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PubMedDate not supplied

The volar extension of the lunate facet of the distal radius: a quantitative anatomic study.

PURPOSE: To describe quantitatively the protrusion of the volar part of the lunate facet of the distal radius articular surface anterior to the volar metaphyseal cortex, which is susceptible to fracture and can be difficult to control with plates and screws alone. METHODS: Quantitative anatomic measurements of 48 3-dimensional computed tomography scans of the distal radius were analyzed to quantify the anatomy of the volar part of the lunate facet of the distal radius. The measurements were scaled to account for overall bone size. Male and female anatomies were compared. RESULTS: The height and width of the volar extension of the lunate facet were 3 +/- 1 mm and 19 +/- 4 mm, respectively. The mean height of the lunate facet was 19 +/- 3 mm. An average of 16% of the lunate facet projects anterior to the flat volar surface of the distal radius. The thickness of the volar extension of the lunate facet averaged 5 +/- 1 mm. There were no statistically significant differences between men and women for any of the scaled measurements. CONCLUSIONS: The observation that the volar lunate facet projects approximately 3 mm (or 16% of the dorsal-volar height of the lunate facet) anterior to the flat volar surface of the distal radius and is approximately 5 mm thick helps explain its relative vulnerability to injury and the difficulty encountered when trying to secure it with a plate and screws.

Adult↗
PubMed2004

Cluster analysis in kinetic modelling of the brain: a noninvasive alternative to arterial sampling.

In emission tomography, quantification of brain tracer uptake, metabolism or binding requires knowledge of the cerebral input function. Traditionally, this is achieved with arterial blood sampling. We propose a noninvasive alternative via the use of a blood vessel time-activity curve (TAC) extracted directly from dynamic positron emission tomography (PET) scans by cluster analysis. Five healthy subjects were injected with the 5HT(2A)-receptor ligand [(18)F]-altanserin and blood samples were subsequently taken from the radial artery and cubital vein. Eight regions-of-interest (ROI) TACs were extracted from the PET data set. Hierarchical K-means cluster analysis was performed on the PET time series to extract a cerebral vasculature ROI. The number of clusters was varied from K = 1 to 10 for the second of the two-stage method. Determination of the correct number of clusters was performed by the 'within-variance' measure and by 3D visual inspection of the homogeneity of the determined clusters. The cluster-determined input curve was then used in Logan plot analysis and compared with the arterial and venous blood samples, and additionally with one of the currently used alternatives to arterial blood sampling, the Simplified Reference Tissue Model (SRTM) and Logan analysis with cerebellar TAC as an input. There was a good agreement (P < 0.05) between the values of Distribution Volume (DV) obtained from the K-means-clustered input function and those from the arterial blood samples. This work acts as a proof-of-principle that the use of cluster analysis on a PET data set could obviate the requirement for arterial cannulation when determining the input function for kinetic modelling of ligand binding, and that this may be a superior approach as compared to the other noninvasive alternatives.

Adult↗
PubMed2004

A comparison of methods for characterizing the event-related BOLD timeseries in rapid fMRI.

Information about the shape and temporal duration of the blood oxygenation level dependent (BOLD) response can inform both functional neuroanatomy and psychological theory. However, the BOLD response evolves over 20 s or more, making it difficult to distinguish the unique characteristics of the response evoked by temporally adjacent stimuli. Fortunately, event-related BOLD signals can be extracted given that there is adequate variance in the distribution of inter-stimulus intervals (ISI). Unfortunately, the ISI distribution that yields the highest statistical efficiency is not always optimal from a psychological perspective; variability in the stimulus timing may complicate the interpretation of neuroimaging data in terms of underlying cognitive operations. In the present paper, Monte Carlo simulations are used to evaluate two techniques for estimating the event-related BOLD timeseries-event-related averaging and deconvolution using the Ordinary Least Squares estimate -with respect to maintaining acceptable levels of statistical power and experimental validity. While the unbiased deconvolution technique more robustly estimates the shape of the BOLD response functions, both methods succeed in accurately re-producing known differences between evoked BOLD responses when the stimulus ordering is randomized. However, the deconvolution method is more effective at preserving differences when there are sequential dependencies in the stimulus presentation order and restricted ISI distributions are used; particularly if the second of two sequentially dependent stimuli is omitted on some portion of the trials. Importantly, the successful re-production of the evoked BOLD response using restricted ISI distributions often maximizes the ability to make psychologically valid experimental conclusions.

