Lichte Cognitieve Stoornissen (MCI): Prodromen van dementie?

Mild cognitive impairment: a prodromal phase of dementia? Cognitive decline without dementia is common among older persons. A variety of clinical concepts have been introduced in the past 30 years, in order to describe these cognitive deficits arising in older persons. The most frequently used concept is Mild Cognitive Impairment (MCI). MCI is generally seen as a prodromal phase of Alzheimer disease (AD). Several concepts are described, with the neuropsychiatric features and predictors of conversion to dementia c.q. AD. Finally, consequences of preclinically diagnoses for health care are clarified. Tijdschr Gerontol Geriatr 2007; 38:115-121     

Combined Metaheuristic Algorithm and Radiomics Strategy for the Analysis of Neuroanatomical Structures in Schizophrenia and Schizoaffective Disorders

ObjectivesSchizophrenia (SZ) is the most chronic disabling psychotic brain disorder. It is characterized by delusions and auditory hallucinations, as well as impairments in memory. Schizoaffective (SA) signs are co-morbid with SZ and are characterized by symptoms of SZ and mood disorder. Various researches suggest that SZ and SA share a number of equally severe cognitive deficits, but the pathophysiology has not yet been addressed in a comprehensive way. In this work, the heterogeneity in whole brain, ventricle and cerebellum region from psychotic MR brain images is examined using Machine learning and radiomic features.Materials and methodsT1 weighted MR brain images are obtained from Schizconnect database for the analysis. The shape prior level set method is used to segment the ventricle and cerebellum structures. The radiomic features which include shape and texture are extracted from these regions to discriminate the SZ and SA subjects. The performance of these features is evaluated with Binary Particle Swarm Optimization (BPSO) based Fuzzy Support Vector Machine (FSVM) classifier.ResultsThe shape constrained Level Set method is able to better segment ventricles and cerebellum regions from the images. The significant features that are extracted from whole brain, ventricle and cerebellum are identified by the BPSO based FSVM. The combination of radiomic features extracted from cerebellum region achieved high classification accuracy (90.09%) using metaheuristic algorithm. The extracted features from cerebellum are correlated with PANSS score. The causal analysis shows that there is an association been the tissue texture variation in identifying the disease severity. The symmetry analysis shows that left brain mean area is larger than the right side area. In particular SA has low cerebellum area compared to SZ. The radiomic features such as Hermite, Laws and tensor extracted from the left cerebellum show a significant texture variation in all the considered subjects (p<0.0001).ConclusionsThe results are clinically relevant in discriminating the pattern change in the structure, hence this biomarker and frame work could be used for the severity study of psychotic disorders.     

基于体素的形态测量学在阿尔茨海默病及轻度认知功能障碍研究中的应用

阿尔茨海默病(Alzheimer's disease,AD)是发生于老年和老年前期、以进行性认知功能障碍和行为异常为特征的中枢神经系统退行性疾病,是老年痴呆中最常见类型。轻度认知功能障碍(mild cognitive impairment,MCI)是介于正常衰老和痴呆之间的一种中间状态,指有轻度的记忆或认知损伤,但尚未达到痴呆程度的一种状态,日常生活和社会功能不受影响,其中很大一部分患者最终进展为AD。临床诊断AD患者多已达中晚期,为了能早期诊断AD及预测MCI的转归,有关AD的生物学标注物的研究成为近年来的科研热点。AD患者颅脑的大体病理特征为脑萎缩,其萎缩有别于正常老龄化所致的退行性改变,有其自身特点,这种特定形式的萎缩有可能成为AD早期诊断的生物学标志物。基于体素的形态测量学(voxel-based morphometry,VBM)是一种基于像素水平对脑核磁图像进行自动、全面、客观分析的技术,可以定量分析全脑结构、刻画出局部脑区结构特征,是一种较好的脑形态分析工具,广泛用于阿尔茨海默病及轻度认知功能障碍的研究中,本文综述了近年来其研究进展,期望为临床及科研提供参考。     

Predicting Progression from Mild Cognitive Impairment to Alzheimer's Dementia Using Clinical,MRI, and Plasma Biomarkers via Probabilistic Pattern Classification

Background

Individuals with mild cognitive impairment (MCI) have a substantially increased risk of developing dementia due to Alzheimer''s disease (AD). In this study, we developed a multivariate prognostic model for predicting MCI-to-dementia progression at the individual patient level.

