Diffusion tensor changes in patients with amnesic mild cognitive impairment and various dementias

Unsupervised machine learning model to predict cognitive impairment in subcortical ischemic vascular disease

INTRODUCTION

It is challenging to predict which patients who meet criteria for subcortical ischemic vascular disease (SIVD) will ultimately progress to subcortical vascular cognitive impairment (SVCI).

METHODS

We collected clinical information, neuropsychological assessments, T1 imaging, diffusion tensor imaging, and resting-state functional magnetic resonance imaging from 83 patients with SVCI and 53 age-matched patients with SIVD without cognitive impairment. We built an unsupervised machine learning model to isolate patients with SVCI. The model was validated using multimodal data from an external cohort comprising 45 patients with SVCI and 32 patients with SIVD without cognitive impairment.

RESULTS

The accuracy, sensitivity, and specificity of the unsupervised machine learning model were 86.03%, 79.52%, and 96.23% and 80.52%, 71.11%, and 93.75% for internal and external cohort, respectively.

DISCUSSION

We developed an accurate and accessible clinical tool which requires only data from routine imaging to predict patients at risk of progressing from SIVD to SVCI.

HIGHLIGHTS

Our unsupervised machine learning model provides an accurate and accessible clinical tool to predict patients at risk of progressing from subcortical ischemic vascular disease (SIVD) to subcortical vascular cognitive impairment (SVCI) and requires only data from imaging routinely used during the diagnosis of suspected SVCI. The model yields good accuracy, sensitivity, and specificity and is portable to other cohorts and to clinical practice to distinguish patients with SIVD at risk for progressing to SVCI. The model combines assessment of diffusion tensor imaging and functional magnetic resonance imaging measures in patients with SVCI to analyze whether the "disconnection hypothesis" contributes to functional and structural changes and to the clinical presentation of SVCI.

Diffusion Tensor Imaging as a Tool to Evaluate the Cognitive Function of Patients With Vascular Dementia: A Meta-Analysis

BACKGROUND

Vascular dementia (VaD) is the most common type of dementia secondary to Alzheimer's disease. The pathologic mechanism of VaD is complex, and VaD still lacks a more objective diagnosis and evaluation method. Diffusion tensor imaging (DTI) can better detect the organizational structure and functional characteristics compared with any other diagnosis methods. Therefore, DTI has broad application in evaluating the severity and prognosis of VaD. This study aimed to assess the value of DTI in evaluating the cognitive function of patients with VaD.

METHODS

Authors searched Pubmed, Embase, and Cochrane Library, using the search terms, such as "diffusion tensor imaging," "DTI," "Vascular Dementia," "Arteriosclerotic Dementia," "Cognition," and "Cognitive." A voxel-based meta-analysis combined with quality statistics was performed, using the anisotropic effect-size version of the signed differential mapping method.

RESULTS

A total of 8 case-control studies were included in this meta-analysis. The sample size of patients ranged from 35 to 60, including 166 patients in the VaD group and 177 healthy individuals. The DTI imaging of the brain tissue of VaD patients was significantly different from that of healthy individuals.

CONCLUSIONS

DTI imaging of the brain tissue of VaD patients was clearly different from that of healthy controls. Therefore it may be feasible to use DTI imaging as a diagnostic method for VaD.

Research hotspots and trends of multimodality MRI on vascular cognitive impairment in recent 12 years: A bibliometric analysis

BACKGROUND

Multimodality magnetic resonance imaging (MRI) is widely used to detect vascular cognitive impairment (VCI). However, a bibliometric analysis of this issue remains unknown. Therefore, this study aimed to explore the research hotspots and trends of multimodality MRI on VCI over the past 12 years based on the Web of Science core collection using CiteSpace Software (6.1R2).

METHODS

Literature related to multimodality MRI for VCI from 2010 to 2021 was identified and analyzed from the Web of Science core collection database. We analyzed the countries, institutions, authors, cited journals, references, keyword bursts, and clusters using CiteSpace.

RESULTS

In total, 587 peer-reviewed documents were retrieved, and the annual number of publications showed an exponential growth trend over the past 12 years. The most productive country was the USA, with 182 articles, followed by China with 134 papers. The top 3 active academic institutions were Capital Medical University, Radboud UNIV Nijmegen, and UNIV Toronto. The most productive journal was the Journal of Alzheimer's Disease (33 articles). The most co-cited journal was Neurology, with the highest citations (492) and the highest intermediary centrality (0.14). The top-ranked publishing author was De Leeuw FE (17 articles) with the highest intermediary centrality of 0.04. Ward Law JM was the most cited author (123 citations) and Salat Dh was the most centrally cited author (0.24). The research hotspots of multimodal MRI for VCI include Alzheimer disease, vascular cognitive impairment, white matter intensity, cerebrovascular disease, dementia, mild cognitive impairment, neurovascular coupling, acute ischemic stroke, depression, and cerebral ischemic stroke. The main frontiers in the keywords are fMRI, vascular coupling, and cerebral ischemic stroke, and current research trends include impact, decline, and classification.

CONCLUSIONS

The findings from this bibliometric study provide research hotspots and trends for multimodality MRI for VCI over the past 12 years, which may help researchers identify hotspots and explore cutting-edge trends in this field.

White matter pathology in alzheimer's transgenic mice with chronic exposure to low-level ambient fine particulate matter

BACKGROUND

Air pollution, especially fine particulate matter (PM), can cause brain damage, cognitive decline, and an increased risk of neurodegenerative disease, especially alzheimer's disease (AD). Typical pathological findings of amyloid and tau protein accumulation have been detected in the brain after exposure in animal studies. However, these observations were based on high levels of PM exposure, which were far from the WHO guidelines and those present in our environment. In addition, white matter involvement by air pollution has been less reported. Thus, this experiment was designed to simulate the true human world and to discuss the possible white matter pathology caused by air pollution.

RESULTS

6 month-old female 3xTg-AD mice were divided into exposure and control groups and housed in the Taipei Air Pollutant Exposure System (TAPES) for 5 months. The mice were subjected to the Morris water maze test after exposure and were then sacrificed with brain dissection for further analyses. The mean mass concentration of PM2.5 during the exposure period was 13.85 μg/m3. After exposure, there was no difference in spatial learning function between the two groups, but there was significant decay of memory in the exposure group. Significantly decreased total brain volume and more neuronal death in the cerebral and entorhinal cortex and demyelination of the corpus callosum were noted by histopathological staining after exposure. However, there was no difference in the accumulation of amyloid or tau on immunohistochemistry staining. For the protein analysis, amyloid was detected at significantly higher levels in the cerebral cortex, with lower expression of myelin basic protein in the white matter. A diffuse tensor image study also revealed insults in multiple white matter tracts, including the optic tract.

CONCLUSIONS

In conclusion, this pilot study showed that even chronic exposure to low PM2.5 concentrations still caused brain damage, such as gross brain atrophy, cortical neuron damage, and multiple white matter tract damage. Typical amyloid cascade pathology did not appear prominently in the vulnerable brain region after exposure. These findings imply that multiple pathogenic pathways induce brain injury by air pollution, and the optic nerve may be another direct invasion route in addition to olfactory nerve.

Cognitive Profile of Large-Vessel Vascular Dementia—An Observational Study from a Tertiary Care Center in Kolkata

Introduction  Vascular dementia is the second leading cause of dementia worldwide. Its heterogenous presentation along with potential for reversibility at earlier stages makes it unique among all dementias.

Objectives  We aimed to study the cognitive dysfunction in large-vessel vascular dementia. Second, we tried to study the cognitive dysfunction in large-vessel vascular dementia as per the arterial territory involvement. Additionally, we also tried to study the contribution of hemispheric involvement to the dementia severity as evidenced by clinical dementia rating (CDR) scale.