Brain↗
PubMed2004

Multilevel linear modelling for FMRI group analysis using Bayesian inference.

Functional magnetic resonance imaging studies often involve the acquisition of data from multiple sessions and/or multiple subjects. A hierarchical approach can be taken to modelling such data with a general linear model (GLM) at each level of the hierarchy introducing different random effects variance components. Inferring on these models is nontrivial with frequentist solutions being unavailable. A solution is to use a Bayesian framework. One important ingredient in this is the choice of prior on the variance components and top-level regression parameters. Due to the typically small numbers of sessions or subjects in neuroimaging, the choice of prior is critical. To alleviate this problem, we introduce to neuroimage modelling the approach of reference priors, which drives the choice of prior such that it is noninformative in an information-theoretic sense. We propose two inference techniques at the top level for multilevel hierarchies (a fast approach and a slower more accurate approach). We also demonstrate that we can infer on the top level of multilevel hierarchies by inferring on the levels of the hierarchy separately and passing summary statistics of a noncentral multivariate t distribution between them.

Bayes Theorem↗
PubMed2004

Constrained linear basis sets for HRF modelling using Variational Bayes.

FMRI modelling requires flexible haemodynamic response function (HRF) modelling, with the HRF being allowed to vary spatially and between subjects. To achieve this flexibility, voxelwise parameterised HRFs have been proposed; however, inference on such models is very slow. An alternative approach is to use basis functions allowing inference to proceed in the more manageable General Linear Model (GLM) framework. However, a large amount of the subspace spanned by the basis functions produces nonsensical HRF shapes. In this work we propose a technique for choosing a basis set, and then the means to constrain the subspace spanned by the basis set to only include sensible HRF shapes. Penny et al. showed how Variational Bayes can be used to infer on the GLM for FMRI. Here we extend the work of Penny et al. to give inference on the GLM with constrained HRF basis functions and with spatial Markov Random Fields on the autoregressive noise parameters. Constraining the subspace spanned by the basis set allows for far superior separation of activating voxels from nonactivating voxels in FMRI data. We use spatial mixture modelling to produce final probabilities of activation and demonstrate increased sensitivity on an FMRI dataset.

Bayes Theorem↗
PubMed2004

Deformable registration of cortical structures via hybrid volumetric and surface warping.

Registration of cortical structures across individuals is a very important step for quantitative analysis of the human brain cortex. This paper presents a method for deformable registration of cortical structures across individuals, using hybrid volumetric and surface warping. In the first step, a feature-based volumetric registration algorithm is used to warp a model cortical surface to the individual's space. This step greatly reduces the variation between the model and individual, thus providing a good initialization for the next step of surface warping. In the second step, a surface registration method, based on matching geometric attributes, warps the model surface to the individual. Point correspondences are also established at this step. The attribute vector, as the morphological signature of surface, was designed to be as distinctive as possible, so that each vertex on the model surface can find its correspondence on the individual surface. Experimental results on both synthesized and real brain data demonstrate the performance of the proposed method in the registration of cortical structures across individuals.

Artifacts↗
PubMed2004

Cross-relaxation imaging reveals detailed anatomy of white matter fiber tracts in the human brain.

Cross-relaxation imaging is a new quantitative MRI modality, which allows mapping of fundamental parameters determining the magnetization transfer (MT) effect in tissues, cross-relaxation rate constant (k) and bound pool fraction (f). This study introduces a new time-efficient technique for cross-relaxation imaging, which obtains three-dimensional (3D) whole-brain k and f maps with scan time of <30 min and isotropic spatial resolution of 1.4 mm. The technical principle of the method is based on four-point fit of a matrix model of pulsed MT to imaging data obtained with variable offset frequency saturation while using a complimentary R1 (=1 / T1) map. Anatomical correlations of in vivo cross-relaxation parametric maps were evaluated in three healthy subjects. The f maps revealed correspondence of areas with highly elevated f = 12-15% to major fiber tracts such as corpus callosum, anterior commissure, optic radiations, and major brain fasciculi. The rest of white matter (WM) demonstrated lower f = 9-11%, resulting in clear visual contrast of fiber tracts. Even lower f = 6.5-8.5% were found in gray matter (GM) with the highest f = 8.5% in the anterior thalamus. Distribution of k was relatively uniform in WM and produced sharp contrast between GM and WM (k = 1.6 and 3.3 s(-1), respectively). The most marked feature of k maps was their ability to visualize the corticospinal tract, which had elevated k = 3.4-3.8 s(-1) but appeared invisible on f maps. The observed patterns on f maps can be explained by variations in the density of myelinated fibers, while the trends of k may reflect regional differences in axonal organization. Cross-relaxation imaging can be used in various clinical studies focused on brain development and white matter diseases.

