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At least 1,135 records · Page 63Linked to original sources
PubMed2002

Effects of temporal modelling on the statistical uncertainty of spatiotemporal distributions estimated directly from dynamic SPECT projections.

Artefacts can result when reconstructing a dynamic image sequence from inconsistent single photon emission computed tomography (SPECT) projection data acquired by a slowly rotating gantry. The artefacts can lead to biases in kinetic parameters estimated from time-activity curves generated by overlaying volumes of interest on the images. Insufficient sampling and truncation of projections by cone-beam collimators can cause additional artefacts. To overcome these sources of bias in conventional image based dynamic data analysis, we have been investigating the estimation of time-activity curves and kinetic model parameters directly from dynamic SPECT projection data by modelling the spatial and temporal distribution of the radiopharmaceutical throughout the projected field of view. In the present work, we perform Monte Carlo simulations to study the effects of the temporal modelling on the statistical variability of the reconstructed spatiotemporal distributions. The simulations utilize fast methods for fully four-dimensional (4D) direct estimation of spatiotemporal distributions and their statistical uncertainties, using a spatial segmentation and temporal B-splines. The simulation results suggest that there is benefit in modelling higher orders of temporal spline continuity. In addition, the accuracy of the time modelling can be increased substantially without unduly increasing the statistical uncertainty, by using relatively fine initial time sampling to capture rapidly changing activity distributions.

Algorithms↗
PubMed2004

Effect of compensation for scattering angular uncertainty in analytical Compton camera reconstruction.

In Compton cameras, the measured scattering angle is associated with an uncertainty which becomes larger as the incident gamma-ray energy decreases. Since this uncertainty degrades the spatial resolution of reconstructed images, Hirasawa and Tomitani (2003 Phys. Med. Biol. 48 1009-26) previously revised their analytical reconstruction algorithm to compensate for it. As the new algorithm improved the spatial resolution in effect, they expected an enhancement of the statistical noise. In this paper, the effect of this compensation has been analysed in view of spatial resolution (the FWHM of the noise-free reconstructed image for a point source distribution), statistical noise (the relative standard deviation of reconstructed images for an isotropic source distribution) and image quality (the roughness of reconstructed images for a phantom). The results describe not only the effect of the compensation, but also the relation between the statistical noise and three parameters, i.e., the incident gamma-ray energy, the spatial resolution and the measured total event numbers, in reconstruction with compensation. This relation should be taken into account for the design of Compton cameras with good quality images, i.e., useful image, output.

Algorithms↗
PubMed2004

A three-dimensional theoretical model incorporating spatial detection uncertainty in continuous detector PET.

In this paper, we will describe a theoretical model of the spatial uncertainty for a line of response, due to the imperfect localization of events on the detector heads of a positron emission tomography (PET) camera. The forward acquisition problem is modelled by a Gaussian distribution of the position of interaction on a detector head, centred at the measured position. The a posteriori probability that an event originates from a certain point in the field of view (FOV) is calculated by integrating all the possible lines of response (LORs) through this point, weighted with the Gaussian detection likelihood at the LOR's end points. We have calculated these a posteriori probabilities both for perpendicular and oblique coincidences. For the oblique coincidence case it was necessary to incorporate the effect of the crystal thickness in the calculations. We found in the perpendicular incidence case as well as in the oblique incidence case that the probability density function cannot be analytically expressed in a closed form, and it was thus calculated by means of numerical integration. A Gaussian was fit to the transversal profiles of this function for a given distance to the detectors. From these fits, we can conclude that the profiles can be accurately approximated by a Gaussian, both for perpendicular and oblique coincidences. The FWHM reaches a maximum at the detector heads, and decreases towards the centre of the FOV, as was expected. Afterwards we extended this two-dimensional model to three dimensions, thus incorporating the spatial uncertainty in both transversal directions. This theoretical model was then evaluated and a very good agreement was found with theoretical calculations and with geometric Monte Carlo simulations. Possible improvements for the above-described incorporation of crystal thickness are discussed. Therefore a detailed Monte Carlo study has been performed in order to investigate the interaction probability of photons of different energies along their path in several detector materials dedicated to PET. Finally two approaches for the incorporation of this theoretical model in reconstruction algorithms are outlined.