Materials and Methods  We recruited 28 patients of large-vessel vascular dementia and categorized them on the basis of the arterial territories and hemisphere involved. The groups were later studied for the type of cognitive and behavioral dysfunctions as well as the dementia severity.

Results  Among 28 patients of large-vessel vascular dementia, attention (100%), executive function (100%), and behavior (100%) were more impaired in anterior cerebral artery territory infarcts ( p  < 0.05). Language (53.8%) and memory (53.8%) were more impaired in middle cerebral artery territory infarcts, while visuoperceptual (33.3%) domains were more impaired in posterior cerebral artery territory infarcts ( p  > 0.05). The mean CDR was lower in patients of right-sided lesions (1.292) than in those with left-sided (1.750) or bilateral lesions (2.000).

Conclusion  Different arterial territory lesions have different patterns of cognitive impairment in large-vessel vascular dementia. The dementia severity is less in right-sided lesions when compared with left-sided or bilateral lesions.

The changing landscape of neuroimaging in frontotemporal lobar degeneration: from group-level observations to single-subject data interpretation

INTRODUCTION

While the imaging signatures of frontotemporal lobar degeneration (FTLD) phenotypes and genotypes are well-characterised based on group-level descriptive analyses, the meaningful interpretation of single MRI scans remains challenging. Single-subject MRI classification frameworks rely on complex computational models and large training datasets to categorise individual patients into diagnostic subgroups based on distinguishing imaging features. Reliable individual subject data interpretation is hugely important in the clinical setting to expedite the diagnosis and classify individuals into relevant prognostic categories.

AREAS COVERED

This article reviews (1) the neuroimaging studies that propose single-subject MRI classification strategies in symptomatic and pre-symptomatic FTLD, (2) potential practical implications and (3) the limitations of current single-subject data interpretation models.

EXPERT OPINION

Classification studies in FTLD have demonstrated the feasibility of categorising individual subjects into diagnostic groups based on multiparametric imaging data. Preliminary data indicate that pre-symptomatic FTLD mutation carriers may also be reliably distinguished from controls. Despite momentous advances in the field, significant further improvements are needed before these models can be developed into viable clinical applications.

Reduced fractional anisotropy of the genu of the corpus callosum as a cerebrovascular disease marker and predictor of longitudinal cognition in MCI

Our goal was to evaluate the utility of diffusion tensor imaging (DTI) for predicting future cognitive decline in mild cognitive impairment (MCI) in conjunction with Alzheimer's disease (AD) biomarkers (amyloid positron emission tomography and AD signature neurodegeneration) in 132 MCI individuals ≥60 year old with structural magnetic resonance imaging, DTI, amyloid positron emission tomography, and at least one clinical follow-up. We used mixed-effect models to evaluate the prognostic ability of fractional anisotropy of the genu of the corpus callosum (FA-Genu), as a cerebrovascular disease marker, for predicting cognitive decline along with AD biomarkers. We contrasted the value of white matter hyperintensities, a traditional cerebrovascular disease marker as well as FA in the hippocampal cingulum bundle with the FA-Genu models. FA-Genu significantly predicted cognitive decline even after accounting for AD biomarkers. WMH was not associated with cognitive decline in the model with both WMH and FA-Genu. DTI specifically FA-Genu provides unique complementary information to AD biomarkers and has significant utility for prediction of cognitive decline in MCI.

Neuroimaging in aging and neurologic diseases

Neuroimaging biomarkers for neurologic diseases are important tools, both for understanding pathology associated with cognitive and clinical symptoms and for differential diagnosis. This chapter explores neuroimaging measures, including structural and functional measures from magnetic resonance imaging (MRI) and molecular measures primarily from positron emission tomography (PET), in healthy aging adults and in a number of neurologic diseases. The spectrum covers neuroimaging measures from normal aging to a variety of dementias: late-onset Alzheimer's disease [AD; including mild cognitive impairment (MCI)], familial and nonfamilial early-onset AD, atypical AD syndromes, posterior cortical atrophy (PCA), logopenic aphasia (lvPPA), cerebral amyloid angiopathy (CAA), vascular dementia (VaD), sporadic and familial behavioral-variant frontotemporal dementia (bvFTD), semantic dementia (SD), progressive nonfluent aphasia (PNFA), frontotemporal dementia with motor neuron disease (FTD-MND), frontotemporal dementia with amyotrophic lateral sclerosis (FTD-ALS), corticobasal degeneration (CBD), progressive supranuclear palsy (PSP), dementia with Lewy bodies (DLB), Parkinson's disease (PD) with and without dementia, and multiple systems atrophy (MSA). We also include a discussion of the appropriate use criteria (AUC) for amyloid imaging and conclude with a discussion of differential diagnosis of neurologic dementia disorders in the context of neuroimaging.

How does white matter microstructure differ between the vascular and amnestic mild cognitive impairment?

Changes in white matter (WM) microstructure may relate to the pathophysiology of cognitive impairment. Whether WM microstructure differs in two common pre-dementia subtypes, vascular mild cognitive impairment (VaMCI) and amnestic mild cognitive impairment (aMCI), is largely unknown. This study included 28 VaMCI (12 men, age: 46 ~ 77 years) and 34 aMCI patients (14 men, age: 51 ~ 79 years). All patients underwent a battery of neuropsychological tests and structural and diffusion magnetic resonance imaging (MRI) scanning. WM microstructure was quantified using diffusion MRI parameters: fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AxD) and radial diffusivity (RD). These parameters were compared between the two patient groups using tract-based spatial statistics (TBSS) after controlling for age, gender, and education. No significant differences in FA/MD/AxD/RD were observed between the VaMCI and aMCI groups, which suggests a similar pattern of WM microstructure in the early stage of cognitive impairment for different dementia types. However, the two groups exhibited significant differences in the relationship between FA and the Auditory Verbal Learning Test (AVLT), which were primarily located around the corona radiate and corpus callosum. Specifically, there were significant positive correlations (R = 0.64, P < 0.001) between the FA and AVLT in the VaMCI group, but the opposite trend was observed in the aMCI group (R = -0.34, P = 0.047). The differential relationship between WM and memory between VaMCI and aMCI indicates an independent neuropathology for specific memory deficits in different types of dementia.

Contribution of diffusion, perfusion and functional MRI to the disconnection hypothesis in subcortical vascular cognitive impairment

Vascular cognitive impairment (VCI) describes all forms of cognitive impairment caused by any type of cerebrovascular disease. Early identification of VCI is quite difficult due to the lack of both sensitive and specific biomarkers. Extensive damage to the white matter tracts, which connect the cortical and subcortical regions, has been shown in subcortical VCI (SVCI), the most common subtype of VCI that is caused by small vessel disease. Two specific MRI sequences, including diffusion tensor imaging (DTI) and functional MRI (fMRI), have emerged as useful tools for identifying subtle white matter changes and the intrinsic connectivity between distinct cortical regions. This review describes the advantages of these two modalities in SVCI research and the current DTI and fMRI findings on SVCI. Using DTI technique, a variety of studies found that white matter microstructural damages in the anterior and superior areas are more specific to SVCI. Similarly, functional brain abnormalities detected by fMRI have also been mainly shown in anterior brain areas in SVCI. The characteristic distribution of brain abnormalities in SVCI interrupts the prefrontal-subcortical loop that results in cognitive impairments in particular domains, which further confirms the ‘disconnection syndrome’ hypothesis. In addition, another MRI technique, arterial spin labelling (ASL), has been used to describe the disconnection patterns in a variety of conditions by measuring cerebral blood flow. The role of the ASL technique in SVCI research is also assessed. Finally, the review proposes the application of multimodality fusion in the investigation of SVCI pathogenesis.

