Tissue microstructural changes in dementia with Lewy bodies revealed by quantitative MRI.

We aimed to characterize dementia with Lewy bodies (DLB) by the quantitative MRI parameters of longitudinal relaxation time (qT1) and transverse relaxation time (qT2). These parameters reflect potential pathological changes in tissue microstructures, which may be detectable noninvasively in brain areas without evident atrophy, so may have potential value in revealing the early neuropathological changes in DLB. We conducted a cross-sectional study of subjects with DLB (N = 35) and similarly aged control participants (N = 35). All subjects underwent a detailed clinical and neuropsychological assessment and structural and quantitative 3T MRI. Quantitative MRI maps were obtained using relaxation time mapping methods. Statistical analysis was performed on gray matter qT1 and qT2 values. We found significant alterations of quantitative parameters in DLB compared to controls. In particular, qT1 decreases in bilateral temporal lobes, right parietal lobes, basal ganglia including left putamen, left caudate nucleus and left amygdala, and left hippocampus/parahippocampus; qT2 decreases in left putamen and increases in left precuneus. These regions showed only partial overlap with areas where grey matter loss was found, making atrophy an unlikely explanation for our results. Our findings support that DLB is predominantly associated with changes in posterior regions, such as visual association areas, and subcortical structures, and that qT1 and qT2 measurement can detect subtle changes not seen on structural volumetric imaging. Hence, quantitative MRI may compliment other imaging techniques in detecting early changes in DLB and in understanding neurobiological changes associated with the disorder.This is the author accepted manuscript. The final version is available from Springer via http://dx.doi.org/10.1007/s00415-014-7541-

The role of neuroimaging in the diagnosis of the atypical parkinsonian syndromes in clinical practice

Atypical parkinsonian disorders (APD) are a heterogenous group of neurodegenerative diseases such as: progressive supranuclear palsy (PSP), multiple system atrophy (MSA), cortico-basal degeneration (CBD) and dementia with Lewy bodies (DLB). In all of them core symptoms of parkinsonian syndrome are accompanied by many additional clinical features not typical for idiopathic Parkinson's disease (PD) like rapid progression, gaze palsy, apraxia, ataxia, early cognitive decline, dysautonomia and usually poor response to levodopa therapy. In the absence of reliably validated biomarkers the diagnosis is still challenging and mainly based on clinical criteria. However, robust data emerging from routine magnetic resonance imaging (MRI) as well as from many advanced MRI techniques such as: diffusion weighted imaging (DWI) and diffusion tensor imaging (DTI), magnetic resonance spectroscopy (MRS), voxel-based morphometry (VBM), susceptibility-weighted imaging (SWI) may help in differential diagnosis. The main aim of this review is to summarize briefly the most important and acknowledged radiological findings of conventional MRI due to its availability in standard clinical settings. Nevertheless, we present shortly other methods of structural (like TCS – transcranial sonography) and functional imaging (like SPECT – single photon emission computed tomography or PET – positron emission tomography) as well as some selected advanced MRI techniques and their potential future applications in supportive role in distinguishing APD

MEG resting state functional connectivity in Parkinson's disease related dementia

Parkinson's disease (PD) related dementia (PDD) develops in up to 60% of patients, but the pathophysiology is far from being elucidated. Abnormalities of resting state functional connectivity have been reported in Alzheimer's disease (AD). The present study was performed to determine whether PDD is likewise characterized by changes in resting state functional connectivity. MEG recordings were obtained in 13 demented and 13 non-demented PD patients. The synchronization likelihood (SL) was calculated within and between cortical areas in six frequency bands. Compared to non-demented PD, PDD was characterized by lower fronto-temporal SL in the alpha range, lower intertemporal SL in delta, theta and alpha1 bands as well as decreased centro-parietal gamma band synchronization. In addition, higher parieto-occipital synchronization in the alpha2 and beta bands was found in PDD. The observed changes in functional connectivity are reminiscent of changes in AD, and may reflect reduced cholinergic activity and/or loss of cortico-cortical anatomical connections in PDD. © 2008 The Author(s)

Accuracy of MRI Classification Algorithms in a Tertiary Memory Center Clinical Routine Cohort

