Role of imaging techniques in the diagnosis of dementia

The association of GNB5 with Alzheimer disease revealed by genomic analysis restricted to variants impacting gene function

Disease-associated variants identified from genome-wide association studies (GWASs) frequently map to non-coding areas of the genome such as introns and intergenic regions. An exclusive reliance on gene-agnostic methods of genomic investigation could limit the identification of relevant genes associated with polygenic diseases such as Alzheimer disease (AD). To overcome such potential restriction, we developed a gene-constrained analytical method that considers only moderate- and high-risk variants that affect gene coding sequences. We report here the application of this approach to publicly available datasets containing 181,388 individuals without and with AD and the resulting identification of 660 genes potentially linked to the higher AD prevalence among Africans/African Americans. By integration with transcriptome analysis of 23 brain regions from 2,728 AD case-control samples, we concentrated on nine genes that potentially enhance the risk of AD: AACS, GNB5, GNS, HIPK3, MED13, SHC2, SLC22A5, VPS35, and ZNF398. GNB5, the fifth member of the heterotrimeric G protein beta family encoding Gβ5, is primarily expressed in neurons and is essential for normal neuronal development in mouse brain. Homozygous or compound heterozygous loss of function of GNB5 in humans has previously been associated with a syndrome of developmental delay, cognitive impairment, and cardiac arrhythmia. In validation experiments, we confirmed that Gnb5 heterozygosity enhanced the formation of both amyloid plaques and neurofibrillary tangles in the brains of AD model mice. These results suggest that gene-constrained analysis can complement the power of GWASs in the identification of AD-associated genes and may be more broadly applicable to other polygenic diseases.

Multimodal learning of clinically accessible tests to aid diagnosis of neurodegenerative disorders: a scoping review

With ageing populations around the world, there is a rapid rise in the number of people with Alzheimer's disease (AD) and Parkinson's disease (PD), the two most common types of neurodegenerative disorders. There is an urgent need to find new ways of aiding early diagnosis of these conditions. Multimodal learning of clinically accessible data is a relatively new approach that holds great potential to support early precise diagnosis. This scoping review follows the PRSIMA guidelines and we analysed 46 papers, comprising 11,750 participants, 3569 with AD, 978 with PD, and 2482 healthy controls; the recency of this topic was highlighted by nearly all papers being published in the last 5 years. It highlights the effectiveness of combining different types of data, such as brain scans, cognitive scores, speech and language, gait, hand and eye movements, and genetic assessments for the early detection of AD and PD. The review also outlines the AI methods and the model used in each study, which includes feature extraction, feature selection, feature fusion, and using multi-source discriminative features for classification. The review identifies knowledge gaps around the need to validate findings and address limitations such as small sample sizes. Applying multimodal learning of clinically accessible tests holds strong potential to aid the development of low-cost, reliable, and non-invasive methods for early detection of AD and PD.

Serial Nigrostriatal Dopaminergic Imaging in Mild Cognitive Impairment With Lewy Bodies, Alzheimer Disease, and Age-Matched Controls

BACKGROUND AND OBJECTIVES

Progressive nigrostriatal pathway degeneration occurs in individuals with dementia with Lewy bodies (LB). Our objective was to investigate whether repeat 123[I]-N-(3-fluoropropyl)-2β-carboxymethoxy-3β-(4-iodophenyl) nortropane (FP-CIT) single photon emission computed tomography (SPECT) can identify progressive dopaminergic loss in mild cognitive impairment (MCI) with Lewy bodies (MCI-LB).

METHODS

Individuals with MCI-LB and MCI due to Alzheimer disease (MCI-AD) underwent comprehensive clinical assessment, 123[I]-FP-CIT SPECT at baseline and annual reviews, and baseline cardiac 123 iodine metaiodobenzylguanidine (I-MIBG). Mixed-effects models were used to investigate changes in 123[I]-FP-CIT specific binding ratio (SBR) in the striatum for each diagnostic group compared with controls. The time interval to the development of a quantitatively abnormal 123[I]-FP-CIT SPECT in the possible and probable MCI-LB groups was determined as the time it took for these groups to reach a striatal uptake 2 SDs below aged-matched controls. Test-retest variation was assessed using baseline and repeat scans in controls.

RESULTS

We recruited 20 individuals with MCI-AD, 11 with possible MCI-LB, 25 with probable MCI-LB, and 29 age-matched controls. The mean time between baseline and the final image was 1.6 years (SD = 0.9, range 1.0-4.3). The annual estimated change in SBR was 0.23 for controls (95% CI -0.07 to 0.53), -0.09 (-0.55 to 0.36) for MCI-AD, -0.50 (-1.03 to 0.04) for possible MCI-LB, and -0.48 (-0.89 to -0.06) for probable MCI-LB. The median annual percentage change in SBR in MCI-LB was -5.6% (95% CI -8.2% to -2.9%) and 2.1% (-3.5% to 8.0%) for MCI-AD. The extrapolated time for a normal scan to become abnormal was 6 years. Controls and MCI-AD showed no significant change in dopaminergic binding over time. The mean test-retest variation in controls was 12% (SD 5.5%), which cautions against overinterpretation of small changes on repeat scanning.

DISCUSSION

Progressive dopaminergic loss in the striatum is detectable using 123[I]-FP-CIT SPECT in MCI-LB at a group level. In clinical practice, individual change in striatal 123[I]-FP-CIT uptake seems to be of limited diagnostic value because of high test-retest variation.

CLASSIFICATION OF EVIDENCE

This study provides Class II evidence that longitudinal declines in striatal uptake measured using 123[I]-FP-CIT SPECT are associated with MCI due to Lewy body disease but not MCI due to Alzheimer disease.

Investigation of Risk Factors for Postoperative Delirium after Transcatheter Aortic Valve Implantation: A Retrospective Study

Transcatheter aortic valve implantation (TAVI) is an effective treatment for severe aortic stenosis (AS); however, postoperative delirium (POD) can worsen patient outcomes. This study aimed to examine the risk factors for POD after TAVI, including possible intervening factors. We included 87 patients (mean age: 83) who underwent TAVI between May 2014 and September 2018. POD was defined by the presence or absence of delirium on ICU admission, assessed using the Confusion Assessment Method for the ICU. Factors that showed significant differences in the univariate analysis were analyzed using a multiple logistic regression analysis. In total, 31 patients (36%) had POD after ICU admission, and 56 (64%) did not. The preoperative frailty score and aortic valve opening area (AVA) were significant risk factors for POD. The multivariate analysis also showed that both factors were independent risk factors for POD (area under the receiver operating characteristic curve: 0.805). There were no significant differences in the number of ICU days. However, postoperative hospitalization was significantly longer in the POD group (19 (17–31) days vs. 16 (13–22) days; p = 0.002). POD was associated with a narrow AVA and frailty; this suggests that frailty prevention interventions according to the AVA may be important.