Multimodality Neuroimaging in Mild Cognitive Impairment: A Cross-sectional Comparison Study

Background and Purpose

Mild cognitive impairment (MCI) is a focus of considerable research. The present study aimed to test the utility of a logistic regression-derived classifier, combining specific quantitative multimodal magnetic resonance imaging (MRI) data for the early objective phenotyping of MCI in the clinic, over structural MRI data.

Methods

Thirty-three participants with cognitively stable amnestic MCI; 15 MCI converters to early Alzheimer's disease (AD; diseased controls) and 20 healthy controls underwent high-resolution T1-weighted volumetric MRI, diffusion tensor imaging (DTI), and proton magnetic resonance spectroscopy (¹H MR spectroscopy). The regional volumes were obtained from T1-weighted MRI. The fractional anisotropy and mean diffusivity maps were derived from DTI over multiple white matter regions. The ¹H MRS voxels were placed over posterior cingulate gyri, and N-acetyl aspartate (NAA)/creatine (Cr), choline (Cho)/Cr, myoinositol (mI/Cr), and NAA/mI ratios were obtained. A multimodal classifier comprising MR volumetry, DTI, and MRS was prepared. A cutoff point was arrived based on receiver operator characteristics analysis. Results were considered significant, if P < 0.05.

Results

The most sensitive individual marker to discriminate MCI from controls was DTI (90.9%), with a specificity of 50%. For classifying MCI from AD, the best individual modality was DTI (72.7%), with a high specificity of 87.9%. The multimodal classifier approach for MCI control classification achieved an area under curve (AUC) (AUC = 0.89; P < 0.001), with 93.9% sensitivity and 70% specificity. The combined classifier for MCI-AD achieved a highest AUC (AUC = 0.93; P < 0.001), with 93% sensitivity and 85.6% specificity.

Conclusions

The combined method of gray matter atrophy, white matter tract changes, and metabolite variation achieved a better performance at classifying MCI compared to the application of individual MRI biomarkers.

Effectiveness of diffusion tensor imaging in differentiating early-stage subcortical ischemic vascular disease, Alzheimer's disease and normal ageing

Objective

To describe and compare diffusion tensor imaging (DTI) parameters between patients with subcortical ischemic vascular disease (SIVD) and Alzheimer’s disease (AD) diagnosed using structuralized neuropsychiatric assessments, and investigate potential neuronal substrates related to cognitive performance.

Methods

Thirty-five patients with SIVD, 40 patients with AD, and 33 cognitively normal control (NC) subjects matched by age and education level were consecutively recruited and underwent cognitive function assessments and DTI examinations. Comparisons among these three subgroups with regards to cognitive performance and DTI parameters including fractional anisotropy (FA) and mean diffusivity (MD) values were performed. Partial correlation analysis after controlling for age and education was used to evaluate associations between cognitive performance and DTI parameters.

Results

With regards to cognitive performance, the patients with SIVD had lower total scores in frontal assessment battery (FAB) compared to those with AD (p < 0.05) in the context of comparable Mini-Mental Status Examination and Cognitive Abilities Screening Instrument scores. With regards to DTI parameters, there were more regions of significant differences in FA among these three subgroups compared with MD. Compared with NC group, the patients with SIVD had significant global reductions in FA (p < 0.001 ~ 0.05), while significant reductions in FA among the patients with AD were regionally confined within the left superior longitudinal fasciculus, genu and splenium of the corpus callosum, and bilateral forceps major, and the anterior thalamic radiation, uncinate fasciculus, and cingulum of the left side (p < 0.01 ~ 0.05). Analysis of FA values within the left forceps major, left anterior thalamic radiation, and genu of the corpus callosum revealed a 71.8% overall correct classification (p < 0.001) with sensitivity of 69.4%, specificity of 73.8%, positive predictive value of 69.4%, and negative predictive value of 73.8% in discriminating patients with SIVD from those with AD. In combined analysis of the patients with SIVD and AD (n = 75), the total FAB score was positively correlated with FA within the bilateral forceps minor, genu of the corpus callosum, left forceps major, left uncinate fasciculus, and right inferior longitudinal fasciculus (p = 0.001 ~ 0.038), and inversely correlated with MD within the right superior longitudinal fasciculus, genu and body of the corpus callosum, bilateral forceps minor, right uncinate fasciculus, and right inferior longitudinal fasciculus (p = 0.003 ~ 0.040)

Conclusions

Our findings suggest the effectiveness of DTI measurements in distinguishing patients with early-stage AD from those with SIVD, with discernible changes in spatial distribution and magnitude of significance of the DTI parameters. Strategic FA assessments provided the most robust discriminative power to differentiate SIVD from AD, and FAB may serve as an additional cognitive marker. We also identified the neuronal substrates responsible for FAB performance.

Low uric acid is a risk factor in mild cognitive impairment

BACKGROUND

Mild cognitive impairment (MCI) represents a transitional stage between normal aging and dementia. Uric acid is a water-soluble antioxidant found in the body. Many recent studies have found that uric acid plays an important role in cognitive impairment, although the effects of uric acid on MCI are not clear.

OBJECTIVE

The objective of this study was to explore the relationship between uric acid and MCI.

METHODS

Using a random sampling method, this study investigated 58 patients with MCI and 57 healthy elderly from January 2016 to November 2016. Demographic information was collected, the subjects were evaluated using the Mini Mental Status Examination (MMSE), and uric acid was measured in fasting venous blood.

RESULTS

A total of 57 (49.6%) participants are healthy and 58 (50.4%) participants had MCI. The uric acid level was significantly lower in the patients with MCI (292.28±63.71 μmol/L) than in the normal controls (322.49±78.70 μmol/L; P<0.05). There were significant positive correlations between the MMSE scores, for each dimension and the total score, and uric acid level (all P<0.05). Multivariate logistic regression models illustrated that uric acid was a protective factor for MCI (odds ratio =0.999, 95% CI =0.987-0.999).

CONCLUSION

A low uric acid level is a risk factor for MCI, and an appropriate increase in uric acid can be used to slow down the occurrence and development of MCI.

Novel imaging techniques in cerebral small vessel diseases and vascular cognitive impairment

Dementia is a global growing concern, affecting over 35 million people with a global economic impact of over $604 billion US. With an ageing population the number of people affected is expected double over the next two decades. Vascular cognitive impairment can be caused by various types of cerebrovascular disease, including cortical and subcortical infarcts, and the more diffuse white matter injury due to cerebral small vessel disease. Although this type of cognitive impairment is usually considered the second most common form of dementia after Alzheimer's disease, there is increasing recognition of the vascular contribution to neurodegeneration, with both pathologies frequently coexisting. The aim of this review is to highlight the recent advances in the understanding of vascular cognitive impairment, with a focus on small vessel diseases of the brain. We discuss recently identified small vessel imaging markers that have been associated with cognitive impairment, namely cerebral microbleeds, enlarged perivascular spaces, cortical superficial siderosis, and microinfarcts. We will also consider quantitative techniques including diffusion tensor imaging, magnetic resonance perfusion imaging with arterial spin labelling, functional magnetic resonance imaging and positron emission tomography. As well as potentially shedding light on the mechanism by which cerebral small vessel diseases cause dementia, these novel imaging biomarkers are also of increasing relevance given their ability to guide diagnosis and reflect disease progression, which may in the future be useful for therapeutic interventions. This article is part of a Special Issue entitled: Vascular Contributions to Cognitive Impairment and Dementia edited by M. Paul Murphy, Roderick A. Corriveau and Donna M. Wilcock.

