnostic and prognostic variance of LR+ and 16% and 24% of LR-. Across all markers, metrics accounted for an equal or larger amount of variance than markers: 13% and 62% of diagnostic and prognostic variance of LR+, and 29% and 18% of LR-. Within markers, the largest proportion of diagnostic LR+ and LR- variability was within ¹⁸F-FDG-PET and MRI metrics, respectively. Diagnostic and prognostic accuracy of imaging AD biomarkers is at least as dependent on how the biomarker is measured as on the biomarker itself. Standard operating procedures are key to biomarker use in the clinical routine and drug trials.

Structural and Functional Magnetic Resonance Imaging: Mild Cognitive Impairment and Alzheimer Disease

Magnetic resonance (MR) imaging is playing an increasingly pivotal role in the clinical management of dementia, including Alzheimer disease (AD). In addition to established MR imaging procedures, the introduction of advanced instrumentation such as 7-T MR imaging, as well as novel MR imaging sequences such as arterial spin labeling, MR spectroscopy, diffusion tensor imaging, and resting-state functional MR imaging, may open new pathways toward improved diagnosis of AD even in early stages of disease such as mild cognitive impairment (MCI). This article describes the typical findings of established and new MR imaging procedures in healthy aging, MCI, and AD.

Prediction of outcomes in MCI with (123)I-IMP-CBF SPECT: a multicenter prospective cohort study

Objective

The multicenter prospective cohort study (Japan Cooperative SPECT Study on Assessment of Mild Impairment of Cognitive Function: J-COSMIC) aimed to examine the value of ¹²³I-N-isopropyl-4-iodoamphetamine cerebral blood flow (IMP-CBF) SPECT in regards to early diagnosis of Alzheimer’s disease (AD) in patients with mild cognitive impairment (MCI).

Methods

Three hundred and nineteen patients with amnestic MCI at 41 participating institutions each underwent clinical and neuropsychological examinations and ¹²³I-IMP-CBF SPECT at baseline. Subjects were followed up periodically for 3 years, and progression to dementia was evaluated. SPECT images were classified as AD/DLB (dementia with Lewy bodies) pattern and non-AD/DLB pattern by central image interpretation and automated region of interest (ROI) analysis, respectively. Logistic regression analyses were used to assess whether baseline ¹²³I-IMP-CBF SPECT was predictive of longitudinal clinical outcome.

Results

Ninety-nine of 216 amnestic MCI patients (excluding 3 cases with epilepsy (n = 2) or hydrocephalus (n = 1) and 100 cases with incomplete follow-up) converted to AD within the observation period. Central image interpretation and automated ROI analysis predicted conversion to AD with 56 and 58 % overall diagnostic accuracy (sensitivity, 76 and 81 %; specificity, 39 and 37 %), respectively. Multivariate logistic regression analysis identified SPECT as a predictor, which distinguished AD converters from non-converters. The odds ratio for a positive SPECT to predict conversion to AD with automated ROI analysis was 2.5 and combining SPECT data with gender and mini-mental state examination (MMSE) further improved classification (joint odds ratio 20.08).

Conclusions

¹²³I-IMP-CBF SPECT with both automated ROI analysis and central image interpretation was sensitive but relatively nonspecific for prediction of clinical outcome during the 3-year follow-up in individual amnestic MCI patients. A combination of statistically significant predictors, both SPECT with automated ROI analysis and neuropsychological evaluation, may increase predictive utility.

Electronic supplementary material

The online version of this article (doi:10.1007/s12149-013-0768-7) contains supplementary material, which is available to authorized users.

PET approaches for diagnosis of dementia

There is increasing use of neuroimaging modalities, including PET, for diagnosing dementia. For example, FDG-PET demonstrates hypometabolic regions in the posterior cingulate gyri, precuneus, and parietotemporal association cortices, while amyloid PET indicates amyloid deposition in Alzheimer disease and mild cognitive impairment due to Alzheimer disease. Furthermore, the use of combination PET with structural MR imaging can improve the diagnostic accuracy of dementia. In other neurodegenerative dementias, each disease exhibits a specific metabolic reduction pattern. In dementia with Lewy bodies, occipital glucose metabolism is decreased, while in frontotemporal dementia, frontal and anterior temporal metabolism is predominantly decreased. These FDG-PET findings and positive or negative amyloid deposits are important biomarkers for various neurodegenerative dementias.

Visual-statistical interpretation of (18)F-FDG-PET images for characteristic Alzheimer patterns in a multicenter study: inter-rater concordance and relationship to automated quantitative evaluation

BACKGROUND AND PURPOSE

The role of (18)F-FDG-PET in the diagnosis of Alzheimer disease is increasing and should be validated. The aim of this study was to assess the inter-rater variability in the interpretation of (18)F-FDG-PET images obtained in the Japanese Alzheimer's Disease Neuroimaging Initiative, a multicenter clinical research project.

MATERIALS AND METHODS

This study analyzed 274 (18)F-FDG-PET scans (67 mild Alzheimer disease, 100 mild cognitive impairment, and 107 normal cognitive) as baseline scans for the Japanese Alzheimer's Disease Neuroimaging Initiative, which were acquired with various types of PET or PET/CT scanners in 23 facilities. Three independent raters interpreted all PET images by using a combined visual-statistical method. The images were classified into 7 (FDG-7) patterns by the criteria of Silverman et al and further into 2 (FDG-2) patterns.

RESULTS

Agreement among the 7 visual-statistical categories by at least 2 of the 3 readers occurred in >94% of cases for all groups: Alzheimer disease, mild cognitive impairment, and normal cognitive. Perfect matches by all 3 raters were observed for 62% of the cases by FDG-7 and 76 by FDG-2. Inter-rater concordance was moderate by FDG-7 (κ = 0.57) and substantial in FDG-2 (κ = 0.67) on average. The FDG-PET score, an automated quantitative index developed by Herholz et al, increased as the number of raters who voted for the AD pattern increased (ρ = 0.59, P < .0001), and the FDG-PET score decreased as those for normal pattern increased (ρ = -0.64, P < .0001).

CONCLUSIONS

Inter-rater agreement was moderate to substantial for the combined visual-statistical interpretation of (18)F-FDG-PET and was also significantly associated with automated quantitative assessment.