Medial temporal lobe atrophy on MRI scans and the diagnosis of Alzheimer disease

Causal structural covariance network revealing atrophy progression in Alzheimer's disease continuum

The structural covariance network (SCN) has provided a perspective on the large‐scale brain organization impairment in the Alzheimer's Disease (AD) continuum. However, the successive structural impairment across brain regions, which may underlie the disrupted SCN in the AD continuum, is not well understood. In the current study, we enrolled 446 subjects with AD, mild cognitive impairment (MCI) or normal aging (NA) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The SCN as well as a casual SCN (CaSCN) based on Granger causality analysis were applied to the T1‐weighted structural magnetic resonance images of the subjects. Compared with that of the NAs, the SCN was disrupted in the MCI and AD subjects, with the hippocampus and left middle temporal lobe being the most impaired nodes, which is in line with previous studies. In contrast, according to the 194 subjects with records on CSF amyloid and Tau, the CaSCN revealed that during AD progression, the CaSCN was enhanced. Specifically, the hippocampus, thalamus, and precuneus/posterior cingulate cortex (PCC) were identified as the core regions in which atrophy originated and could predict atrophy in other brain regions. Taken together, these findings provide a comprehensive view of brain atrophy in the AD continuum and the relationships among the brain atrophy in different regions, which may provide novel insight into the progression of AD.

A longitudinal observation of brain structure between AD and FTLD

INTRODUCTION

Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) are the leading causes of dementia. To better understand the disease development of cognitive function and anatomical structure in AD and FTLD, we analyzed the changes in brain volume by MRI and the psychological test results. Here, we report a dynamic observation of brain structure.

METHODS

Thirteen patients diagnosed with probable AD by the 2011 NIA-AA criteria and eight FTLD patients diagnosed by the FTLD criteria underwent MRI at baseline. All subjects were rescanned after 5 months to 3 years of follow-up. The anatomic changes on T1-weighted imaging of each subject were measured, and the separate changes in the two groups and the differences in the changes between AD and FTLD were analyzed.

RESULTS

In AD patients, the anterior and posterior horns of the lateral ventricle and lateral fissure enlarged progressively (p < 0.001). The volume of the regions, including the medial and lateral temporal lobe, especially the parahippocampal gyrus, and the frontal lobe decreased significantly as the disease progressed (p < 0.001). Additionally, the volume of white matter in the frontal, parietal, temporal lobe and cerebellum decreased in a relatively symmetric pattern (p < 0.001). In FTLD patients, the anterior horn of the lateral ventricle, lateral fissure, cerebral longitudinal fissure, external space of the orbitofrontal cortex, and mesencephalon surrounding the cisterna were enlarged (p < 0.005), while regions including the left frontal lobe, anterior cingulate cortex, basal ganglia (especially the left basal ganglia), left lateral temporal lobe and inferior cerebellar vermis decreased as the disease progressed (p < 0.005). Regarding the differences between AD and FTLD, atrophy of the frontal lobe and bilateral basal ganglia was more significant in FTLD than in AD (p < 0.01). In addition, enlargements of the anterior horn of the lateral ventricle, left lateral fissure and interpeduncular cistern were more significant in FTLD patients than in AD patients (p < 0.01).

CONCLUSIONS

These findings suggest that AD and FTLD have distinctly different atrophy patterns: AD patients show diffuse atrophy while FTLD patients show an asymmetrical focal atrophy pattern, which might explain the relatively better and longer preservation of daily living function in FTLD patients.

Mild behavioral impairment as a predictor of cognitive functioning in older adults

OBJECTIVE

To assess the influence of mild behavioral impairment (MBI) on the cognitive performance of older adults who are cognitively healthy or have mild cognitive impairment (MCI).

METHODS

Secondary data analysis of a sample (n = 497) of older adults from the Florida Alzheimer's Disease Research Center who were either cognitively healthy (n = 285) or diagnosed with MCI (n = 212). Over half of the sample (n = 255) met the operationalized diagnostic criteria for MBI. Cognitive domains of executive function, attention, short-term memory, and episodic memory were assessed using a battery of neuropsychological tests.

RESULTS

Older adults with MBI performed worse on tasks of executive function, attention, and episodic memory compared to those without MBI. A significant interaction revealed that persons with MBI and MCI performed worse on tasks of episodic memory compared to individuals with only MCI, but no significant differences were found in performance in cognitively healthy older adults with or without MBI on this cognitive domain. As expected, cognitively healthy older adults performed better than individuals with MCI on every domain of cognition.

CONCLUSIONS

The present study found evidence that independent of cognitive status, individuals with MBI performed worse on tests of executive function, attention, and episodic memory than individuals without MBI. Additionally, those with MCI and MBI perform significantly worse on episodic memory tasks than individuals with only MCI. These results provide support for a unique cognitive phenotype associated with MBI and highlight the necessity for assessing both cognitive and behavioral symptoms.

Discriminative Feature Network Based on a Hierarchical Attention Mechanism for Semantic Hippocampus Segmentation

The morphological analysis of hippocampus is vital to various neurological studies including brain disorders and brain anatomy. To assist doctors in analyzing the shape and volume of the hippocampus, an accurate and automatic hippocampus segmentation method is highly demanded in the clinical practice. Given that fully convolutional networks (FCNs) have made significant contributions in biomedical image segmentation applications, we propose a notably discriminative feature network based on a hierarchical attention mechanism in hippocampal segmentation. First, considering the problem that the hippocampus is a rather small part in MR images, we design a context-aware high-level feature extraction module (CHFEM) to extract high-level features of scale invariance in the encoder stage. Further, we introduce a hierarchical attention mechanism into our segmentation framework. The mechanism is divided into three parts: a low-level feature spatial attention module (LFSAM) is developed to learn the spatial relationship between different pixels on each channel in the low-level stage of the encoder, a high-level feature channel attention module (HFCAM) is to model the semantic information relationship on different channel images in the high-level stage of the encoder, and a cross-connected attention module (CCAM) is designed in the decoder part to further suppress the noisy boundaries of hippocampus and simultaneously utilize the attentional low-level features from the encoder to better guide the high-level hippocampus edge segmentation in the decoder phase. The proposed approach achieves outstanding performance on the ADNI dataset and the Decathlon dataset compared with other semantic segmentation models and existing hippocampal segmentation approaches. Source code is available at https://github.com/LannyShi/Hippocampal-segmentation.

Evaluation of MR Visual Rating Scales in Major Forms of Dementia

Objective  The aim of the study is to visually rate major forms of dementia using global cortical atrophy (GCA), medial temporal lobe atrophy (MTA), and Fazeka’s scales and Koedam’s score using magnetic resonance imaging (MRI). The purpose is to correlate the visual rating scales (VRS) with severity of dementia.

Materials and Methods  Thirty patients fulfilling DSM 5 (Diagnostic and Statistical Manual of Mental Disorders) criteria for Alzheimer’s dementia (AD), vascular dementia (VaD), and frontotemporal dementia (FTD) underwent MRI brain. Cortical atrophy, medial temporal, and parietal lobe atrophy were assessed using GCA and MTA scales and Koedam’s score, respectively. White matter hyperintensities were assessed using Fazeka’s scale. Correlation between VRS and mini-mental state exam (MMSE) scores was done using Pearson correlation coefficient.

Results  70% of patients had Grade 2 GCA. More patients with AD had higher MTA scores as compared with others with 57% of AD patients showing abnormal for age MTA scores. Fazeka’s scale was abnormal for age in 58.33% of VaD and 57% AD patients. Majority (75%) showing severe parietal atrophy (Grade 3 Koedam’s score) were AD patients. Disproportionate frontal lobe atrophy was seen in all four (100%) FTD patients. Significant negative correlation was seen between MMSE and GCA scores of all patients ( p -value = 0.003) as well as between MTA and MMSE scores in AD patients ( p -value = 0.00095).

Conclusion  Visual rating of MTA is a reliable method for detecting AD and correlates strongly with memory scores. Atrophy of specific regions is seen more commonly in some conditions, for instance, where MTA and parietal atrophy are specific for AD while asymmetric frontal lobe and temporal pole atrophy favor FTD.

Abnormal cortical regions and subsystems in whole brain functional connectivity of mild cognitive impairment and Alzheimer's disease: a preliminary study

The disease roots of Alzheimer's disease (AD) are unknown. Functional connection (FC) methodology based on functional MRI data is an effective lever to investigate macroscopic neural activity patterns. However, regional properties of brain architecture have been less investigated by special markers of graph indexes in general mental disorders. In terms of the set of the abnormal edges in the FCs matrix, this paper introduces the strength index (S-scores) of region centrality on the principle of holism. Then, the important process is to investigate the S-scores of regions and subsystems in 36 healthy controls, 38 mild cognitive impairment (MCI) patients and 34 AD patients. At the edge level, abnormal FCs is numerically increasing progressively from MCI to AD brains. At the region level, the CUN.L, PAL.R, THA.L, and TPOsup.R regions are highlighted with abnormal S-scores in MCI patients. By comparison, more regions are abnormal in AD patients, which are PreCG.L, INS.R, DCG.L, AMYG.R, IOG.R, FFG.L, PoCG.L, PCUN.R, TPOsup.L, MTG.L, and TPOmid.L. Importantly, the regions in DMN have abnormal S-scores in AD groups. At the module level, the S-scores of frontal, parietal, occipital lobe, and cerebellum are found in MCI and AD patients. Meanwhile, the abnormal lateralization is inferred because of the S-scores of left and top hemisphere in the AD group. Though this is strictly a contrastive study, the S-score may be a meaningful imaging marker for excavating AD psychopathology.