Algorithms↗
PubMed2005

Incorporating organ movements in inverse planning: assessing dose uncertainties by Bayesian inference.

We present a method to calculate dose uncertainties due to inter-fraction organ movements in fractionated radiotherapy, i.e. in addition to the expectation value of the dose distribution a variance distribution is calculated. To calculate the expectation value of the dose distribution in the presence of organ movements, one estimates a probability distribution of possible patient geometries. The respective variance of the expected dose distribution arises for two reasons: first, the patient is irradiated with a finite number of fractions only and second, the probability distribution of patient geometries has to be estimated from a small number of images and is therefore not exactly known. To quantify the total dose variance, we propose a method that is based on the principle of Bayesian inference. The method is of particular interest when organ motion is incorporated in inverse IMRT planning by means of inverse planning performed on a probability distribution of patient geometries. In order to make this a robust approach, it turns out that the dose variance should be considered (and minimized) in the optimization process. As an application of the presented concept of Bayesian inference, we compare three approaches to inverse planning based on probability distributions that account for an increasing degree of uncertainty. The Bayes theorem further provides a concept to interpolate between patient specific data and population-based knowledge on organ motion which is relevant since the number of CT images of a patient is typically small.

Algorithms↗
PubMed2005

The influence of measurement uncertainties on the evaluation of the distribution volume ratio and binding potential in rat studies on a microPET R4: a phantom study.

In small animal positron emission tomography (PET) imaging, the injectable radiotracer dose is often limited by the tracer mass which, together with the tracer kinetics and scanner sensitivity, dictates the statistical quality of the time activity curves (TACs) used to extract biological parameters. We investigated the effect of measurement uncertainty on the determination of the distribution volume ratio (DVR) and binding potential (BP) as estimated using the tissue input Logan (DVR(L), BP(L)) and the ratio (DVRr, BPr) methods for two tracers, with the Concorde microPET R4 camera. Parameters' coefficients of variation (COV) were estimated from a combination of rat and phantom data. For 11C-dihydrotetrabenazine, the COV was 11% for the BP(L) and 13.4% for the BPr when using TACs obtained from individual regions of interest (ROIs) and segmented attenuation correction. The COVs were reduced to 7.5% (BP(L)) and 8.6% (BPr) when the striatal and cerebellar TACs were estimated as averages of 3 and 2 ROIs respectively. Results obtained for 11C-methylphenidate (MP) yielded approximately 30% higher COVs. With measured attenuation correction, the COVs were on average 100% higher. The presented method can be used to examine the contribution of a variety of imaging conditions to the uncertainty of biologically meaningful parameters.

Affinity Labels↗
PubMed2006

Ideal spatial radiotherapy dose distributions subject to positional uncertainties.

In radiotherapy a common method used to compensate for patient setup error and organ motion is to enlarge the clinical target volume (CTV) by a 'margin' to produce a 'planning target volume' (PTV). Using weighted power loss functions as a measure of performance for a treatment plan, a simple method can be developed to calculate the ideal spatial dose distribution (one that minimizes expected loss) when there is uncertainty. The spatial dose distribution is assumed to be invariant to the displacement of the internal structures and the whole patient. The results provide qualitative insights into the suitability of using a margin at all, and (if one is to be used) how to select a 'good' margin size. The common practice of raising the power parameters in the treatment loss function, in order to enforce target dose requirements, is shown to be potentially counter-productive. These results offer insights into desirable dose distributions and could be used, in conjunction with well-established inverse radiotherapy planning techniques, to produce dose distributions that are robust against uncertainties.

Algorithms↗
PubMed2006

Electron radiotherapy: a study on dosimetric uncertainty using small cutouts.

