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

Differential diagnosis of neurodegenerative dementias with the explainable MRI based machine learning algorithm MUQUBIA

Biomarker-based differential diagnosis of the most common forms of dementia is becoming increasingly important. Machine learning (ML) may be able to address this challenge. The aim of this study was to develop and interpret a ML algorithm capable of differentiating Alzheimer's dementia, frontotemporal dementia, dementia with Lewy bodies and cognitively normal control subjects based on sociodemographic, clinical, and magnetic resonance imaging (MRI) variables. 506 subjects from 5 databases were included. MRI images were processed with FreeSurfer, LPA, and TRACULA to obtain brain volumes and thicknesses, white matter lesions and diffusion metrics. MRI metrics were used in conjunction with clinical and demographic data to perform differential diagnosis based on a Support Vector Machine model called MUQUBIA (Multimodal Quantification of Brain whIte matter biomArkers). Age, gender, Clinical Dementia Rating (CDR) Dementia Staging Instrument, and 19 imaging features formed the best set of discriminative features. The predictive model performed with an overall Area Under the Curve of 98%, high overall precision (88%), recall (88%), and F1 scores (88%) in the test group, and good Label Ranking Average Precision score (0.95) in a subset of neuropathologically assessed patients. The results of MUQUBIA were explained by the SHapley Additive exPlanations (SHAP) method. The MUQUBIA algorithm successfully classified various dementias with good performance using cost-effective clinical and MRI information, and with independent validation, has the potential to assist physicians in their clinical diagnosis.

(Dis-)Connected Dots in Dementia with Lewy Bodies-A Systematic Review of Connectivity Studies

Studies on dementia with Lewy bodies (DLB) have mainly focused on the degeneration of distinct cortical and subcortical regions related to the deposition of Lewy bodies. In view of the proposed trans-synaptic spread of the α-synuclein pathology, investigating the disease only in this segregated fashion would be detrimental to our understanding of its progression. In this systematic review, we summarize findings on structural and functional brain connectivity in DLB, as connectivity measures may offer better insights on how the brain is affected by the spread of the pathology. Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Web of Science, PubMed, and SCOPUS for relevant articles published up to November 1, 2021. Of 1215 identified records, we selected and systematically reviewed 53 articles that compared connectivity features between patients with DLB and healthy controls. Structural and functional magnetic resonance imaging, positron emission tomography, single-positron emission computer tomography, and electroencephalography assessments of patients revealed widespread abnormalities within and across brain networks in DLB. Frontoparietal, default mode, and visual networks and their connections to other brain regions featured the most consistent disruptions, which were also associated with core clinical features and cognitive impairments. Furthermore, graph theoretical measures revealed disease-related decreases in local and global network efficiency. This systematic review shows that structural and functional connectivity characteristics in DLB may be particularly valuable at early stages, before overt brain atrophy can be observed. This knowledge may help improve the diagnosis and prognosis in DLB as well as pinpoint targets for future disease-modifying treatments. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Visual hallucinations in dementia with Lewy bodies originate from necrosis of characteristic neurons and connections in three-module perception model

Mathematical and computational approaches were used to investigate dementia with Lewy bodies (DLB), in which recurrent complex visual hallucinations (RCVH) is a very characteristic symptom. Beginning with interpretative analyses of pathological symptoms of patients with RCVH-DLB in comparison with the veridical perceptions of normal subjects, we constructed a three-module scenario concerning function giving rise to perception. The three modules were the visual input module, the memory module, and the perceiving module. Each module interacts with the others, and veridical perceptions were regarded as a certain convergence to one of the perceiving attractors sustained by self-consistent collective fields among the modules. Once a rather large but inhomogeneously distributed area of necrotic neurons and dysfunctional synaptic connections developed due to network disease, causing irreversible damage, then bottom-up information from the input module to both the memory and perceiving modules were severely impaired. These changes made the collective fields unstable and caused transient emergence of mismatched perceiving attractors. This may account for the reason why DLB patients see things that are not there. With the use of our computational model and experiments, the scenario was recreated with complex bifurcation phenomena associated with the destabilization of collective field dynamics in very high-dimensional state space.

Functional and structural brain network correlates of visual hallucinations in Lewy body dementia

Visual hallucinations are a common feature of Lewy body dementia. Previous studies have shown that visual hallucinations are highly specific in differentiating Lewy body dementia from Alzheimer’s disease dementia and Alzheimer–Lewy body mixed pathology cases. Computational models propose that impairment of visual and attentional networks is aetiologically key to the manifestation of visual hallucinations symptomatology. However, there is still a lack of experimental evidence on functional and structural brain network abnormalities associated with visual hallucinations in Lewy body dementia.

We used EEG source localization and network based statistics to assess differential topographical patterns in Lewy body dementia between 25 participants with visual hallucinations and 17 participants without hallucinations. Diffusion tensor imaging was used to assess structural connectivity between thalamus, basal forebrain and cortical regions belonging to the functionally affected network component in the hallucinating group, as assessed with network based statistics. The number of white matter streamlines within the cortex and between subcortical and cortical regions was compared between hallucinating and not hallucinating groups and correlated with average EEG source connectivity of the affected subnetwork. Moreover, modular organization of the EEG source network was obtained, compared between groups and tested for correlation with structural connectivity.

Network analysis showed that compared to non-hallucinating patients, those with hallucinations feature consistent weakened connectivity within the visual ventral network, and between this network and default mode and ventral attentional networks, but not between or within attentional networks. The occipital lobe was the most functionally disconnected region. Structural analysis yielded significantly affected white matter streamlines connecting the cortical regions to the nucleus basalis of Meynert and the thalamus in hallucinating compared to not hallucinating patients. The number of streamlines in the tract between the basal forebrain and the cortex correlated with cortical functional connectivity in non-hallucinating patients, while a correlation emerged for the white matter streamlines connecting the functionally affected cortical regions in the hallucinating group.

This study proposes, for the first time, differential functional networks between hallucinating and not hallucinating Lewy body dementia patients, and provides empirical evidence for existing models of visual hallucinations. Specifically, the outcome of the present study shows that the hallucinating condition is associated with functional network segregation in Lewy body dementia and supports the involvement of the cholinergic system as proposed in the current literature.

Temporal dynamic changes of intrinsic brain activity in Alzheimer's disease and mild cognitive impairment patients: a resting-state functional magnetic resonance imaging study

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by memory impairment. Previous studies have largely focused on alterations of static brain activity occurring in patients with AD. Few studies to date have explored the characteristics of dynamic brain activity in cognitive impairment, and their predictive ability in AD patients.

METHODS

One hundred and eleven AD patients, 29 MCI patients, and 73 healthy controls (HC) were recruited. The dynamic amplitude of low-frequency fluctuation (dALFF) and the dynamic fraction amplitude of low-frequency fluctuation (dfALFF) were used to assess the temporal variability of local brain activity in patients with AD or mild cognitive impairment (MCI). Pearson's correlation coefficients were calculated between the metrics and subjects' behavioral scores.