Bayesian model selection favors parametric over categorical fMRI subsequent memory models in young and older adults

Subsequent memory paradigms allow to identify neural correlates of successful encoding by separating brain responses as a function of memory performance during later retrieval. In functional magnetic resonance imaging (fMRI), the paradigm typically elicits activations of medial temporal lobe, prefrontal and parietal cortical structures in young, healthy participants. This categorical approach is, however, limited by insufficient memory performance in older and particularly memory-impaired individuals. A parametric modulation of encoding-related activations with memory confidence could overcome this limitation. Here, we applied cross-validated Bayesian model selection (cvBMS) for first-level fMRI models to a visual subsequent memory paradigm in young (18-35 years) and older (51-80 years) adults. Nested cvBMS revealed that parametric models, especially with non-linear transformations of memory confidence ratings, outperformed categorical models in explaining the fMRI signal variance during encoding. We thereby provide a framework for improving the modeling of encoding-related activations and for applying subsequent memory paradigms to memory-impaired individuals.

Personalized Healthcare for Dementia

Dementia is one of the most common health problems affecting older adults, and the population with dementia is growing. Dementia refers to a comprehensive syndrome rather than a specific disease and is characterized by the loss of cognitive abilities. Many factors are related to dementia, such as aging, genetic profile, systemic vascular disease, unhealthy diet, and physical inactivity. As the causes and types of dementia are diverse, personalized healthcare is required. In this review, we first summarize various diagnostic approaches associated with dementia. Particularly, clinical diagnosis methods, biomarkers, neuroimaging, and digital biomarkers based on advances in data science and wearable devices are comprehensively reviewed. We then discuss three effective approaches to treating dementia, including engineering design, exercise, and diet. In the engineering design section, recent advances in monitoring and drug delivery systems for dementia are introduced. Additionally, we describe the effects of exercise on the treatment of dementia, especially focusing on the effects of aerobic and resistance training on cognitive function, and the effects of diets such as the Mediterranean diet and ketogenic diet on dementia.

Olfactory-cognitive index distinguishes involvement of frontal lobe shrinkage, as in sarcopenia from shrinkage of medial temporal areas, and global brain, as in Kihon Checklist frailty/dependence, in older adults with progression of normal cognition to Alzheimer's disease

Aim

Olfactory impairment as a prodromal symptom, as well as sarcopenia, frailty and dependence as geriatric syndromes, is often associated with cognitive decline in older adults with progression of Alzheimer's disease. The present study aimed to evaluate the associations of olfactory and cognitive decline with these geriatric syndromes, and with structural changes of the brain in older adults.

Methods

The participants were 135 older adults (47 men and 88 women, mean age 79.5 years), consisting of 64 with normal cognition, 23 with mild cognitive impairment and 48 with Alzheimer's disease. Olfactory function was evaluated by the Open Essence odor identification test. Shrinkage of the regional brain was determined by magnetic resonance imaging.

Results

Logistic regression analysis with Open Essence, Mini‐Mental State Examination, age and sex as covariates showed higher olfactory‐cognitive index (|coefficient for Open Essence (a) / coefficient for Mini‐Mental State Examination (b)|) in participants with sarcopenia (Asia Working Group for Sarcopenia), and lower values of (|a/b|) in participants with Barthel Index dependence, Kihon Checklist frailty, Lawton Index dependence and support/care‐need certification as objective variables. Logistic regression analysis adjusted by age and sex also showed significant shrinkage of the frontal lobe in participants with AWGS sarcopenia, especially in women, and shrinkage of the medial temporal areas and global brain in participants with Kihon Checklist frailty/dependence.

Conclusions

Olfactory‐cognitive index (|a/b|) might be a useful tool to distinguish involvement of frontal lobe shrinkage, as in sarcopenia from shrinkage of the medial temporal areas, and global brain, as in frailty/dependence, in older adults with progression of normal cognition to Alzheimer's disease. Geriatr Gerontol Int 2021; ••: ••–••.

Diagnosis of Rapidly Progressive Dementia in a Referral Center in Argentina

INTRODUCTION

Rapidly progressive dementia (RPD) is a broadly defined clinical syndrome. Our aim was to describe clinical and ancillary study findings in patients with RPD and evaluate their diagnostic performance for the identification of nonchronic neurodegenerative rapidly progressive dementia (ncnRPD).

METHODS

We reviewed clinical records and ancillary methods of patients evaluated for RPD at our institution in Buenos Aires, Argentina from 2011 to 2017. We compared findings between chronic neurodegenerative RPD and ncnRPD and evaluated the diagnostic metrics using receiver operating characteristic curves.

RESULTS

We included 104 patients with RPD, 29 of whom were chronic neurodegenerative RPD and 75 of whom were ncnRPD. The 6-month time to dementia cutpoint had a sensitivity of 89% and specificity of 100% for ncnRPD, with an area under the receiver operating characteristic curve of 0.965 (95% confidence interval=0.935-0.99; P<0.001). A decision tree that included time to dementia, brain magnetic resonance imaging, and cerebrospinal fluid analysis identified ncnRPD patients with a sensitivity of 100%, specificity of 79%, positive predictive value of 93%, and negative predictive value of 100% overall.

DISCUSSION

RPD is a clinical syndrome that comprises different diagnoses, many of them for treatable diseases. Using the time to dementia, brain magnetic resonance imaging, and cerebrospinal fluid analysis when triaging these patients could help identify those diseases that need to be studied more aggressively.

Neuropsychiatric symptoms as a distinguishing factor between memory diagnoses

OBJECTIVES

To determine whether neuropsychiatric symptoms (NPS) are able to differentiate those with mild cognitive impairment (MCI) and dementia from persons who are cognitively healthy.

METHODS

Multinomial and binary logistic regressions were used to assess secondary data of a sample (n = 613) of older adults with NPS. Analyses evaluated the ability to differentiate between diagnoses, as well as the influence of these symptoms for individuals with amnestic MCI (MCI-A), non-amnestic MCI (MCI-NA), and dementia compared with those who are cognitively healthy.

RESULTS

Persons with MCI were more likely to have anxiety, apathy, and appetite changes compared with cognitively healthy individuals. Persons with dementia were more likely to have aberrant motor behaviors, anxiety, apathy, appetite changes, and delusions compared with those who were cognitively healthy. Individuals with any type of cognitive impairment were more likely to have anxiety, apathy, appetite changes, and delusions. Specifically, anxiety, apathy, appetite changes, and disinhibition were predictors of MCI-A; agitation and apathy were predictors of MCI-NA; and aberrant motor behaviors, anxiety, apathy, appetite changes, and delusions were predictors of dementia. Finally, nighttime behavior disorders were less likely in individuals with dementia.

CONCLUSIONS

The present study's results demonstrate that specific NPS are differentially represented among types of cognitive impairment and establish the predictive value for one of these cognitive impairment diagnoses.

The neurophysiology and seizure outcomes of late onset unexplained epilepsy

OBJECTIVE

To investigate neurophysiologic and neuroimaging characteristics of patients with late onset unexplained epilepsy (LOUE).

METHODS

We performed a retrospective chart review of elderly patients with ICD9 diagnosis codes consistent with epilepsy/seizures. Inclusion criteria included unprovoked seizures, and absence of cortical lesions on magnetic resonance imaging (MRI). Electroencephalograms (EEGs) findings were also analyzed. MRI images were scored for degree of white matter hyperintensities (Fazekas Scale) and mesial temporal atrophy (MTA). Vascular risk factors, and Framingham Heart Study general cardiovascular disease (FHS-CVD) risk scores were compared to controls from the Harvard Aging Brain study (HABS).

RESULTS

We identified 224 LOUE patients and 8% were drug resistant. Epileptiform abnormalities were captured on EEG in 35%. The location was temporal with left sided predominance in 49%. Fazekas scale consisted of 25% beginning of confluent lesions, and 10% large confluent lesions. MTA scores consisted of 21% moderate-severe hippocampal atrophy. LOUE patients had on average a 2.3% (adjusted), 7.4% (unadjusted) increased FHS-CVD score.

CONCLUSIONS

Our findings highlight LOUE as pharmacosensitive and left temporal predominant. Given the higher prevalence of vascular risk factors, investigations are needed to study their role in pathophysiology.

SIGNIFICANCE

Physicians caring for patients with LOUE should evaluate for vascular risk factors and investigate the presence of hippocampal atrophy.

