Construction of boundary element models in bioelectromagnetism

Multisensor electro- and magnetoencephalographic (EEG and MEG) as well as electro- and magnetocardiographic (ECG and MCG) recordings have been proved useful in noninvasively extracting information on bioelectric excitation. The anatomy of the patient needs to be taken into account, when excitation sites are localized by solving the inverse problem. In this work, a methodology has been developed to construct patient specific boundary element models for bioelectromagnetic inverse problems from magnetic resonance (MR) data volumes as well as from two orthogonal X-ray projections. The process consists of three main steps: reconstruction of 3-D geometry, triangulation of reconstructed geometry, and registration of the model with a bioelectromagnetic measurement system. The 3-D geometry is reconstructed from MR data by matching a 3-D deformable boundary element template to images. The deformation is accomplished as an energy minimization process consisting of image and model based terms. The robustness of the matching is improved by multi-resolution and global-to-local approaches as well as using oriented distance maps. A boundary element template is also used when 3-D geometry is reconstructed from X-ray projections. The deformation is first accomplished in 2-D for the contours of simulated, built from the template, and real X-ray projections. The produced 2-D vector field is back-projected and interpolated on the 3-D template surface. A marching cube triangulation is computed for the reconstructed 3-D geometry. Thereafter, a non-iterative mesh-simplification method is applied. The method is based on the Voronoi-Delaunay duality on a 3-D surface with discrete distance measures. Finally, the triangulated surfaces are registered with a bioelectromagnetic measurement utilizing markers. More than fifty boundary element models have been successfully constructed from MR images using the methods developed in this work. A simulation demonstrated the feasibility of X-ray reconstruction; some practical problems of X-ray imaging need to be solved to begin tests with real data.reviewe

Systems medicine and the integration of bioinformatic tools for the diagnosis of Alzheimer's disease

Because of the changes in demographic structure, the prevalence of Alzheimer's disease is expected to rise dramatically over the next decades. The progression of this degenerative and terminal disease is gradual, with the subclinical stage of illness believed to span several decades. Despite this, no therapy to prevent or cure Alzheimer's disease is currently available. Early disease detection is still important for delaying the onset of the disease with pharmacological treatment and/or lifestyle changes, assessing the efficacy of potential therapeutic agents, or monitoring disease progression more closely using medical imaging. Sensitive cerebrospinal-fluid-derived marker candidates exist, but given the invasiveness of sample collection their use in routine diagnostics may be limited. The pathogenesis of Alzheimer's disease is complex and poorly understood. There is thus a strong case for integrating information across multiple physiological levels, from molecular profiling (metabolomics, lipidomics, proteomics and transcriptomics) and brain imaging to cognitive assessments. To facilitate the integration of heterogeneous data, such as molecular and image data, sophisticated statistical approaches are needed to segment the image data and study their dependencies on molecular changes in the same individuals. Molecular profiling, combined with biophysical modeling of molecular assemblies associated with the disease, offer an opportunity to link the molecular pathway changes with cell- and tissue-level physiology and structure. Given that data acquired at different levels can carry complementary information about early Alzheimer's disease pathology, it is expected that their integration will improve early detection as well as our understanding of the disease