RESULTS

The results of analysis of variance indicated that the AD, MCI, and HC groups showed significant variability of dALFF in the cerebellar posterior and middle temporal lobes. In AD patients, these brain regions had high dALFF variability. Significant dfALFF variability was found between the three groups in the left calcarine cortex and white matter. The AD group showed lower dfALFF than the MCI group in the left calcarine cortex.

CONCLUSIONS

Compared to HC, AD patients were found to have increased dALFF variability in the cerebellar posterior and temporal lobes. This abnormal pattern may diminish the capacity of the cerebellum and temporal lobes to participate in the cerebrocerebellar circuits and default mode network (DMN), which regulate cognition and emotion in AD. The findings above indicate that the analysis of dALFF and dfALFF based on functional magnetic resonance imaging data may give a new insight into the neurophysiological mechanisms of AD.

Neuroimaging Advances in Parkinson's Disease and Atypical Parkinsonian Syndromes

Parkinson's disease (PD) and atypical Parkinsonian syndromes are progressive heterogeneous neurodegenerative diseases that share clinical characteristic of parkinsonism as a common feature, but are considered distinct clinicopathological disorders. Based on the predominant protein aggregates observed within the brain, these disorders are categorized as, (1) α-synucleinopathies, which include PD and other Lewy body spectrum disorders as well as multiple system atrophy, and (2) tauopathies, which comprise progressive supranuclear palsy and corticobasal degeneration. Although, great strides have been made in neurodegenerative disease research since the first medical description of PD in 1817 by James Parkinson, these disorders remain a major diagnostic and treatment challenge. A valid diagnosis at early disease stages is of paramount importance, as it can help accommodate differential prognostic and disease management approaches, enable the elucidation of reliable clinicopathological relationships ideally at prodromal stages, as well as facilitate the evaluation of novel therapeutics in clinical trials. However, the pursuit for early diagnosis in PD and atypical Parkinsonian syndromes is hindered by substantial clinical and pathological heterogeneity, which can influence disease presentation and progression. Therefore, reliable neuroimaging biomarkers are required in order to enhance diagnostic certainty and ensure more informed diagnostic decisions. In this article, an updated presentation of well-established and emerging neuroimaging biomarkers are reviewed from the following modalities: (1) structural magnetic resonance imaging (MRI), (2) diffusion-weighted and diffusion tensor MRI, (3) resting-state and task-based functional MRI, (4) proton magnetic resonance spectroscopy, (5) transcranial B-mode sonography for measuring substantia nigra and lentiform nucleus echogenicity, (6) single photon emission computed tomography for assessing the dopaminergic system and cerebral perfusion, and (7) positron emission tomography for quantifying nigrostriatal functions, glucose metabolism, amyloid, tau and α-synuclein molecular imaging, as well as neuroinflammation. Multiple biomarkers obtained from different neuroimaging modalities can provide distinct yet corroborative information on the underlying neurodegenerative processes. This integrative "multimodal approach" may prove superior to single modality-based methods. Indeed, owing to the international, multi-centered, collaborative research initiatives as well as refinements in neuroimaging technology that are currently underway, the upcoming decades will mark a pivotal and exciting era of further advancements in this field of neuroscience.

Alzheimer's disease diagnosis from diffusion tensor images using convolutional neural networks

Machine learning algorithms are currently being implemented in an escalating manner to classify and/or predict the onset of some neurodegenerative diseases; including Alzheimer's Disease (AD); this could be attributed to the fact of the abundance of data and powerful computers. The objective of this work was to deliver a robust classification system for AD and Mild Cognitive Impairment (MCI) against healthy controls (HC) in a low-cost network in terms of shallow architecture and processing. In this study, the dataset included was downloaded from the Alzheimer's disease neuroimaging initiative (ADNI). The classification methodology implemented was the convolutional neural network (CNN), where the diffusion maps, and gray-matter (GM) volumes were the input images. The number of scans included was 185, 106, and 115 for HC, MCI and AD respectively. Ten-fold cross-validation scheme was adopted and the stacked mean diffusivity (MD) and GM volume produced an AUC of 0.94 and 0.84, an accuracy of 93.5% and 79.6%, a sensitivity of 92.5% and 62.7%, and a specificity of 93.9% and 89% for AD/HC and MCI/HC classification respectively. This work elucidates the impact of incorporating data from different imaging modalities; i.e. structural Magnetic Resonance Imaging (MRI) and Diffusion Tensor Imaging (DTI), where deep learning was employed for the aim of classification. To the best of our knowledge, this is the first study assessing the impact of having more than one scan per subject and propose the proper maneuver to confirm the robustness of the system. The results were competitive among the existing literature, which paves the way for improving medications that could slow down the progress of the AD or prevent it.

Correlation of microglial activation with white matter changes in dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is characterized by alpha-synuclein protein deposition with variable degree of concurrent Alzheimer's pathology. Neuroinflammation is also increasingly recognized as a significant contributor to degeneration. We aimed to examine the relationship between microglial activation as measured with [¹¹C]-PK11195 brain PET, MR diffusion tensor imaging (DTI) and grey matter atrophy in DLB. Nineteen clinically probable DLB and 20 similarly aged controls underwent 3T structural MRI (T1-weighted) and diffusion-weighted imaging. Eighteen DLB subjects also underwent [¹¹C]-PK11195 PET imaging and 15 had [¹¹C]-Pittsburgh compound B amyloid PET, resulting in 9/15 being amyloid-positive. We used Computational Anatomy Toolbox (CAT12) for volume-based morphometry (VBM) and Tract-Based Spatial Statistics (TBSS) for DTI to assess group comparisons between DLB and controls and to identify associations of [¹¹C]-PK11195 binding with grey/white matter changes and cognitive score in DLB patients. VBM analyses showed that DLB had extensive reduction of grey matter volume in superior frontal, temporal, parietal and occipital cortices (family-wise error (FWE)-corrected p < 0.05). TBSS showed widespread changes in DLB for all DTI parameters (reduced fractional anisotropy, increased diffusivity), involving the corpus callosum, corona radiata and superior longitudinal fasciculus (FWE-corrected p < 0.05). Higher [¹¹C]-PK11195 binding in parietal cortices correlated with widespread lower mean and radial diffusivity in DLB patients (FWE-corrected p < 0.05). Furthermore, preserved cognition in DLB (higher Addenbrookes Cognitive Evaluation revised score) also correlated with higher [¹¹C]-PK11195 binding in frontal, temporal, and occipital lobes. However, microglial activation was not significantly associated with grey matter changes. Our study suggests that increased microglial activation is associated with a relative preservation of white matter and cognition in DLB, positioning neuroinflammation as a potential early marker of DLB etio-pathogenesis.

