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At least 829 records · Page 46Linked to original sources
PubMed2007

Towards natural stimulation in fMRI--issues of data analysis.

In search for suitable tools to study brain activation in natural environments, where the stimuli are multimodal, poorly predictable and irregularly varying, we collected functional magnetic resonance imaging data from 6 subjects during a continuous 8-min stimulus sequence that comprised auditory (speech or tone pips), visual (video clips dominated by faces, hands, or buildings), and tactile finger stimuli in blocks of 6-33 s. Results obtained by independent component analysis (ICA) and general-linear-model-based analysis (GLM) were compared. ICA separated in the superior temporal gyrus one independent component (IC) that reacted to all auditory stimuli and in the superior temporal sulcus another IC responding only to speech. Several distinct and rather symmetric vision-sensitive ICs were found in the posterior brain. An IC in the V5/MT region reacted to videos depicting faces or hands, whereas ICs in the V1/V2 region reacted to all video clips, including buildings. The corresponding GLM-derived activations in the auditory and early visual cortices comprised sub-areas of the ICA-revealed activations. ICA separated a prominent IC in the primary somatosensory cortex whereas the GLM-based analysis failed to show any touch-related activation. "Intrinsic" components, unrelated to the stimuli but spatially consistent across subjects, were discerned as well. The individual time courses were highly consistent in sensory projection cortices and more variable elsewhere. The ability to differentiate functionally meaningful composites of activated brain areas and to straightforwardly reveal their temporal dynamics renders ICA a sensitive tool to study brain responses to complex natural stimuli.

Acoustic Stimulation↗
PubMed2001

Multivariate data analysis of quality parameters in drinking water.

The quality of water destined for human consumption has been treated as a multivariate property. Since most of the quality parameters are obtained by applying analytical methods, the routine analytical laboratory (responsible for the accuracy of analytical data) has been treated as a process system for water quality estimation. Multivariate tools, based on principal component analysis (PCA) and partial least squares (PLS) regression, are used in the present paper to: (i) study the main factors of the latent data structure and (ii) characterize the water samples and the analytical methods in terms of multivariate quality control (MQC). Such tools could warn of both possible health risks related to anomalous sample composition and failures in the analytical methods.

Multivariate Analysis↗
PubMed2002

Fundamentals of quantitative PET data analysis.

Drug analysis and development with PET should fully exhaust the ability of this tomographic technique to quantify regional tracer concentrations in vivo. Data evaluation based on visual inspection or assessment of regional image contrast is not sufficient for this purpose since much of the information present in dynamically acquired data is not used by these approaches. Compartment modelling of dynamic PET data is generally the method of choice since it allows a quantitative assessment of the underlying pharmacokinetic parameters describing drug transport, metabolism and molecular interactions. We present here an overview of key issues of compartment modelling with specific attention to the assumptions underlying the various models and their limitations. We believe that a thorough understanding of the applicability of models is mandatory for the development, successful execution and analysis of quantitative PET studies. Otherwise, meaningful and interpretable results will often not be obtained.

Animals↗
PubMed2006

Fusion of radiostereometric analysis data into computed tomography space: application to the elbow joint.

Improvement of joint prostheses is dependent upon information concerning the biomechanical properties of the joint. Radiostereometric analysis (RSA) and electromagnetic techniques have been applied in previous cadaver and in vivo studies on the elbow joint to provide valuable information concerning joint motion axes. However, such information is limited to mathematically calculated positions of the axes according to an orthogonal coordinate system and is difficult to relate to individual skeletal anatomy. The aim of this study was to evaluate the in vivo application of a new fusion method to provide three-dimensional (3D) visualization of flexion axes according to bony landmarks. In vivo RSA data of the elbow joint's flexion axes was combined with data obtained by 3D computed tomography (CT). Results were obtained from five healthy subjects after one was excluded due to an instable RSA marker. The median error between imported and transformed RSA marker coordinates and those obtained in the CT volume was 0.22 mm. Median maximal rotation error after transformation of the rigid RSA body to the CT volume was 0.003 degrees . Points of interception with a plane calculated in the RSA orthogonal coordinate system were imported into the CT volume, facilitating the 3D visualization of the flexion axes. This study demonstrates a successful fusion of RSA and CT data, without significant loss of RSA accuracy. The method could be used for relating individual motion axes to a 3D representation of relevant joint anatomy, thus providing important information for clinical applications such as the development of joint prostheses.

Adult↗
PubMed2004

Evaluation and optimization of clustering in gene expression data analysis.

MOTIVATION: A measurement of cluster quality is needed to choose potential clusters of genes that contain biologically relevant patterns of gene expression. This is strongly desirable when a large number of gene expression profiles have to be analyzed and proper clusters of genes need to be identified for further analysis, such as the search for meaningful patterns, identification of gene functions or gene response analysis. RESULTS: We propose a new cluster quality method, called stability, by which unsupervised learning of gene expression data can be performed efficiently. The method takes into account a cluster's stability on partition. We evaluate this method and demonstrate its performance using four independent, real gene expression and three simulated datasets. We demonstrate that our method outperforms other techniques listed in the literature. The method has applications in evaluating clustering validity as well as identifying stable clusters. AVAILABILITY: Please contact the first author.