Neurodegenerative Disorders of Alzheimer, Parkinsonism, Amyotrophic Lateral Sclerosis and Multiple Sclerosis: An Early Diagnostic Approach for Precision Treatment

Neurodegenerative diseases (NDs) are characterised by progressive dysfunction of synapses, neurons, glial cells and their networks. Neurodegenerative diseases can be classified according to primary clinical features (e.g., dementia, parkinsonism, or motor neuron disease), anatomic distribution of neurodegeneration (e.g., frontotemporal degenerations, extrapyramidal disorders, or spinocerebellar degenerations), or principal molecular abnormalities. The most common neurodegenerative disorders are amyloidosis, tauopathies, a-synucleinopathy, and TAR DNA-binding protein 43 (TDP-43) proteopathy. The protein abnormalities in these disorders have abnormal conformational properties along with altered cellular mechanisms, and they exhibit motor deficit, mitochondrial malfunction, dysfunctions in autophagic-lysosomal pathways, synaptic toxicity, and more emerging mechanisms such as the roles of stress granule pathways and liquid-phase transitions. Finally, for each ND, microglial cells have been reported to be implicated in neurodegeneration, in particular, because the microglial responses can shift from neuroprotective to a deleterious role. Growing experimental evidence suggests that abnormal protein conformers act as seed material for oligomerization, spreading from cell to cell through anatomically connected neuronal pathways, which may in part explain the specific anatomical patterns observed in brain autopsy sample. In this review, we mention the human pathology of select neurodegenerative disorders, focusing on how neurodegenerative disorders (i.e., Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and multiple sclerosis) represent a great healthcare problem worldwide and are becoming prevalent because of the increasing aged population. Despite many studies have focused on their etiopathology, the exact cause of these diseases is still largely unknown and until now with the only available option of symptomatic treatments. In this review, we aim to report the systematic and clinically correlated potential biomarker candidates. Although future studies are necessary for their use in early detection and progression in humans affected by NDs, the promising results obtained by several groups leads us to this idea that biomarkers could be used to design a potential therapeutic approach and preclinical clinical trials for the treatments of NDs.

Diffusion tension imaging is a good tool for assessing patients with dementia and behavioral problems and discriminating them from other dementia patients

Background

Dementia is one of the leading public health concerns as the world’s population ages. Although Alzheimer’s disease (AD) is the most common dementia diagnosis among older patients, some patients have additional behavioral symptoms. It is therefore important to provide an exact diagnosis, both to provide the best possible treatment for patients and to facilitate better understanding.

Purpose

To investigate whether magnetic resonance imaging (MRI) with fractional anisotropy (FA) can accurately find patients with behavioral symptoms within a group of AD patients.

Material and Methods

Forty-five patients from the geriatric outpatient clinic were recruited consecutively to form a group of patients with AD and behavioral symptoms (AD + BS) and a control group of 50 patients with established AD. All patients had a full assessment for dementia to establish the diagnosis according to ICD-10. MRI included 3D anatomical recordings for morphometric measurements, DTI for fiber tracking, and quantitative assessment of regional white matter integrity. The DTI analyses included computing of the diffusion tensor and its derived FA index.

Results

We found a significant difference in FA values between the patient groups’ frontal lobes. The FA was greater in the study group in both left (0.39 vs 0.09, p < 0.05) and right (0.40 vs 0.16, p < 0.05) frontal lobes.

Conclusion

MRI with FA will find damage in frontal tracts and may be used as a diagnostic tool and be considered a robust tool for the recognizing different types of dementia in the future.

Value of magnetic resonance spectroscopy in geriatric patients with cognitive impairment

Background

Mild cognitive impairment is a transitional stage prior to dementia, and it is reported in depressed patients. Early diagnosis could predict the reversible etiologies and prevent further deterioration. Proton magnetic resonance spectroscopy has been used for early diagnosis and differential diagnosis of cognitive impairment.

Objective

We aimed to study the difference of hippocampal and frontal white matter metabolites between patients with Alzheimer’s disease, mild cognitive impairment, and cognitive impairment associated with depression, and if those metabolites can differentiate between them.

Subjects and methods

Geriatric patients with cognitive impairment were recruited from neurology and psychiatry clinics. All subjects underwent comprehensive medical evaluations, neuropsychological testing, laboratory tests as well as brain MRI and 1H-MRS studies.

Results

The present study included 85 subjects. Patients with MCI and AD had lower hippocampal NAA and NAA/Cr ratio than patients with depression and normal controls, while, frontal NAA and NAA/Cr ratio were lower in all patient’s subgroups compared to normal control.

Conclusion

Hippocampal NAA and NAA/Cr ratio might help to differentiate between MCI and cognitive impairment associated with depression.

Published Human Cadaveric Measurements Are Strongly Biased Toward the Elderly Population

Understanding of anatomy is based on the study of anatomical variations. Morphometric variations can have important implications in surgical practice. The sizes of some anatomical structures are affected by age; however, cadavers used in anatomical research are usually of advanced age. The main aim of this study is to quantify the mean age of samples in cadaveric studies reporting morphometric values. PubMed was searched for the last 3 years to locate cadaveric studies reporting size values, excluding histological, forensic, and osteological collections. Out of the 390 potentially relevant papers, 109 (28%) studies did not report the ages of their samples. In total, 177 studies were included for analysis comprising 4,807 subjects. The most studied structures were those of the musculoskeletal system. The mean age of the pooled sample was 71.1 ± 11.0 years. The lowest reported age was 16 while the highest was 104 years. Univariate and multivariate analyses showed no correlation with any of the following variables: country of study, anatomical region, anatomical structure, or journal type. The mean age of cadavers used to measure the sizes of human anatomical structures falls largely within the senior age category. The reported values in an aging population will not necessarily mirror other populations such as the pediatric. The outcomes of surgeries that depend to some extent on tight morphometric values such as flap surgeries, microsurgery, tendon transfer, or mini-invasive procedures could differ when they are performed on other age categories. More anatomical research is needed for better reporting of age-related morphometric changes. Clin. Anat., 33:804-808, 2020. © 2019 Wiley Periodicals, Inc.

[Neurodegenerative diseases]

Neurodegenerative diseases are sporadic and rare hereditary disorders of the central nervous system, which cause a slowly progressive loss of function of specific neuron populations and their connections. Severe impairments and care dependency can be the sequelae. Neurodegenerative disorders are diseases of older people; therefore, the demographic shift leads to an increase in the number of affected patients. Radiologists will also become more involved. For this reason important neurodegenerative diseases are presented in this article. In addition to Alzheimer's and Parkinson's diseases these also include frontotemporal lobar degeneration, Lewy body dementia, vascular dementia, Creutzfeldt-Jakob disease and Huntington's chorea. The clinical symptoms and diagnostics are described, whereby the focus lies on typical results of morphological imaging.

A Retrospective Belgian Multi-Center MRI Biomarker Study in Alzheimer's Disease (REMEMBER)

Background:

Magnetic resonance imaging (MRI) acquisition/processing techniques assess brain volumes to explore neurodegeneration in Alzheimer’s disease (AD).

Objective:

We examined the clinical utility of MSmetrix and investigated if automated MRI volumes could discriminate between groups covering the AD continuum and could be used as a predictor for clinical progression.

Methods:

The Belgian Dementia Council initiated a retrospective, multi-center study and analyzed whole brain (WB), grey matter (GM), white matter (WM), cerebrospinal fluid (CSF), cortical GM (CGM) volumes, and WM hyperintensities (WMH) using MSmetrix in the AD continuum. Baseline (n = 887) and follow-up (FU, n = 95) T1-weighted brain MRIs and time-linked neuropsychological data were available.

Results:

The cohort consisted of cognitively healthy controls (HC, n = 93), subjective cognitive decline (n = 102), mild cognitive impairment (MCI, n = 379), and AD dementia (n = 313). Baseline WB and GM volumes could accurately discriminate between clinical diagnostic groups and were significantly decreased with increasing cognitive impairment. MCI patients had a significantly larger change in WB, GM, and CGM volumes based on two MRIs (n = 95) compared to HC (FU>24months, p = 0.020). Linear regression models showed that baseline atrophy of WB, GM, CGM, and increased CSF volumes predicted cognitive impairment.