BACKGROUND:Automated volumetry software (AVS) has recently become widely available to neuroradiologists. MRI volumetry with AVS may support the diagnosis of dementias by identifying regional atrophy. Moreover, automatic classifiers using machine learning techniques have recently emerged as promising approaches to assist diagnosis. However, the performance of both AVS and automatic classifiers has been evaluated mostly in the artificial setting of research datasets.OBJECTIVE:Our aim was to evaluate the performance of two AVS and an automatic classifier in the clinical routine condition of a memory clinic.METHODS:We studied 239 patients with cognitive troubles from a single memory center cohort. Using clinical routine T1-weighted MRI, we evaluated the classification performance of: 1) univariate volumetry using two AVS (volBrain and Neuroreader$^{TM}$); 2) Support Vector Machine (SVM) automatic classifier, using either the AVS volumes (SVM-AVS), or whole gray matter (SVM-WGM); 3) reading by two neuroradiologists. The performance measure was the balanced diagnostic accuracy. The reference standard was consensus diagnosis by three neurologists using clinical, biological (cerebrospinal fluid) and imaging data and following international criteria.RESULTS:Univariate AVS volumetry provided only moderate accuracies (46% to 71% with hippocampal volume). The accuracy improved when using SVM-AVS classifier (52% to 85%), becoming close to that of SVM-WGM (52 to 90%). Visual classification by neuroradiologists ranged between SVM-AVS and SVM-WGM.CONCLUSION:In the routine practice of a memory clinic, the use of volumetric measures provided by AVS yields only moderate accuracy. Automatic classifiers can improve accuracy and could be a useful tool to assist diagnosis

APOE-ε4 associates with hippocampal volume, learning, and memory across the spectrum of Alzheimer's disease and dementia with Lewy bodies

Introduction Although the apolipoprotein E ε4-allele (APOE-ε4) is a susceptibility factor for Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), its relationship with imaging and cognitive measures across the AD/DLB spectrum remains unexplored. Methods We studied 298 patients (AD = 250, DLB = 48; 38 autopsy confirmed; NCT01800214) using neuropsychological testing, volumetric magnetic resonance imaging, and APOE genotyping to investigate the association of APOE-ε4 with hippocampal volume and learning/memory phenotypes, irrespective of diagnosis. Results Across the AD/DLB spectrum: (1) hippocampal volumes were smaller with increasing APOE-ε4 dosage (no genotype × diagnosis interaction observed), (2) learning performance as assessed by total recall scores was associated with hippocampal volumes only among APOE-ε4 carriers, and (3) APOE-ε4 carriers performed worse on long-delay free word recall. Discussion These findings provide evidence that APOE-ε4 is linked to hippocampal atrophy and learning/memory phenotypes across the AD/DLB spectrum, which could be useful as biomarkers of disease progression in therapeutic trials of mixed disease

What can imaging tell us about cognitive impairment and dementia?

Peer reviewedPublisher PD

Longitudinal evolution of cortical thickness signature reflecting Lewy body dementia in isolated REM sleep behavior disorder: a prospective cohort study

Background The isolated rapid-eye-movement sleep behavior disorder (iRBD) is a prodromal condition of Lewy body disease including Parkinson's disease and dementia with Lewy bodies (DLB). We aim to investigate the longitudinal evolution of DLB-related cortical thickness signature in a prospective iRBD cohort and evaluate the possible predictive value of the cortical signature index in predicting dementia-first phenoconversion in individuals with iRBD. Methods We enrolled 22 DLB patients, 44 healthy controls, and 50 video polysomnography-proven iRBD patients. Participants underwent 3-T magnetic resonance imaging (MRI) and clinical/neuropsychological evaluations. We characterized DLB-related whole-brain cortical thickness spatial covariance pattern (DLB-pattern) using scaled subprofile model of principal components analysis that best differentiated DLB patients from age-matched controls. We analyzed clinical and neuropsychological correlates of the DLB-pattern expression scores and the mean values of the whole-brain cortical thickness in DLB and iRBD patients. With repeated MRI data during the follow-up in our prospective iRBD cohort, we investigated the longitudinal evolution of the cortical thickness signature toward Lewy body dementia. Finally, we analyzed the potential predictive value of cortical thickness signature as a biomarker of phenoconversion in iRBD cohort. Results The DLB-pattern was characterized by thinning of the temporal, orbitofrontal, and insular cortices and relative preservation of the precentral and inferior parietal cortices. The DLB-pattern expression scores correlated with attentional and frontal executive dysfunction (Trail Making Test-A and B: R = − 0.55, P = 0.024 and R = − 0.56, P = 0.036, respectively) as well as visuospatial impairment (Rey-figure copy test: R = − 0.54, P = 0.0047). The longitudinal trajectory of DLB-pattern revealed an increasing pattern above the cut-off in the dementia-first phenoconverters (Pearsons correlation, R = 0.74, P = 6.8 × 10−4) but no significant change in parkinsonism-first phenoconverters (R = 0.0063, P = 0.98). The mean value of the whole-brain cortical thickness predicted phenoconversion in iRBD patients with hazard ratio of 9.33 [1.16–74.12]. The increase in DLB-pattern expression score discriminated dementia-first from parkinsonism-first phenoconversions with 88.2% accuracy. Conclusion Cortical thickness signature can effectively reflect the longitudinal evolution of Lewy body dementia in the iRBD population. Replication studies would further validate the utility of this imaging marker in iRBD