Multimodality Imaging Approach in Alzheimer disease. Part I: Structural MRI, Functional MRI, Diffusion Tensor Imaging and Magnetization Transfer Imaging

The authors make a complete review of the potential clinical applications of traditional and novel magnetic resonance imaging (MRI) techniques in the evaluation of patients with Alzheimer's disease, including structural MRI, functional MRI, diffusion tension imaging and magnetization transfer imaging.

Hippocampal diffusion tensor imaging microstructural changes in vascular dementia

To explore microstructural integrity of hippocampus in vascular dementia (VD) using DTI. Twenty-five individuals with VD, without magnetic resonance imaging (MRI) evidence of gray matter pathology, and 25 matched healthy control (HC) individuals underwent a 3T MRI protocol including T2, FLAIR, and PD in the axial plane, 3D whole-brain T1-weighted with an isotropic resolution of 1 mm, and DTI acquired using 64 diffusion sensitizing directions, b value of 1,500 s/mm(2), 65 axial slices, isotropic resolution of 1.8 mm. Images were processed to obtain indices of microstructural variations of bilateral hippocampi. Mean diffusivity (MD) in the hippocampus of patients with VD was significantly increased (p < 0.05) bilaterally with respect to that of the group of HC examinees. In VD group left hippocampal MD (10(-6 )× mm(2)/s) was 833.4 ± 92.8; in HC group left MD was 699.8 ± 56. In VD group, right hippocampal MD was 859.1 ± 69.8; in HC group right MD was 730.4 ± 40.2. No group differences were found in hippocampal FA. DTI shows microstructural hippocampal damage in VD in patients with normal appearing gray matter structures on conventional MRI, indicating the need for further research on the link between VD and AD.

Joint assessment of white matter integrity, cortical and subcortical atrophy to distinguish AD from behavioral variant FTD: A two-center study

We investigated the ability of cortical and subcortical gray matter (GM) atrophy in combination with white matter (WM) integrity to distinguish behavioral variant frontotemporal dementia (bvFTD) from Alzheimer's disease (AD) and from controls using voxel-based morphometry, subcortical structure segmentation, and tract-based spatial statistics. To determine which combination of MR markers differentiated the three groups with the highest accuracy, we conducted discriminant function analyses. Adjusted for age, sex and center, both types of dementia had more GM atrophy, lower fractional anisotropy (FA) and higher mean (MD), axial (L1) and radial diffusivity (L23) values than controls. BvFTD patients had more GM atrophy in orbitofrontal and inferior frontal areas than AD patients. In addition, caudate nucleus and nucleus accumbens were smaller in bvFTD than in AD. FA values were lower; MD, L1 and L23 values were higher, especially in frontal areas of the brain for bvFTD compared to AD patients. The combination of cortical GM, hippocampal volume and WM integrity measurements, classified 97-100% of controls, 81-100% of AD and 67-75% of bvFTD patients correctly. Our results suggest that WM integrity measures add complementary information to measures of GM atrophy, thereby improving the classification between AD and bvFTD.

Using structural and diffusion magnetic resonance imaging to differentiate the dementias

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

Quantitative measurement to evaluate morphological changes of the corpus callosum in patients with subcortical ischemic vascular dementia

BACKGROUND

Subcortical ischemic vascular dementia (SIVD) is a subtype of dementia associated with abnormalities in the subcortical white matter regions. Recent imaging techniques can be used to detect such abnormalities in vivo.

PURPOSE

To examine morphological changes of the corpus callosum in patients with SIVD by using magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI).

MATERIAL AND METHODS

MRI was performed to explore changes of cerebral white matter, especially corpus callosum. Brain matter diffusivity was examined with DTI by measuring the fractional anisotropy (FA). Results of 30 patients diagnosed with SIVD and 30 healthy subjects were analyzed and compared.

RESULTS

The thicknesses of the genu, the anterior third, middle, and posterior third of the body, and the splenium of the corpus callosum were smaller in SIVD patients compared to healthy controls (0.54 ± 0.08 vs. 0.68 ± 0.09 cm, P = 0.0011; 0.27 ± 0.06 vs. 0.38 ± 0.07 cm, P = 0.002; 0.28 ± 0.05 vs. 0.38 ± 0.08 cm, P = 0.009; 0.18 ± 0.04 vs. 0.26 ± 0.06 cm, P = 0.013; 0.54 ± 0.07 vs. 0.72 ± 0.09 cm, P = 0.003, respectively). The FA values of the genu and splenium of the corpus callosum in patients with SIVD were decreased compared to healthy controls (0.664 ± 0.042 vs. 0.778 ± 0.041, P < 0.001; 0.691 ± 0.038 vs. 0.786 ± 0.039, P = 0.001, respectively).

CONCLUSION

Patients with SIVD exhibit corpus callosum atrophy and morphological changes, and these characteristics may be useful for diagnosis.

Plasma Aβ but not tau is related to brain PiB retention in early Alzheimer's disease

Recent advances in biomarkers provide the possibility of early or preclinical diagnosis of Alzheimer's pathology. Currently, decreased levels of Aβ-42 and increased levels of tau proteins in cerebral spinal fluid are considered reliable biomarkers of Alzheimer's disease (AD); however, little evidence exists for the use of amyloid and tau protein levels in the plasma as useful biomarkers. We investigated the potential use of plasma biomarkers to diagnose AD and explored their relationships with brain Aβ deposition in amyloid imaging. We used an immunomagnetic reduction assay to measure the plasma levels of Aβ40, Aβ42, and tau proteins in 20 older control participants and 25 participants who had either mild cognitive impairment due to AD or early AD dementia. All participants received (11)C-labeled Pittsburgh compound B PET scans. The sensitivity of the plasma tau level at the cutoff value of 28.27 pg/mL was 92%, and the specificity was 100%; the sensitivity of the Aβ42/40 ratio at the cutoff value of 0.3693 was 84%, and the specificity was 100%. Regression analyses of the effects of plasma protein levels on brain amyloid retention, as determined by standard uptake value ratios in either side of the frontal, parietal, and temporal lobes and the precuneus, are predicted only by ratios of plasma Aβ42/40 (R(2) 0.326-0.449, all p < 0.001) but not by plasma tau levels. Plasma Aβ in terms of Aβ42/40 might provide an indirect estimation of Aβ deposition in the brain.

Cognitive impairments associated with periventricular white matter hyperintensities are mediated by cortical atrophy

BACKGROUND

Previous studies have shown that white matter lesions (WMLs) is an important risk factor for cognitive impairment, but the underlying mechanisms have not been clarified.

OBJECTIVE

We tested the hypothesis that the cognitive impairments associated with periventricular white matter hyperintensities (PWMHs) on magnetic resonance imaging (MRI) would be mediated by the cortical thinning of corresponding area.

METHOD

Sixteen stroke- and dementia-free subjects with PWMHs and 16 healthy control subjects were enrolled in this study. All participants underwent an examination of cognition, MRI-based cortical thickness measurement and a MRI-DTI scan. Then, the possible relationships among cognitive impairments, PWMHs and the topography of cortical thinning were analyzed.

RESULTS

Comparing with the controls, the cognitive tests of the subjects with PWMHs showed significant decline in the domains of verbal fluency and executive function. After accounting for age, gender, years of education, and treatable vascular risk factors related to cognitive performance, cortical thickness had an independent influence on the cognitive impairments, especially in the frontal pole, orbitofrontal cortex, superior and middle frontal gyrus, superior and middle temporal gyrus, insula, and cuneus.

CONCLUSIONS

Our results suggest that the association between PWMHs and cognitive impairments is mediated by cortical thinning.