Methods

Using baseline data from 259 MCI patients and a probabilistic, kernel-based pattern classification approach, we trained a classifier to distinguish between patients who progressed to AD-type dementia (n = 139) and those who did not (n = 120) during a three-year follow-up period. More than 750 variables across four data sources were considered as potential predictors of progression. These data sources included risk factors, cognitive and functional assessments, structural magnetic resonance imaging (MRI) data, and plasma proteomic data. Predictive utility was assessed using a rigorous cross-validation framework.

Results

Cognitive and functional markers were most predictive of progression, while plasma proteomic markers had limited predictive utility. The best performing model incorporated a combination of cognitive/functional markers and morphometric MRI measures and predicted progression with 80% accuracy (83% sensitivity, 76% specificity, AUC = 0.87). Predictors of progression included scores on the Alzheimer''s Disease Assessment Scale, Rey Auditory Verbal Learning Test, and Functional Activities Questionnaire, as well as volume/cortical thickness of three brain regions (left hippocampus, middle temporal gyrus, and inferior parietal cortex). Calibration analysis revealed that the model is capable of generating probabilistic predictions that reliably reflect the actual risk of progression. Finally, we found that the predictive accuracy of the model varied with patient demographic, genetic, and clinical characteristics and could be further improved by taking into account the confidence of the predictions.

Conclusions

We developed an accurate prognostic model for predicting MCI-to-dementia progression over a three-year period. The model utilizes widely available, cost-effective, non-invasive markers and can be used to improve patient selection in clinical trials and identify high-risk MCI patients for early treatment.     

Cognitive dysfunction in rapid eye movement sleep behavior disorder

Cognitive impairment is a frequent feature of rapid eye movement sleep behavior disorder (RBD). The cognitive profile of RBD patients is heterogeneous, with impairments in attention, executive functions, episodic memory, and visuospatial abilities. Moreover, over 50% of RBD patients meet the diagnostic criteria for mild cognitive impairment (MCI). Although a comprehensive neuropsychological assessment remains the most sensitive way to detect MCI, three cognitive screening tests have been validated in RBD. The Montreal Cognitive Assessment was found to be the most appropriate screening test for detecting MCI in RBD. In addition RBD in Parkinson’s disease may be a risk factor for MCI and dementia.

     

Déficit cognitif léger : mythe ou réalité ?

The concept of mild cognitive impairment, MCI, has been proposed by Petersen and described like a state between the cognitive changes of normal aging and very early dementia. However, MCI appears to be a heterogeneous clinical syndrome in term of etiological factors, clinical patterns or clinical course. New criteria of MCI are proposed for use in clinical research. Identification of patients at risk for Alzheimer disease, AD, is an important goal. Ongoing clinical and neuroimaging (magnetic resonance imaging (MRI), single photon emission computed tomography (SPECT),¹⁸F flouorodeoxyglucose-photo emission tomography (FDG-PET)) studies are focusing on the identification of those individuals with mild cognitive impairment (MCI) who are most likely to convert to AD.     

Effects of Baseline CSF α-Synuclein on Regional Brain Atrophy Rates in Healthy Elders,Mild Cognitive Impairment and Alzheimer’s Disease

Background

Cerebrospinal fluid (CSF) α-synuclein is reduced in synucleinopathies, including dementia with Lewy bodies, and some studies have found increased CSF α-synuclein in Alzheimer’s disease (AD). No study has explored effects of CSF α-synuclein on brain atrophy. Here we tested if baseline CSF α-synuclein affects brain atrophy rates and if these effects vary across brain regions, and across the cognitive spectrum from healthy elders (NL), to patients with mild cognitive impairment (MCI) and AD.