Algorithms↗
PubMed1985

Multiwell chamber chemotaxis assays: improved experimental design and data analysis.

The chemotaxis assay using the Boyden transfilter technique has become widely used in recent years for assessing migratory responses of a wide variety of cell types. In the study reported here we examined the migratory responses of mouse peritoneal macrophages using a multiwell chamber. The experiments were designed to analyze the components of variance in the assay method, to optimize the experimental design, and to develop objective statistical criteria for choosing among experiments with disparate results. Cell counts were obtained with the aid of an image analyzer coupled to a light microscope. Microcomputer software was developed to drive the image analyzer, collect data and conduct statistical analyses. Nested analysis of variance (ANOVA, either 2- or 3-level) was employed to partition the components of variance and F-tests were used to determine their significance. Significant sources of experimental error were identified both within and among wells and were attributed mostly to variability in the chamber/filter assembly and counting procedure. Statistical analyses demonstrated that there was significant variation among assays conducted in different multiwell chambers on the same day, among assays where the same agent was tested on different days in the same chamber, and among replicate counts of the same assay. The following recommendations were made: use ANOVA to distinguish differences due to biological effects from those due to experimental error, design experiments so that all relevant comparisons are included in the same chamber and the same assay, avoid pooling data from different assays unless ANOVA treatment variances are comparable, and when replicate assays yield disparate results choose the assay with the lowest percentage of variation due to experimental error.

Animals↗
PubMed1985

Comments on Frey's "Data analysis reveals significant microwave-induced eye damage in humans".

Frey's critique and analysis of the Appleton-McCrossan and Appleton et al studies were examined. Frey is criticized for: ignoring pooling problems in his chi-square test; not analyzing the opacity data in Appleton et al; not analyzing the data on vacuoles and posterior subcapsular iridescence in Appleton and McCrossan and Appleton et al; and failing to do log-linear analysis which is appropriate for the design in the two studies. Application of log-linear tests to the opacity data in both studies leads to the conclusion that subject age was significantly associated with the occurrence of opacities, but, contrary to Frey's conclusion, microwave radiation was not.

Aging↗
PubMedDate not supplied

Dynamic PET data analysis.

A general method for estimating the precision of parameters resulting from the use of various experimental designs (rate of injection and rate of tomographic data collection) in emission tomography studies is proposed. The sensitivity matrix of the study model and an estimate of the statistical uncertainty of the tomographic data are used to compute the covariance matrix of the parameters. The determinant of this covariance matrix (proportional to the total volume of uncertainty of the model parameters) serves as a criterion to be minimized. The method is applied to a three-compartment, three-transfer rate constant for glucose metabolism using dynamic positron emission tomography, and a comparison of various current protocols is made with simulated data. The results show that higher rates of injection and higher rates of tomographic data collection at early times lead to smaller statistical uncertainties for the estimates of rate constants. However, for the range of rate constants encountered in practice, differences are insignificant when an initial scan duration less than 30 s is used, without regarding the injection duration.

Deoxyglucose↗
PubMed1998

Factors influencing oral cavity status during high-dose antineoplastic therapy: a secondary data analysis.

PURPOSE/OBJECTIVES: To identify factors associated with oral cavity status in patients receiving high-dose antineoplastic therapy. DESIGN: Descriptive, correlational secondary analysis. SETTING: Midwestern university oncology special care unit. SAMPLE: 50 males and females, ages 15-69. METHODS: The Oral Assessment Guide (OAG) was used to assess oral cavity status every shift throughout hospitalization. Additional data were collected by chart audit. Correlations and Cox regression analysis were performed. MAIN RESEARCH VARIABLES: Oral cavity status, absolute granulocyte count, blood urea nitrogen (BUN), creatinine, mean OAG score during the preparative regimen (prep-OAG), age, and total body irradiation (TBI). FINDINGS: Elevated BUN and creatinine, higher prep-OAG, older age, and TBI were associated with higher OAG scores. Cox analysis revealed that TBI was predictive of an OAG score > or = 16, and an OAG score > or = 18 was predictive of death by day +20. CONCLUSIONS: Patients who receive TBI and chemotherapy in combination are most likely to experience severely compromised oral cavity status. Those who are older, have poorer oral status, and have decreased renal function are at increased risk. IMPLICATIONS FOR NURSING PRACTICE: High-risk patients must be identified early, and oral assessments and care must be given consistently to decrease morbidity and potential mortality.

Adolescent↗
PubMed2006

Using nonlinear models in fMRI data analysis: model selection and activation detection.