Korsibiomassojen tuotantoketjut ja energiantuotanto kokopaalikattilalla

Suomessa ja muissa Pohjoismaissa kasvaa monenlaista vajaasti hyödynnettyä biomassaa, kuten viherkesantojen ja suojavyöhykkeiden heinäbiomassat, viljojen oljet sekä vesistöissä kasvava järviruoko. Osa tästä biomassasta voitaisiin muuttaa energiaksi biokaasutuksen tai polton avulla. Tämän tutkimuksen tavoitteena oli selvittää ruokohelven, järviruo on, suojavyöhykeheinän ja vehnän oljen sopivuus tanskalaistyyppisessä kokopaalikattilassa poltettavaksi. Kattilan teho on 380 kW ja siihen on kytketty 70 m3 kokoinen varaaja. Kattila täytetään kolmella pyöröpaalilla traktorin etukuormaajalla, sytytetään ja annetaan palaa täytöksen loppuun, mikä kestää yleensä 6 8 tuntia. Lopuksi tuhkat vedetään pois tulipesän pohjalta erikoisvalmisteisella etukuormaajakauhalla. Tutkimusta varten kattila varustettiin savukaasuanalysaattorilla, joka pystyy mittaamaan savukaasujen lämmön sekä CO, CO2, O2, NO ja NO2 pitoisuudet. Palamisen hyötysuhde voitiin laskea näistä arvoista. Kokeissa käytetyt pyöröpaalit olivat kuivia (kosteus 10 14 %) ja niiden tiheys vaihteli välillä 66 131 kg kuiva-ainetta/m3, materiaalista riippuen. Löysät vehnäolkipaalit paloivat parhaiten. Palaminen oli heikointa tiiveillä ruokohelpipaaleilla, järviruokopaalien ja suojavyöhykeheinäpaalien palaminen oli näiden kahden ääripään välissä. Tuhka-analyysien mukaan kaikkien polttoaineiden tuhkien raskasmetallipitoisuudet olivat niin alhaisia, että niiden tuhka voidaan levittää takaisin peltoon. Ei ole täysin selvää, miksi ruokohelpi- ja suojavyöhykeheinäpaalit paloivat heikosti, mutta todennäköistä on, että nämä paalit olivat liian tiiviitä tämäntyyppiselle kattilalle. Kattilan omistajan mukaan palaminen on ollut parasta, kun olkipaalit ovat olleet tarpeeksi löysiä (< 100 kg kuiva-ainetta/m3).There are many types of biomass that grow in the Nordic countries, and which are poorly utilized. Examples include hay from green fallows and buffer zones, cereal straw and reeds from lakeshores and coasts. Such biomass could be locally converted into energy via biogas production or through combustion. Our target was to study the suitability of reed canary grass, common reed, buffer zone grass and wheat straw for combustion in a Danish whole round-bale boiler (380 kW, accumulator 70 m3). The boiler is fed with three round bales by a tractor with a front loader, the bales are combusted in 6 8 hours and finally the ashes are removed from the boiler by tractor. For this study, the boiler was equipped with a smoke gas analyser, which can measure flue gas temperature, and CO, CO2, O2, NO and NO2 concentrations. Combustion efficiency can be calculated using these values. The round bales were dry (10 14 %, w.b.) and their density was between 66 131 kg DM/m3, depending on the material. Loose wheat straw bales burnt best (average CO 1356 ppm, NOx 98 ppm, efficiency 79 %). Combustion was poorest with dense reed canary grass bales (average CO 3969 ppm, NOx 50 ppm, efficiency 64 %). Combustion of common reed and buffer zone grass was intermediate. According to ash analyses all materials had sufficiently low heavy metal concentrations that it would be safe to spread the ash on fields. It is not fully clear why reed canary grass and buffer zone grass combusted poorly, but it is probable that the density of the bales was too high for this type of boiler. According to the boiler owner, combustion has been best when the straw bales have been sufficiently loose (< 100 kg DM/m3).vokKATProduction chains for straw biomass and energy production using a whole bale boile

Neurofilament light level correlates with brain atrophy, and cognitive and motor performance

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Brain volumes in relation to loneliness and social competence in preadolescents born very preterm

Introduction The aim of the present study was to assess how regional brain volumes associate with self-experienced social and emotional loneliness and social competence in very preterm and term-born preadolescents. Materials and methods Thirty-four very preterm subjects (birthweight Results In the very preterm group, a number of significant associations were found between smaller regional brain volumes and self-experienced emotional loneliness, more impulsivity and more disruptiveness. In the control group, brain volumes and loneliness were not associated, and brain volumes and social competence were associated with a lesser degree than in the very preterm group. Conclusion Experiences of emotional loneliness and poorer social competence appear to be more related to brain volumes in very preterm preadolescents than in those born full-term. It also appears that in very preterm preadolescents, emotional loneliness may be more reflected in brain development than social loneliness.Peer reviewe

Association between Deep Gray Matter Changes and Neurocognitive Function in Mild Cognitive Impairment and Alzheimer’s Disease: A Tensor-Based Morphometric MRI Study

Background Atrophy of deep gray matter (DGM) has been associated with a risk of conversion from mild cognitive impairment (MCI) to Alzheimer’s disease (AD) and the degree of cognitive impairment. However, specific knowledge of the associations between degenerative DGM changes and neurocognitive functions remains scarce.Objectives To examine degenerative DGM changes and evaluate their association with neurocognitive functions.Method We examined DGM volume changes with tensor-based morphometry (TBM) and analyzed the relationships between DGM changes and neurocognitive functions in the control (n =58), MCI (n = 38) and AD (n = 58) groups with multiple linear regression analyses.Results In all DGM areas, the AD group had the largest TBM volume changes. The differences in TBM volume changes were larger between the control group and the AD group than between the other pairs of groups. In the AD group, volume changes of the right thalamus were significantly associated with episodic memory, learning and semantic processing. Significant or trend-level associations were identified between the bilateral caudate nucleus changes and episodic memory as well as semantic processing. In the control and MCI groups, very few significant associations emerged.Conclusions Atrophy of the DGM structures, especially the thalamus and caudate nucleus is related to cognitive impairment in AD. DGM atrophy is associated with tests reflecting both subcortical and cortical cognitive functions. </p

Predicting Global Cognitive Decline in the General Population Using the Disease State Index