This note investigated the dosimetric uncertainties due to the positional error when centring a small cutout to the machine central beam axis (CAX) in electron radiotherapy. A group of six circular cutouts with 4 cm diameter were made with their centres shifting 0, 2, 4, 6, 8 and 10 mm from the machine CAX for the 6 x 6 cm(2) applicator. The per cent depth doses, beam profiles and output factors were measured using the 4, 9 and 16 MeV clinical electron beams produced by a Varian 21 EX linear accelerator. The 2D isodose distributions in the z-x (or cross-line) and z-y (or in-line) plane were calculated by Monte Carlo simulation using the EGSnrc system. When the cutout centre was shifted away from the machine CAX for the 4 MeV beam, the d(m), R(80) and R(90) at the machine CAX had no significant change (<0.1 mm). For higher energies of 9 and 16 MeV beams, the d(m) was reduced by 0.45 and 1.63 mm per mm, between the cutout centre and the machine CAX with off-axis shift <6 mm respectively. R(80) and R(90) were reduced by more than 0.3 mm per mm off-axis shift for both energies. The isodose coverage of the in-line axis beam profile was reduced when the cutout centre was shifted away from machine CAX. It is important for oncology staff to note such dosimetric changes in the clinical electron radiotherapy, particularly when a high energy electron beam is used for small cutout. Such positional uncertainty is unavoidable in fabricating an electron cutout in the mould room.

Breast Neoplasms↗
PubMed1998

Joint EC/USNRC expert judgement driven radiological protection uncertainty analysis.

The development of two probabilistic accident consequence codes sponsored by the European Commission and the United States Nuclear Regulatory Commission, COSYMA and MACCS respectively, was completed in 1990. These codes estimate the risks and other endpoints associated with accidents from hypothesised nuclear installations. In 1991, both commissions sponsored a joint project for an uncertainty analysis of these two codes. The main objective of this joint project was to systematically derive credible and traceable probability distributions for the respective code input variables. These input distributions will subsequently be used in two uncertainty analyses for each code separately. A formal expert judgement elicitation and evaluation process was used as the best available technique to accomplish that objective. This paper describes the process and some of the findings of the eight expert judgement exercises performed under the joint study.

Animals↗
PubMed1998

Stochastic dose/risk assessment uncertainty and the concept of potential exposures.

Assessments of future potential doses and risks (e.g. in connection with radioactive waste disposal) can be associated with substantial uncertainties. These uncertainties are often incorporated into assessments using stochastic models, and give rise to doses characterised in probabilistic terms. Questions about how doses should be related to risks arise even in the case of deterministic dose assessments. However, results of a probabilistic dose assessment may lead to additional issues when interpreting them or attempting to convert them to risk for regulatory purposes. Some problems are shown to originate from the difference between the meaning of a probabilistic dose value and the definition of potential exposure. Others relate to the appropriate choice of, or approach to compliance with, a regulatory limit. A possible method for setting limits on probabilistic (potential) doses or risks is proposed, based on an accepted technique for determining detection limits.

Computer Simulation↗
PubMed2005

Uncertainty and power at low levels of incurred radiation dose.

It is common practice when calculating dose to exposed populations to average the variables that go into the dose calculation (e.g. environmental concentrations, air kerma, consumption rates, occupancy rates). This approach is simple and can be useful where data are obtained over different periods (weekly, monthly, quarterly), where samples may be bulked for some analyses but not others and where gaps in the data are present. However, such an approach does not yield information on the degree of uncertainty around the average dose calculated. An alternative approach is to estimate the dose to each individual and to obtain an average from this data set, which can then also be used to derive a measure of uncertainty around the central dose estimate. In this study, we demonstrate the variability in dose estimates using a hypothetical data set and consider the implications for sample size to achieve fixed confidence or resolving power. We recommend calculating the dose to every individual sampled, in order both to obtain the average dose and to estimate its variability. We argue that it is best practice to obtain information as complete as possible from the available sample of individuals.

Animals↗
PubMed1994

Computer-assisted restriction mapping: an integrated approach to handling experimental uncertainty.

Building a map of restriction sites from double-digest gel data can be a complex and frustrating task, especially when many DNA fragments are detected or when the gel results are ambiguous. 'Double Digester' is an interactive, graphical computer program which helps researchers understand and resolve such data. It explicitly represents the experimental data, the associated uncertainties, the researcher's hypotheses and possible map interpretations. Alternative solutions are frequently possible, and the differences between them may help determine which additional experiments might resolve ambiguities. Initial use has confirmed the benefits of this approach, and has suggested ways in which it can be refined and extended. Double Digester meets the need for a practical tool to help build restriction maps, and also illustrates how a computer-based tool can confront experimental uncertainty in an integrated fashion.