Conclusion:

WB and GM volumes extracted by MSmetrix could be used to define the clinical spectrum of AD accurately and along with CGM, they are able to predict cognitive impairment based on (decline in) MMSE scores. Therefore, MSmetrix can support clinicians in their diagnostic decisions, is able to detect clinical disease progression, and is of help to stratify populations for clinical trials.

Random forest feature selection, fusion and ensemble strategy: Combining multiple morphological MRI measures to discriminate among healhy elderly, MCI, cMCI and alzheimer's disease patients: From the alzheimer's disease neuroimaging initiative (ADNI) database

BACKGROUND

In the era of computer-assisted diagnostic tools for various brain diseases, Alzheimer's disease (AD) covers a large percentage of neuroimaging research, with the main scope being its use in daily practice. However, there has been no study attempting to simultaneously discriminate among Healthy Controls (HC), early mild cognitive impairment (MCI), late MCI (cMCI) and stable AD, using features derived from a single modality, namely MRI.

NEW METHOD

Based on preprocessed MRI images from the organizers of a neuroimaging challenge,³ we attempted to quantify the prediction accuracy of multiple morphological MRI features to simultaneously discriminate among HC, MCI, cMCI and AD. We explored the efficacy of a novel scheme that includes multiple feature selections via Random Forest from subsets of the whole set of features (e.g. whole set, left/right hemisphere etc.), Random Forest classification using a fusion approach and ensemble classification via majority voting. From the ADNI database, 60 HC, 60 MCI, 60 cMCI and 60 CE were used as a training set with known labels. An extra dataset of 160 subjects (HC: 40, MCI: 40, cMCI: 40 and AD: 40) was used as an external blind validation dataset to evaluate the proposed machine learning scheme.

RESULTS

In the second blind dataset, we succeeded in a four-class classification of 61.9% by combining MRI-based features with a Random Forest-based Ensemble Strategy. We achieved the best classification accuracy of all teams that participated in this neuroimaging competition.

COMPARISON WITH EXISTING METHOD(S)

The results demonstrate the effectiveness of the proposed scheme to simultaneously discriminate among four groups using morphological MRI features for the very first time in the literature.

CONCLUSIONS

Hence, the proposed machine learning scheme can be used to define single and multi-modal biomarkers for AD.

Taking a positive spin: preserved initiative and performance of everyday activities across mild Alzheimer's, vascular and mixed dementia

OBJECTIVES

The literature commonly evaluates those daily activities which are impaired in dementia. However, in the mild stages, people with dementia (PwD) are still able to initiate and perform many of those tasks. With a lack of research exploring variations between different dementia diagnoses, this study sought to investigate those daily activities with modest impairments in the mild stages and how these compare between Alzheimer's disease (AD), vascular dementia (VaD) and mixed dementia.

METHODS

Staff from memory assessment services from nine National Health Service trusts across England identified and approached informal carers of people with mild dementia. Carers completed the newly revised Interview for Deteriorations in Daily Living Activities in Dementia 2 assessing the PwD's initiative and performance of instrumental activities of daily living (IADLs). Data were analysed using analysis of variance and Chi-square tests to compare the maintenance of IADL functioning across AD, VaD, and mixed dementia.

RESULTS

A total of 160 carers returned the Interview for Deteriorations in Daily Living Activities in Dementia 2, of which 109, 21, and 30 cared for someone with AD, VaD, and mixed dementia, respectively. There were significant variations across subtypes, with AD showing better preserved initiative and performance than VaD for several IADLs. Overall, PwD showed greater preservation of performance than initiative, with tasks such as preparing a hot drink and dressing being best maintained.

CONCLUSION

Findings can help classify dementia better into subtypes in order to receive bespoke support. It suggests that interventions should primarily address initiative to improve overall functioning. Copyright © 2016 John Wiley & Sons, Ltd.

Clinical practice with anti-dementia drugs: A revised (third) consensus statement from the British Association for Psychopharmacology

The British Association for Psychopharmacology coordinated a meeting of experts to review and revise its previous 2011 guidelines for clinical practice with anti-dementia drugs. As before, levels of evidence were rated using accepted standards which were then translated into grades of recommendation A-D, with A having the strongest evidence base (from randomised controlled trials) and D the weakest (case studies or expert opinion). Current clinical diagnostic criteria for dementia have sufficient accuracy to be applied in clinical practice (B) and both structural (computed tomography and magnetic resonance imaging) and functional (positron emission tomography and single photon emission computerised tomography) brain imaging can improve diagnostic accuracy in particular situations (B). Cholinesterase inhibitors (donepezil, rivastigmine, and galantamine) are effective for cognition in mild to moderate Alzheimer's disease (A), memantine for moderate to severe Alzheimer's disease (A) and combination therapy (cholinesterase inhibitors and memantine) may be beneficial (B). Drugs should not be stopped just because dementia severity increases (A). Until further evidence is available other drugs, including statins, anti-inflammatory drugs, vitamin E, nutritional supplements and Ginkgo biloba, cannot be recommended either for the treatment or prevention of Alzheimer's disease (A). Neither cholinesterase inhibitors nor memantine are effective in those with mild cognitive impairment (A). Cholinesterase inhibitors are not effective in frontotemporal dementia and may cause agitation (A), though selective serotonin reuptake inhibitors may help behavioural (but not cognitive) features (B). Cholinesterase inhibitors should be used for the treatment of people with Lewy body dementias (both Parkinson's disease dementia and dementia with Lewy bodies), and memantine may be helpful (A). No drugs are clearly effective in vascular dementia, though cholinesterase inhibitors are beneficial in mixed dementia (B). Early evidence suggests multifactorial interventions may have potential to prevent or delay the onset of dementia (B). Though the consensus statement focuses on medication, psychological interventions can be effective in addition to pharmacotherapy, both for cognitive and non-cognitive symptoms. Many novel pharmacological approaches involving strategies to reduce amyloid and/or tau deposition in those with or at high risk of Alzheimer's disease are in progress. Though results of pivotal studies in early (prodromal/mild) Alzheimer's disease are awaited, results to date in more established (mild to moderate) Alzheimer's disease have been equivocal and no disease modifying agents are either licensed or can be currently recommended for clinical use.

(1)H-MRS asymmetry changes in the anterior and posterior cingulate gyrus in patients with mild cognitive impairment and mild Alzheimer's disease

Alzheimer's disease (AD) is the most common cause of dementia worldwide. Amnestic mild cognitive impairment (aMCI) is often the prodromal stage to AD. Most patients with aMCI harbor the pathologic changes of AD and demonstrate transition to AD at a rate of 10%-15% per year. Patients with AD and aMCI experience progressive brain metabolite changes. Accumulating evidence indicates that the asymmetry changes of left and right brain happen in the early stage of AD. However, the features of asymmetry changes in both anterior cingulate gyrus (ACG) and posterior cingulate gyrus (PCG) are still unclear. Here, we examine the left-right asymmetry changes of metabolites in ACG and PCG. Fifteen cases of mild AD patients meeting criteria for probable AD of NINDS-ADRDA, thirteen cases of aMCI according to the Mayo Clinic Alzheimer's Disease Research Center criteria, and sixteen cases of age-matched normal controls (NC) received Proton magnetic resonance spectroscopy ((1)H-MRS) for measurement of NAA/mI, NAA/Cr, Cho/Cr, and mI/Cr ratios in the PCG and ACG bilaterally. We analyzed (1)H-MRS data by paired t-test to validate the left-right asymmetry of (1)H-MRS data in the PCG and ACG. In AD, there was a significant difference in mI/Cr between the left and right ACG (P<0.001) and the left and right PCG (P=0.007). In aMCI, there was a significant difference in mI/Cr between the left and right ACG (P<0.001). In NC, there were no differences in the ratio value of metabolites NAA/mI, NAA/Cr, Cho/Cr, and mI/Cr between the left and right ACG and PCG. Thus, the left-right asymmetry of mI/Cr in the ACG and PCG may be an important biological indicator of mild AD.