Methods

Baseline CSF α-synuclein measurements and longitudinal structural brain magnetic resonance imaging was performed in 74 NL, 118 MCI patients and 55 AD patients. Effects of baseline CSF α-synuclein on regional atrophy rates were tested in 1) four pre-hoc defined regions possibly associated with Lewy body and/or AD pathology (amygdala, caudate, hippocampus, brainstem), and 2) all available regions of interest. Differences across diagnoses were tested by assessing the interaction of CSF α-synuclein and diagnosis (testing NL versus MCI, and NL versus AD).

Results

The effects of CSF α-synuclein on longitudinal atrophy rates were not significant after correction for multiple comparisons. There were tendencies for effects in AD in caudate (higher atrophy rates in subjects with higher CSF α-synuclein, P=0.046) and brainstem (higher atrophy rates in subjects with lower CSF α-synuclein, P=0.063). CSF α-synuclein had significantly different effects on atrophy rates in NL and AD in brainstem (P=0.037) and caudate (P=0.006). Discussion: With the possible exception of caudate and brainstem, the overall weak effects of CSF α-synuclein on atrophy rates in NL, MCI and AD argues against CSF α-synuclein as a biomarker related to longitudinal brain atrophy in these diagnostic groups. Any effects of CSF α-synuclein may be attenuated by possible simultaneous occurrence of AD-related neuronal injury and concomitant Lewy body pathology, which may elevate and reduce CSF α-synuclein levels, respectively.     

Proteomic identification of nitrated brain proteins in amnestic mild cognitive impairment: a regional study

Oxidative stress is an imbalance between the level of antioxidants and oxidants in a cell. Oxidative stress has been shown in brain of subjects with mild cognitive impairment (MCI) as well Alzheimer's disease (AD). MCI is considered as a transition phase between control and AD. The focus of the current study was to identify nitrated proteins in the hippocampus and inferior parietal lobule (IPL) brain regions of subjects with amnestic MCI using proteomics. The identified nitrated proteins in MCI brain were compared to those previously reported to be nitrated and oxidatively modified in AD brain, a comparison that might provide an invaluable insight into the progression of the disease.     

Measuring breathing induced oesophageal motion and its dosimetric impact

Purpose: Stereotactic body radiation therapy allows for a precise dose delivery. Organ motion bears the risk of undetected high dose healthy tissue exposure. An organ very susceptible to high dose is the oesophagus. Its low contrast on CT and the oblong shape render motion estimation difficult. We tackle this issue by modern algorithms to measure oesophageal motion voxel-wise and estimate motion related dosimetric impacts.Methods: Oesophageal motion was measured using deformable image registration and 4DCT of 11 internal and 5 public datasets. Current clinical practice of contouring the organ on 3DCT was compared to timely resolved 4DCT contours. Dosimetric impacts of the motion were estimated by analysing the trajectory of each voxel in the 4D dose distribution. Finally an organ motion model for patient-wise comparisons was built.Results: Motion analysis showed mean absolute maximal motion amplitudes of 4.55 $\pm$ 1.81 mm left-right, 5.29 $\pm$ 2.67 mm anterior-posterior and 10.78 $\pm$ 5.30 mm superior-inferior. Motion between cohorts differed significantly. In around 50% of the cases the dosimetric passing criteria was violated. Contours created on 3DCT did not cover 14% of the organ for 50% of the respiratory cycle and were around 38% smaller than the union of all 4D contours. The motion model revealed that the maximal motion is not limited to the lower part of the organ. Our results showed motion amplitudes higher than most reported values in the literature and that motion is very heterogeneous across patients.Conclusions: Individual motion information should be considered in contouring and planning.