Global Brain Involvement in Posterior Cortical Atrophy: Multimodal MR Imaging Investigation

Posterior cortical atrophy (PCA), considered a visual variant of Alzheimer's disease, has similar pathological characteristics yet shows a selective visual manifestation with relative preservation of other cortical areas, at least at early stages of disease. Using a gamut of imaging methods, we aim to evaluate the global aspect of this relatively local disease and describe the interplay of the involvement of the different brain components. Ten PCA patients and 14 age-matched controls underwent MRI scans. Cortical thickness was examined to identify areas of cortical thinning. Hippocampal volume was assessed using voxel-based morphometry. The integrity of 20 fiber tracts was assessed by Diffusion Tensor Imaging. Regions of difference in global functional connectivity were identified by resting-state fMRI, using multi-variant pattern analysis. Correlations were examined to evaluate the connection between grey matter atrophy, the network changes and the disease load. The patients presented bilateral cortical thinning, primarily in their brains' posterior segments. Impaired segments of white matter integrity were evident only within three fiber tracts in the left hemisphere. Four areas were identified as different in their global connectivity pattern. The visual network-related areas showed reduced connectivity and was correlated to atrophy. Right Broadman area 39 showed in addition increased connectivity to the frontal areas. Global structural and functional imaging pointed to the highly localized nature of PCA. Functional connectivity followed grey matter atrophy in visual regions. White matter involvement seemed less prominent, however damage is directly related to presence of disease and not mediated only by grey matter damage.

Structural magnetic resonance imaging for the early diagnosis of dementia due to Alzheimer's disease in people with mild cognitive impairment

BACKGROUND

Mild cognitive impairment (MCI) due to Alzheimer's disease is the symptomatic predementia phase of Alzheimer's disease dementia, characterised by cognitive and functional impairment not severe enough to fulfil the criteria for dementia. In clinical samples, people with amnestic MCI are at high risk of developing Alzheimer's disease dementia, with annual rates of progression from MCI to Alzheimer's disease estimated at approximately 10% to 15% compared with the base incidence rates of Alzheimer's disease dementia of 1% to 2% per year.

OBJECTIVES

To assess the diagnostic accuracy of structural magnetic resonance imaging (MRI) for the early diagnosis of dementia due to Alzheimer's disease in people with MCI versus the clinical follow-up diagnosis of Alzheimer's disease dementia as a reference standard (delayed verification). To investigate sources of heterogeneity in accuracy, such as the use of qualitative visual assessment or quantitative volumetric measurements, including manual or automatic (MRI) techniques, or the length of follow-up, and age of participants. MRI was evaluated as an add-on test in addition to clinical diagnosis of MCI to improve early diagnosis of dementia due to Alzheimer's disease in people with MCI.

SEARCH METHODS

On 29 January 2019 we searched Cochrane Dementia and Cognitive Improvement's Specialised Register and the databases, MEDLINE, Embase, BIOSIS Previews, Science Citation Index, PsycINFO, and LILACS. We also searched the reference lists of all eligible studies identified by the electronic searches.

SELECTION CRITERIA

We considered cohort studies of any size that included prospectively recruited people of any age with a diagnosis of MCI. We included studies that compared the diagnostic test accuracy of baseline structural MRI versus the clinical follow-up diagnosis of Alzheimer's disease dementia (delayed verification). We did not exclude studies on the basis of length of follow-up. We included studies that used either qualitative visual assessment or quantitative volumetric measurements of MRI to detect atrophy in the whole brain or in specific brain regions, such as the hippocampus, medial temporal lobe, lateral ventricles, entorhinal cortex, medial temporal gyrus, lateral temporal lobe, amygdala, and cortical grey matter.

DATA COLLECTION AND ANALYSIS

Four teams of two review authors each independently reviewed titles and abstracts of articles identified by the search strategy. Two teams of two review authors each independently assessed the selected full-text articles for eligibility, extracted data and solved disagreements by consensus. Two review authors independently assessed the quality of studies using the QUADAS-2 tool. We used the hierarchical summary receiver operating characteristic (HSROC) model to fit summary ROC curves and to obtain overall measures of relative accuracy in subgroup analyses. We also used these models to obtain pooled estimates of sensitivity and specificity when sufficient data sets were available.

MAIN RESULTS

We included 33 studies, published from 1999 to 2019, with 3935 participants of whom 1341 (34%) progressed to Alzheimer's disease dementia and 2594 (66%) did not. Of the participants who did not progress to Alzheimer's disease dementia, 2561 (99%) remained stable MCI and 33 (1%) progressed to other types of dementia. The median proportion of women was 53% and the mean age of participants ranged from 63 to 87 years (median 73 years). The mean length of clinical follow-up ranged from 1 to 7.6 years (median 2 years). Most studies were of poor methodological quality due to risk of bias for participant selection or the index test, or both. Most of the included studies reported data on the volume of the total hippocampus (pooled mean sensitivity 0.73 (95% confidence interval (CI) 0.64 to 0.80); pooled mean specificity 0.71 (95% CI 0.65 to 0.77); 22 studies, 2209 participants). This evidence was of low certainty due to risk of bias and inconsistency. Seven studies reported data on the atrophy of the medial temporal lobe (mean sensitivity 0.64 (95% CI 0.53 to 0.73); mean specificity 0.65 (95% CI 0.51 to 0.76); 1077 participants) and five studies on the volume of the lateral ventricles (mean sensitivity 0.57 (95% CI 0.49 to 0.65); mean specificity 0.64 (95% CI 0.59 to 0.70); 1077 participants). This evidence was of moderate certainty due to risk of bias. Four studies with 529 participants analysed the volume of the total entorhinal cortex and four studies with 424 participants analysed the volume of the whole brain. We did not estimate pooled sensitivity and specificity for the volume of these two regions because available data were sparse and heterogeneous. We could not statistically evaluate the volumes of the lateral temporal lobe, amygdala, medial temporal gyrus, or cortical grey matter assessed in small individual studies. We found no evidence of a difference between studies in the accuracy of the total hippocampal volume with regards to duration of follow-up or age of participants, but the manual MRI technique was superior to automatic techniques in mixed (mostly indirect) comparisons. We did not assess the relative accuracy of the volumes of different brain regions measured by MRI because only indirect comparisons were available, studies were heterogeneous, and the overall accuracy of all regions was moderate.

AUTHORS' CONCLUSIONS

The volume of hippocampus or medial temporal lobe, the most studied brain regions, showed low sensitivity and specificity and did not qualify structural MRI as a stand-alone add-on test for an early diagnosis of dementia due to Alzheimer's disease in people with MCI. This is consistent with international guidelines, which recommend imaging to exclude non-degenerative or surgical causes of cognitive impairment and not to diagnose dementia due to Alzheimer's disease. In view of the low quality of most of the included studies, the findings of this review should be interpreted with caution. Future research should not focus on a single biomarker, but rather on combinations of biomarkers to improve an early diagnosis of Alzheimer's disease dementia.

Cognitive impairments in type 2 diabetes, risk factors and preventive strategies

Mild cognitive impairment (MCI) is a modifiable risk factor in progression of several diseases including dementia and type 2 diabetes. If cognitive impairments are not reversed at an early stage of appearance of symptoms, then the prolonged pathogenesis can lead to dementia and Alzheimer's disease (AD). Therefore, it is necessary to detect the risk factors and mechanism of prevention of cognitive dysfunction at an early stage of disease. Poor lifestyle, age, hyperglycemia, hypercholesterolemia, and inflammation are some of the major risk factors that contribute to cognitive and memory impairments in diabetic patients. Mild cognitive impairment was seen in those individuals of type 2 diabetes, who are on an unhealthy diet. Physical inactivity, frequent alcohol consumptions, and use of packed food products that provides an excess of cheap calories are found associated with cognitive impairment and depression in diabetic patients. Omega fatty acids (FAs) and polyphenol-rich foods, especially flavonoids, can reduce the bad effects of an unhealthy lifestyle; therefore, the consumption of omega FAs and flavonoids may be beneficial in maintaining normal cognitive function. These functional foods may improve cognitive functions by targeting many enzymes and molecules in cells chiefly through their anti-inflammatory, antioxidant, or signaling actions. Here, we provide the current concepts on the risk factors of cognitive impairments in type 2 diabetes and the mechanism of prevention, using omega FAs and bioactive compounds obtained from fruits and vegetables. The knowledge derived from such studies may assist physicians in managing the health care of patients with cognitive difficulties.

Utility of Amyloid PET Scans in the Evaluation of Patients Presenting with Diverse Cognitive Complaints

BACKGROUND

The impact of amyloid positron emission tomography (Aβ-PET) in a "real-world" memory disorders clinic remains poorly studied.

OBJECTIVE

We studied the impact of Aβ-PET in diagnosis and management in the memory clinic and factors making the most impact in diagnosis and management.

METHODS

We studied 102 patients who had presented at a memory disorders clinic (the Wien Center for Alzheimer's Disease and Memory Disorders, Miami Beach, FL) and had a diagnostic work-up for cognitive complaints, including Aβ-PET scans.