Potential Therapies by Stem Cell-Derived Exosomes in CNS Diseases: Focusing on the Neurogenic Niche

Neurodegenerative disorders are one of the leading causes of death and disability and one of the biggest burdens on health care systems. Novel approaches using various types of stem cells have been proposed to treat common neurodegenerative disorders such as Alzheimer's Disease, Parkinson's Disease, or stroke. Moreover, as the secretome of these cells appears to be of greater benefit compared to the cells themselves, the extracellular components responsible for its therapeutic benefit have been explored. Stem cells, as well as most cells, release extracellular vesicles such as exosomes, which are nanovesicles able to target specific cell types and thus to modify their function by delivering proteins, lipids, and nucleic acids. Exosomes have recently been tested in vivo and in vitro as therapeutic conveyors for the treatment of diseases. As such, they could be engineered to target specific populations of cells within the CNS. Considering the fact that many degenerative brain diseases have an impact on adult neurogenesis, we discuss how the modulation of the adult neurogenic niches may be a therapeutic target of stem cell-derived exosomes. These novel approaches should be examined in cellular and animal models to provide better, more effective, and specific therapeutic tools in the future.

What can imaging tell us about cognitive impairment and dementia?

Dementia is a contemporary global health issue with far reaching consequences, not only for affected individuals and their families, but for national and global socio-economic conditions. The hallmark feature of dementia is that of irreversible cognitive decline, usually affecting memory, and impaired activities of daily living. Advances in healthcare worldwide have facilitated longer life spans, increasing the risks of developing cognitive decline and dementia in late life. Dementia remains a clinical diagnosis. The role of structural and molecular neuroimaging in patients with dementia is primarily supportive role rather than diagnostic, American and European guidelines recommending imaging to exclude treatable causes of dementia, such as tumor, hydrocephalus or intracranial haemorrhage, but also to distinguish between different dementia subtypes, the commonest of which is Alzheimer’s disease. However, this depends on the availability of these imaging techniques at individual centres. Advanced magnetic resonance imaging (MRI) techniques, such as functional connectivity MRI, diffusion tensor imaging and magnetic resonance spectroscopy, and molecular imaging techniques, such as 18F fluoro-deoxy glucose positron emission tomography (PET), amyloid PET, tau PET, are currently within the realm of dementia research but are available for clinical use. Increasingly the research focus is on earlier identification of at risk preclinical individuals, for example due to family history. Intervention at the preclinical stages before irreversible brain damage occurs is currently the best hope of reducing the impact of dementia.

Neuroimaging referral for dementia diagnosis: The specialist's perspective in Ireland

BACKGROUND

Neuroimaging is an increasingly important tool in the diagnostic workup of dementia. Neurologists, geriatricians, and old-age psychiatrists are involved in key tasks in the diagnostic process, frequently referring patients with suspected dementia for neuroimaging.

METHODS

The research design was a postal survey of all geriatricians, old-age psychiatrists, and neurologists in the Republic of Ireland (N = 176) as identified by the Irish Medical Directory 2011-2012 and supplementary listings.

RESULTS

Almost 65% of specialists did not have access to 2-[18F]fluoro-2-deoxy-D-glucose positron emission (FDG-PET) or FDG-PET/computed tomography (CT), and 80.3% did not have access to perfusion hexamethylpropyleneamine oxime single-photon emission computed tomography (SPECT) or dopaminergic iodine-123-radiolabeled 2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl) nortropane SPECT. Most specialists (88.7%) referred patients with mild cognitive impairment or suspected dementia for magnetic resonance imaging (MRI), 81.7% referred for CT, and 26.8% for FDG-PET or FDG-PET/CT. Only 44.6% of respondents were aware of dementia-specific protocols for referrals for neuroimaging.

CONCLUSION

Specialist access to imaging modalities other than CT and MRI is restricted. Improved access may affect patient treatment and care.

Delirium and dementia with Lewy bodies: distinct diagnoses or part of the same spectrum?

Dementia with Lewy bodies (DLB) is recognised as the second most common form of dementia in older people. Delirium is a condition of acute brain dysfunction for which a pre-existing diagnosis of dementia is a risk factor. Conversely delirium is associated with an increased risk of developing dementia. The reasons for this bidirectional relationship are not well understood. Our aim was to review possible similarities in the clinical presentation and pathophysiology between delirium and DLB, and explore possible links between these diagnoses. A systematic search using Medline, Embase and Psychinfo was performed. References were scanned for relevant articles, supplemented by articles identified from reference lists and those known to the authors. 94 articles were selected for inclusion in the review. Delirium and DLB share a number of clinical similarities, including global impairment of cognition, fluctuations in attention and perceptual abnormalities. Delirium is a frequent presenting feature of DLB. In terms of pathophysiological mechanisms, cholinergic dysfunction and genetics may provide a common link. Neuroimaging studies suggest a brain vulnerability in delirium which may also occur in dementia. The basal ganglia, which play a key role in DLB, have also been implicated in delirium. The role of Cerebrospinal fluid (CSF) and serum biomarkers for both diagnoses is an interesting area although some results are conflicting and further work in this area is needed. Delirium and DLB share a number of features and we hypothesise that delirium may, in some cases, represent early or 'prodromal' DLB. Further research is needed to test the novel hypothesis that delirium may be an early marker for future DLB, which would aid early diagnosis of DLB and identify those at high risk.

How does additional diagnostic testing influence the initial diagnosis in patients with cognitive complaints in a memory clinic setting?

BACKGROUND

patients suspected of dementia frequently undergo additional diagnostic testing (e.g. brain imaging or neuropsychological assessment) after standard clinical assessment at a memory clinic. This study investigates the use of additional testing in an academic outpatient memory clinic and how it influences the initial diagnosis.

METHODS

the initial diagnosis after standard clinical assessment (history, laboratory tests, cognitive screening and physical and neurological examination) and the final diagnosis after additional testing of 752 memory clinic patients were collected. We specifically registered if, and what type of, additional testing was requested.

RESULTS

additional testing was performed in 518 patients (69%), 67% of whom underwent magnetic resonance imaging, 45% had neuropsychological assessment, 14% had cerebrospinal fluid analysis and 49% had (combinations of) other tests. This led to a modification of the initial diagnosis in 17% of the patients. The frequency of change was highest in patients with an initial non-Alzheimer's disease (AD) dementia diagnosis (54%, compared with 11 and 14% in patients with AD and 'no dementia'; P < 0.01). Finally, after additional testing 44% was diagnosed with AD, 9% with non-AD dementia and 47% with 'no dementia'.

CONCLUSION

additional testing should especially be considered in non-AD patients. In the large group of patients with an initial AD or 'no dementia' diagnosis, additional tests have little diagnostic impact and may perhaps be used with more restraint.

Chronic pain in "probable" vascular dementia: preliminary findings

BACKGROUND

In a previous study, the levels of pain reported by patients with "possible" vascular dementia (VaD) were higher than those reported by older individuals without dementia.

OBJECTIVE

To examine experienced pain in patients with "probable" VaD, confirmed by brain imaging.

STUDY DESIGN

Observational, cross sectional.