Recent research about mild cognitive impairment in China

The rapid aging of the Chinese population has spurred interest in research about the cause and prevention of dementia and its precursor, mild cognitive impairment (MCI). This review summarizes the last decade of research in China about MCI. Extensive research about the epidemiology, neuropsychological characteristics, diagnosis, genetic etiology, neuroimaging and electrophysiological changes, and treatment of MCI has provided some new insights but few breakthroughs. Further advances in the prevention and treatment of MCI will require a greater emphasis on multi-disciplinary prospective studies with large, representative samples that use standardized methods to assess and monitor changes in cognitive functioning over time.

In vivo parahippocampal white matter pathology as a biomarker of disease progression to Alzheimer's disease

Noninvasive diagnostic tests for Alzheimer's disease (AD) are limited. Postmortem diagnosis is based on density and distribution of neurofibrillary tangles (NFTs) and amyloid-rich neuritic plaques. In preclinical stages of AD, the cells of origin for the perforant pathway within the entorhinal cortex are among the first to display NFTs, indicating its compromise in early stages of AD. We used diffusion tensor imaging (DTI) to assess the integrity of the parahippocampal white matter in mild cognitive impairment (MCI) and AD, as a first step in developing a noninvasive tool for early diagnosis. Subjects with AD (N = 9), MCI (N = 8), or no cognitive impairment (NCI; N = 20) underwent DTI-MRI. Fractional anisotropy (FA) and mean (MD) and radial (RD) diffusivity measured from the parahippocampal white matter in AD and NCI subjects differed greatly. Discriminant analysis in the MCI cases assigned statistical membership of 38% of MCI subjects to the AD group. Preliminary data 1 year later showed that all MCI cases assigned to the AD group either met the diagnostic criteria for probable AD or showed significant cognitive decline. Voxelwise analysis in the parahippocampal white matter revealed a progressive change in the DTI patterns in MCI and AD subjects: whereas converted MCI cases showed structural changes restricted to the anterior portions of this region, in AD the pathology was generalized along the entire anterior-posterior axis. The use of DTI for in vivo assessment of the parahippocampal white matter may be useful for identifying individuals with MCI at highest risk for conversion to AD and for assessing disease progression.

Cingulum correlates of cognitive functions in patients with mild cognitive impairment and early Alzheimer's disease: a diffusion spectrum imaging study

Diffusion spectrum imaging (DSI) of MRI can detect neural fiber tract changes. We investigated integrity of cingulum bundle (CB) in patients with mild cognitive impairment (MCI) and early Alzheimer's disease (EAD) using DSI tractography and explored its relationship with cognitive functions. We recruited 8 patients with MCI, 9 with EAD and 15 healthy controls (HC). All subjects received a battery of neuropsychological tests to access their executive, memory and language functions. We used a 3.0-tesla MRI scanner to obtain T1- and T2-weighted images for anatomy and used a pulsed gradient twice-refocused spin-echo diffusion echo-planar imaging sequence to acquire DSI. Patients with EAD performed significantly poorer than the HC on most tests in executive and memory functions. Significantly smaller general fractional anisotropy (GFA) values were found in the posterior and inferior segments of left CB and of the anterior segment of right CB of the EAD compared with those of the HC. Spearman's correlation on the patient groups showed that GFA values of the posterior segment of the left CB were significantly negatively associated with the time used to complete Color Trails Test Part II and positively correlated with performance of the logical memory and visual reproduction. GFA values of inferior segment of bilateral CB were positively associated with the performance of visual recognition. DSI tractography demonstrates significant preferential degeneration of the CB on the left side in patients with EAD. The location-specific degeneration is associated with corresponding declines in both executive and memory functions.

Full diffusion characterization implicates regionally disparate neuropathology in mild cognitive impairment

Diffusion tensor imaging (DTI) is used to detect tissue pathology. In Alzheimer's disease (AD) research, DTI has been used to elucidate differences in disease stages and to track progression over time and clinical severity. Many of these studies have identified the fornix as particularly vulnerable in the early stages of pathology associated with memory decline in prodromal AD. Emerging research suggests principal tensor components, axial (DA) and radial (DR) diffusivity, are more sensitive to underlying tissue pathology than are mean diffusivity (MD) and fractional anisotropy (FA). Given the established regionally specific tissue decline in MCI, we examined components of the full diffusion tensor (MD, FA, DR, and DA) for sensitivity to regional pathology associated with specific memory deficits in 18 individuals with MCI. We investigated multiple regions of interest, including fornix, temporal stem, and control regions for association with severity of impairment on multiple memory measures, including a type of neuropsychological task shown to be particularly sensitive to early memory decline in MCI. Better paired associate learning was selectively associated with lower DA (β = -0.663, p = 0.003), but not with DR, MD, or FA of the temporal stems. Conversely, better paired associate learning was associated with lower DR (β = -0.523, p = 0.026), higher FA (β = 0.498, p = 0.036), and lower MD (β = -0.513, p = 0.030), but not DA in the fornix. No association was found for control regions, or for control cognitive measures. These findings suggest disparate pathology of temporal stems and fornix white matter in association with early memory impairment in MCI. Further, they highlight the methodological importance of evaluating the full tensor, rather than only summative metrics in research using DTI.

Early morphological brain abnormalities in patients with amnestic mild cognitive impairment

Patients with amnestic mild cognitive impairment (aMCI) are at an increased risk of further deterioration and eventually developing Alzheimer’s disease (AD). Therefore, the identification of specific markers for this disease such as radiological markers is of great diagnostic and clinical significance. Our previous work has shown that magnetic resonance imaging (MRI) is a powerful tool to identify unique imaging features in patients with aMCI. Herein, we calculated the gray matter volume by structural magnetic resonance imaging (sMRI), and spontaneous low frequency fluctuations (LFF) using resting-state functional MRI (rs-fMRI) in 11 patients with aMCI and 22 normal control patients. Compared with the control group, patients with aMCI showed significant reduction of gray matter volume in the inferior frontal gyrus, inferior parietal lobule, anterior cingulated cortex, and insula and superior temporal gyrus. Patients with aMCI also showed significantly lower amplitudes of low-frequency fluctuations (ALFF) in the posterior cingulate cortex, precuneus, temporal gyrus and inferior parietal lobule when compared with the control group. However, in several other brain regions including the occipital lobe and cerebellum, the ALFF in patients with aMCI was significantly increased. The variation in ALFF between the two groups remained significant after adjustment for structural differences. Our results obtained in this pilot study are consistent with our previous finding and collectively show that patients with aMCI have abnormal MRI imaging findings. The pathological basis of these imaging features in patients with aMCI needs to be further explored.

Combined plasma biomarkers for diagnosing mild cognition impairment and Alzheimer's disease

A highly sensitive immunoassay, the immunomagnetic reduction, is used to measure several biomarkers for plasma that is related to Alzheimer's disease (AD). These biomarkers include Aβ-40, Aβ-42, and tau proteins. The samples are composed of four groups: healthy controls (n=66), mild cognitive impairment (MCI, n=22), very mild dementia (n=23), and mild-to-serve dementia, all due to AD (n=22). It is found that the concentrations of both Aβ-42 and tau protein for the healthy controls are significantly lower than those of all of the other groups. The sensitivity and the specificity of plasma Aβ-42 and tau protein in differentiating MCI from AD are all around 0.9 (0.88-0.97). However, neither plasma Aβ-42 nor tau-protein concentration is an adequate parameter to distinguish MCI from AD. A parameter is proposed, which is the product of plasma Aβ-42 and tau-protein levels, to differentiate MCI from AD. The sensitivity and specificity are found to be 0.80 and 0.82, respectively. It is concluded that the use of combined plasma biomarkers not only allows the differentiation of the healthy controls and patients with AD in both the prodromal phase and the dementia phase, but it also allows AD in the prodromal phase to be distinguished from that in the dementia phase.