RESULTS

Following Aβ-PET, changes were made in diagnosis (37.3%), in specific treatments for Alzheimer's disease (26.5%) and in psychiatric treatments (25.5%). The agreement between diagnosis pre-Aβ-PET versus post-Aβ-PET diagnosis was only fair, with a Cohen's kappa of 0.23 (95% CI 0-0.42). Patients with MRI findings suggestive of AD (medial temporal and/or parietal atrophy) were more frequently amyloid positive than amyloid negative (66.2% versus 33.8%, p = 0.04). Among patients with atypical clinical features for AD, but with MRI findings suggestive of AD, an amyloid negative PET scan had a greater impact than an amyloid positive PET scan on diagnosis (84.2% versus 17.1%, p < 0.001), management (84.2% versus 40%, p < 0.01) and discussion of results and advice on lifestyle (73.7% versus 22.9%, p < 0.001).

CONCLUSIONS

We conclude that MRI features suggestive of AD predict a positive amyloid PET scan. However, among those with MRI features suggestive of AD but with atypical clinical features of AD, the clinical impact on diagnosis and management is greater for an amyloid negative than an amyloid positive Aβ-PET scans.

Are Linear Measurements of the Nucleus Basalis of Meynert Suitable as a Diagnostic Biomarker in Mild Cognitive Impairment and Alzheimer Disease?

BACKGROUND AND PURPOSE

Cell loss within the nucleus basalis of Meynert is an early event in Alzheimer disease. The thickness of the nucleus basalis of Meynert (NBM) can be measured on structural MR imaging. We investigated NBM thickness in relation to cognitive state and biochemical markers.

MATERIALS AND METHODS

Mean bilateral nucleus basalis of Meynert thickness was measured on coronal T1-weighted MR imaging scans from the Alzheimer's Disease Neuroimaging Initiative dataset. Three hundred and fifteen scans (80 controls, 79 cases of early mild cognitive impairment, 77 cases of late mild cognitive impairment and 79 cases of Alzheimer disease) were assessed. Alzheimer's Disease Assessment Scale-Cognitive scores, CSF tau, and amyloid quantification were extracted. Group differences in NBM thickness, their correlates and measurement reliability were assessed.

RESULTS

Mean NBM thickness ± SD progressively declined from 2.9 ± 0.3, 2.5 ± 0.3, and 2.3 ± 0.3 to 1.8 ± 0.4 mm in healthy controls, patients with early mild cognitive impairment, late mild cognitive impairment and Alzheimer disease respectively (P < .001). NBM thickness was negatively correlated with Alzheimer's Disease Assessment Scale-Cognitive scores (r = -0.53, P < .001) and weakly positively correlated with CSF amyloid (r = 0.250, P < .001) respectively. No association with CSF tau was found. NBM thickness showed excellent diagnostic accuracy to differentiate Alzheimer disease (area under the curve, 0.986) and late mild cognitive impairment from controls (area under the curve, 0.936) with excellent sensitivity, but lower specificity 66.7%. Intra- and interrater reliability for measurements was 0.66 and 0.47 (P < .001).

CONCLUSIONS

There is progressive NBM thinning across the aging-dementia spectrum, which correlates with cognitive decline and CSF markers of amyloid-β pathology. We show high diagnostic accuracy but limited reliability, representing an area for future improvement. NBM thickness is a promising, readily available MR imaging biomarker of Alzheimer disease warranting diagnostic-accuracy testing in clinical practice.

Longitudinal brain atrophy patterns and neuropsychological performance in older adults with HIV-associated neurocognitive disorder compared with early Alzheimer's disease

Older HIV-infected patients are at risk for both HIV-associated neurocognitive disorder (HAND) and Alzheimer's disease. We investigated neuroimaging and neuropsychological performance of 61 virally suppressed older adults with HAND (mean (SD) age 64.3 (3.9) years), 53 demographically matched individuals with mild cognitive impairment of the Alzheimer's type (MCI-AD; 65.0 [4.8]), and 89 healthy controls (65.0 [4.3]) cross-sectionally and over 20 months. At the baseline, both disease groups exhibited lower volumes in multiple cortical and subcortical regions compared with controls. Hippocampal volume differentiated MCI-AD from HAND. Cognitively, MCI-AD performed worse on memory and language compared with HAND. Adjusted longitudinal models revealed greater diffuse brain atrophy in MCI-AD compared with controls, whereas HAND showed greater atrophy in frontal gray matter and cerebellum compared with controls. Comparing HAND with MCI-AD showed similar atrophy rates in all brain regions explored, with no significant findings. MCI-AD exhibited more pronounced language decline compared with HAND. These findings reveal the need for further work on unique cognitive phenotypes and neuroimaging signatures of HAND compared with early AD, providing preliminary clinical insight for differential diagnosis of age-related brain dysfunction in geriatric neuroHIV.

Factors influencing attrition in 35 Alzheimer's Disease Centers across the USA: a longitudinal examination of the National Alzheimer's Coordinating Center's Uniform Data Set

OBJECTIVE

A lack of understanding of the causes of attrition in longitudinal studies of older adults may lead to higher attrition rates and bias longitudinal study results. In longitudinal epidemiological studies of Alzheimer's disease and related dementias, high rates of attrition may cause a systematic underestimation of dementia prevalence and skew the characterization of the disease. This can compromise the generalizability of the study results and any inferences based on the surviving sample may grossly misrepresent the importance of the risk factors for dementia. The National Institute on Aging outlined a National Strategy for Recruitment and Participation in Alzheimer's Disease Clinical Research to address this problem, providing evidence of the magnitude of this problem.

METHOD

To explore predictors of attrition, this study examined the National Alzheimer's Coordinating Center (NACC) Uniform Data Set, a repository of observations of older adults spanning 11 years, using survival analysis. Four samples were examined: the full sample (n = 30,433), the alive subsample excluding those who died (n = 24,231), the MRI sample [participants with complete MRI data (n = 1104)], and the alive MRI subsample [participants with MRI data excluding those who died (n = 947)].

RESULTS

Worsening cognitive impairment, neuropsychiatric symptoms, and difficulty with functional activities predicted attrition, as did lower hippocampal volume in the MRI subsample. Questionable co-participant reliability and an informant other than a spouse also increased risk of attrition.

DISCUSSION

Special considerations exist in recruiting and retaining older adults in longitudinal studies, and results of baseline psychological, functional, and cognitive functioning should be used to identify targeted retention strategies.

A clinically-translatable machine learning algorithm for the prediction of Alzheimer's disease conversion: further evidence of its accuracy via a transfer learning approach

BACKGROUND

In a previous study, we developed a highly performant and clinically-translatable machine learning algorithm for a prediction of three-year conversion to Alzheimer's disease (AD) in subjects with Mild Cognitive Impairment (MCI) and Pre-mild Cognitive Impairment. Further tests are necessary to demonstrate its accuracy when applied to subjects not used in the original training process. In this study, we aimed to provide preliminary evidence of this via a transfer learning approach.

METHODS

We initially employed the same baseline information (i.e. clinical and neuropsychological test scores, cardiovascular risk indexes, and a visual rating scale for brain atrophy) and the same machine learning technique (support vector machine with radial-basis function kernel) used in our previous study to retrain the algorithm to discriminate between participants with AD (n = 75) and normal cognition (n = 197). Then, the algorithm was applied to perform the original task of predicting the three-year conversion to AD in the sample of 61 MCI subjects that we used in the previous study.

RESULTS

Even after the retraining, the algorithm demonstrated a significant predictive performance in the MCI sample (AUC = 0.821, 95% CI bootstrap = 0.705-0.912, best balanced accuracy = 0.779, sensitivity = 0.852, specificity = 0.706).

CONCLUSIONS

These results provide a first indirect evidence that our original algorithm can also perform relevant generalized predictions when applied to new MCI individuals. This motivates future efforts to bring the algorithm to sufficient levels of optimization and trustworthiness that will allow its application in both clinical and research settings.

Findings from the Swedish Study on Familial Alzheimer's Disease Including the APP Swedish Double Mutation

This is a brief summary of the findings from the Swedish study on familial Alzheimer's disease (FAD). Similar to other FAD studies, it includes prospective assessments of cognitive function, tissue sampling, and technical analyses such as MRI and PET. This 24-year-old study involves 69 individuals with a 50% risk of inheriting a disease-causing mutation in presenilin 1 (PSEN1 H163Y or I143T), or amyloid precursor protein (the Swedish APP or the arctic APP mutation) who have made a total of 169 visits. Our results show the extraordinary power in this study design to unravel the earliest changes in preclinical AD. The Swedish FAD study will continue and future research will focus on disentangling the order of pathological change using longitudinal data as well as modeling the changes in patient derived cell systems.

Prevalence, Semiology, and Risk Factors of Epilepsy in Alzheimer's Disease: An Ambulatory EEG Study

BACKGROUND

Alzheimer's disease (AD) is the primary cause of cognitive decline. A growing body of evidence suggests that AD patients have a higher risk to develop epileptic seizures; however, results are contradictory due to different methodological approaches of previous studies.