Analysis of Variance↗
PubMed2005

Effects of oxygen saturation on BOLD and arterial spin labelling perfusion fMRI signals studied in a motor activation task.

Effects of oxygen availability on blood oxygenation level dependent (BOLD) and arterial spin labelling (ASL) perfusion functional magnetic resonance imaging (fMRI) signal changes upon motor activation were studied. Mild hypoxic hypoxia was induced by reducing the inspired oxygen content (FIO(2)) to 12%, decreasing blood oxygen saturation (Y) from 0.99 +/- 0.01 to 0.85 +/- 0.03. The fMRI signal characteristics were determined during finger tapping. BOLD activation volume decreased as a function of declining Y in the brain structures involved in execution of the motor task, however, the BOLD signal increase in activated parenchyma was not influenced by Y. ASL fMRI showed that the baseline CBF of 61.8 +/- 3.6 ml/100 g/min was not affected by hypoxic hypoxia. Similar to the BOLD fMRI, the volume of motor cortex areas displaying increase in perfusion by ASL fMRI decreased, but the signal change due to perfusion increase was not influenced in hypoxia. The present fMRI results show distinct patterns of haemodynamic and metabolic responses in the brain to motor task between normoxia and hypoxia. On one hand, neither BOLD nor ASL fMRI signal changes are influenced by hypoxia during motor activation. On the other hand, hypoxia attenuates increase in both BOLD and perfusion fMRI signals upon finger tapping from the levels determined in normoxia. These observations indicate that haemodynamic and metabolic responses may be heterogeneous in brain during execution of motor functions in mild hypoxia.

Adult↗
PubMed2006

Generality and specificity in cognitive aging: a volumetric brain analysis.

OBJECTIVE: To investigate whether, in old age, brain volume differences are associated with age-related change in general mental ability and/or specific cognitive abilities. METHODS: The authors investigate the association between brain volumes and current cognitive function in a well-characterized sample of healthy old people (aged 79-80) whose intelligence was recorded at age 11. This allowed estimation of intellectual change over the life span. RESULTS: After accounting for childhood intelligence, associations were found between specific cognitive measures and brain volumes. An association was also found between volumes and the general intelligence factor g. After removing the influence of g from each of the specific cognitive measures, no remaining significant associations were found between brain volumes and the specific part of each test. CONCLUSIONS: Generalized cognitive aging is associated with brain volume differences, but there is no evidence in this sample that specific components of cognitive aging are associated with differences in brain volume.

Adolescent↗
PubMed2006

Phase contrast radiography of Lewy bodies in Parkinson disease.

Parkinson's disease (PD), defined as a neurodegenerative disorder, is characterized by the loss of dopaminergic neurons and the presence of Lewy bodies in neurons. Morphological study of Lewy bodies is important to identify the causes and the processes of PD. Here, we investigate a possibility of phase contrast radiography using coherent synchrotron X-rays to explore the microscopic details of Lewy bodies in thick (approximately 3 mm) midbrain tissues. Autopsied midbrain tissues of a PD patient were sliced in 3 mm thickness and then examined using synchrotron X-rays from the 7B2 beamline of the Pohang Light Source. Refraction-enhanced phase contrast radiography and microtomography were adopted to identify dark core and dim edge of Lewy bodies in neurons. The morphology of Lewy bodies was clearly revealed by the phase contrast radiography in very thick (3 mm) midbrain tissues without any staining treatment. Three-dimensional volume rendered microtomography of the autopsied midbrain tissues demonstrates striking evidence that several Lewy bodies are agglomerated by dim edges in a neuron. We suggest that the phase contrast radiography could be a useful tool to morphologically investigate the causes or the processes in PD.