There is an increasing interest in using physiologically plausible models in fMRI analysis. These models do raise new mathematical problems in terms of parameter estimation and interpretation of the measured data. In this paper, we show how to use physiological models to map and analyze brain activity from fMRI data. We describe a maximum likelihood parameter estimation algorithm and a statistical test that allow the following two actions: selecting the most statistically significant hemodynamic model for the measured data and deriving activation maps based on such model. Furthermore, as parameter estimation may leave much incertitude on the exact values of parameters, model identifiability characterization is a particular focus of our work. We applied these methods to different variations of the Balloon Model (Buxton, R.B., Wang, E.C., and Frank, L.R. 1998. Dynamics of blood flow and oxygenation changes during brain activation: the balloon model. Magn. Reson. Med. 39: 855-864; Buxton, R.B., Uludağ, K., Dubowitz, D.J., and Liu, T.T. 2004. Modelling the hemodynamic response to brain activation. NeuroImage 23: 220-233; Friston, K. J., Mechelli, A., Turner, R., and Price, C. J. 2000. Nonlinear responses in fMRI: the balloon model, volterra kernels, and other hemodynamics. NeuroImage 12: 466-477) in a visual perception checkerboard experiment. Our model selection proved that hemodynamic models better explain the BOLD response than linear convolution, in particular because they are able to capture some features like poststimulus undershoot or nonlinear effects. On the other hand, nonlinear and linear models are comparable when signals get noisier, which explains that activation maps obtained in both frameworks are comparable. The tools we have developed prove that statistical inference methods used in the framework of the General Linear Model might be generalized to nonlinear models.

Adult↗
PubMed1997

Homogeneous two-site immunometric assay kinetics as a theoretical tool for data analysis.

The easily accessible kinetics of a new homogeneous two-site fluorometric immunoassay for prolactin was studied, in order to determine its usefulness for assay data reduction and optimization. The combined use of a simple descriptive model fitted to experimental data and a mechanistic model to simulate the kinetics revealed that (i) the kinetics curve presented an early inflexion point. Its time of occurrence was constant as long as the antigen concentration was below the smallest antibody concentration and decreased to zero for higher concentrations. It may therefore be used as an indicator of hooked samples. (ii) The kinetics steepest slope was correlated with antigen concentration. Its use as a dose-response curve variable would allow higher concentrations to be assayed than with the classical end-point dose-response curve. The results suggest that control and exploitation of kinetic parameters could help to improve the rapidity, analytical range, and reliability of homogeneous two-site immunometric assays.

Animals↗
PubMed2003

Using motion analysis data for foot-floor contact detection.

A simple, fast and straightforward method was developed for automatically deriving foot-floor contact information from tracking motion analysis system markers attached to the shoes of the subjects. The method was based on an accurate calibration of the motion analysis system prior to the experiments and a trivial off-line threshold-based algorithm using dedicated foot-attached marker positions and velocities as inputs. The main purpose of the method was to obtain the results almost instantaneously. The accuracy was poorer when compared with the classic, man-assisted and time-consuming methods, but the average error was less than 0.1 s compared with the force plate or pressure insole/foot switch-based methods. The method eliminates the need for foot switches when a motion analysis system is already being used. As encumbrance is reduced for the subjects, the method is also applicable to pathological gait patterns.

Biomechanical Phenomena↗
PubMed2005

Long-term survival after cisplatin-based induction chemotherapy and radiotherapy for nasopharyngeal carcinoma: a pooled data analysis of two phase III trials.

PURPOSE: To evaluate the long-term outcome in patients with nasopharyngeal carcinoma (NPC) treated with induction chemotherapy and radiotherapy (CRT) versus radiotherapy alone (RT). PATIENTS AND METHODS: The data from two phase III studies comparing CRT with RT in NPC were updated and pooled together for analysis. A total of 784 patients were included for analysis, with an equal number of patients in both arms. Induction chemotherapy consisted of two to three cycles of cisplatin, bleomycin, and fluorouracil, or cisplatin and epirubicin. RT was given to the nasopharynx and neck using megavoltage radiation (median dose, 70 Gy). The median follow-up time for surviving patients was 67 months. Analysis was based on intention to treat. RESULTS: The addition of induction chemotherapy to RT was associated with a decrease in relapse by 14.3% and cancer-related deaths by 12.9% at 5 years. The 5-year relapse-free survival rate was 50.9% and 42.7% in the CRT and RT arm, respectively (P = .014), and the 5-year disease-specific survival rate was 63.5% and 58.1% in the CRT and RT arm, respectively (P = .029). The 5-year overall survival rate was 61.9% and 58.1% in CRT and RT arm, respectively (P = .092). The incidence of locoregional failure and distant metastases was reduced by 18.3% and 13.3% at 5 years, respectively, with induction chemotherapy. There was no significant difference in the treatment failure patterns between the two arms. CONCLUSION: The addition of cisplatin-based induction chemotherapy to RT was associated with a modest but significant decrease in relapse and improvement in disease-specific survival in advanced-stage NPC. However, there was no improvement in overall survival.

Antineoplastic Combined Chemotherapy Protocols↗