OBJECTIVE

We aimed to identify the prevalence, semiology, and risk factors of epilepsy in AD using long-term EEG.

METHODS

We selected forty-two AD patients and examined them using 24-hour ambulatory EEG. Neurological and epileptological data were collected with retro- and prospective methods. We analyzed the semiology of the identified seizures and the possible risk factors using logistic regression analysis.

RESULTS

We identified seizures confirmed by EEG in 24%. The majority of the seizures were aware focal (72%) without any motor activity (55%). We found epileptiform discharges without seizures in 28%. Patients with seizures and only with epileptic EEG activity showed similar clinical and demographical features. Higher education (OR:1.8) and lower Addenbrooke Examination Score (OR: 0.9) were identified as risk factors of epilepsy. Increase of 0.1 point in the Verbal-Language/Orientation-Memory ratio (VLOM) was associated with higher epilepsy risk as well (OR:2.9).

CONCLUSION

Epilepsy is a frequent comorbidity of AD. Since most of the seizures are aware non-motor focal seizures, sensitive EEG techniques are required for precise diagnosis of epilepsy. Long-term ambulatory EEG is a safe and well-tolerated option. Epileptiform EEG in AD signals the presence of concomitant epilepsy. Clinicians have to pay attention to comorbid epilepsy in dementia patients with high education, with high VLOM ratio and severe stage.

Alzheimer Disease-associated Cortical Atrophy Does not Differ Between Chinese and Whites

PURPOSE

To assess whether there are differences in Alzheimer disease (AD)-associated atrophy regions in Chinese and white patients with AD versus cognitively normal older adults, and to test whether associations between clinical severity and gray matter volume are similar or different across these ethnic groups in a cross-sectional analysis.

MATERIALS AND METHODS

Chinese and white patients with AD, individuals with mild cognitive impairment, and cognitively normal controls (46 white and 48 Chinese) were clinically evaluated at an academic center within 1 year of magnetic resonance imaging acquisition. Clinical severity was assessed using the Clinical Dementia Rating Sum of Boxes and cortical atrophy was measured using voxel-based morphometry as well as Freesurfer. Chinese and white cohorts were demographically matched for age, sex, and education.

RESULTS

Clinical severity by diagnosis was similar across ethnicities. Chinese and white patient groups showed similar amounts of atrophy in the regions most affected in AD after accounting for demographic variables and head size. There was no significant difference between ethnic groups when compared by atrophy and clinical severity.

CONCLUSIONS

Our study suggests that Chinese and white patients with AD, when matched demographically, are clinically and neuroanatomically similar on normalized measures of cortical atrophy and clinical severity.

The usefulness of visual rating of posterior atrophy in predicting rapid cognitive decline in Alzheimer disease: A preliminary study

BACKGROUND

Approximately 10% to 30% of Alzheimer disease (AD) patients progress rapidly in severity and become more dependent on caregivers. Although several studies have investigated whether imaging biomarkers such as medial temporal atrophy (MTA) and posterior atrophy (PA) are useful for predicting the rapid progression of AD, their results have been inconsistent.

OBJECTIVE

The study aims to investigate the association of visually rated MTA and PA with rapid disease progression in AD.

METHODS

This was a retrospective cohort study of 159 AD patients who were initially diagnosed with mild AD and were followed for 1 year to determine whether they progressed rapidly (a decrease of three points or more on the Mini-Mental State Examination over 1 year). We used 5-point and 4-point visual rating scales to assess MTA and PA, respectively. MTA and PA scores for each patient were dichotomized as normal (without atrophy) or abnormal (atrophy). We performed a logistic regression analysis to determine the odds ratios (ORs) of MTA and PA for rapid disease progression with adjustment for covariates.

RESULTS

Within the study population, 47 (29.6%) patients progressed rapidly. Visual assessment of the magnetic resonance imaging (MRI) scans revealed that 112 patients (70.4%) showed MTA, whereas 80 patients (50.3%) showed PA. The ORs with 95% confidence intervals for MTA and PA were 1.825 (0.819-4.070) and 2.844 (1.378-5.835), respectively. The association of visually assessed PA, but not MTA, with rapid progression was significant after adjustment for covariates.

CONCLUSION

In patients with mild AD, visual assessment of PA exhibits independent predictive value for rapid disease progression.

Identifying brain changes related to cognitive aging using VBM and visual rating scales

Aging is often associated with changes in brain structures as well as in cognitive functions. Structural changes can be visualized with Magnetic Resonance Imaging (MRI) using voxel-based grey matter morphometry (VBM) and visual rating scales to assess atrophy level. Several MRI studies have shown that possible neural correlates of cognitive changes can be seen in normal aging. It is still not fully understood how cognitive function as measured by tests and demographic factors are related to brain changes in the MRI. We recruited 55 healthy elderly subjects aged 50–79 years. A battery of cognitive tests was administered to all subjects prior to MRI scanning. Our aim was to assess correlations between age, sex, education, cognitive test performance, and the said two MRI-based measures. Our results show significant differences in VBM grey matter volume for education level (≤ 12 vs. > 12 years), with a smaller amount of grey matter volume in subjects with lower educational levels, and for age in interaction with education, indicating larger grey matter volume for young, higher educated adults. Also, grey matter volume was found to be correlated with working memory function (Digit Span Backward). Furthermore, significant positive correlations were found between visual ratings and both age and education, showing larger atrophy levels with increasing age and decreasing level of education. These findings provide supportive evidence that MRI-VBM detects structural differences for education level, and correlates with educational level and age, and working memory task performance.

•

VBM grey matter volume differences were significant for the interaction of age and education level.

•

Grey matter volume correlated with education level and working memory function (Digit Span Backward).

•

Significant correlations were found between visual rating scales and both age and education.

•

VBM is able to detect structural differences for age and education, and correlates with education and working memory.

Structural imaging findings on non-enhanced computed tomography are severely underreported in the primary care diagnostic work-up of subjective cognitive decline

Purpose

The purpose of this study was to investigate how structural imaging findings of medial temporal lobe atrophy (MTA), posterior cortical atrophy (PCA), global cortical atrophy (GCA), white matter changes (WMC), and Evans’ index/width of lateral ventricles (EI/WLV) are reported in the primary care diagnostic work-up of patients with subjective cognitive decline or mild cognitive impairment.

Methods

We included 197 patients referred to a non-enhanced computed tomography (NECT) as part of the diagnostic work-up. We compared the frequencies of reported findings in radiology reports written by neuroradiologists and general radiologists with actual pathological findings in a second view done by a single neuroradiologist using the MTA, PCA, GCA, WMC, and EI/WLV visual rating scales. Structural findings were also compared to cognitive tests.

Results

We found that MTA and PCA were clearly underreported by both neuroradiologists and general radiologists. The presence of GCA and WMC was also underreported among general radiologists. Only MTA showed a clear association with cognitive test results.

Conclusions

We believe that the use of visual rating scales should be put into clinical practice to increase the yield of clinical NECT exams in the investigation of cognitive impairment. Special emphasis should be put on reporting MTA.

Resilience and amygdala function in older healthy and depressed adults

BACKGROUND

Previous studies suggest that low emotional resilience may correspond with increased or over-active amygdala function. Complementary studies suggest that emotional resilience increases with age; older adults tend to have decreased attentional bias to negative stimuli compared to younger adults. Amygdala nuclei and related brain circuits have been linked to negative affect, and depressed patients have been demonstrated to have abnormal amygdala function.

METHODS

In the current study, we correlated psychological resilience measures with amygdala function measured with resting-state arterial spin-labelled (ASL) and blood-oxygenation-level-dependent (BOLD) functional magnetic resonance imaging (fMRI) in older adults with and without depression. Specifically, we targeted the basolateral, centromedial, and superficial nuclei groups of the amygdala, which have different functions and brain connections.

RESULTS

High levels of psychological resilience correlated with lower basal levels of amygdala activity measured with ASL fMRI. High resilience also correlated with decreased connectivity between amygdala nuclei and the ventral default-mode network independent of depression status. Instead, lower depression symptoms were associated with higher connectivity between the amygdalae and dorsal frontal networks.

LIMITATIONS

Future multi-site studies with larger sample size and improved neuroimaging technologies are needed. Longitudinal studies that target resilience to naturalistic stressors will also be a powerful contribution to the field.

CONCLUSIONS

Our results suggest that resilience in older adults is more closely related to function in ventral amygdala networks, while late-life depression is related to reduced connectivity between the amygdala and dorsal frontal regions.