Genetic influences on white matter and metabolism abnormal change in Alzheimer's disease: Meta-analysis for neuroimaging research on presenilin 1 mutation

Mutations in the presenilin1 (PSEN1) cause familial Alzheimer's disease (FAD), providing a special opportunity to study pre-symptomatic individuals who would be predicted to develop Alzheimer's disease (AD) in the future. However, whether presenilin1 (PSEN1) genotype and neuroimaging markers is a harbinger of AD remains controversial. We aimed to explore the association of PSEN1 genotype with neuroimaging markers of AD: white matter integrity, cerebral amyloid deposition and brain metabolism. We reviewed studies of diffusion tensor imaging (DTI), amyloid deposition and cerebral metabolism in patients with AD and control, in order to address the relative change of white matter microstructural associated with PSEN1 genotype. We performed a systematic meta-analysis and review of 11 cross-sectional studies identified in several database from 2008 to 2018 (n = 165). The pooled standard mean difference (SMD) value was calculated to estimate the association between PSEN1 and white matter change and brain metabolism. PSEN1 mutation carrier status was associated with mean diffusivity (MD) change (pooled SMD: 2.29; 95% CI 1.04 to 3.53; p < 0.001) and increased cerebral amyloid positron emission tomography tracer (pooled SMD: 3.78, 95% CI 1.04 to 6.53, p = 0.007). PSEN1 was not associated with white matter metabolism change (p = 0.069). PSEN1 was associated with mean diffusivity (MD) increase in DTI markers and decreased brain metabolism. Theses associations may suggest the potential role of the PSEN1 gene and imaging marker in Alzheimer's disease.

Structural and Functional Magnetic Resonance Imaging of Dementia With Lewy Bodies

Dementia with Lewy bodies (DLB) is the second most common cause of neurodegenerative dementia after Alzheimer's disease (AD). Although diagnosis may be challenging, there is increasing evidence that the use of biomarkers according to 2017 revised criteria for diagnosis and management of dementia with Lewy bodies can increase diagnostic accuracy. Apart from nuclear medicine techniques, various magnetic resonance imaging (MRI) techniques have been utilized in attempt to enhance diagnostic accuracy. This chapter reviews structural, functional and diffusion MRI studies in DLB cohorts being compared to healthy controls, AD or dementia in Parkinson's disease (PDD). We also included relatively new MRI methods that may have potential to identify early DLB subjects and aim at examining brain iron and neuromelanin.

The Effects of Mindfulness on Older Adults with Mild Cognitive Impairment

Background

The current lack of an effective cure for dementia would exacerbate its prevalence and incidence globally. Growing evidence has linked mindfulness to cognitive and psychological improvements that could be relevant for mild cognitive impairment (MCI).

Objective

To investigate whether mindfulness practice can improve health outcomes of MCI.

Methods

The study is the first longitudinal mixed-methods observational study with a one-year follow-up period, that customized an eight-week group-based mindfulness training program for older adults with MCI (n = 14). Measures included cognitive function, psychological health, trait mindfulness, adherence to mindfulness practice, and everyday activities functioning as assessed at pre-intervention, post-intervention, and one-year follow-up. Repeated measures ANOVAs, Pearson's correlation analyses, and Mann-Whitney U tests were performed.

Results

The MCI participants showed significant improvements in cognitive function (p < 0.05) and trait mindfulness (p < 0.05) after completing the intervention. Between program intervention and one-year follow-up (59 weeks), positive correlations were found between their cognitive function (p < 0.05) and everyday activities functioning (p < 0.05) with the duration of mindfulness meditation; and between trait mindfulness and the level of informal mindfulness practice (p < 0.05). Those who meditated more during these 59 weeks, showed greater improvements in cognitive function (p < 0.05) and everyday activities functioning (p < 0.05), with large effect sizes at the one-year follow-up. Qualitative findings will be reported separately.

Conclusion

Long-term mindfulness practice may be associated with cognitive and functional improvements for older adults with MCI. Mindfulness training could be a potential efficacious non-pharmacological therapeutic intervention for MCI.

Imaging biomarkers in Parkinson's disease and Parkinsonian syndromes: current and emerging concepts

Two centuries ago in 1817, James Parkinson provided the first medical description of Parkinson’s disease, later refined by Jean-Martin Charcot in the mid-to-late 19th century to include the atypical parkinsonian variants (also termed, Parkinson-plus syndromes). Today, Parkinson’s disease represents the second most common neurodegenerative disorder with an estimated global prevalence of over 10 million. Conversely, atypical parkinsonian syndromes encompass a group of relatively heterogeneous disorders that may share some clinical features with Parkinson’s disease, but are uncommon distinct clinicopathological diseases. Decades of scientific advancements have vastly improved our understanding of these disorders, including improvements in in vivo imaging for biomarker identification. Multimodal imaging for the visualization of structural and functional brain changes is especially important, as it allows a ‘window’ into the underlying pathophysiological abnormalities. In this article, we first present an overview of the cardinal clinical and neuropathological features of, 1) synucleinopathies: Parkinson’s disease and other Lewy body spectrum disorders, as well as multiple system atrophy, and 2) tauopathies: progressive supranuclear palsy, and corticobasal degeneration. A comprehensive presentation of well-established and emerging imaging biomarkers for each disorder are then discussed. Biomarkers for the following imaging modalities are reviewed: 1) structural magnetic resonance imaging (MRI) using T1, T2, and susceptibility-weighted sequences for volumetric and voxel-based morphometric analyses, as well as MRI derived visual signatures, 2) diffusion tensor MRI for the assessment of white matter tract injury and microstructural integrity, 3) proton magnetic resonance spectroscopy for quantifying proton-containing brain metabolites, 4) single photon emission computed tomography for the evaluation of nigrostriatal integrity (as assessed by presynaptic dopamine transporters and postsynaptic dopamine D2 receptors), and cerebral perfusion, 5) positron emission tomography for gauging nigrostriatal functions, glucose metabolism, amyloid and tau molecular imaging, as well as neuroinflammation, 6) myocardial scintigraphy for dysautonomia, and 7) transcranial sonography for measuring substantia nigra and lentiform nucleus echogenicity. Imaging biomarkers, using the ‘multimodal approach’, may aid in making early, accurate and objective diagnostic decisions, highlight neuroanatomical and pathophysiological mechanisms, as well as assist in evaluating disease progression and therapeutic responses to drugs in clinical trials.

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.