Algorithms↗
PubMed2002

Probabilistic Boolean Networks: a rule-based uncertainty model for gene regulatory networks.

MOTIVATION: Our goal is to construct a model for genetic regulatory networks such that the model class: (i) incorporates rule-based dependencies between genes; (ii) allows the systematic study of global network dynamics; (iii) is able to cope with uncertainty, both in the data and the model selection; and (iv) permits the quantification of the relative influence and sensitivity of genes in their interactions with other genes. RESULTS: We introduce Probabilistic Boolean Networks (PBN) that share the appealing rule-based properties of Boolean networks, but are robust in the face of uncertainty. We show how the dynamics of these networks can be studied in the probabilistic context of Markov chains, with standard Boolean networks being special cases. Then, we discuss the relationship between PBNs and Bayesian networks--a family of graphical models that explicitly represent probabilistic relationships between variables. We show how probabilistic dependencies between a gene and its parent genes, constituting the basic building blocks of Bayesian networks, can be obtained from PBNs. Finally, we present methods for quantifying the influence of genes on other genes, within the context of PBNs. Examples illustrating the above concepts are presented throughout the paper.

Cell Cycle↗
PubMed1993

Response choice in Parkinson's disease. The effects of uncertainty and stimulus-response compatibility.

Reaction time paradigms provide a set of methods for assessing aspects of the planning and execution of voluntary movements in Parkinson's disease. Attention has focused mainly on the issue of programming of responses, employing a combination of simple reaction time (SRT) and choice reaction time (CRT) paradigms. The first part of the present study replicated an earlier finding in which patients showed a disproportionate slowing in CRT compared with SRT. The main aim of the study was to investigate the possible role of response choice, a key stage prior to motor programming in this CRT deficit. Two factors were manipulated: (i) response uncertainty and (ii) stimulus-response compatibility. The patients showed a normal increase in reaction time with increasing uncertainty in the compatible conditions, and a normal response to stimulus-response compatibility in the two-choice task. However, the two groups showed qualitatively different patterns of interaction between the two experimental factors, with only the patients showing a disproportionate slowing with incompatible stimulus-response relationships in the four-choice task. The data were interpreted in terms of Hasbroucq et al.'s (1990) list-rule model of stimulus-response compatibility effects, which suggested that the patients and controls were using different strategies for dealing with incompatible stimulus-response relationships. The use of different strategies makes it impossible to determine whether or not the processing of the patients is impaired in Parkinson's disease, although further research is suggested to clarify the question. However, the present data suggest that any impairment in response choice is unlikely to contribute to the slowing in CRT in Parkinson's disease under conditions of high stimulus-response compatibility.

Aged↗
PubMed1993

A cladistic analysis of phenotypic associations with haplotypes inferred from restriction endonuclease mapping. IV. Nested analyses with cladogram uncertainty and recombination.

We previously developed an analytical strategy based on cladistic theory to identify subsets of haplotypes that are associated with significant phenotypic deviations. Our initial approach was limited to segments of DNA in which little recombination occurs. In such cases, a cladogram can be constructed from the restriction site data to estimate the evolutionary steps that interrelate the observed haplotypes to one another. The cladogram is then used to define a nested statistical design for identifying mutational steps associated with significant phenotypic deviations. The central assumption behind this strategy is that a mutation responsible for a particular phenotypic effect is embedded within the evolutionary history that is represented by the cladogram. The power of this approach depends on the accuracy of the cladogram in portraying the evolutionary history of the DNA region. This accuracy can be diminished both by recombination and by uncertainty in the estimated cladogram topology. In a previous paper, we presented an algorithm for estimating the set of likely claodgrams and recombination events. In this paper we present an algorithm for defining a nested statistical design under cladogram uncertainty and recombination. Given the nested design, phenotypic associations can be examined using either a nested analysis of variance (for haploids or homozygous strains) or permutation testing (for outcrossed, diploid gene regions). In this paper we also extend this analytical strategy to include categorical phenotypes in addition to quantitative phenotypes. Some worked examples are presented using Drosophila data sets. These examples illustrate that having some recombination may actually enhance the biological inferences that may derived from a cladistic analysis. In particular, recombination can be used to assign a physical localization to a given subregion for mutations responsible for significant phenotypic effects.

