Spatiotemporal analysis of multichannel EEG: CARTOOL.

This paper describes methods to analyze the brain's electric fields recorded with multichannel Electroencephalogram (EEG) and demonstrates their implementation in the software CARTOOL. It focuses on the analysis of the spatial properties of these fields and on quantitative assessment of changes of field topographies across time, experimental conditions, or populations. Topographic analyses are advantageous because they are reference independents and thus render statistically unambiguous results. Neurophysiologically, differences in topography directly indicate changes in the configuration of the active neuronal sources in the brain. We describe global measures of field strength and field similarities, temporal segmentation based on topographic variations, topographic analysis in the frequency domain, topographic statistical analysis, and source imaging based on distributed inverse solutions. All analysis methods are implemented in a freely available academic software package called CARTOOL. Besides providing these analysis tools, CARTOOL is particularly designed to visualize the data and the analysis results using 3-dimensional display routines that allow rapid manipulation and animation of 3D images. CARTOOL therefore is a helpful tool for researchers as well as for clinicians to interpret multichannel EEG and evoked potentials in a global, comprehensive, and unambiguous way.

An active contour-based atlas registration model applied to automatic subthalamic nucleus targeting on MRI: method and validation.

This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.

Nonlinear analysis of human physical activity patterns in health and disease.

The reliable and objective assessment of chronic disease state has been and still is a very significant challenge in clinical medicine. An essential feature of human behavior related to the health status, the functional capacity, and the quality of life is the physical activity during daily life. A common way to assess physical activity is to measure the quantity of body movement. Since human activity is controlled by various factors both extrinsic and intrinsic to the body, quantitative parameters only provide a partial assessment and do not allow for a clear distinction between normal and abnormal activity. In this paper, we propose a methodology for the analysis of human activity pattern based on the definition of different physical activity time series with the appropriate analysis methods. The temporal pattern of postures, movements, and transitions between postures was quantified using fractal analysis and symbolic dynamics statistics. The derived nonlinear metrics were able to discriminate patterns of daily activity generated from healthy and chronic pain states.

Hippocampal atrophy predicts conversion to dementia after STN-DBS in Parkinson's disease.

BACKGROUND: Hippocampal atrophy (HA) is a known predictor of dementia in Alzheimer's disease. HA has been found in advanced Parkinson's disease (PD), but no predicting value has been demonstrated yet. The identification of such a predictor in candidates for subthalamic deep brain stimulation (STN-DBS) would be of value. Our objective was to compare preoperative hippocampal volumes (HV) between PD patients who subsequently converted to dementia (PDD) after STN-DBS and those who did not (PDnD). METHODS: From a cohort of 70 consecutive STN-DBS treated PD patients, 14 converted to dementia over 25.6+/-20.2 months (PDD). They were compared to 14 matched controls (PDnD) who did not convert to dementia after 43.9+/-11.7 months. On the preoperative 3D MPRAGE MRI images, HV and total brain volumes (TBV) were measured by a blinded investigator using manual and automatic segmentation respectively. RESULTS: PDD had smaller preoperative HV than PDnD (1.95+/-0.29 ml; 2.28+/-0.33 ml; p<0.01). This difference reinforced after normalization for TBV (3.28+/-0.48, 3.93+/-0.60; p<0.01). Every 0.1 ml decrease of HV increased the likelihood to develop dementia by 24.6%. A large overlap was found between PD and PDnD HVs, precluding the identification of a cut-off score. CONCLUSIONS: As in Alzheimer's disease, HA may be a predictor of the conversion to dementia in PD. This preoperative predictor suggests that the development of dementia after STN-DBS is related to the disease progression, rather then the procedure. Further studies are needed to define a cut-off score for HA, in order to affine its predictive value for an individual patient.

Hippocampal and amygdalar volume changes in elderly patients with Alzheimer's disease and schizophrenia.

Patients with Alzheimer's disease (AD) and schizophrenia display cognitive, behavioural disturbances and morphological abnormalities. Although these latter reflect progressive neurodegeneration in AD, their significance in schizophrenia is still unclear. We explored the patterns of hippocampal and amygdalar atrophy in those patients and their associations with clinical parameters. Structural magnetic resonance imaging was performed in 20 elderly schizophrenia patients, 20 AD and 19 healthy older controls. Hippocampal and amygdalar volumes were obtained by manual segmentation with a standardized protocol and compared among groups. In both schizophrenia and AD patients, left hippocampal and amygdalar volumes were significantly smaller. The hippocampus/amygdala ratio was significantly lower in schizophrenia compared to both AD cases [2.4 bilaterally, 95% C.I. 2.2 to 2.7] and healthy controls bilaterally [2.5, 95% C.I. 2.3 to 2.9 in left and 2.7, 95% C.I. 2.4 to 3.1 in right hemisphere]. In schizophrenia patients, a significant positive correlation was found between age at disease onset and the right hippocampus/amygdala volume ratio (Spearman rho=0.56). Negative symptoms correlated with higher right/left amygdala volume ratio (Spearman's rho=0.43). Our data show that unlike AD, the hippocampus/amygdala ratio is abnormally low and correlates with the age at onset in schizophrenia, being a neurodevelopmental signature of the disease.