Fractional anisotropy of the fornix and hippocampal atrophy in Alzheimer's disease

Decrease in the directionality of water diffusion measured with fractional anisotropy (FA) on diffusion tensor imaging has been linked to loss of myelin and axons in the white matter. Fornix FA is consistently decreased in patients with mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Furthermore, decreased fornix FA is one of the earliest MRI abnormalities observed in cognitively normal individuals who are at an increased risk for AD, such as in pre-symptomatic carriers of familial AD mutations and in pre-clinical AD. Reductions of FA at these early stages, which predicted the decline in memory function. Fornix carries the efferent projections from the CA1 and CA3 pyramidal neurons of the hippocampus and subiculum, connecting these structures to the septal nuclei, anterior thalamic nucleus, mammillary bodies, and medial hypothalamus. Fornix also carries the afferent cholinergic and GABAergic projections from the medial septal nuclei and the adjacent diagonal band back to the medial temporal lobe, interconnecting the core limbic structures. Because fornix carries the axons projecting from the hippocampus, integrity of the fornix is in-part linked to the integrity of the hippocampus. In keeping with that, fornix FA is reduced in subjects with hippocampal atrophy, correlating with memory function. The literature on FA reductions in the fornix in the clinical spectrum of AD from pre-symptomatic carriers of familial AD mutations to pre-clinical AD, MCI, and dementia stages is reviewed.

Relevance of subcortical visual pathways disruption to visual symptoms in dementia with Lewy bodies

Visual hallucinations represent a core diagnostic criterion for dementia with Lewy bodies (DLB). We hypothesized that thalamic regions, which are critically involved in the modulation of visual transmission, may be differentially disrupted in DLB as compared to Alzheimer's Disease (AD) and that these deficits could relate to visual dysfunction in DLB patients. Magnetic Resonance and Diffusion Tensor Imaging (DTI) were performed with a 3 T scanner on a sample population of 15 DLB patients, 15 AD patients and 13 healthy volunteers. Regional thalamic micro-structural changes were assessed by parcelling the thalamus based on its connectivity to cortex and to amygdala and by measuring the mean diffusivity (MD) in each connectivity-defined sub-region. Micro-structural grey matter damage associated to higher MD values was found bilaterally in DLB compared to controls in the sub-regions projecting from thalamus to prefrontal and parieto-occipital cortices. Right thalamic sub-region projecting to amygdala and left thalamic sub-region projecting to motor cortex were also affected in DLB compared to controls. Higher MD values were found bilaterally in AD compared to controls in the thalamic sub-regions projecting to temporal cortex. Specific comparison between the two forms of dementia found differences: the sub-regions which project from thalamus to parieto-occipital cortex and to amygdala showed higher MD values in DLB compared to AD patients. In DLB patients, correlation analysis showed a significant correlation between NPI hallucinations item scores and MD values in the right thalamic sub-regions projecting to parietal and occipital cortices. The present study demonstrates how thalamic connectivity alterations between higher and lower visual areas may be relevant in explaining visual hallucinations in DLB.

The role of functional dopamine-transporter SPECT imaging in parkinsonian syndromes, part 2

SUMMARY

The functional imaging technique most widely used in European clinics to differentiate a true parkinsonian syndrome from vascular parkinsonism, drug-induced changes, or essential tremor is dopamine-transporter SPECT. This technique commonly reports dopamine-transporter function, with decreasing striatal uptake demonstrating increasingly severe disease. The strength of dopamine-transporter SPECT is that nigrostriatal degeneration is observed in both clinically inconclusive parkinsonism and early, even premotor, disease. In this clinical review (Part 2), we present the dopamine-transporter SPECT findings in a variety of neurodegenerative diseases, including multiple system atrophy, progressive supranuclear palsy, corticobasal degeneration, and dementia with Lewy bodies. The findings in vascular parkinsonism, drug-induced parkinsonism, and essential tremor are also described. It is hoped that this technique will be the forerunner of a range of routinely used, process-specific ligands that can identify early degenerative disease and subsequently guide disease-modifying interventions.

Assessment of regional MR diffusion changes in dementia with Lewy bodies and Alzheimer's disease

BACKGROUND

Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) are common forms of dementia, yet diagnosis is often difficult. Diffusion tensor imaging (DTI) is an MR technique used to assess neuronal microstructural integrity that may help develop a better understanding of the differences between the conditions.

METHODS

We recruited subjects with DLB (n = 35), AD (n = 36), and similar aged healthy controls (n = 35). T1 weighted anatomical and diffusion MR images were acquired at 3 Tesla. Region of interest (ROI) analysis was used to measure fractional anisotropy (FA) and mean diffusivity (MD) in five structures: precuneus, thalamus, pons, midbrain, and amygdala. Where appropriate diffusivity measures (FA, MD) were correlated with selected clinical measures.

RESULTS

Compared to controls, DLB subjects were characterized by reduced FA (p = 0.016) and increased MD (p = 0.007) in the precuneus. Amygdala diffusivity was positively correlated with UPDRS-III score in DLB (p = 0.003). In AD, reduced FA in the precuneus was also observed compared to controls (p = 0.026), and was associated with impaired global cognition (MMSE score) (p = 0.03).

CONCLUSIONS

Our findings highlight the potential importance of the precuneus in the pathogenesis of DLB as well as AD. Diffusion tensor MRI may shed new light on the different neurobiological changes underpinning the key clinical features of DLB and AD.

Diffusion tensor imaging in parkinsonian syndromes: a systematic review and meta-analysis

OBJECTIVES

We performed a systematic review to assess alterations in measures of diffusion tensor imaging (DTI) in parkinsonian syndromes, exploring the potential role of DTI in diagnosis and as a candidate biomarker.

METHODS

We searched EMBASE and Medline databases for DTI studies comparing parkinsonian syndromes or related dementias with controls or another defined parkinsonian syndrome. Key details for each study regarding participants, imaging methods, and results were extracted. Estimates were pooled, where appropriate, by random-effects meta-analysis.

RESULTS

Of 333 results, we identified 43 studies suitable for inclusion (958 patients, 764 controls). DTI measures detected alterations in all parkinsonian syndromes, with distribution varying differentially with disease type. Nine studies were included in a meta-analysis of the substantia nigra in Parkinson disease. A notable effect size was found for lowered fractional anisotropy in the substantia nigra for patients with Parkinson disease vs controls (-0.639, 95% confidence interval -0.860 to -0.417, p < 0.0001).

CONCLUSION

DTI may be a promising biomarker in parkinsonian syndromes and have a future role in differential diagnosis. Larger cohort studies are required to investigate some encouraging preliminary findings. Given the complexity of the parkinsonian syndromes, it is likely that any potential DTI biomarker would be used in combination with other relevant biomarkers.

Magnetic resonance imaging: a biomarker for cognitive impairment in Parkinson's disease?