Dopamine↗
PubMed2006

A theoretical and experimental study of vibrational properties of alkyl xanthates.

Geometrical structure and vibrational modes of potassium and sodium ethyl/heptyl xanthates were studied, using both theoretical and experimental methods. Both Hartree-Fock and density functional theory were used. The experimental method used was infrared absorption spectroscopy (FTIR). Our work showed that vibrational frequencies calculated with density functional theory, using the local density approximation, are in very good agreement with experiments. The results were not improved by using the more sophisticated and computationally demanding B3LYP functional.

Mathematical Computing↗
PubMed2000

Salt-dependent compaction of di- and trinucleosomes studied by small-angle neutron scattering.

Using small-angle neutron scattering (SANS), we have measured the salt-dependent static structure factor of di- and trinucleosomes from chicken erythrocytes and from COS-7 cells. We also determined the sedimentation coefficients of these dinucleosomes and dinucleosomes reconstituted on a 416-bp DNA containing two nucleosome positioning sequences of the 5S rDNA of Lytechinus variegatus at low and high salt concentrations. The internucleosomal distance d was calculated by simulation as well as Fourier back-transformation of the SANS curves and by hydrodynamic simulation of sedimentation coefficients. Nucleosome dimers from chicken erythrocyte chromatin show a decrease in d from approximately 220 A at 5 mM NaCl to 150 A at 100 mM NaCl. For dinucleosomes from COS-7 chromatin, d decreases from 180 A at 5 mM to 140 A at 100 mM NaCl concentration. Our measurements on trinucleosomes are compatible with a compaction through two different mechanisms, depending on the salt concentration. Between 0 and 20 mM NaCl, the internucleosomal distance between adjacent nucleosomes remains constant, whereas the angle of the DNA strands entering and leaving the central nucleosome decreases. Above 20 mM NaCl, the adjacent nucleosomes approach each other, similar to the compaction of dinucleosomes. The internucleosomal distance of 140-150 A at 100 mM NaCl is in agreement with distances measured by scanning force microscopy and electron microscopy on long chromatin filaments.

Animals↗
PubMed2001

The neuronal refractory period causes a short-term peak in the autocorrelation function.

Autocorrelation functions are a major tool for the understanding of single-cell firing patterns. Short-term peaks in autocorrelation functions have previously been interpreted as a tendency towards bursting activity or elevated probability to emit spikes in a short time-scale. These peaks can actually be a result of the firing of a neuron with a refractory period followed by a period of constant firing probability. Analytic studies and simulations of such neurons replicate the autocorrelation functions of real-world neurons. The relative size of the peak increases with the refractory period and with the firing rate of the cell. This phenomenon is therefore more notable in areas such as the globus pallidus and cerebellum and less clear in the cerebral cortex. We describe here a compensation factor that can be calculated from the neuron's hazard function. This factor can be removed from the original autocorrelation function to reveal the underlying firing pattern of the cell.

Animals↗
PubMedDate not supplied

Strong gradients for spatially resolved diffusion measurements.

A new multilayer approach to gradient coil design, which allows the production of very strong gradient coils with reasonable resistance and consequent power dissipation, has been developed. Using this approach we have designed and built a strong z-gradient coil that will accommodate vertically mounted samples contained in 5-mm nuclear magnetic resonance tubes. The coil has an efficiency of 1.73 Tm-1A-1, an inductance of 49 microH, and a resistance of 1.8 omega, with a homogeneous volume consisting of a central cylinder of 4.5-mm length and diameter. This coil has been used to monitor the diffusion of water in Nylon 6.6 at room temperature, during desorption. This system is difficult to monitor via nuclear magnetic resonance (NMR), because the diffusion coefficients are typically less than 10(-13) m2s-1, while the T2 relaxation time is less than 1 ms even when the sample is fully saturated. The resulting measurements show a strong concentration dependence of the T2 relaxation time and self-diffusion coefficient of the absorbed water. The measured concentration profiles are consistent with a Fickian diffusion process with a concentration-dependent diffusion coefficient. The measured self-diffusion values are in reasonable agreement with those inferred from the variation of the concentration profiles as a function of time, using the one-dimensional Fickian diffusion equation.

Absorption↗
PubMed1987

Intraocular lens calculation formulas for new intraocular lens implants.