SETTING

Nursing home.

METHODS

The participants were 20 nursing home residents (14 females, 6 males) who met the NINDS-AIREN criteria for "probable" VaD and 22 nursing home residents with a normal mental status (18 females, 4 males). The patients were in a mild to moderate stage of dementia. All of the participants were suffering from arthritis/arthrosis or osteoporosis. Global cognitive functioning was measured by the Mini-Mental State Examination. Pain was assessed by the Coloured Analogue Scale (CAS: original and modified version) and the Faces Pain Scale. The Geriatric Depression Scale and the Symptom Checklist-90 were used to assess mood.

RESULTS

The main finding was that, after controlling for mood, the pain levels indicated by patients with "probable" VaD (M = 102.32; standard deviation [SD] = 53.42) were significantly higher than those indicated by the control group (M = 59.17; SD = 38.75), only according to the CAS modified version (F[1,29]) = 5.62, P = 0.01, η2  = 0.16).

CONCLUSION

As VaD patients may experience greater pain than controls, it is essential for prescribers to be aware of the presence of this neuropathology if these patients are to receive adequate treatment.

Concordance between (99m)Tc-ECD SPECT and 18F-FDG PET interpretations in patients with cognitive disorders diagnosed according to NIA-AA criteria

OBJECTIVES

The purpose of this study was to clarify the concordance of diagnostic abilities and interobserver agreement between 18F-fluorodeoxyglucose (FDG) positron emission tomography (PET) and brain perfusion single photon-emission computed tomography (SPECT) in patients with Alzheimer's disease (AD) who were diagnosed according to the research criteria of the National Institute of Aging-Alzheimer's Association Workshop.

METHODS

Fifty-five patients with "AD and mild cognitive impairment (MCI)" (n = 40) and "non-AD" (n = 15) were evaluated with 18F-FDG PET and (99m)Tc-ethyl cysteinate dimer (ECD) SPECT during an 8-week period. Three radiologists independently graded the regional uptake in the frontal, temporal, parietal, and occipital lobes as well as the precuneus/posterior cingulate cortex in both images. Kappa values were used to determine the interobserver reliability regarding regional uptake.

RESULTS

The regions with better interobserver reliability between 18F-FDG PET and (99m)Tc-ECD SPECT were the frontal, parietal, and temporal lobes. The (99m)Tc-ECD SPECT agreement in the occipital lobes was not significant. The frontal, temporal, and parietal lobes showed good correlations between 18F-FDG PET and (99m)Tc-ECD SPECT in the degree of uptake, but the occipital lobe and precuneus/posterior cingulate cortex did not show good correlations. The diagnostic accuracy rates of "AD and MCI" ranged from 60% to 70% in both of the techniques.

CONCLUSIONS

The degree of uptake on 18F-FDG PET and (99m)Tc-ECD SPECT showed significant correlations in the frontal, temporal, and parietal lobes. The diagnostic abilities of 18F-FDG PET and (99m)Tc-ECD SPECT for "AD and MCI," when diagnosed according to the National Institute of Aging-Alzheimer's Association Workshop criteria, were nearly identical.

Back propagation artificial neural network for community Alzheimer's disease screening in China

Alzheimer's disease patients diagnosed with the Chinese Classification of Mental Disorders diagnostic criteria were selected from the community through on-site sampling. Levels of macro and trace elements were measured in blood samples using an atomic absorption method, and neurotransmitters were measured using a radioimmunoassay method. SPSS 13.0 was used to establish a database, and a back propagation artificial neural network for Alzheimer's disease prediction was simulated using Clementine 12.0 software. With scores of activities of daily living, creatinine, 5-hydroxytryptamine, age, dopamine and aluminum as input variables, the results revealed that the area under the curve in our back propagation artificial neural network was 0.929 (95% confidence interval: 0.868-0.968), sensitivity was 90.00%, specificity was 95.00%, and accuracy was 92.50%. The findings indicated that the results of back propagation artificial neural network established based on the above six variables were satisfactory for screening and diagnosis of Alzheimer's disease in patients selected from the community.

Random Forest ensembles for detection and prediction of Alzheimer's disease with a good between-cohort robustness

Computer-aided diagnosis of Alzheimer's disease (AD) is a rapidly developing field of neuroimaging with strong potential to be used in practice. In this context, assessment of models' robustness to noise and imaging protocol differences together with post-processing and tuning strategies are key tasks to be addressed in order to move towards successful clinical applications. In this study, we investigated the efficacy of Random Forest classifiers trained using different structural MRI measures, with and without neuroanatomical constraints in the detection and prediction of AD in terms of accuracy and between-cohort robustness. From The ADNI database, 185 AD, and 225 healthy controls (HC) were randomly split into training and testing datasets. 165 subjects with mild cognitive impairment (MCI) were distributed according to the month of conversion to dementia (4-year follow-up). Structural 1.5-T MRI-scans were processed using Freesurfer segmentation and cortical reconstruction. Using the resulting output, AD/HC classifiers were trained. Training included model tuning and performance assessment using out-of-bag estimation. Subsequently the classifiers were validated on the AD/HC test set and for the ability to predict MCI-to-AD conversion. Models' between-cohort robustness was additionally assessed using the AddNeuroMed dataset acquired with harmonized clinical and imaging protocols. In the ADNI set, the best AD/HC sensitivity/specificity (88.6%/92.0% - test set) was achieved by combining cortical thickness and volumetric measures. The Random Forest model resulted in significantly higher accuracy compared to the reference classifier (linear Support Vector Machine). The models trained using parcelled and high-dimensional (HD) input demonstrated equivalent performance, but the former was more effective in terms of computation/memory and time costs. The sensitivity/specificity for detecting MCI-to-AD conversion (but not AD/HC classification performance) was further improved from 79.5%/75%-83.3%/81.3% by a combination of morphometric measurements with ApoE-genotype and demographics (age, sex, education). When applied to the independent AddNeuroMed cohort, the best ADNI models produced equivalent performance without substantial accuracy drop, suggesting good robustness sufficient for future clinical implementation.

Application of a MRI based index to longitudinal atrophy change in Alzheimer disease, mild cognitive impairment and healthy older individuals in the AddNeuroMed cohort

Cross sectional studies of patients at risk of developing Alzheimer disease (AD) have identified several brain regions known to be prone to degeneration suitable as biomarkers, including hippocampal, ventricular, and whole brain volume. The aim of this study was to longitudinally evaluate an index based on morphometric measures derived from MRI data that could be used for classification of AD and healthy control subjects, as well as prediction of conversion from mild cognitive impairment (MCI) to AD. Patients originated from the AddNeuroMed project at baseline (119 AD, 119 MCI, 110 controls (CTL)) and 1-year follow-up (62 AD, 73 MCI, 79 CTL). Data consisted of 3D T1-weighted MR images, demographics, MMSE, ADAS-Cog, CERAD and CDR scores, and APOE e4 status. We computed an index using a multivariate classification model (AD vs. CTL), using orthogonal partial least squares to latent structures (OPLS). Sensitivity, specificity and AUC were determined. Performance of the classifier (AD vs. CTL) was high at baseline (10-fold cross-validation, 84% sensitivity, 91% specificity, 0.93 AUC) and at 1-year follow-up (92% sensitivity, 74% specificity, 0.93 AUC). Predictions of conversion from MCI to AD were good at baseline (77% of MCI converters) and at follow-up (91% of MCI converters). MCI carriers of the APOE e4 allele manifested more atrophy and presented a faster cognitive decline when compared to non-carriers. The derived index demonstrated a steady increase in atrophy over time, yielding higher accuracy in prediction at the time of clinical conversion. Neuropsychological tests appeared less sensitive to changes over time. However, taking the average of the two time points yielded better correlation between the index and cognitive scores as opposed to using cross-sectional data only. Thus, multivariate classification seemed to detect patterns of AD changes before conversion from MCI to AD and including longitudinal information is of great importance.