Dementia is a frequent and disabling complication of Parkinson's disease (PD). Clinicians and researchers lack a biomarker capable of tracking the structural and functional changes that underlie the evolution of cognitive dysfunction in PD. Magnetic resonance imaging (MRI) has been adopted as a biomarker in natural history and interventional studies of Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI), but its utility as a biomarker for PD and Parkinson's disease dementia (PDD) is unclear. In this review, the authors summarize the studies that have used MRI to investigate cognitive decline in PD, outline limitations of those studies, and suggest directions for future research. PD dementia is associated with extensive cortical atrophy, which may be quantified with structural MRI. More promisingly, patterns of atrophy may be present in those who have PD with MCI (PD-MCI). Subcortical white matter tract degeneration is detectable early in the disease with diffusion tensor imaging and may precede changes observed on conventional structural MRI. Although less well studied, other MR techniques, such as functional MRI, MR perfusion imaging with arterial spin labeling, and MR spectroscopy, have demonstrated differences in activation and metabolism between PD and PDD. In this review, the ability to compare studies was limited by the heterogeneity of study populations, cognitive testing methods, and imaging protocols. Future work should adopt agreed scan protocols, should be adequately powered, and should use carefully phenotyped patients to fully maximize the contribution of MRI as a biomarker for PDD.

Magnetic resonance spectroscopy in common dementias

Neurodegenerative dementias are characterized by elevated myoinositol and decreased N-acetylaspartate (NAA) levels. The increase in myoinositol seems to precede decreasing NAA levels in Alzheimer's diseases. NAA/myo-inositol ratio in the posterior cingulate gyri decreases with increasing burden of Alzheimer's disease pathologic conditions. Proton magnetic resonance spectroscopy ((1)H MRS) is sensitive to the pathophysiologic processes associated with the risk of dementia in patients with mild cognitive impairment. Although significant progress has been made in improving the acquisition and analysis techniques in (1)H MRS, translation of these technical developments to clinical practice have not been effective because of the lack of standardization for multisite applications and normative data and an insufficient understanding of the pathologic basis of (1)H MRS metabolite changes.

Default network is not hypoactive in dementia with fluctuating cognition: an Alzheimer disease/dementia with Lewy bodies comparison

Default mode network resting state activity in posterior cingulate cortex is abnormally reduced in Alzheimer disease (AD) patients. Fluctuating cognition and electroencephalogram abnormalities are established core and supportive elements respectively for the diagnosis of dementia with Lewy bodies (DLB). Our aim was to assess whether patients with DLB with both of these features have different default mode network patterns during resting state functional magnetic resonance imaging compared with AD. Eighteen patients with DLB, 18 AD patients without fluctuating cognition, and 15 control subjects were selected after appropriate matching and followed for 2-5 years to confirm diagnosis. Independent component analysis with functional connectivity (FC) and Granger causality approaches were applied to isolate and characterize resting state networks. FC was reduced in AD and DLB patients compared with control subjects. Posterior cingulate cortex activity was lower in AD than in control subjects and DLB patients (p < 0.05). Right hemisphere FC was reduced in DLB patients in comparison with control subjects but not in patients with AD, and was correlated with severity of fluctuations (ρ = -0.69; p < 0.01). Causal flow analysis showed differences between patients with DLB and AD and control subjects.

Neuroimaging in dementia

As treatment of neurodegenerative disease moves toward therapies aimed at specific molecular abnormalities, the importance of early and accurate diagnosis will increase, as will the need for sensitive measures for tracking disease progression. Brain imaging, using MRI and PET scanning, offers a variety of highly reliable techniques that examine the structure, chemical content, metabolic state, and functional capacity of the brain. For all the major neurodegenerative disorders, relatively specific findings can be identified with some or all of these techniques. New approaches for imaging specific molecular pathology likely will revolutionize brain imaging and be combined with established imaging approaches to obtain a complete molecular, structural, and metabolic characterization, which could be used to improve diagnosis, and to stage each patient and follow disease progression and response to treatment.

Characterizing dementia with Lewy bodies by means of diffusion tensor imaging

OBJECTIVE

To investigate patterns of in vivo white matter tract change using diffusion tensor imaging (DTI), we conducted a cross-sectional study of dementia with Lewy bodies (DLB) in comparison with Alzheimer disease (AD) and normal aging.

METHODS

The study included 106 subjects (35 with DLB, 36 with AD, and 35 elderly controls) who underwent clinical and neuropsychological assessment and diffusion tensor MRI. We used tract-based spatial statistics to investigate patterns of reduced fractional anisotropy (FA) and increased mean diffusivity (MD) across the entire white matter tract skeleton and also investigated correlations with clinical features.

RESULTS

Areas of reduced FA in subjects with DLB vs controls were found primarily in parieto-occipital white matter tracts; in AD, the changes were much more diffuse. DLB was also associated with reduced FA in the pons and left thalamus, in comparison with AD. The pattern of MD increase was diffuse in AD and DLB. We found an association between DTI parameters and impaired episodic memory, letter fluency, and severity of motor parkinsonism in DLB.

CONCLUSIONS

Despite a similar level of dementia severity, patterns of DTI changes in AD and DLB differed significantly. The selective involvement of the visual association areas and subcortical structures and the significant clinical correlations highlight the potential importance of white matter tract change in the pathogenesis of DLB. DTI may be a useful technique to investigate early and possible preclinical changes in DLB and warrants further investigation.

Differentiating dementia with Lewy bodies and Alzheimer’s disease using MRI

SUMMARY Despite the characteristic clinical differences between dementia with Lewy bodies (DLB) and Alzheimer’s disease (AD), a large degree of overlap exists. In particular, the clinical diagnostic criteria for DLB lack sensitivity so that many cases of DLB will be missed during life. MRI techniques offer a noninvasive method to assess the brain structure and function in more detail. In particular, advanced MRI methods such as diffusion-tensor imaging, functional MRI, arterial spin labeling (perfusion) and magnetic resonance spectroscopy may offer more sensitive methods to detect early and, possibly, preclinical change in dementia and contribute to our understanding of the differences between AD and DLB. This paper provides an overview of MRI changes in DLB and AD, the relationship to other imaging modalities such as single-photon emission computed tomography and PET, highlighting the differences between the conditions currently applicable to the clinical setting, as well as recent developments in MRI methods yet to be translated into large-scale clinical studies.

Neuroimaging of dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is a relative newcomer to the field of late-life dementia. Although a diversity of imaging methodologies is now available for the study of dementia, these have been applied most often to Alzheimer's disease (AD). Studies on DLB, although fewer, have yielded fascinating and important insights into the underlying pathophysiology of this condition and allowed clinical differentiation of DLB from other dementias. Imaging research on DLB has had significant ramifications in terms of raising the profile of DLB and helping define it as a distinctive and separate disease entity from AD.

DTI analyses and clinical applications in Alzheimer's disease

DTI is one of the most effective MR tools for the investigation of the brain anatomy. In addition to the gray matter, histopathological studies indicate that white matter is also a good target for both the early diagnosis of AD and for monitoring disease progression, which motivates us to use DTI to study AD patients in vivo. There are already a large amount of studies reporting significant differences between AD patients and controls, as well as to predict progression of disease in symptomatic non-demented individuals. Application of these findings in clinical practice remains to be demonstrated.