Algorithms↗
PubMed1987

Demographic heterogeneity and uncertainty in population projections.

Recent developments in a class of stochastic population processes were used to study the impact of demographic heterogeneity on the uncertainty of population projections. Selected for study by computer simulation were population projections for East Africa designed to quantify opinions regarding expected fertility and mortality declines. Since both fertility and mortality declined in these projections, their laws of evolution may be described as time inhomogeneous. The computer simulation studies reported in this paper strongly suggest that randomized laws of evolution should be taken into account in further developments of population projection methodologies designed formally and computationally to accommodate uncertainty. Variability in fecundability, the kind of demographic heterogeneity studied in this paper, is only one aspect of these randomized laws.

Africa, Eastern↗
PubMed1997

Illness uncertainty, attributional style, and psychological adjustment in older adolescents and young adults with asthma.

Examined psychological adjustment in a college sample of older adolescents and young adults (n = 49) with histories of childhood asthma. A substantial number of subjects evidenced clinically significant levels of overall distress. In addition, greater perceived asthma uncertainty and increased stable attributions for negative events were significantly associated with poorer psychological adjustment after controlling for demographic and disease variables. Further analyses revealed a moderating influence of uncertainty on attribution-adjustment relationships. These findings provide initial support for a cognitive diathesis-stress view of adjustment in long-standing asthma. Results also support a growing body of evidence suggesting that the focus of efforts to enhance adjustment to asthma need to be expanded beyond childhood and early adolescence.

Adaptation, Psychological↗
PubMed2006

Exploratory and confirmatory factor analysis of the Child Uncertainty in Illness Scale among children with chronic illness.

OBJECTIVE: To conduct an exploratory factor analysis (EFA) and a confirmatory factor analysis (CFA) of the Child Uncertainty in Illness Scale (CUIS) with a sample of children and adolescents with a chronic health condition. Developmental differences in factor structure were also examined. METHODS: A sample of 373 children aged 8-18 years with chronic conditions completed the CUIS as a part of a larger battery of measures. RESULTS: The EFA yielded a 16-item two-factor model termed Unpredictability/Ambiguity and Comprehension. The CFA yielded a 14-item two-factor model that fits the data very well, where chi2(df = 74) = 95.396, Comparative Fit Index (CFI) = .973, Tucker Lewis Index (TLI) = .967, and Root Mean Square error of approximation (RMSEA) = .038. No developmental differences were found in underlying factor structures: Deltachi2(df = 12) = 17.754, DeltaCFI = .004, DeltaTLI = -.001, and DeltaRMSEA = .000. CONCLUSIONS: The two-factor CUIS measure could be a useful tool for assessing illness uncertainty among children with chronic illness.

Adolescent↗
PubMed2006

The relationship of hope and illness-related uncertainty to emotional adjustment and adherence among pediatric renal and liver transplant recipients.

OBJECTIVE: To examine, using partial least squares (PLS) modeling, the associations among hope, illness-related uncertainty, anxiety, depression, and adherence in a sample of children with renal and liver transplantations. METHODS: Seventy pediatric renal and liver transplant recipients and their caregivers participated in a 3-month study which involved completing questionnaires and monitoring adherence via self-report and electronic monitoring (MEMS caps). A PLS estimation procedure was used to examine the associations among constructs in the theoretical model. RESULTS: Hope and uncertainty were associated with both depressive symptoms and anxiety, and depressive symptoms were associated with treatment adherence. The association of hope and adherence to treatment was fully mediated by depressive symptoms. CONCLUSIONS: Findings suggest mechanisms for identifying patients that may be at risk for nonadherence and components for intervention programs to improve adherence rates among pediatric transplant recipients.

Adaptation, Psychological↗