Influence of APOE genotype on whole-brain functional networks in cognitively normal elderly

This study aimed to investigate the influence of apolipoprotein E (APOE) ε4 allele on whole-brain functional networks in cognitively normal (CN) elderly by applying graph theoretical analysis to brain glucose metabolism. Eighty-six CN elderly [28 APOE ε4 carriers (ε4+) and 58 non-carriers (ε4-)] underwent clinical evaluation and resting [(18)F] fluorodeoxyglucose positron emission tomography scan. Whole-brain functional networks were constructed from correlations of the 90 regions of interest using the automated anatomical labeling template, and analyzed using graph theoretical approaches. The overall small-world property seen in ε4- was preserved in ε4+. However, both local clustering and path length were lower in ε4+ compared to ε4-. In terms of the hubs of functional networks, ε4+ showed decreased centrality of the right hippocampus but increased centrality of several brain regions associated with the default mode network compared to ε4-. Our results indicate that genetic vulnerability to Alzheimer's disease may alter whole-brain functional networks even before clinical symptoms appear.

Plasma tau as a window to the brain-negative associations with brain volume and memory function in mild cognitive impairment and early Alzheimer's disease

Neurofibrillary tangles are associated with cognitive dysfunction, and hippocampal atrophy with increased CSF tau markers. However, the plasma tau levels of Alzheimer's disease (AD) have not been well studied. We investigated plasma tau by using an immunomagnetic reduction assay in 20 patients with mild cognitive impairment (MCI) due to AD, 10 early AD dementia, and 30 healthy elders (HE). All received a 3D-brain MRI scan and a set of cognitive function test. We explored their relationships with both brain structure and cognitive functions. Images were analyzed to determine the brain volumes and gray matter densities. Patients with MCI or early AD had significantly increased plasma tau levels compared with HE. Plasma tau levels were negatively associated with the performance of logical memory, visual reproduction, and verbal fluency; also negatively associated with volume of total gray matter, hippocampus, amygdala; and gray matter densities of various regions. Regression analyses indicated that logical memory explained 0.394 and hippocampus volume predicted .608 of the variance of plasma tau levels, both P < 0.001. Education years were negatively associated with the gray matter densities of the supramarginal (r = -0.407), middle temporal gyrus (r = -0.40) and precuneus (r = -0.377; all P < 0.05) in HE; and negatively associated with plasma tau levels in patients (r = -0.626). We propose that plasma tau may serve as a window to both structure and function of the brain. Higher education is a protective factor against AD and is associated with lower plasma tau levels in patients.

Cerebral small vessel disease affects white matter microstructure in mild cognitive impairment

Microstructural white matter deterioration is a frequent finding in mild cognitive impairment (MCI), potentially underlying default mode network (DMN) dysfunctioning. Thus far, microstructural damage in MCI has been attributed to Alzheimer's disease pathophysiology. A cerebrovascular role, in particular the role of cerebral small vessel disease (CSVD), received less interest. Here, we used diffusion tensor imaging (DTI) to examine the role of CSVD in microstructural deterioration within the normal appearing white matter (NAWM) in MCI. MCI patients were subdivided into those with (n = 20) and without (n = 31) macrostructural CSVD evidence on MRI. Using TBSS we performed microstructural integrity comparisons within the whole brain NAWM. Secondly, we segmented white matter tracts interconnecting DMN brain regions by means of automated tractography segmentation. We used NAWM DTI measures from these tracts as dependent variables in a stepwise-linear regression analysis, with structural and demographical predictors. Our results indicated microstructural deterioration within the anterior corpus callosum, internal and external capsule and periventricular white matter in MCI patients with CSVD, while in MCI patients without CSVD, deterioration was restricted to the right perforant path, a tract along the hippocampus. Within the full cohort of MCI patients, microstructure within the NAWM of the DMN fiber tracts was affected by the presence of CSVD. Within the cingulum along the hippocampal cortex we found a relationship between microstructural integrity and ipsilateral hippocampal volume and the extent of white matter hyperintensity. In conclusion, we found evidence of CSVD-related microstructural damage in fiber tracts subserving the DMN in MCI.

Neuroimaging biomarkers of neurodegenerative diseases and dementia

Neurodegenerative disorders leading to dementia are common diseases that affect many older and some young adults. Neuroimaging methods are important tools for assessing and monitoring pathological brain changes associated with progressive neurodegenerative conditions. In this review, the authors describe key findings from neuroimaging studies (magnetic resonance imaging and radionucleotide imaging) in neurodegenerative disorders, including Alzheimer's disease (AD) and prodromal stages, familial and atypical AD syndromes, frontotemporal dementia, amyotrophic lateral sclerosis with and without dementia, Parkinson's disease with and without dementia, dementia with Lewy bodies, Huntington's disease, multiple sclerosis, HIV-associated neurocognitive disorder, and prion protein associated diseases (i.e., Creutzfeldt-Jakob disease). The authors focus on neuroimaging findings of in vivo pathology in these disorders, as well as the potential for neuroimaging to provide useful information for differential diagnosis of neurodegenerative disorders.

Loss of olfactory tract integrity affects cortical metabolism in the brain and olfactory regions in aging and mild cognitive impairment

Olfactory dysfunction is an early feature of Alzheimer disease. This study used multimodal imaging of PET and (18)F-FDG combined with diffusion tensor imaging (DTI) to investigate the association of fiber tract integrity in the olfactory tract with cortical glucose metabolism in subjects with mild cognitive impairment (MCI) and normal controls. We hypothesized that MCI subjects would show loss of olfactory tract integrity and may have altered associations with glucose metabolism.

METHODS

Subjects diagnosed with amnestic MCI (n = 12) and normal controls (n = 23) received standard brain (18)F-FDG PET and DTI with 32 gradient directions on a 3-T MR imaging scanner. Fractional anisotropy (FA) maps were generated. Voxelwise correlation analysis of olfactory tract FA values with (18)F-FDG PET images was performed.

RESULTS

Integrated analysis over all subjects indicated a positive correlation between white matter integrity in the olfactory tract and metabolic activity in olfactory processing structures, including the rostral prefrontal cortex, dorsomedial thalamus, hypothalamus, orbitofrontal cortex, and uncus, and in the superior temporal gyrus, insula, and anterior cingulate cortex. Subjects with MCI, compared with normal controls, showed differential associations of olfactory tract integrity with medial temporal lobe and posterior cortical structures.

CONCLUSION

These findings indicate that impairment of axonal integrity or neuronal loss may be linked to functional metabolic changes and that disease-specific neurodegeneration may affect this relationship. Multimodal imaging using (18)F-FDG PET and DTI may provide better insights into aging and neurodegenerative processes.

Diffusion tensor imaging measures of normal appearing white matter in patients who are aging, or have amnestic mild cognitive impairment, or Alzheimer's disease

To evaluate whether cerebral white matter integrity is related to cognitive function, and whether diffusion tensor imaging (DTI) could differentiate amnestic mild cognitive impairment (aMCI) from Alzheimer's disease (AD), 12 patients with AD, 12 with aMCI, and 12 controls were recruited for this study. Cognitive functions of all subjects were assessed using the Mini-Mental State Examination (MMSE) and AD Assessment Scale - Cognitive Subscale (ADAS-Cog). DTI studies were acquired, and fractional anisotropy (FA) and mean diffusivity (MD) values of normal-appearing white matter (NAWM) in multiple brain regions were obtained. Results showed that MMSE and ADAS-Cog subscores were significantly associated with white matter integrity of the temporal-parietal lobes. A decrease in FA values and an increase in MD values in multiple cortical regions were confirmed in patients with AD compared to controls. MD values in the posterior region of the corpus callosum in aMCI differed from those of early AD. Significant reductions of FA values in the NAWM of the parietal lobe was observed in aMCI compared to controls. Our data indicate that the microstructural white matter integrity in the temporal-parietal lobes is gradually impaired in the progressive process of AD, and that splenium MD values could be used as a biomarker differentiating aMCI from AD.