Neuroimaging in the early diagnosis of neurodegenerative disease

Functional imaging may be useful for both the early diagnosis as well as preclinical detection of neurodegenerative disease. Additionally, while structural imaging has traditionally been regarded as a tool to exclude alternate diagnoses, recent advances in magnetic resonance show promise for greater diagnostic specificity. The role of MR and radionuclide imaging in early diagnosis and preclinical detection of dementia and parkinsonism are reviewed here.

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.

White matter changes in dementia with Lewy bodies and Alzheimer's disease: a tractography-based study

Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) are different types of dementia. However, their clinical symptoms partially overlap and differential diagnosis is occasionally difficult. There is need for additional diagnostic criteria to reliably differentiate between these two conditions. Meanwhile, several imaging studies have showed inconsistent results between DLB and AD. The aim of this study was to use a tractography-based analysis to elucidate white matter alterations in subjects with DLB compared to those with AD and to controls. An understanding of the white matter connectivity differences between AD, DLB and controls will be helpful for differential diagnosis and an understanding of the pathophysiology. Twenty-six subjects with DLB, 26 with AD and 26 controls underwent magnetic resonance diffusion tensor imaging and neuropsychological assessment. Diffusion tensors were computed and fiber-tract maps were created using "dTV II" software. We measured mean fractional anisotropy (FA) values along the uncinate fasciculus (UNC), the inferior occipitofrontal fasciculus (IOFF) and the inferior longitudinal fasciculus (ILF). Both subjects with DLB and AD had lower FA values for the bilateral UNC than controls. Subjects with DLB exhibited significantly lower FA values on both sides of the IOFF and the left side of the ILF than those of controls. Although there were no significant differences between subjects with DLB and AD for any measurements, those with DLB exhibited lower FA values especially in visual-related white matter. These different changes in white matter tracts among groups could be helpful for differential diagnosis and an understanding of the pathophysiology.

Bridging molecular genetics and biomarkers in lewy body and related disorders

Recent advances have been made in defining the genetic and molecular basis of dementia with Lewy bodies (DLBs) and related neurodegenerative disorders such as Parkinson's disease (PD) and Parkinson's disease dementia (PDD) which comprise the spectrum of “Lewy body disorders” (LBDs). The genetic alterations and underlying disease mechanisms in the LBD overlap substantially, suggesting common disease mechanisms. As with the other neurodegenerative dementias, early diagnosis in LBD or even identification prior to symptom onset is key to developing effective therapeutic strategies, but this is dependent upon the development of robust, specific, and sensitive biomarkers as diagnostic tools and therapeutic endpoints. Recently identified mutations in the synucleins and other relevant genes in PD and DLB as well as related biomolecular pathways suggest candidate markers from biological fluids and imaging modalities that reflect the underlying disease mechanisms. In this context, several promising biomarkers for the LBD have already been identified and examined, while other intriguing possible candidates have recently emerged. Challenges remain in defining their correlation with pathological processes and their ability to detect DLB and related disorders, and perhaps a combined array of biomarkers may be needed to distinguish various LBDs.

Neuroimaging and cognition in Parkinson's disease dementia

The prevalence of cognitive impairment and dementia in Parkinson's disease (PD) is high and can potentially occur as the result of multiple differing pathologies. Neuroimaging has provided evidence of decreased cortical volume, increased white matter diffusion changes, and decreased resting metabolic activity that appears to begin prior to the onset of dementia in PD patients. Cognitive impairment has been found to be associated with multiple neurotransmitter transmission deficiencies, including dopamine and acetylcholine, indicating a widespread neurotransmitter dysfunction in PD-related dementia. Findings of increased Pittsburgh Compound B (PiB) binding in subjects with Lewy Body Disease (LBD) compared with Parkinson's disease and dementia (PDD) may explain phenotype differences in the spectrum of Dementia with Lewy Bodies (DLB), and show promise in guiding future therapeutic trials aimed at this disease. Advances in neuroimaging now allow for the detection of volumetric, pharmacologic, and pathological changes that may assist in the diagnosis and prediction of cognitive impairment in Parkinson's patients so that better evaluation of disease progression and treatment can be obtained.

Neuroimaging in dementia

Dementia is a common illness with an incidence that is rising as the aged population increases. There are a number of neurodegenerative diseases that cause dementia, including Alzheimer's disease, dementia with Lewy bodies, and frontotemporal dementia, which is subdivided into the behavioral variant, the semantic variant, and nonfluent variant. Numerous other neurodegenerative illnesses have an associated dementia, including corticobasal degeneration, Creutzfeldt-Jakob disease, Huntington's disease, progressive supranuclear palsy, multiple system atrophy, Parkinson's disease dementia, and amyotrophic lateral sclerosis. Vascular dementia and AIDS dementia are secondary dementias. Diagnostic criteria have relied on a constellation of symptoms, but the definite diagnosis remains a pathologic one. As treatments become available and target specific molecular abnormalities, differentiating amongst the various primary dementias early on becomes essential. The role of imaging in dementia has traditionally been directed at ruling out treatable and reversible etiologies and not to use imaging to better understand the pathophysiology of the different dementias. Different brain imaging techniques allow the examination of the structure, biochemistry, metabolic state, and functional capacity of the brain. All of the major neurodegenerative disorders have relatively specific imaging findings that can be identified. New imaging techniques carry the hope of revolutionizing the diagnosis of neurodegenerative disease so as to obtain a complete molecular, structural, and metabolic characterization, which could be used to improve diagnosis and to stage each patient and follow disease progression and response to treatment. Structural and functional imaging modalities contribute to the diagnosis and understanding of the different dementias.

Measurement of gray and white matter atrophy in dementia with Lewy bodies using diffeomorphic anatomic registration through exponentiated lie algebra: A comparison with conventional voxel-based morphometry

BACKGROUND AND PURPOSE

DLB is recognized as the second major form of dementia in the elderly. The regional pattern of GM atrophy in DLB highly overlaps that in AD. The aim of this study was to identify the critical pattern of atrophy in DLB by using DARTEL, which provides improved registration accuracy compared with that of conventional VBM.

MATERIALS AND METHODS

We evaluated 51 patients with probable AD, 43 patients with probable DLB, and 40 age-matched healthy controls. The pattern of GM atrophy in each group was compared by using conventional VBM and VBM-DARTEL.

RESULTS

Regional patterns of atrophy identified by using conventional VBM differed significantly from those identified by using VBM-DARTEL. A decrease in GM volume in the MTLs in both AD and DLB was identified with VBM-DARTEL; the decrease was greater in patients with AD than in those with DLB. Comparisons with healthy controls revealed that the WM volume of the whole brain was preserved in patients with DLB. In contrast, a severe bilateral decrease in WM in the MTLs was detected in patients with AD.