Automatic ROI selection in structural brain MRI using SOM 3D projection

This paper presents a method for selecting Regions of Interest (ROI) in brain Magnetic Resonance Imaging (MRI) for diagnostic purposes, using statistical learning and vector quantization techniques. The proposed method models the distribution of GM and WM tissues grouping the voxels belonging to each tissue in ROIs associated to a specific neurological disorder. Tissue distribution of normal and abnormal images is modelled by a Self-Organizing map (SOM), generating a set of representative prototypes, and the receptive field (RF) of each SOM prototype defines a ROI. Moreover, the proposed method computes the relative importance of each ROI by means of its discriminative power. The devised method has been assessed using 818 images from the Alzheimer's disease Neuroimaging Initiative (ADNI) which were previously segmented through Statistical Parametric Mapping (SPM). The proposed algorithm was used over these images to parcel ROIs associated to the Alzheimer's Disease (AD). Additionally, this method can be used to extract a reduced set of discriminative features for classification, since it compresses discriminative information contained in the brain. Voxels marked by ROIs which were computed using the proposed method, yield classification results up to 90% of accuracy for controls (CN) and Alzheimer's disease (AD) patients, and 84% of accuracy for Mild Cognitive Impairment (MCI) and AD patients.

Pattern of cerebral hyperperfusion in Alzheimer's disease and amnestic mild cognitive impairment using voxel-based analysis of 3D arterial spin-labeling imaging: initial experience

Purpose

A three-dimensional (3D) continuous pulse arterial spin labeling (ASL) technique was used to investigate cerebral blood flow (CBF) changes in patients with Alzheimer’s disease (AD), amnestic mild cognitive impairment (aMCI), and age- and sex-matched healthy controls.

Materials and methods

Three groups were recruited for comparison, 24 AD patients, 17 MCI patients, and 21 age- and sex-matched control subjects. Three-dimensional ASL scans covering the entire brain were acquired with a 3.0 T magnetic resonance scanner. Spatial processing was performed with statistical parametric mapping 8. A second-level one-way analysis of variance analysis (threshold at P<0.05) was performed on the preprocessed ASL data. An average whole-brain CBF for each subject was also included as group-level covariates for the perfusion data, to control for individual CBF variations.

Results

Significantly increased CBF was detected in bilateral frontal lobes and right temporal subgyral regions in aMCI compared with controls. When comparing AD with aMCI, the major hyperperfusion regions were the right limbic lobe and basal ganglia regions, including the putamen, caudate, lentiform nucleus, and thalamus, and hypoperfusion was found in the left medial frontal lobe, parietal cortex, the right middle temporo-occipital lobe, and particularly, the left anterior cingulate gyrus. We also found decreased CBF in the bilateral temporo-parieto-occipital cortices and left limbic lobe in AD patients, relative to the control group. aMCI subjects showed decreased blood flow in the left occipital lobe, bilateral inferior temporal cortex, and right middle temporal cortex.

Conclusion

Our results indicated that ASL provided useful perfusion information in AD disease and may be used as an appealing alternative for further pathologic and neuropsychological studies, especially of compensatory mechanisms for cerebral hypoperfusion.

Relationships between diabetes and cognitive impairment

Epidemics of obesity, diabetes, nonalcoholic fatty liver disease, and cognitive impairment/Alzheimer disease have emerged over the past 3 to 4 decades. These diseases share in common target-organ insulin resistance with a constellation of molecular and biochemical abnormalities that lead to organ/tissue degeneration over time. This article discusses the fundamental links among these diseases and how peripheral organ insulin resistance diseases contribute to cognitive impairment and neurodegeneration. A future role of endocrinologists and diabetologists could be to provide integrative diagnostic and treatment approaches for this collection of diseases that seem to share pathophysiological and pathogenetic bases.

Potential Applications of Spectral-Domain Optical Coherence Tomography (SD-OCT) in the Study of Alzheimer's Disease

Alzheimer's Disease (AD) is the most common subtype of dementia. As the prevalence of dementia is projected to increase, the burden of the disease on society is expected to become increasingly significant. The link between eye pathology and neurodegenerative diseases has been established in multiple studies. In particular, optic nerve parameters associated with neuronal loss in AD include retinal ganglion cells (RGC). Retinal ganglion cells are similar to neurons in the cerebral cortex, and have been correlated to neurodegeneration in AD. Ocular imaging techniques such as optical coherence tomography (OCT) have provided a rapid and non-invasive method for quantifying optic nerve parameters in vivo. Spectral domain (SD)-OCT has shown good potential in the study of the optic nerve in AD as it enables more comprehensive assessment of RGCs. Earlier generation OCT techniques only assess the retinal nerve fibre layer, which consists of RGC axons. Spectral domain-OCT offers ultra-high scan speed and image resolution, enabling improved sampling of retinal layers. Retinal layers such as the ganglion cell-inner plexiform layer (GC-IPL), which contain the dendrites and nuclei of RGCs, can be assessed with SD-OCT. This article presents a review of literature associating eye pathology with AD, and explores the potential of SD-OCT in future AD studies. Spectral domain-OCT has the potential to draw more links between optic nerve pathology and neurodegeneration.

[Dementia: diagnosis and therapy]

Dementia is a clinical syndrome characterized by progressive memory loss. Alzheimer's disease, a neurodegenerative disorder, accounts for the majority of clinical cases. The differential diagnosis comprises other neurodegenerative disease entities and vascular dementia, but also secondary and potentially reversible disturbances of cognitive function such as delirium or depression. Diagnostic work-up consists of standardized cognitive testing, neuroimaging, and a basic laboratory test battery. Pharmacological treatment of cognitive symptoms is accompanied by pharmacological and nonpharmacological treatment of psychiatric and behavioral symptoms, establishment of a supportive social network, as well as prevention and treatment of medical complications of dementia. This article summarizes current clinical knowledge on dementia and has a special interest in treatment and prophylaxis of complications in the field of internal medicine.

Inflammatory proteins in plasma are associated with severity of Alzheimer's disease

Markers of Alzheimer’s disease (AD) are being widely sought with a number of studies suggesting blood measures of inflammatory proteins as putative biomarkers. Here we report findings from a panel of 27 cytokines and related proteins in over 350 subjects with AD, subjects with Mild Cognitive Impairment (MCI) and elderly normal controls where we also have measures of longitudinal change in cognition and baseline neuroimaging measures of atrophy. In this study, we identify five inflammatory proteins associated with evidence of atrophy on MR imaging data particularly in whole brain, ventricular and entorhinal cortex measures. In addition, we observed six analytes that showed significant change (over a period of one year) in people with fast cognitive decline compared to those with intermediate and slow decline. One of these (IL-10) was also associated with brain atrophy in AD. In conclusion, IL-10 was associated with both clinical and imaging evidence of severity of disease and might therefore have potential to act as biomarker of disease progression.

Classification and prediction of clinical diagnosis of Alzheimer's disease based on MRI and plasma measures of α-/γ-tocotrienols and γ-tocopherol

BACKGROUND

The aim of this study was to evaluate the accuracy of combined structural magnetic resonance imaging (MRI) measures and plasma levels of vitamin E forms, including all eight natural vitamin E congeners (four tocopherols and four tocotrienols) and markers of vitamin E oxidative/nitrosative damage, in differentiating individuals with Alzheimer's disease (AD) and mild cognitive impairment (MCI) from cognitively intact control (CTL) subjects.