Changes in brain magnetic resonance imaging in Alzheimer's disease

Changes in brain magnetic resonance imaging in Alzheimer's disease Introduction Brain MRI is important auxiliary examination method in the diagnosis of Alzheimer's disease (AD). Mediotemporal atrophy is typical for late-onset AD. Brain atrophy can be different in patients with early-onset AD. Current visual scales for assessing brain atrophy in AD may be too complicated for routine clinical practice. Aims The main goal was to develop new, simple and reliable visual scales for the evaluation of mediotemporal and parietal atrophy on brain MRI, which will be suitable for the diagnosis of AD in routine clinical practice. Methods and patients We have developed a Parietal Atrophy Score (PAS) for the assessment of parietal atrophy, which is based on the evaluation of atrophy of 3 structures (sulcus cingularis posterior, precuneus, parietal gyri) on a sequence of coronal slices of the parietal lobe. We first used this scale to assess parietal cortex atrophy in 74 cognitively normal individuals from the Czech cohort (age range 48-87 years, MMSE 29 ± 1). The brain MRI of 25 people from this cohort were assessed by 4 evaluators with different professional experience to determine the reliability of the PAS. Parietal atrophy was compared between 24 patients with late-onset AD (MMSE 21 ± 3) and 26 cognitively normal...Změny na magnetické rezonanci mozku u Alzheimerovy nemoci Úvod MR mozku je hlavní pomocnou vyšetřovací metodou v diagnostice Alzheimerovy nemoci (AN). U AN s pozdním začátkem bývá typická mediotemporální atrofie. U vzácnější AN s časným začátkem může být atrofie mozku odlišná. Dosavadní vizuální škály pro hodnocení mozkové atrofie u AN mohou být pro běžnou klinickou praxi příliš komplikované. Cíl Hlavním cílem bylo vytvořit nové, jednoduché a spolehlivé vizuální škály pro hodnocení mediotemporální a parietální atrofie na MR mozku, které budou vhodné pro diagnostiku AN v běžné klinické praxi. Metodika a pacienti Vyvinuli jsme Parietální Atrofický Skór (PAS) pro posuzování parietální atrofie, který je založen na hodnocení atrofie 3 struktur (sulcus cingularis posterior, precuneus a parietální gyry) na sekvenci koronárních řezů parietálním lalokem. Nejprve jsme tuto škálu využili k posouzení atrofie parietální kůry u 74 kognitivně normálních osob z české kohorty (věkové rozmezí 48-87 let, MMSE 29 ± 1). 4 hodnotitelé s odlišnými profesními zkušenostmi posuzovali MR mozků 25 osob z této kohorty ke stanovení reliability PAS. Následně jsme porovnali parietální atrofii pomocí PAS mezi 24 pacienty s AN s pozdním začátkem (MMSE 2 1 ± 3) a 26 kognitivně normálními jedinci (MMSE 29 ± 1) z české kohorty. Škálu...Department of Neurology 3FM CU and UHKVNeurologická klinika 3. LF UK a FNKV3. lékařská fakultaThird Faculty of Medicin