CONCLUSIONS

VBM-DARTEL provided more accurate results, and it enabled the identification of more localized morphologic alterations than did conventional VBM. Analysis of WM preservation in DLB could help to differentiate this condition from AD.

A meta-analysis of diffusion tensor imaging in mild cognitive impairment and Alzheimer's disease

We reviewed case-control studies of diffusion tensor imaging (DTI) in patients with Alzheimer's dementia (AD) and mild cognitive impairment (MCI), in order to establish the relative severity and location of white matter microstructural changes. EMBASE and MEDLINE were searched using the keywords, (["diffusion tensor"] and ["Alzheimer*" or "mild cognitive impairment"]), as were reference lists of relevant papers. Forty-one diffusion tensor imaging studies contained data that were suitable for inclusion. Group means and standard deviations for fractional anisotropy and mean diffusivity, or p values from 2-sample tests, were extracted and pooled, using standard methods of meta-analysis and metaregression. Fractional anisotropy was decreased in AD in all regions except parietal white matter and internal capsule, while patients with MCI had lower values in all white matter regions except parietally and occipitally. Mean diffusivity was increased in AD in all regions, and in MCI in all but occipital and frontal regions.

Dementia with Lewy bodies and Alzheimer disease: neurodegenerative patterns characterized by DTI

OBJECTIVE

To identify the patterns of diffusivity changes in patients with dementia with Lewy bodies (DLB) and Alzheimer disease (AD) and to determine whether diffusion tensor MRI (DTI) is complementary to structural MRI in depicting the tissue abnormalities characteristic of DLB and AD.

METHODS

We studied clinically diagnosed age-, gender-, and education-matched subjects with DLB (n = 30), subjects with AD (n = 30), and cognitively normal (CN) subjects (n = 60) in a case-control study. DTI was performed at 3T with a fluid-attenuated inversion recovery-based DTI sequence that enabled cortical diffusion measurements. Mean diffusivity (MD) and gray matter (GM) density were measured from segmented cortical regions. Tract-based diffusivity was measured using color-coded fractional anisotropy (FA) maps.

RESULTS

Patients with DLB were characterized by elevated MD in the amygdala and decreased FA in the inferior longitudinal fasciculus (ILF). ILF diffusivity was associated with the presence of visual hallucinations (p = 0.007), and amygdala diffusivity was associated with Unified Parkinson's Disease Rating Scale (r = 0.50; p = 0.005) in DLB. In contrast, patients with AD were characterized by elevated MD in the medial temporal, temporal, and parietal lobe association cortices and decreased FA in the fornix, cingulum, and ILF. Amygdala diffusivity was complementary to GM density in discriminating DLB from CN; hippocampal and parahippocampal diffusivity was complementary to GM density in discriminating AD from CN.

CONCLUSION

Increased amygdalar diffusivity in the absence of tissue loss in dementia with Lewy bodies (DLB) may be related to microvacuolation, a common pathology associated with Lewy body disease in the amygdala. Diffusivity measurements were complementary to structural MRI, demonstrating that measures of diffusivity on diffusion tensor MRI are valuable tools for characterizing the tissue abnormalities characteristic of Alzheimer disease and DLB.

Smoothing that does not blur: effects of the anisotropic approach for evaluating diffusion tensor imaging data in the clinic

PURPOSE

To compare the effects of anisotropic and Gaussian smoothing on the outcomes of diffusion tensor imaging (DTI) voxel-based (VB) analyses in the clinic, in terms of signal-to-noise ratio (SNR) enhancement and directional information and boundary structures preservation.

MATERIALS AND METHODS

DTI data of 30 Alzheimer's disease (AD) patients and 30 matched control subjects were obtained at 3T. Fractional anisotropy (FA) maps with variable degrees and quality (Gaussian and anisotropic) of smoothing were created and compared with an unsmoothed dataset. The two smoothing approaches were evaluated in terms of SNR improvements, capability to separate differential effects between patients and controls by a standard VB analysis, and level of artifacts introduced by the preprocessing.

RESULTS

Gaussian smoothing regionally biased the FA values and introduced a high variability of results in clinical analysis, greatly dependent on the kernel size. On the contrary, anisotropic smoothing proved itself capable of enhancing the SNR of images and maintaining boundary structures, with only moderate dependence of results on smoothing parameters.

CONCLUSION

Our study suggests that anisotropic smoothing is more suitable in DTI studies; however, regardless of technique, a moderate level of smoothing seems to be preferable considering the artifacts introduced by this manipulation.

Neuroimaging for Lewy body disease: is the in vivo molecular imaging of α-synuclein neuropathology required and feasible?

Alpha-synuclein aggregation is a neuropathological hallmark of many neurodegenerative diseases including Parkinson's disease (PD), Parkinson's disease with dementia (PDD) and dementia with Lewy bodies (DLB), collectively termed the α-synucleinopathies. Substantial advances in clinical criteria and neuroimaging technology over the last 20 years have allowed great strides in the detection and differential diagnosis of these disorders. Nevertheless, it is clear that whilst the array of different imaging modalities in clinical use allow for a robust diagnosis of α-synucleinopathy in comparison to healthy subjects, there is no clear diagnostic imaging marker that affords a reliable differential diagnosis between the different forms of Lewy body disease (LBD) or that could facilitate tracking of disease progression. This has led to a call for a biomarker based on the pathological hallmarks of these diseases, namely α-synuclein-positive Lewy bodies (LBs). This potentially may be advantageous in terms of early disease detection, but may also be leveraged into a potential marker of disease progression. We here aim to firstly review the current status of neuroimaging biomarkers in PD and related synucleinopathies. Secondly, we outline the rationale behind α-synuclein imaging as a potential novel biomarker as well as the potential benefits and limitations of this approach. Thirdly, we attempt to illustrate the likely technical hurdles to be overcome to permit successful in vivo imaging of α-synuclein pathology in the diseased brain. Our overriding aim is to provide a framework for discussion of how to address this major unmet clinical need.

Imaging improves diagnosis of dementia with lewy bodies

Dementia with Lewy bodies (DLB) is the second most common cause of degenerative dementia after Alzheimer's disease (AD), and is clinically characterized by the progressive cognitive decline with fluctuations in cognition and alertness, recurrent visual hallucinations and Parkinsonism. Once these characteristic symptoms of DLB emerge, discriminating it from AD is relatively easy. However, in the early disease stages, the clinical symptoms of various types of dementias largely overlap and it is difficult to distinguish DLB from other neurodegenerative dementias based on clinical manifestations alone. To increase the accuracy of antemortem diagnosis of DLB, the latest diagnostic criteria incorporate findings from 123I-metaiodobenzylguanidine (MIBG) myocardial scintigraphy, or from neuroimaging such as computed tomography (CT), magnetic resonance imaging (MRI), single photon emission computed tomography (SPECT), and positron emission tomography (PET). In the present guidelines, decreased dopamine transporter uptake revealed by SPECT or PET receives the greatest importance among various neuroimaging findings and is listed as one of the suggestive features. Supportive features that commonly present but are not proven to have diagnostic specificity include relatively-preserved medial-temporal-lobe structures, occipital hypoperfusion, and abnormal MIBG myocardial scintigraphy. In this paper, we review the major findings on various neuroimaging modalities and discuss the clinical usefulness of them for the diagnosis of DLB. Although there is not enough evidence to reach the conclusion, considering the accessibility in clinical practice, in our personal views, we recommend the use of brain-perfusion SPECT and MIBG myocardial scintigraphy to improve the diagnosis of DLB.