METHODS

Overall, 81 patients with AD, 86 with MCI and 86 CTL individuals were enrolled from the longitudinal multicentre AddNeuroMed study. MRI and plasma vitamin E data were acquired at baseline. MRI scans were analysed using Freesurfer, an automated segmentation scheme which generates regional volume and cortical thickness measures. Orthogonal partial least squares to latent structures (OPLS), a multivariate data analysis technique, was used to analyse MRI and vitamin E measures in relation to AD and MCI diagnosis.

RESULTS

The joint evaluation of MRI and plasma vitamin E measures enhanced the accuracy of differentiating individuals with AD and MCI from CTL subjects: 98.2% (sensitivity 98.8%, specificity 97.7%) for AD versus CTL, and 90.7% (sensitivity 91.8%, specificity 89.5%) for MCI versus CTL. This combination of measures also identified 85% of individuals with MCI who converted to clinical AD at follow-up after 1 year.

CONCLUSIONS

Plasma levels of tocopherols and tocotrienols together with automated MRI measures can help to differentiate AD and MCI patients from CTL subjects, and to prospectively predict MCI conversion into AD. Our results suggest the potential role of nutritional biomarkers detected in plasma-tocopherols and tocotrienols-as indirect indicators of AD pathology, and the utility of a multimodality approach.

Different multivariate techniques for automated classification of MRI data in Alzheimer's disease and mild cognitive impairment

Automated structural magnetic resonance imaging (MRI) processing pipelines and different multivariate techniques are gaining popularity for Alzheimer's disease (AD) research. We used four supervised learning methods to classify AD patients and controls (CTL) and to prospectively predict the conversion of mild cognitive impairment (MCI) to AD from baseline MRI data. A total of 345 participants from the AddNeuroMed cohort were included in this study; 116 AD patients, 119 MCI patients and 110 CTL individuals. High resolution sagittal 3D MP-RAGE datasets were acquired and MRI data were processed using FreeSurfer. We explored the classification ability of orthogonal projections to latent structures (OPLS), decision trees (Trees), artificial neural networks (ANN) and support vector machines (SVM). Applying 10-fold cross-validation demonstrated that SVM and OPLS were slightly superior to Trees and ANN, although not statistically significant for distinguishing between AD and CTL. The classification experiments resulted in up to 83% sensitivity and 87% specificity for the best techniques. For the prediction of conversion of MCI patients at baseline to AD at 1-year follow-up, we obtained an accuracy of up to 86%. The value of the multivariate models derived from the classification of AD vs. CTL was shown to be robust and efficient in the identification of MCI converters.

FDG-PET in early AD diagnosis

FDG-PET is a valuable tool that will continue to aid in identifying AD in its prodromal and early dementia stages, distinguishing it from other causes of dementia, and tracking progression of the disease. As brain FDG-PET scans and well-trained readers of these scans are becoming more widely available to clinicians who are becoming more informed about the role FDG-PET can play in early AD diagnosis, its use is expected to increase.

Impact of homocysteine on cortical perfusion and cognitive decline in mild Alzheimer's dementia

BACKGROUND AND PURPOSE

Elevated plasma total homocysteine level (tHcy) is associated with increased risk of dementia via increased white matter changes or reduction in cortical volume. Whether tHcy has an independent impact on regional perfusion and if it can predict a more rapid cognitive decline in mild Alzheimer dementia (AD) warrants investigation.

METHODS

Eighty AD patients with a clinical dementia rating of 1 were enrolled. Their Cognitive Ability Screening Instrument (CASI) scores on enrolment and after 1 year of follow-up as well as their perfusion index (PI) from single photon emission computed tomography upon enrolment were analyzed.

RESULTS

In cross-sectional analysis, elevated tHcy was associated with lower frontal PI independent of cerebrovascular risk factors (β = -0.35, P = 0.009). The CASI scores correlated with temporo-parietal PI (Pearson r range 0.3-0.39, P < 0.01) but not with tHcy or frontal PI. By longitudinal analysis, only tHcy level was related to a more rapid cognitive decline (odds ratio for executive function score 1.82; odds ratio for total CASI score 1.74).

CONCLUSIONS

Cognitive performance in mild AD can be reflected by hypo-perfusion of the temporo-parietal region while frontal hypo-perfusion may be mediated by tHcy. tHcy level is an independent risk factor for rapid cognitive decline, especially in the executive function.

Multivariate classification of patients with Alzheimer's and dementia with Lewy bodies using high-dimensional cortical thickness measurements: an MRI surface-based morphometric study

CONTEXT

Alzheimer's disease (AD) and dementia with Lewy bodies (DLB) are the most common neurodegenerative dementia types. It is important to differentiate between them because of the differences in prognosis and treatment approaches.

OBJECTIVE

Investigate if sparse partial least squares (SPLS) classification of cortical thickness measurements could differentiate between AD and DLB.

METHODS

Two independent cohorts without MR-protocol alignment in Norway and Slovenia with 97 AD and DLB subjects were enrolled. Cortical thickness measurements acquired with Freesurfer were used in subsequent SPLS classification runs. The cohorts were analyzed separately and afterwards combined. The models were trained with leave-one-out cross validation and test datasets where used when available. To study the impact of MR-protocol alignment, the classifiers were additionally tested on sets drawn exclusively from the independent cohorts.

RESULTS

The obtained sensitivity/specificity/AUC values were 94.4/88.89/0.978 and 88.2/94.1/0.969 in the Norwegian and Slovenian cohorts, respectively. Both cohorts showed AD-associated pattern of thinning in mid-anterior temporal, occipital and subgenual cingulate cortex, whereas the pattern supportive for DLB included thinning in dorsal cingulate, posterior temporal and lateral orbitofrontal regions. When combining the cohorts, sensitivity/specificity/AUC were 82.1/85.7/0.948 for the training and 77.8/75/0.731 for the testing datasets with the same pattern-of-difference. The models tested on datasets drawn exclusively from the independent cohorts did not produce adequate accuracy.

CONCLUSION

SPLS classification of cortical thickness is a good method for differentiating between AD and DLB, relatively stable even for mixed data, but not when tested on completely independent data drawn from different cohorts (without MR-protocol alignment).

Regional magnetic resonance imaging measures for multivariate analysis in Alzheimer's disease and mild cognitive impairment

Automated structural magnetic resonance imaging (MRI) processing pipelines are gaining popularity for Alzheimer’s disease (AD) research. They generate regional volumes, cortical thickness measures and other measures, which can be used as input for multivariate analysis. It is not clear which combination of measures and normalization approach are most useful for AD classification and to predict mild cognitive impairment (MCI) conversion. The current study includes MRI scans from 699 subjects [AD, MCI and controls (CTL)] from the Alzheimer’s disease Neuroimaging Initiative (ADNI). The Freesurfer pipeline was used to generate regional volume, cortical thickness, gray matter volume, surface area, mean curvature, gaussian curvature, folding index and curvature index measures. 259 variables were used for orthogonal partial least square to latent structures (OPLS) multivariate analysis. Normalisation approaches were explored and the optimal combination of measures determined. Results indicate that cortical thickness measures should not be normalized, while volumes should probably be normalized by intracranial volume (ICV). Combining regional cortical thickness measures (not normalized) with cortical and subcortical volumes (normalized with ICV) using OPLS gave a prediction accuracy of 91.5 % when distinguishing AD versus CTL. This model prospectively predicted future decline from MCI to AD with 75.9 % of converters correctly classified. Normalization strategy did not have a significant effect on the accuracies of multivariate models containing multiple MRI measures for this large dataset. The appropriate choice of input for multivariate analysis in AD and MCI is of great importance. The results support the use of un-normalised cortical thickness measures and volumes normalised by ICV.