Longitudinal changes in the brain in mild cognitive impairment: a magnetic resonance imaging study using the visual rating method and tensor-based morphometry

Background Brain atrophy is associated with mild cognitive impairment (MCI), and by using volumetric and visual analyzing methods, it is possible to differentiate between individuals with progressive MCI (MCIp) and stable MCI (MCIs). Automated analysis methods detect degenerative changes in the brain earlier and more reliably than visual methods. Purpose To detect and evaluate structural brain changes between and within the MCIs, MCIp, and control groups during a two-year follow-up period. Material and Methods Brain magnetic resonance imaging (MRI) scans of 11 participants with MCIs, 18 participants with MCIp, and 84 controls were analyzed by the visual rating method (VRM) and tensor-based morphometry (TBM). Results At baseline, both VRM and TBM differentiated the whole MCI group (combined MCIs and MCIp) and the MCIp group from the control group, but they did not differentiate the MCIs group from the control group. At follow-up, both methods differentiated the MCIp group from the control group, but minor differences between the MCIs and control groups were only seen by TBM. Neuropsychological tests did not find differences between the MCIs and control groups at follow-up. Neither method revealed relevant signs of brain atrophy progression within or between MCI subgroups during the follow-up time. Conclusion Both methods are equally good in the evaluation of structural brain changes in MCI if the groups are sufficiently large and the disease progresses to AD. Only TBM disclosed minor atrophic changes in the MCIs group compared to controls at follow-up. The results need to be confirmed with a large patient group and longer follow-up time.

Visual Evaluation of Medial Temporal Lobe Atrophy as a Clinical Marker of Conversion from Mild Cognitive Impairment to Dementia and for Predicting Progression in Patients with Mild Cognitive Impairment and Mild Alzheimer's Disease

BACKGROUND/AIMS

To evaluate whether visual assessment of medial temporal lobe atrophy (vaMTA) can predict 2-year conversion from mild cognitive impairment (MCI) to dementia and progression of MCI and Alzheimer's disease dementia as measured by the Clinical Dementia Rating Scale Sum of Boxes score (CDR-SB).

METHODS

vaMTA was performed in 94 patients with MCI according to the Winblad criteria and in 124 patients with AD according to ICD-10 and NINCDS-ADRDA criteria. Demographic data, the Consortium to Establish a Registry for Alzheimer's Disease 10-word delayed recall, APOE ɛ4 status, Cornell Scale for Depression in Dementia, and comorbid hypertension were used as covariates.

RESULTS

vaMTA was associated with MCI conversion in an unadjusted model but not in an adjusted model (p = 0.075), where delayed recall and APOE ɛ4 status were significant predictors. With CDR-SB change as the outcome, an interaction between vaMTA and diagnosis was found, but in the adjusted model only delayed recall and age were significant predictors. For vaMTA below 2, the association between vaMTA and CDR-SB change differed between diagnostic groups. Similar results were found based on a trajectory analysis.

CONCLUSION

In adjusted models, memory function, APOE ɛ4 status and age were significant predictors of disease progression, not vaMTA. The association between vaMTA and CDR-SB change was different in patients with MCI and Alzheimer's disease dementia.

Altered Whole-Brain Structural Covariance of the Hippocampal Subfields in Subcortical Vascular Mild Cognitive Impairment and Amnestic Mild Cognitive Impairment Patients

The hippocampus plays important roles in memory processing. However, the hippocampus is not a homogeneous structure, which consists of several subfields. The hippocampal subfields are differently affected by many neurodegenerative diseases, especially mild cognitive impairment (MCI). Amnestic mild cognitive impairment (aMCI) and subcortical vascular mild cognitive impairment (svMCI) are the two subtypes of MCI. aMCI is characterized by episodic memory loss, and svMCI is characterized by extensive white matter hyperintensities and multiple lacunar infarctions on magnetic resonance imaging. The primary cognitive impairment in svMCI is executive function, attention, and semantic memory. Some variations or disconnections within specific large-scale brain networks have been observed in aMCI and svMCI patients. The aim of this study was to investigate abnormalities in structural covariance networks (SCNs) between hippocampal subfields and the whole cerebral cortex in aMCI and svMCI patients, and whether these abnormalities are different between the two groups. Automated segmentation of hippocampal subfields was performed with FreeSurfer 5.3, and we selected five hippocampal subfields as the seeds of SCN analysis: CA1, CA2/3, CA4/dentate gyrus (DG), subiculum, and presubiculum. SCNs were constructed based on these hippocampal subfield seeds for each group. Significant correlations between hippocampal subfields, fusiform gyrus (FFG), and entorhinal cortex (ERC) in gray matter volume were found in each group. We also compared the differences in the strength of structural covariance between any two groups. In the aMCI group, compared to the normal controls (NC) group, we observed an increased association between the left CA1/CA4/DG/subiculum and the left temporal pole. Additionally, the hippocampal subfields (bilateral CA1, left CA2/3) significantly covaried with the orbitofrontal cortex in the svMCI group compared to the NC group. In the aMCI group compared to the svMCI group, we observed decreased association between hippocampal subfields and the right FFG, while we also observed an increased association between the bilateral subiculum/presubiculum and bilateral ERC. These findings provide new evidence that there is altered whole-brain structural covariance of the hippocampal subfields in svMCI and aMCI patients and provide insights to the pathological mechanisms of different MCI subtypes.

Spared emotional perception in patients with Alzheimer's disease is associated with negative caregiver outcomes

OBJECTIVES

Caregivers (CGs) for patients with Alzheimer's disease (AD) often experience negative mental health and relationship outcomes. Additionally, emotional perception abilities are often compromised in early AD; the relationships between these deficits and CG outcomes are unclear. The present study investigated the relationship between emotional perception abilities in AD participants and CG well-being.

METHODS

Participants included 28 individuals with AD, their spousal CGs, and 30 older controls (OCs). Patients and controls completed the Montreal Cognitive Assessment and Advanced Clinical Solutions: Social Perception subtest. CGs completed questionnaires related to relationship satisfaction, burden, depression, and patient neuropsychiatric symptoms and activities of daily living.

RESULTS

The patient group performed significantly worse than OCs on measures of cognition and emotional perception. Several significant relationships emerged between AD participant emotional perception and CG outcomes. Higher CG depression was associated with greater overall emotional perception abilities (r = .39, p = .041). Caregiver burden was positively correlated with AD participants' ability to label the emotional tones of voices (r = .47, p = .015). Relationship satisfaction was not significantly correlated with emotional perception.

DISCUSSION

This study replicated earlier findings of impaired emotional perception abilities in AD participants. However, preserved abilities in emotional perception were associated greater CG depression and burden. Interestingly, the CGs satisfaction with the marital relationship did not appear to be influenced by changes in emotional perception. Higher emotional engagement among couples in which one spouse has cognitive impairment may contribute to increased negative interactions and in turn a greater sense of burden and depression, while leaving the marital relationship preserved.

The ERICA Score: An MR Imaging-based Visual Scoring System for the Assessment of Entorhinal Cortex Atrophy in Alzheimer Disease

Purpose To establish and evaluate a visual score focused on entorhinal cortex atrophy (ERICA), as the entorhinal cortex is one of the first brain structures affected in Alzheimer disease (AD). Materials and Methods In this retrospective study, ERICA was visually evaluated with magnetic resonance imaging (2009-2016). First, a four-point ERICA score was developed by using data in 48 consecutive subjects (20 patients with AD and 28 control subjects). Then, in the main analysis, ERICA and the standard medial temporal lobe atrophy (MTA) scores were determined in an independent cohort of 60 patients suspected of having AD (mean age, 69.4 years; range, 46-86 years) and in 60 age-matched patients with subjective cognitive decline (SCD) (mean age, 72.4 years; range 50-87 years). Score performances were evaluated with κ statistics, receiver operating characteristic analysis, t tests, and analysis of variance according to the Standards for Reporting of Diagnostic Accuracy Studies. Results Patients with AD had higher MTA scores (mean, 2.13) and ERICA scores (mean, 2.05) than patients with SCD (P < .001). An ERICA score of 2 or greater achieved a higher diagnostic accuracy (91%) than the MTA score (74%), with a sensitivity of 83% versus 57% and a specificity of 98% versus 92% in discriminating dementia caused by AD from SCD (P < .001). The ERICA score was correlated with amyloid β 42/40 ratio (ρ = -0.54, P < .001) and with cerebrospinal fluid tau (ρ = 0.35, P = .001) and p-tau (ρ = 0.31, P = .004). In multivariable linear regression analysis, ERICA was associated with verbal learning and recall (β = -.40 and -.41), nonverbal recall (β = -.28), and cued recall (β = -.41, P ≤ .002 for all). Conclusion An ERICA score of 2 or greater indicates probable AD with high diagnostic accuracy. ^© RSNA, 2018 Online supplemental material is available for this article.

Relationship between Cognitive Performance and Measures of Neurodegeneration among Hispanic and White Non-Hispanic Individuals with Normal Cognition, Mild Cognitive Impairment, and Dementia

OBJECTIVES

The aim of this study was to determine the presence and severity of potential cultural and language bias in widely used cognitive and other assessment instruments, using structural MRI measures of neurodegeneration as biomarkers of disease stage and severity.