Background: Identifying persons at risk for cognitive decline may aid in early detection of persons at risk of dementia and to select those that would benefit most from therapeutic or preventive measures for dementia. Objective: In this study we aimed to validate whether cognitive decline in the general population can be predicted with multivariate data using a previously proposed supervised classification method: Disease State Index (DSI). Methods: We included 2,542 participants, non-demented and without mild cognitive impairment at baseline, from the population-based Rotterdam Study (mean age 60.9 ± 9.1 years). Participants with significant global cognitive decline were defined as the 5% of participants with the largest cognitive decline per year. We trained DSI to predict occurrence of significant global cognitive decline using a large variety of baseline features, including magnetic resonance imaging (MRI) features, cardiovascular risk factors, APOE-ε4 allele carriership, gait features, education, and baseline cognitive function as predictors. The prediction performance was assessed as area under the receiver operating characteristic curve (AUC), using 500 repetitions of 2-fold cross-validation experiments, in which (a randomly selected) half of the data was used for training and the other half for testing. Results: A mean AUC (95% confidence interval) for DSI prediction was 0.78 (0.77–0.79) using only age as input feature. When using all available features, a mean AUC of 0.77 (0.75–0.78) was obtained. Without age, and with age-corrected features and feature selection on MRI features, a mean AUC of 0.70 (0.63–0.76) was obtained, showing the potential of other features besides age. Conclusion: The best performance in the prediction of global cognitive decline in the general population by DSI was obtained using only age as input feature. Other features showed potential, but did not improve prediction. Future studies should evaluate whether the performance could be improved by new features, e.g., longitudinal features, and other prediction methods

Thalamic Atrophy Predicts 5-Year Disability Progression in Multiple Sclerosis

Purpose:Thalamus is among the first brain regions to become atrophic in multiple sclerosis (MS). We studied whether thalamic atrophy predicts disability progression at 5 years in a cohort of Finnish MS patients. Methods:Global and regional brain volumes were measured from 24 newly diagnosed relapsing MS (RMS) patients 6 months after initiation of therapy and from 36 secondary progressive MS (SPMS) patients. The patients were divided into groups based on baseline whole brain parenchymal (BP) and thalamic atrophy. Standard scores (zscores) were computed by comparing individual brain volumes with healthy controls. Azscore cutoff of -1.96 was applied to separate atrophic from normal brain volumes. The Expanded Disability Status Scale (EDSS), brain magnetic resonance imaging (MRI) findings, and relapses were assessed at baseline and at 2 years and EDSS progression at 5 years. Results:Baseline thalamus volume predicted disability in 5 years in a logistic regression model (p= 0.031). At 5 years, EDSS was same or better in 12 of 18 patients with no brain atrophy at baseline but only in 5 of 18 patients with isolated thalamic atrophy [odds ratio (OR) (95% CI) = 5.2 (1.25, 21.57)]. The patients with isolated thalamic atrophy had more escalations of disease-modifying therapies during follow-up. Conclusion:Patients with thalamic atrophy at baseline were at a higher risk for 5-year EDSS increase than patients with no identified brain atrophy. Brain volume measurement at a single time point could help predict disability progression in MS and complement clinical and routine MRI evaluation in therapeutic decision-making.</div

Synergistic associations of cognitive and motor impairments with functional outcome in covert cerebral small vessel disease

Background Cognitive and motor impairments are the key clinical manifestations of cerebral small vessel disease (SVD), but their combined effects on functional outcome have not been elucidated. This study investigated the interactions and mediating effects of cognitive and motor functions on instrumental activities of daily living (IADL) and quality of life in older individuals with various degrees of white matter hyperintensities (WMH). Methods Participants of the Helsinki Small Vessel Disease Study (n = 152) were assessed according to an extensive clinical, physical, neuropsychological and MRI protocol. Volumes of WMH and gray matter (GM) were obtained with automated segmentation. Results Cognitive (global cognition, executive functions, processing speed, memory) and motor functions (gait speed, single-leg stance, timed up-and-go) had strong interrelations with each other, and they were significantly associated with IADL, quality of life as well as WMH and GM volumes. A consistent pattern on significant interactions between cognitive and motor functions was found on informant-evaluated IADL, but not on self-evaluated quality of life. The association of WMH volume with IADL was mediated by global cognition, whereas the association of GM volume with IADL was mediated by global cognition and timed up-and-go performance. Conclusion The results highlight the complex interplay and synergism between motor and cognitive abilities on functional outcome in SVD. The combined effect of motor and cognitive disturbances on IADL is likely to be greater than their individual effects. Patients with both impairments are at disproportionate risk for poor outcome. WMH and brain atrophy contribute to disability through cognitive and motor impairment.Peer reviewe