MRI markers for mild cognitive impairment: comparisons between white matter integrity and gray matter volume measurements

The aim of the study was to evaluate the value of assessing white matter integrity using diffusion tensor imaging (DTI) for classification of mild cognitive impairment (MCI) and prediction of cognitive impairments in comparison to brain atrophy measurements using structural MRI. Fifty-one patients with MCI and 66 cognitive normal controls (CN) underwent DTI and T1-weighted structural MRI. DTI measures included fractional anisotropy (FA) and radial diffusivity (DR) from 20 predetermined regions-of-interest (ROIs) in the commissural, limbic and association tracts, which are thought to be involved in Alzheimer's disease; measures of regional gray matter (GM) volume included 21 ROIs in medial temporal lobe, parietal cortex, and subcortical regions. Significant group differences between MCI and CN were detected by each MRI modality: In particular, reduced FA was found in splenium, left isthmus cingulum and fornix; increased DR was found in splenium, left isthmus cingulum and bilateral uncinate fasciculi; reduced GM volume was found in bilateral hippocampi, left entorhinal cortex, right amygdala and bilateral thalamus; and thinner cortex was found in the left entorhinal cortex. Group classifications based on FA or DR was significant and better than classifications based on GM volume. Using either DR or FA together with GM volume improved classification accuracy. Furthermore, all three measures, FA, DR and GM volume were similarly accurate in predicting cognitive performance in MCI patients. Taken together, the results imply that DTI measures are as accurate as measures of GM volume in detecting brain alterations that are associated with cognitive impairment. Furthermore, a combination of DTI and structural MRI measurements improves classification accuracy.

Measurements of medial temporal lobe atrophy for prediction of Alzheimer's disease in subjects with mild cognitive impairment

Our aim was to compare the predictive accuracy of 4 different medial temporal lobe measurements for Alzheimer's disease (AD) in subjects with mild cognitive impairment (MCI). Manual hippocampal measurement, automated atlas-based hippocampal measurement, a visual rating scale (MTA-score), and lateral ventricle measurement were compared. Predictive accuracy for AD 2 years after baseline was assessed by receiver operating characteristics analyses with area under the curve as outcome. Annual cognitive decline was assessed by slope analyses up to 5 years after baseline. Correlations with biomarkers in cerebrospinal fluid (CSF) were investigated. Subjects with MCI were selected from the Development of Screening Guidelines and Clinical Criteria for Predementia AD (DESCRIPA) multicenter study (n = 156) and the single-center VU medical center (n = 172). At follow-up, area under the curve was highest for automated atlas-based hippocampal measurement (0.71) and manual hippocampal measurement (0.71), and lower for MTA-score (0.65) and lateral ventricle (0.60). Slope analysis yielded similar results. Hippocampal measurements correlated with CSF total tau and phosphorylated tau, not with beta-amyloid 1-42. MTA-score and lateral ventricle volume correlated with CSF beta-amyloid 1-42. We can conclude that volumetric hippocampal measurements are the best predictors of AD conversion in subjects with MCI.

Diffusion tensor imaging in Alzheimer disease and mild cognitive impairment

A wide range of imaging studies provides growing support for the potential role of diffusion tensor imaging (DTI) in evaluating microstructural white matter integrity in Alzheimer disease (AD) and mild cognitive impairment (MCI). Our review aims to present DTI principles, post-processing and analysis frameworks and to report the results of particular studies. The distribution of AD-related white matter abnormalities is widely discussed in the light of deteriorated connectivity within certain tracts due to secondary white matter degeneration; primary alterations are also assumed to contribute to the pattern. The question whether it is more effective to assess the whole-brain diffusion or to directly concentrate on specific regions remains an interesting issue. Assessing white matter microstructure alterations, as evaluated by group-level differences of tensor-derived parameters, may be a promising neuroimaging tool for differential diagnosis between AD, MCI and other cognitive disorders, as well as being particularly helpful in the interpretation of underlying pathological processes.

Different patterns of white matter degeneration using multiple diffusion indices and volumetric data in mild cognitive impairment and Alzheimer patients

Alzheimeŕs disease (AD) represents the most prevalent neurodegenerative disorder that causes cognitive decline in old age. In its early stages, AD is associated with microstructural abnormalities in white matter (WM). In the current study, multiple indices of diffusion tensor imaging (DTI) and brain volumetric measurements were employed to comprehensively investigate the landscape of AD pathology. The sample comprised 58 individuals including cognitively normal subjects (controls), amnestic mild cognitive impairment (MCI) and AD patients. Relative to controls, both MCI and AD subjects showed widespread changes of anisotropic fraction (FA) in the corpus callosum, cingulate and uncinate fasciculus. Mean diffusivity and radial changes were also observed in AD patients in comparison with controls. After controlling for the gray matter atrophy the number of regions of significantly lower FA in AD patients relative to controls was decreased; nonetheless, unique areas of microstructural damage remained, e.g., the corpus callosum and uncinate fasciculus. Despite sample size limitations, the current results suggest that a combination of secondary and primary degeneration occurrs in MCI and AD, although the secondary degeneration appears to have a more critical role during the stages of disease involving dementia.

Corpus callosum in aging and neurodegenerative diseases

SUMMARY The corpus callosum (CC) is a major white matter bundle that connects primarily homologous areas of the cortex. The structure may be involved in interhemispheric communication and enable the lateralization of certain cerebral functions. Despite its possible role as the main conduit for interhemispheric communication, interest from researchers has, at times, been sparse. Renewed interest has led to research that has shown that the CC may play a role in both cognitive aging and neurodegenerative diseases including Alzheimer´s disease and frontotemporal dementia. Studies employing structural MRI and diffusion-weighted MRI have found distinct subregional patterns of callosal atrophy in aging, Alzheimer´s disease and frontotemporal dementia. Furthermore, imaging studies may help to elucidate the underlying pathological mechanisms of callosal atrophy. The present review aims to provide an overview of the current knowledge of the structure and function of the CC and its role in aging and neurodegenerative disease.

Alzheimer disease: new concepts on its neurobiology and the clinical role imaging will play

Alzheimer disease (AD) is one of, if not the most, feared diseases associated with aging. The prevalence of AD increases exponentially with age after 60 years. Increasing life expectancy coupled with the absence of any approved disease-modifying therapies at present position AD as a dominant public health problem. Major advances have occurred in the development of disease biomarkers for AD in the past 2 decades. At present, the most well-developed AD biomarkers are the cerebrospinal fluid analytes amyloid-β 42 and tau and the brain imaging measures amyloid positron emission tomography (PET), fluorodeoxyglucose PET, and magnetic resonance imaging. CSF and imaging biomarkers are incorporated into revised diagnostic guidelines for AD, which have recently been updated for the first time since their original formulation in 1984. Results of recent studies suggest the possibility of an ordered evolution of AD biomarker abnormalities that can be used to stage the typical 20-30-year course of the disease. When compared with biomarkers in other areas of medicine, however, the absence of standardized quantitative metrics for AD imaging biomarkers constitutes a major deficiency. Failure to move toward a standardized system of quantitative metrics has substantially limited potential diagnostic usefulness of imaging in AD. This presents an important opportunity that, if widely embraced, could greatly expand the application of imaging to improve clinical diagnosis and the quality and efficiency of clinical trials.