Use of a dynamic foot pressure index to monitor the effects of treatment for equinus gait in children with cerebral palsy.

The purpose of this study is to introduce and describe a newly developed index using foot pressure analysis to quantify the degree of equinus gait in children with cerebral palsy before and after injection with botulinum toxin. Data were captured preinjection and 12 weeks postinjection. Ten children aged 2(1/2) to 6(1/2) years took part (5 boys and 5 girls). Three of them had a diagnosis of spastic diplegia and 7 of congenital hemiplegia. In total, 13 limbs were analyzed. After orientation and segmentation of raw pedobarographic data, we determined a dynamic foot pressure index graded 0 to 100 that quantified the relative degree of heel and forefoot contact during stance. These data were correlated (Pearson correlation) with clinical measurements of dorsiflexion at the ankle (on a slow and fast stretch) and video observation (using the Observational Gait Scale). Pedobarograph data were strongly correlated with both the Observational Gait Scale scores (R = 0.79, P < 0.005) and clinical measurements of dorsiflexion on a fast stretch, which is reflective of spasticity (R = 0.70, P < 0.005). We demonstrated the index's sensitivity in detecting changes in spasticity and good correlation with video observations seems to indicate this technique's potential validity. When manipulated and segmented appropriately, and with the development of a simple ordinal index, we found that foot pressure data provided a useful tool in tracking changes in patients with spastic equinus.

Multifractal portrayal of the distribution of the Swiss population

The present research studies the spatial patterns of the distribution of the Swiss population (DSP). This description is carried out using a wide variety of global spatial structural analysis tools such as topological, statistical and fractal measures, which enable the estimation of the spatial degree of clustering of a point pattern. A particular attention is given to the analysis of the multifractality to characterize the spatial structure of the DSP at different scales. This will be achieved by measuring the generalized q-dimensions and the singularity spectrum. This research is based on high quality data of the Swiss Population Census of the Year 2000 at a hectometric resolution (grid 100 x 100 m) issued by the Swiss Federal Statistical Office (FSO).

Geographic variation of the greater white-toothed shrew (Crocidura russula Hermann, 1780 Mammalia, Soricidae)

A multivariate morphometric study of the Greater white-toothed shrew (C. russula) throughout its Palearctic range was carried out to search for patterns of geographic variation within the species boundary. Burnaby's and multiple group principal component analysis allowed the adjustment of raw data with respect to within-sample allometric variation. Multivariate 'size-free' results show a stepped dine with the phenotypical trait reduction and shape change from the eastern to the western Maghreb. Pleistocene fossil mandibles proved to have low phenetic distances with eastern populations (Tunisia, east Algeria) and it is argued that their character set is the primitive condition. The ancestral Mid-Pleistocene shrews lived in a relatively more humid climate. Gee-climatic changes in the north African range during the Quaternary provoked phenetic variation of C. russula and, it can be argued, evolution of the modern western C.r. yebalensis. A historical process can thus be assumed as the main cause of this categorical variation, by segmentation of the species range due to gee-climatic events. Morphometric discontinuity within the C. russula Maghreb range is shown to be congruent with karyological and biochemical studies. Moroccan and Tunisian shrews differ, for example, in NFa chromosomes and electrophoretical traits. A stasipatric process should be invoked to explain categorical variation in the Maghreb range. Colonization and divergence of insular populations results in more or less differentiated geographic races. The populations of Ibiza and Pantelleria are close to the species threshold (Nei's D greater than or equal to 0.1). The process of speciation undergone by the Greater white-toothed shrew results in a complex pattern of geographic variation, including both allopatric and non-allopatric modes.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