Vascular dementia

The epidemic growth of dementia causes great concern for the society. It is customary to consider Alzheimer's disease (AD) as the most common cause of dementia, followed by vascular dementia (VaD). This dichotomous view of a neurodegenerative disease as opposed to brain damage caused by extrinsic factors led to separate lines of research in these two entities. Indeed, accumulated data suggest that the two disorders have additive effects and probably interact; however it is still unknown to what degree. Furthermore, epidemiological studies have shown "vascular" risk factors to be associated with AD. Therefore, a clear distinction between AD and VaD cannot be made in most cases, and is furthermore unhelpful. In the absence of efficacious treatment for the neurodegenerative process, special attention must be given to the vascular component, even in patients with presumed mixed pathology. Symptomatic treatment of VaD and AD is similar, although the former is less effective. For prevention of dementia it is important to treat all factors aggressively, even in stroke survivors who do not show evidence of cognitive decline. In this review, we will give a clinical and pathological picture of the processes leading to VaD and discuss its interaction with AD.

Contributions of brain insulin resistance and deficiency in amyloid-related neurodegeneration in Alzheimer's disease

Alzheimer's disease (AD) is the most common cause of dementia in North America. Growing evidence supports the concept that AD is fundamentally a metabolic disease that results in progressive impairment in the brain's capacity to utilize glucose and respond to insulin and insulin-like growth factor (IGF) stimulation. Moreover, the heterogeneous nature of AD is only partly explained by the brain's propensity to accumulate aberrantly processed, misfolded and aggregated oligomeric structural proteins, including amyloid-β peptides and hyperphosphorylated tau. Evidence suggests that other factors, including impaired energy metabolism, oxidative stress, neuroinflammation, insulin and IGF resistance, and insulin/IGF deficiency in the brain should be incorporated into an overarching hypothesis to develop more realistic diagnostic and therapeutic approaches to AD. In this review, the interrelationship between impaired insulin and IGF signalling and amyloid-β pathology is discussed along with potential therapeutic approaches. Impairments in brain insulin/IGF signalling lead to increased expression of amyloid-β precursor protein (AβPP) and accumulation of AβPP-Aβ. In addition, they promote oxidative stress and deficits in energy metabolism, leading to the activation of pro-AβPP-Aβ-mediated neurodegeneration cascades. Although brain insulin/IGF resistance and deficiency can be induced by primary or secondary disease processes, the soaring rates of peripheral insulin resistance associated with obesity, diabetes mellitus and metabolic syndrome quite likely play major roles in the current AD epidemic. Both clinical and experimental data have linked chronic hyperinsulinaemia to cognitive impairment and neurodegeneration with increased AβPP-Aβ accumulation/reduced clearance in the CNS. Correspondingly, both the restoration of insulin responsiveness and the use of insulin therapy can lead to improved cognitive performance, although with variable effects on brain AβPP-Aβ load. On the other hand, experimental evidence supports the concept that the toxic effects of AβPP-Aβ can promote insulin resistance. Together, these findings suggest that a positive feedback loop of progressive neurodegeneration can develop whereby insulin resistance drives AβPP-Aβ accumulation, and AβPP-Aβ fibril toxicity drives brain insulin resistance. This phenomenon could explain why measuring AβPP-Aβ levels in cerebrospinal fluid or imaging of the brain has proven to be inadequate as a stand-alone biomarker for diagnosing AD, and why the clinical trial results of anti-AβPP-Aβ monotherapy have been disappointing. Instead, the aggregate data suggest that brain insulin resistance and deficiency must also be therapeutically targeted to halt AD progression or reverse its natural course. The positive therapeutic effects of different treatments that address the role of brain insulin/IGF resistance and deficiency, including the use of intranasal insulin delivery, incretins and insulin sensitizer agents are discussed along with potential benefits of lifestyle changes to modify risk for developing mild cognitive impairment or AD. Altogether, the data strongly support the notion that we must shift toward the implementation of multimodal rather than unimodal diagnostic and therapeutic strategies for AD.

Vascular dementia: Diagnostic criteria and supplementary exams. Recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology. Part I

Vascular dementia (VaD) is the most prevalent form of secondary dementia and the second most common of all dementias. The present paper aims to define guidelines on the basic principles for treating patients with suspected VaD (and vascular cognitive impairment - no dementia) using an evidence-based, systematized approach. The knowledge used to define these guidelines was retrieved from searches of several databases (Medline, Scielo, Lilacs) containing scientific articles, systematic reviews, meta-analyses, largely published within the last 15 years or earlier when pertinent. Information retrieved and selected for relevance was used to analyze diagnostic criteria and to propose a diagnostic system encompassing diagnostic criteria, anamnesis, as well as supplementary and clinical exams (neuroimaging and laboratory). Wherever possible, instruments were selected that had versions previously adapted and validated for use in Brazil that take into account both schooling and age. This task led to proposed protocols for supplementary exams based on degree of priority, for application in clinical practice and research settings.

Differential diagnosis between dementia and psychiatric disorders: Diagnostic criteria and supplementary exams. Recommendations of the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology

In 2005, the Scientific Department of Cognitive Neurology and Aging of the Brazilian Academy of Neurology published recommendations for the diagnosis of Alzheimer's disease These recommendations were updated following a review of evidence retrieved from national and international studies held on PUBMED, SCIELO and LILACS medical databases. The main aims of this review article are as follows:

1) to present the evidence found on Brazilian (LILACS, SCIELO) and International (MEDLINE) databases from articles published up to May 2011, on the differential diagnosis of these psychiatric disorders and dementia, with special focus on Dementia due to Alzheimer's and vascular dementia, including a review of supplementary exams which may facilitate the diagnostic process; and

2) to propose recommendations for use by clinicians and researchers involved in diagnosing patients with dementia.

Differential diagnosis between dementia and other neuropsychiatric disorders should always include assessments for depression, delirium, and use of psychoactive substances, as well as investigate the use of benzodiazepines, anti-epileptics and pattern of alcohol consumption.

Clinical use of neuroimaging in dementia: an international perspective

Increasingly, a large number of neuroimaging techniques are being developed and used for research, with some ultimately entering clinical practice (Scheltens et al., 2002; O'Brien, 2007). For most clinicians working with dementia patients, it can be very hard to keep abreast of developments in the field. For example, when does a potentially exciting new technique for diagnosis or monitoring disease progression become sufficiently validated to be accepted by the scientific community? When does such a validated method for research then become justified for use in routine clinical practice? Closely linked to this, when does one have sufficient evidence that a diagnostic tool changes practice to engage with discussions with those commissioning or paying for health services to make a strong business case for funding for the method to be made available? It is also often far from clear, when faced with a patient with cognitive difficulties, exactly what scan should be requested, at what point and why. If one scan is uninformative or equivocal then what should be the next steps? Are there factors that limit sensitivity of a given technique, such as age? Is it worth suggesting another form of brain imaging to find further information, should one wait and monitor the patient clinically over time, or even repeat the same scan to look at progression? These are challenging but important questions which are all addressed in this supplement. Different papers look critically at what imaging methods are currently available – or may very soon become available – in the clinic, what they can show in particular circumstances, how they should be interpreted and how and when such scans should be requested.