Assessing corpus callosum changes in Alzheimer's disease: comparison between tract-based spatial statistics and atlas-based tractography

Tractography based on Diffusion Tensor Imaging (DTI) represents a valuable tool for investigating brain white matter (WM) microstructure, allowing the computation of damage-related diffusion parameters such as Fractional Anisotropy (FA) in specific WM tracts. This technique appears relevant in the study of pathologies in which brain disconnection plays a major role, such as, for instance, Alzheimer's Disease (AD). Previous DTI studies have reported inconsistent results in defining WM abnormalities in AD and in its prodromal stage (i.e., amnestic Mild Cognitive Impairment; aMCI), especially when investigating the corpus callosum (CC). A reason for these inconsistencies is the use of different processing techniques, which may strongly influence the results. The aim of the current study was to compare a novel atlas-based tractography approach, that sub-divides the CC in eight portions, with Tract-Based Spatial Statistics (TBSS) when used to detect specific patterns of CC FA in AD at different clinical stages. FA data were obtained from 76 subjects (37 with mild AD, 19 with aMCI and 20 elderly healthy controls, HC) and analyzed using both methods. Consistent results were obtained for the two methods, concerning the comparisons AD vs. HC (significantly reduced FA in the whole CC of AD patients) and AD vs. aMCI (significantly reduced FA in the frontal portions of the CC in AD patients), thus identifying a relative preservation of the frontal CC regions in aMCI patients compared to AD. Conversely, the atlas-based method but not the TBSS showed the ability to detect a selective FA change in the CC parietal, left temporal and occipital regions of aMCI patients compared to HC. This finding indicates that an analysis including a higher number of voxels (with no restriction to tract skeletons) may detect characteristic pattern of FA in the CC of patients with preclinical AD, when brain atrophy is still modest.

The value of diffusion tensor imaging in the differential diagnosis of subcortical ischemic vascular dementia and Alzheimer's disease in patients with only mild white matter alterations on T2-weighted images

BACKGROUND

Diffusion tensor imaging (DTI) is a form of functional magnetic resonance imaging (MRI) that allows examination of the microstructural integrity of white matter in the brain. Dementia is a neurodegenerative disease, and DTI can provide indirect insights of the microstructural characteristics of brains in individuals with different forms of dementia.

PURPOSE

To evaluate the value of DTI in the diagnosis and differential diagnosis of patients with subcortical ischemic vascular dementia (SIVD) and Alzheimer's disease (AD).

MATERIAL AND METHODS

The study included 40 patients (20 AD patients and 20 SIVD patients) and 20 normal controls (NC). After routine MRI and DTI, fractional anisotropy (FA) and apparent diffusion coefficient (ADC) values were measured and compared in regions of interest (ROI).

RESULTS

Compared to NC and AD patients, SIVD patients had lower FA values and higher ADC values in the inferior-fronto-occipital fascicles (IFOF), genu of the corpus callosum (GCC), splenium of the corpus callosum (SCC), and superior longitudinal fasciculus (SLF). Compared to controls and SIVD patients, AD patients had lower FA values in the anterior frontal lobe, temporal lobe, hippocampus, IFOF, GCC, and CF; and higher ADC values in the temporal lobe and hippocampus.

CONCLUSION

DTI can be used to estimate the white matter impairment in dementia patients. There were significant regional reductions of FA values and heightened ADC values in multiple regions in SIVD patients compared to AD patients. When compared with conventional MRI, DTI may provide a more objective method for the differential diagnosis of SIVD and AD disease patients who have only mild white matter alterations on T2-weighted imaging.

Diffusion tensor imaging in Alzheimer's disease and dementia with Lewy bodies

White matter changes have been investigated in Alzheimer's disease (AD) in a number of studies using diffusion imaging. Fewer studies have investigated dementia with Lewy bodies (DLB). We used diffusion-weighted magnetic resonance imaging (MRI) and high-resolution (0.3 mm in-plane) coronal 3T MRI of the medial temporal lobe in 16 subjects with AD, 16 with DLB and 16 similarly aged healthy subjects. We found increased mean diffusivity in the temporal lobe of AD, and reduced fractional anisotropy (FA) in a small cluster in the right postcentral gyrus region in the DLB group. Mean FA in this cluster correlated with UPDRS (Unified Parkinson's Disease Rating Scale) motor score. We had previously reported reduced visibility in the AD group of a dark appearing layer of the hippocampus in the high-resolution images. In an SPM analysis on all subjects, there were significant clusters of reduced FA in the corpus callosum, fornix and stria terminalis that correlated with the visual rating of the hippocampus. These results suggest that changes to the hippocampus are associated with structural changes to the white matter fibres of the hippocampus output, and that changes in motor function are associated with changes in white matter underlying somatosensory cortex.

Other magnetic resonance imaging techniques

Relatively new developments in MRI, such as functional MRI (fMRI), magnetic resonance spectroscopy (MRS) and diffusion tensor imaging (DTI) are rapidly developing into imaging modalities that will become clinically available in the near future. They have in common that their signal is somewhat easier to interpret than structural MRI: fMRI mirrors excess cerebral blood flow, in many cases representing brain activity, MRS gives the average volume concentrations of specific chemical compounds, and DTI reflects "directedness" of micro-anatomical structures, of particular use in white matter where fiber bundle disruption can be detected with great sensitivity. While structural changes in MRI have been disappointing in giving a diagnosis of sufficient sensitivity and specificity, these newer methods hold out hope for elucidating pathological changes and differentiating patient groups more rigorously. This paper summarizes promising research results that will yet have to be translated into real life clinical studies in larger groups of patients (e.g. memory clinic patients). Where available, we have tried to summarize results comparing different types of dementia.

Differential diagnosis of idiopathic normal pressure hydrocephalus from other dementias using diffusion tensor imaging

BACKGROUND AND PURPOSE

Because DTI can provide good markers of white matter pathology, it could be useful in differentiating white matter changes of INPH from those of other dementias. The aim of this study was, by using DTI, to compare the characteristic white matter changes in INPH with those in AD, subcortical vascular dementia, and healthy control subjects.

MATERIALS AND METHODS

Sixteen patients with presurgical INPH, 10 with AD, 10 with subcortical vascular dementia, and 20 healthy control subjects underwent DTI. All patients with INPH showed clinical improvement after shunt surgery, and 9 of them also underwent postshunting DTI. Regions of interest were selected at the periventricular white matter, the anterior limb of the internal capsule, the posterior limb of the internal capsule, the genu and the splenium of the corpus callosum, the superior longitudinal fasciculus, and the inferior longitudinal fasciculus. FA and MD were obtained from each region of interest and were compared among the groups.

RESULTS

Presurgical INPH showed significantly higher FA than all the other groups in the posterior limb of the internal capsule, which was decreased after shunt surgery. Presurgical MD of the INPH group was higher than that in the AD and healthy control groups but lower than that in the subcortical vascular dementia group in the anterior periventricular white matter, the anterior limb of the internal capsule, and the superior longitudinal fasciculus. In differentiating INPH, the sensitivity and specificity of FA in the posterior limb of the internal capsule was 87.5% and 95.0%, respectively.

CONCLUSIONS

Patients with shunt-responsive INPH showed higher FA in the posterior limb of the internal capsule compared with healthy controls and those in other groups of dementia that was reversible with shunt surgery. With this parameter, shunt-responsive INPH could be distinguished from AD, subcortical vascular dementia, and healthy conditions with high diagnostic accuracy.