Several different formulas are available for preoperative calculation of the required implant power for a desired postoperative refraction. However, the application of both theoretical and statistically derived regression formulas to the new generation of soft intraocular lens implants poses several difficulties. In this paper the calculation of an A constant for a specific intraocular hydrogel lens implant, as well as the derivation of a universal theoretical formula, is described. The theoretical formula can be applied to other implant styles with various optical configurations and composed of different biomaterials. The SRK and theoretical formulas have been applied retrospectively to a series of patients receiving an intraocular hydrogel lens implant. A comparison shows that both perform satisfactorily in predicting the desired postoperative refraction.

Computer Simulation↗
PubMed2003

Midpoints for fuzzy sets and their application in medicine.

Using Kosko's hypercube, we identify a fuzzy set with a point in a unit hypercube. A non-fuzzy or crisp subset of a set is a vertex of the hypercube. We introduce some new ideas: the definition of the fuzzy segment joining two given fuzzy subsets of a set, the set of midpoints between those two fuzzy subsets, and the set of equidistant points from given points. We present some basic properties and relations between these concepts and provide a complete description of fuzzy segments and midpoints. In the majority of cases, there is no unique midpoint; one has an infinite set of possibilities to choose from. This situation is totally different from classical Euclidean geometry where, for two given points, there is a unique midpoint. We use the obtained results to study two sets of medical data and present two applications in medicine: the fuzzy degree of two concurrent food and drug addictions, and a fuzzy representation of concomitant causal mechanisms of stroke.

Adolescent↗
PubMed2003

Single-shot T(2)* mapping with 3D compensation of local susceptibility gradients in multiple regions.

Macroscopic magnetic field inhomogeneities severely limit sensitivity of blood oxygenation level-dependent (BOLD) functional MRI (fMRI) in frontal and central brain regions close to brain stem. A single-shot multiecho echo-planar imaging method (TurboPEPSI) was developed that combines quantitative T(2)* mapping with gradient compensation of local susceptibility inhomogeneities in multiple volumes of interest (VOIs). Gradient compensation was optimized in individual subjects based on magnetic field mapping and applied at selected echo times, interleaved with acquisition of uncompensated echoes. Intrinsic T(2)* values from uncompensated echoes were obtained in real-time simultaneously with effective T(2)* values from gradient compensated echoes. It is demonstrated that up to three VOIs can be compensated in a single excitation, in addition to collecting uncompensated data, using 8-echo acquisition on a clinical 1.5 Tesla scanner. A theory was developed to optimize the sequence of uncompensated and compensated echoes to achieve maximum BOLD sensitivity. Gradient compensation increased effective T(2)* values in left and right amygdala on average by 18.8 +/- 7.5 ms, while maintaining sensitivity in uncompensated brain areas. In orbitofrontal cortex effective T(2)* values increased by 22.2 +/- 5.3 ms. A CO(2) challenge paradigm was used to demonstrate that this gradient compensation method significantly enhances BOLD signal changes in amygdala as compared to conventional echo-planar imaging (EPI) and uncompensated TurboPEPSI.

Artifacts↗
PubMed2003

Multicontext fuzzy clustering for separation of brain tissues in magnetic resonance images.

A local image model is proposed to eliminate the adverse impact of both artificial and inherent intensity inhomogeneities in magnetic resonance imaging on intensity-based image segmentation methods. The estimation and correction procedures for intensity inhomogeneities are no longer indispensable because the highly convoluted spatial distribution of different tissues in the brain is taken into consideration. On the basis of the local image model, multicontext fuzzy clustering (MCFC) is proposed for classifying 2D and 3D MR data into tissues of white matter, gray matter, and cerebral spinal fluid automatically. In MCFC, multiple clustering contexts are generated for each pixel, and fuzzy clustering is independently performed in each context to calculate the degree of membership of a pixel to each tissue class. To maintain the statistical reliability and spatial continuity of membership distributions, a fusion strategy is adopted to integrate the clustering outcomes from different contexts. The fusion result is taken as the final membership value of the pixel. Experimental results on both real MR images and simulated volumetric MR data show that MCFC outperforms the classic fuzzy c-means (FCM) as well as other segmentation methods that deal with intensity inhomogeneities.

Artifacts↗