Triple-transgenic Alzheimer's disease mice exhibit region-specific abnormalities in brain myelination patterns prior to appearance of amyloid and tau pathology

Alzheimer's disease (AD) is a progressively debilitating brain disorder pathologically defined by extracellular amyloid plaques, intraneuronal neurofibrillary tangles, and synaptic disintegrity. AD has not been widely considered a disease of white matter, but more recent evidence suggests the existence of abnormalities in myelination patterns and myelin attrition in AD-afflicted human brains. Herein, we demonstrate that triple-transgenic AD (3xTg-AD) mice, which harbor the human amyloid precursor protein Swedish mutant transgene, presenilin knock-in mutation, and tau P301L mutant transgene, exhibit significant region-specific alterations in myelination patterns and in oligodendrocyte marker expression profiles at time points preceding the appearance of amyloid and tau pathology. These immunohistochemical signatures are coincident with age-related alterations in axonal and myelin sheath ultrastructure as visualized by comparative electron microscopic examination of 3xTg-AD and nontransgenic mouse brain tissue. Overall, these findings indicate that 3xTg-AD mice represent a viable model in which to examine mechanisms underlying AD-related myelination and neural transmission defects that occur early during presymptomatic stages of the disease process.

Degeneration of dementia with Lewy bodies measured by diffusion tensor imaging

Dementia with Lewy bodies (DLB) is the second most common form of dementia. It is thought to involve impairment of the visual association area. In this study, we applied diffusion tensor imaging (DTI) to examine the microstructural interruption of visual association areas in patients with DLB. The DTI metrics of three visual association fibres - the inferior longitudinal fasciculus (ILF), visual pathway, and splenial fibres - were compared between 14 patients with DLB and 13 healthy subjects. The fractional anisotropy value of the ILF was significantly lower in patients with DLB than in healthy subjects. The difference in the mean diffusivity value of ILF was at trend level. The lambda(2),(3) of ILF were significantly lower in patients with DLB; however, there was no difference in lambda(1). DTI metrics of the visual pathway and splenial fibres showed no differences between the groups. Our results showed degeneration of the ILF, which is responsible for visuospatial cognition. ILF dysfunction may influence the clinical features in DLB.

Diagnostic accuracy of 123I-FP-CIT SPECT in possible dementia with Lewy bodies

BACKGROUND

(123)I-FP-CIT SPECT (single photon emission computed tomography) can help in the differential diagnosis of probable dementia with Lewy bodies (Lewy body dementia) and Alzheimer's disease.

AIMS

Our aim was to determine the accuracy of (123)I-FP-CIT SPECT in diagnosing people with possible dementia with Lewy bodies.

METHOD

We undertook a 12-month follow-up of 325 individuals with probable or possible Lewy body or non-Lewy body dementia who had previously undergone (123)I-FP-CIT SPECT. A consensus panel, masked to SPECT findings, established diagnosis at 12 months in 264 people.

RESULTS

Of 44 people with possible dementia with Lewy bodies at baseline, at follow-up the diagnosis for 19 people was probable dementia with Lewy bodies (43%), in 7 people non-Lewy body dementia (16%) and for 18 individuals it remained possible dementia with Lewy bodies (41%). Of the 19 who at follow-up were diagnosed with probable dementia with Lewy bodies, 12 had abnormal scans at baseline (sensitivity 63%); all 7 individuals with a possible diagnosis who were diagnosed as having Alzheimer's disease at follow-up had normal scans (specificity 100%).

CONCLUSIONS

Our findings confirm the diagnostic accuracy of (123)I-FP-CIT SPECT in distinguishing Lewy body from non-Lewy body dementia and also suggest a clinically useful role in diagnostically uncertain cases, as an abnormal scan in a person with possible dementia with Lewy bodies is strongly suggestive of dementia with Lewy bodies.

Imaging informatics for personalised medicine: applications and challenges

Imaging informatics has emerged as a major research theme in biomedicine in the last few decades. Currently, personalised, predictive and preventive patient care is believed to be one of the top priorities in biomedical research and practice. Imaging informatics plays a major role in biomedicine studies. This paper reviews main applications and challenges of imaging informatics in biomedicine.

Diffusion tensor imaging and tractography of the median nerve in carpal tunnel syndrome: preliminary results

The purpose was to demonstrate the feasibility of in vivo diffusion tensor imaging (DTI) and tractography of the human median nerve with a 1.5-T MR scanner and to assess potential differences in diffusion between healthy volunteers and patients suffering from carpal tunnel syndrome. The median nerve was examined in 13 patients and 13 healthy volunteers with MR DTI and tractography using a 1.5-T MRI scanner with a dedicated wrist coil. T1-weighted images were performed for anatomical correlation. Mean fractional anisotropy (FA) and mean apparent diffusion coefficient (ADC) values were quantified in the median nerve on tractography images. In all subjects, the nerve orientation and course could be detected with tractography. Mean FA values were significantly lower in patients (p=0.03). However, no statistically significant differences were found for mean ADC values. In vivo assessment of the median nerve in the carpal tunnel using DTI with tractography on a 1.5-T MRI scanner is possible. Microstructural parameters can be easily obtained from tractography images. A significant decrease of mean FA values was found in patients suffering from chronic compression of the median nerve. Further investigations are necessary to determine if mean FA values may be correlated with the severity of nerve entrapment.

Current and future uses of neuroimaging for cognitively impaired patients

Technological advances have led to greater use of both structural and functional brain imaging to assist with the diagnosis of dementia for the increasing numbers of people with cognitive decline as they age. In current clinical practice, structural imaging (CT or MRI) is used to identify space-occupying lesions and stroke. Functional methods, such as PET scanning of glucose metabolism, could be used to differentiate Alzheimer's disease from frontotemporal dementia, which helps to guide clinicians in symptomatic treatment strategies. New neuroimaging methods that are currently being developed can measure specific neurotransmitter systems, amyloid plaque and tau tangle concentrations, and neuronal integrity and connectivity. Successful co-development of neuroimaging surrogate markers and preventive treatments might eventually lead to so-called brain-check scans for determining risk of cognitive decline, so that physicians can administer disease-modifying medications, vaccines, or other interventions to avoid future cognitive losses and to delay onset of disease.