METHODS

Hispanic (n=75) and White non-Hispanic (WNH) (n=90) subjects were classified as cognitively normal (CN), amnestic mild cognitive impairment (aMCI) and mild dementia. Performance on the culture-fair and educationally fair Fuld Object Memory Evaluation (FOME) and Clinical Dementia Rating Scale (CDR) between Hispanics and WNHs was equivalent, in each diagnostic group. Volumetric and visually rated measures of the hippocampus entorhinal cortex, and inferior lateral ventricles (ILV) were measured on structural MRI scans for all subjects. A series of analyses of covariance, controlling for age, depression, and education, were conducted to compare the level of neurodegeneration on these MRI measures between Hispanics and WNHs in each diagnostic group.

RESULTS

Among both Hispanics and WNH groups there was a progressive decrease in volume of the hippocampus and entorhinal cortex, and an increase in volume of the ILV (indicating increasing atrophy in the regions surrounding the ILV) from CN to aMCI to mild dementia. For equivalent levels of performance on the FOME and CDR, WNHs had greater levels of neurodegeneration than did Hispanic subjects.

CONCLUSIONS

Atrophy in medial temporal regions was found to be greater among WNH than Hispanic diagnostic groups, despite the lack of statistical differences in cognitive performance between these two ethnic groups. Presumably, unmeasured factors result in better cognitive performance among WNH than Hispanics for a given level of neurodegeneration. (JINS, 2018, 24, 176-187).

Age-Specific Cutoff Scores on a T1-Weighted Axial Medial Temporal-Lobe Atrophy Visual Rating Scale in Alzheimer's Disease Using Clinical Research Center for Dementia of South Korea Data

BACKGROUND AND PURPOSE

Visual assessment of medial temporal-lobe atrophy (MTA) has been quick, reliable, and easy to apply in routine clinical practice. However, one of the limitations in visual assessments of MTA is the lack of widely accepted age-adjusted norms and cutoff scores for MTA for a diagnosis of Alzheimer's disease (AD). This study aimed to determine the optimal cutoff score on a T1-weighted axial MTA Visual Rating Scale (VRS) for differentiating patients with AD from cognitively normal elderly people.

METHODS

The 3,430 recruited subjects comprising 1,427 with no cognitive impairment (NC) and 2003 AD patients were divided into age ranges of 50-59, 60-69, 70-79, and 80-89 years. Of these, 446 participants (218 in the NC group and 228 in the AD group) were chosen by random sampling for inclusion in this study. Each decade age group included 57 individuals, with the exception of 47 subjects being included in the 80- to 89-year NC group. The scores on the T1-weighted axial MTA VRS were graded by two neurologists. The cutoff values were evaluated from the area under the receiver operating characteristic curve.

RESULTS

The optimal axial MTA VRS cutoff score from discriminating AD from NC increased with age: it was ≥as ≥1, ≥2, and ≥3 in subjects aged 50-59, 60-69, 70-79, and 80-89 years, respectively (all p<0.001).

CONCLUSIONS

These results show that the optimal cutoff score on the axial MTA VRS for diagnosing of AD differed according to the decade age group. This information could be of practical usefulness in the clinical setting.

A Clinically-Translatable Machine Learning Algorithm for the Prediction of Alzheimer's Disease Conversion in Individuals with Mild and Premild Cognitive Impairment

BACKGROUND

Available therapies for Alzheimer's disease (AD) can only alleviate and delay the advance of symptoms, with the greatest impact eventually achieved when provided at an early stage. Thus, early identification of which subjects at high risk, e.g., with MCI, will later develop AD is of key importance. Currently available machine learning algorithms achieve only limited predictive accuracy or they are based on expensive and hard-to-collect information.

OBJECTIVE

The current study aims to develop an algorithm for a 3-year prediction of conversion to AD in MCI and PreMCI subjects based only on non-invasively and effectively collectable predictors.

METHODS

A dataset of 123 MCI/PreMCI subjects was used to train different machine learning techniques. Baseline information regarding sociodemographic characteristics, clinical and neuropsychological test scores, cardiovascular risk indexes, and a visual rating scale for brain atrophy was used to extract 36 predictors. Leave-pair-out-cross-validation was employed as validation strategy and a recursive feature elimination procedure was applied to identify a relevant subset of predictors.

RESULTS

16 predictors were selected from all domains excluding sociodemographic information. The best model resulted a support vector machine with radial-basis function kernel (whole sample: AUC = 0.962, best balanced accuracy = 0.913; MCI sub-group alone: AUC = 0.914, best balanced accuracy = 0.874).

CONCLUSIONS

Our algorithm shows very high cross-validated performances that outperform the vast majority of the currently available algorithms, and all those which use only non-invasive and effectively assessable predictors. Further testing and optimization in independent samples will warrant its application in both clinical practice and clinical trials.

Medial temporal lobe atrophy ratings in a large 75-year-old population-based cohort: gender-corrected and education-corrected normative data

Objectives

To find cut-off values for different medial temporal lobe atrophy (MTA) measures (right, left, average, and highest), accounting for gender and education, investigate the association with cognitive performance, and to compare with decline of cognitive function over 5 years in a large population-based cohort.

Methods

Three hundred and ninety 75-year-old individuals were examined with magnetic resonance imaging of the brain and cognitive testing. The Scheltens’s scale was used to assess visually MTA scores (0–4) in all subjects. Cognitive tests were repeated in 278 of them after 5 years. Normal MTA cut-off values were calculated based on the 10th percentile.

Results

Most 75-year-old individuals had MTA score ≤2. Men had significantly higher MTA scores than women. Scores for left and average MTA were significantly higher in highly educated individuals. Abnormal MTA was associated with worse results in cognitive test and individuals with abnormal right MTA had faster cognitive decline.

Conclusion

At age 75, gender and education are confounders for MTA grading. A score of ≥2 is abnormal for low-educated women and a score of ≥2.5 is abnormal for men and high-educated women. Subjects with abnormal right MTA, but normal MMSE scores had developed worse MMSE scores 5 years later.

Key Points

• Gender and education are confounders for MTA grading.

• We suggest cut-off values for 75-year-olds, taking gender and education into account.

• Males have higher MTA scores than women.

• Higher MTA scores are associated with worse cognitive performance.

Association of imaging abnormalities of the subcallosal septal area with Alzheimer's disease and mild cognitive impairment

AIM

To evaluate the use the distance between the adjacent septal nuclei as a surrogate marker of septal area atrophy seen in Alzheimer's disease (AD).

MATERIALS & METHODS

Interseptal distance (ISD) was measured, blind to clinical details, in 250 patients who underwent computed tomography (CT) of the brain at University Hospital of Wales. Clinical details including memory problem history were retrieved. An ISD cut-off value that discriminated those with and without memory symptoms was sought. ISD measurements were also made in 20 AD patients. To test both the method and the defined cut-off, measurements were then made in an independent cohort of 21 mild cognitive impairment (MCI) patients and 45 age-matched healthy controls, in a randomised and blinded fashion.

RESULTS

ISD measurement was achieved in all patients. In 28 patients with memory symptoms, the mean ISD was 5.9 mm compared with 2.3 mm in those without overt symptoms (p=0.001). The optimum ISD cut-off value was 4 mm (sensitivity 85.7% and specificity 85.8%). All AD patients had an ISD of >4 mm (mean ISD= 6.1 mm). The mean ISD for MCI patients was 3.84 mm compared with 2.18 mm in age-matched healthy controls (p=0.001). Using a 4 mm cut-off correctly categorised 10 mild cognitive impairment patients (47.6%) and 38 healthy controls (84.4%).

CONCLUSION

ISD is a simple and reliable surrogate measurement for septal area atrophy, applicable to CT and magnetic resonance imaging (MRI). It can be used to help select patients for further investigation.

Decreasing body mass index is associated with cerebrospinal fluid markers of Alzheimer's pathology in MCI and mild dementia

BACKGROUND

Several studies have identified an association between body mass index (BMI) and the incidence and severity of Alzheimer's disease (AD) but this relationship is not fully understood.

OBJECTIVE

The primary objective of this study was to assess the possible association between BMI and cerebrospinal fluid (CSF) biomarkers of AD pathology in subjects with normal cognition and cognitive impairment. The secondary objective was to test whether BMI may contribute to improve the accuracy of a clinical model to predict AD pathology in memory clinic patients with cognitive impairment.

METHOD

One hundred and seven elderly subjects with cognitive impairment (91 memory clinic patients with mild cognitive impairment [MCI] and 16 with dementia of AD type) and 55 cognitively healthy volunteers were included in this study. All subjects received a comprehensive clinical and neuropsychological evaluation and a lumbar puncture for CSF biomarker analysis. Multiple linear regressions and receiver operating characteristic (ROC) analyses were carried out to assess the association between BMI and the CSF biomarkers of AD pathology.

RESULTS

BMI was positively correlated with the CSF levels of Aβ₄₂ and negatively with tau and P-tau181 in participants with cognitive impairment. The associations were independent of age, sex, educational level, type and severity of cognitive impairment, cerebrovascular risk factors and the presence of the APOEε4 allele. Furthermore, BMI significantly improved the sensitivity and specificity of a multi-factorial model to predict the presence of an AD CSF biomarker profile.