Emergence of Swiss metropole and scaling properties of urban clusters

Defining the limits of an urban agglomeration is essential both for fundamental and applied studies in quantitative and theoretical geography. A simple and consistent way for defining such urban clusters is important for performing different statistical analysis and comparisons. Traditionally, agglomerations are defined using a rather qualitative approach based on various statistical measures. This definition varies generally from one country to another, and the data taken into account are different. In this paper, we explore the use of the City Clustering Algorithm (CCA) for the agglomeration definition in Switzerland. This algorithm provides a systemic and easy way to define an urban area based only on population data. The CCA allows the specification of the spatial resolution for defining the urban clusters. The results from different resolutions are compared and analysed, and the effect of filtering the data investigated. Different scales and parameters allow highlighting different phenomena. The study of Zipf's law using the visual rank-size rule shows that it is valid only for some specific urban clusters, inside a narrow range of the spatial resolution of the CCA. The scale where emergence of one main cluster occurs can also be found in the analysis using Zipf's law. The study of the urban clusters at different scales using the lacunarity measure - a complementary measure to the fractal dimension - allows to highlight the change of scale at a given range.

Autosomal dominant spondylocarpotarsal synostosis syndrome: phenotypic homogeneity and genetic heterogeneity.

Spondylocarpotarsal synostosis syndrome (SCT) (OMIM 272460), originally thought to be a failure of normal spine segmentation, is characterized by progressive fusion of vertebras and associates unsegmented bars, scoliosis, short stature, carpal and tarsal synostosis. Cleft palate, sensorineural or mixed hearing loss, joint limitation, clinodactyly, and dental enamel hypoplasia are variable manifestations. Twenty-five patients have been reported. Thirteen affected individuals were siblings from six families and four of these families were consanguineous. In four of those families, Krakow et al. [Krakow et al. (2004) Nat Genet 36:405-410] found homozygosity or compound heterozygosity for mutations in the gene encoding FLNB. This confirmed autosomal recessive inheritance of the disorder. We report on two new patients (a mother and her son) representing the first case of autosomal dominant inheritance. These patients met the clinical and radiological criteria for SCT and did not present any features which could exclude this diagnosis. Molecular analysis failed to identify mutations in NOG and FLNB. SCT is therefore, genetically heterogeneous. Both dominant and autosomal recessive forms of inheritance should be considered during genetic counseling.

Landmark detection for fusion of fundus and MRI toward a patient-specific multimodal eye model.

Ophthalmologists typically acquire different image modalities to diagnose eye pathologies. They comprise, e.g., Fundus photography, optical coherence tomography, computed tomography, and magnetic resonance imaging (MRI). Yet, these images are often complementary and do express the same pathologies in a different way. Some pathologies are only visible in a particular modality. Thus, it is beneficial for the ophthalmologist to have these modalities fused into a single patient-specific model. The goal of this paper is a fusion of Fundus photography with segmented MRI volumes. This adds information to MRI that was not visible before like vessels and the macula. This paper contributions include automatic detection of the optic disc, the fovea, the optic axis, and an automatic segmentation of the vitreous humor of the eye.

A structural MRI study of motor conversion disorder: evidence of reduction in thalamic volume.

OBJECTIVE: To investigate potential abnormalities in subcortical brain structures in conversion disorder (CD) compared with controls using a region of interest (ROI) approach. METHODS: Fourteen patients with motor CD were compared with 31 healthy controls using high-resolution MRI scans with an ROI approach focusing on the basal ganglia, thalamus and amygdala. Brain volumes were measured using Freesurfer, a validated segmentation algorithm. RESULTS: Significantly smaller left thalamic volumes were found in patients compared with controls when corrected for intracranial volume. These reductions did not vary with handedness, laterality, duration or severity of symptoms. CONCLUSIONS: These differences may reflect a primary disease process in this area or be secondary effects of the disorder, for example, resulting from limb disuse. Larger, longitudinal structural imaging studies will be required to confirm the findings and explore whether they are primary or secondary to CD.

Phenotypic and molecular characterization of a novel case of dyssegmental dysplasia, Silverman-Handmaker type.

Dyssegmental dysplasia, Silverman-Handmaker type (DDSH; #MIM 224410) is an autosomal recessive form of lethal dwarfism characterized by a defect in segmentation and fusion of vertebral bodies components ("anisospondyly") and by severe limb shortening. It is caused by mutations in the perlecan gene (HSPG2), but so far, only three molecularly confirmed cases have been reported. We report a novel case of DDSH in a fetus that presented at 15 weeks gestation with encephalocele, severe micromelic dwarfism and narrow thorax. After termination of pregnancy, radiographs showed short ribs, short and bent long bones and anisospondyly of two vertebral bodies. The fetus was homozygous for a previously undescribed null mutation in HSPG2.