CONCLUSION

Lower BMI is associated with cerebral AD pathology rather than with cognitive impairment in elderly subjects with MCI and mild dementia. Along with other clinical factors, decreasing BMI may help the clinician to identify patients with cognitive impairment due to AD.

Distinguishing early and late brain aging from the Alzheimer's disease spectrum: consistent morphological patterns across independent samples

Alzheimer's disease (AD) is a debilitating age-related neurodegenerative disorder. Accurate identification of individuals at risk is complicated as AD shares cognitive and brain features with aging. We applied linked independent component analysis (LICA) on three complementary measures of gray matter structure: cortical thickness, area and gray matter density of 137 AD, 78 mild (MCI) and 38 subjective cognitive impairment patients, and 355 healthy adults aged 18-78 years to identify dissociable multivariate morphological patterns sensitive to age and diagnosis. Using the lasso classifier, we performed group classification and prediction of cognition and age at different age ranges to assess the sensitivity and diagnostic accuracy of the LICA patterns in relation to AD, as well as early and late healthy aging. Three components showed high sensitivity to the diagnosis and cognitive status of AD, with different relationships with age: one reflected an anterior-posterior gradient in thickness and gray matter density and was uniquely related to diagnosis, whereas the other two, reflecting widespread cortical thickness and medial temporal lobe volume, respectively, also correlated significantly with age. Repeating the LICA decomposition and between-subject analysis on ADNI data, including 186 AD, 395 MCI and 220 age-matched healthy controls, revealed largely consistent brain patterns and clinical associations across samples. Classification results showed that multivariate LICA-derived brain characteristics could be used to predict AD and age with high accuracy (area under ROC curve up to 0.93 for classification of AD from controls). Comparison between classifiers based on feature ranking and feature selection suggests both common and unique feature sets implicated in AD and aging, and provides evidence of distinct age-related differences in early compared to late aging.

Heterogeneity of Neuropsychological Impairment in HIV Infection: Contributions from Mild Cognitive Impairment

Despite longstanding acknowledgement of the heterogeneity of HIV-associated neurocognitive disorders (HAND), existing HAND diagnostic methods classify according to the degree of impairment, without regard to the pattern of neuropsychological strengths and weaknesses. Research in mild cognitive impairment (MCI) has demonstrated that classifying individuals into subtypes by both their level and pattern of impairment, using either conventional or statistical methods, has etiologic and prognostic utility. Methods for characterizing the heterogeneity of MCI provide a framework that can be applied to other disorders and may be useful in clarifying some of the current challenges in the study of HAND. A small number of studies have applied these methods to examine the heterogeneity of neurocognitive function among individuals with HIV. Most have supported the existence of multiple subtypes of neurocognitive impairment, with some evidence for distinct clinicodemographic features of these subtypes, but a number of gaps exist. Following a review of diagnostic methods and challenges in the study of HAND, we summarize the literature regarding conventional and empirical subtypes of MCI and HAND and identify directions for future research regarding neurocognitive heterogeneity in HIV infection.

Language background in early life may be related to neuropsychiatry symptoms in patients with Alzheimer disease

Background

The relationship between early life experience and the occurrence of neuropsychiatry symptoms (NPSs) in patients with Alzheimer disease (AD) is unclear.

Methods

From 2012 to 2014, we prospectively recruited 250 patients with probable AD from the memory clinic of Taipei Veterans General Hospital. All patients underwent standard assessments, including brain magnetic resonance imaging or computed tomography, neuropsychological tests, neuropsychiatry inventory (NPI-Q) and related blood tests. A linear regression analysis was performed to investigate the relationship between NPSs and age, gender, disease severity, depression, language background (with or without Japanese education).

Results

Among the 250 participants, 113 (45.2%) were women. Their average age was 82.6 years. Of all the participants, 93 (37.2%) had received formal Japanese education, whereas 157 (62.8%) did not receive Japanese education. The participants with Japanese education were slightly younger (83.1 ± 3.6 vs. 81.4 ± 3.4, P = 0.006), with a higher proportion of them were women (30.5% vs. 69.8%, P < 0.001) and fewer years of total education (10.8 ± 4.5 vs. 7.7 ± 3.2, P < 0.001), compared to the participants without Japanese education. NPI-Q scores significantly differed between the two groups (15.8 vs. 24.1, P = 0.024). Both disease severity and language background predicted NPI-Q scores.

Conclusions

Language background in early life may be related to NPSs in patients with AD, and this effect is more significant in patients with a lower education level than in those with a higher education level. More NPSs may be the result of negative effects on dominant language or early life experiences.

Electronic supplementary material

The online version of this article (doi:10.1186/s12877-017-0435-2) contains supplementary material, which is available to authorized users.

Practical use of visual medial temporal lobe atrophy cut-off scores in Alzheimer's disease: Validation in a large memory clinic population

Objective

To provide age-specific medial temporal lobe atrophy (MTA) cut-off scores for routine clinical practice as marker for Alzheimer’s disease (AD).

Methods

Patients with AD (n = 832, mean age 81.8 years) were compared with patients with subjective cognitive impairment (n = 333, mean age 71.8 years) in a large single-centre memory clinic. Mean of right and left MTA scores was determined with visual rating (Scheltens scale) using CT (0, no atrophy to 4, severe atrophy). Relationships between age and MTA scores were analysed with regression analysis. For various MTA cut-off scores, decade-specific sensitivity and specificity and area under the curve (AUC) values, computed with receiver operator characteristic curves, were determined.

Results

MTA strongly increased with age in both groups to a similar degree. Optimal MTA cut-off values for the age ranges <65, 65–74, 75–84 and ≥85 were: ≥1.0, ≥1.5, ≥ 2.0 and ≥2.0. Corresponding values of sensitivity and specificity were 83.3% and 86.4%; 73.7% and 84.6%; 73.7% and 76.2%; and 84.0% and 62.5%.

Conclusion

From this large unique memory clinic cohort we suggest decade-specific MTA cut-off scores for clinical use. After age 85 years, however, the practical usefulness of the MTA cut-off is limited.

Key Points

• We suggest decade-specific MTA cut-off scores for AD.

• MTA cut-off after the age of 85 years has limited use.

• CT is feasible and accurate for visual MTA rating.

Structural MR Imaging in the Diagnosis of Alzheimer's Disease and Other Neurodegenerative Dementia: Current Imaging Approach and Future Perspectives

With the rise of aging population, clinical concern and research attention has shifted towards neuroimaging of dementia. The advent of 3T, magnetic resonance imaging (MRI) has permitted the anatomical imaging of neurodegenerative disease, specifically dementia, with improved resolution. Furthermore, more powerful techniques such as diffusion tensor imaging, quantitative susceptibility mapping, and magnetic transfer imaging have successfully emerged for the detection of micro-structural abnormalities. In the present review article, we provide a brief overview of Alzheimer's disease and explore recent neuroimaging developments in the field of dementia with an emphasis on structural MR imaging in order to propose a simple and easily applicable systematic approach to the imaging diagnosis of dementia.

Identify the Atrophy of Alzheimer's Disease, Mild Cognitive Impairment and Normal Aging Using Morphometric MRI Analysis

Quantitatively assessing the medial temporal lobe (MTL) structures atrophy is vital for early diagnosis of Alzheimer's disease (AD) and accurately tracking of the disease progression. Morphometry characteristics such as gray matter volume (GMV) and cortical thickness have been proved to be valuable measurements of brain atrophy. In this study, we proposed a morphometric MRI analysis based method to explore the cross-sectional differences and longitudinal changes of GMV and cortical thickness in patients with AD, MCI (mild cognitive impairment) and the normal elderly. High resolution 3D MRI data was obtained from ADNI database. SPM8 plus DARTEL was carried out for data preprocessing. Two kinds of z-score map were calculated to, respectively, reflect the GMV and cortical thickness decline compared with age-matched normal control database. A volume of interest (VOI) covering MTL structures was defined by group comparison. Within this VOI, GMV, and cortical thickness decline indicators were, respectively, defined as the mean of the negative z-scores and the sum of the normalized negative z-scores of the corresponding z-score map. Kruskal-Wallis test was applied to statistically identify group wise differences of the indicators. Support vector machines (SVM) based prediction was performed with a leave-one-out cross-validation design to evaluate the predictive accuracies of the indicators. Linear least squares estimation was utilized to assess the changing rate of the indicators for the three groups. Cross-sectional comparison of the baseline decline indicators revealed that the GMV and cortical thickness decline were more serious from NC, MCI to AD, with statistic significance. Using a multi-region based SVM model with the two indicators, the discrimination accuracy between AD and NC, MCI and NC, AD and MCI was 92.7, 91.7, and 78.4%, respectively. For three-way prediction, the accuracy was 74.6%. Furthermore, the proposed two indicators could also identify the atrophy rate differences among the three groups in longitudinal analysis. The proposed method could serve as an automatic and time-sparing approach for early diagnosis and tracking the progression of AD.