Biomedical subjects

F DuBois Bowman

Publications and source records attributed to F DuBois Bowman.

11 recordsLinked to original sources

PubMed2007

Improving point predictions of random effects for subjects at high risk.

The prediction of random effects corresponding to subject-specific characteristics (e.g. means or rates of change) can be very useful in medical and epidemiologic research. At times, one may be most interested in obtaining accurate and/or precise predictions for subjects whose characteristic places them in a tail of the distribution. While the typical posterior mean predictor dominates others in terms of overall mean squared error of prediction (MSEP), its tendency to 'overshrink' has motivated research into alternatives emphasizing other criteria. Here, we specifically target MSEP within a certain region (e.g. above a known cut-off for high risk or a specified percentile of the random effect distribution), and we consider minimizing this quantity with and without constraints on overall MSEP efficiency. We use the normal-theory random intercept model to derive prediction methods with potential to yield markedly better performance for subjects in the specified region, given a well-controlled and (if desired) modest concession of overall MSEP. Criteria geared toward classification as well as overall and regional prediction unbiasedness are also provided. We evaluate the proposed techniques and illustrate them using repeated measures data on fasting blood glucose from type 2 diabetes patients. A simulation study verifies that theoretical properties and relative performances of the proposed predictors are essentially maintained when calculating them in practice based on estimated mixed linear model parameters. Straightforward extensions to incorporate covariates and additional random effects are briefly outlined.

Bias↗

PubMed2007

Initial experience with the radiotracer anti-1-amino-3-18F-fluorocyclobutane-1-carboxylic acid with PET/CT in prostate carcinoma.

UNLABELLED: Conventional imaging techniques have serious limitations in the detection, staging, and restaging of prostate carcinoma. Anti-1-amino-3-(18)F-fluorocyclobutane-1-carboxylic acid (anti-(18)F-FACBC)is a synthetic l-leucine analog that has excellent in vitro uptake within the DU-145 prostate carcinoma cell line and orthotopically implanted prostate tumor in nude rats. There is little renal excretion compared with (18)F-FDG. The present study examines anti-(18)F-FACBC uptake in patients with newly diagnosed and recurrent prostate carcinoma. METHODS: Fifteen patients with a recent diagnosis of prostate carcinoma (n = 9) or suspected recurrence (n = 6) underwent 65-min dynamic PET/CT of the pelvis after intravenous injection of 300-410 MBq anti-(18)F-FACBC followed by static body images. Each study was evaluated qualitatively and quantitatively. Maximum standardized uptake values were recorded in the prostate or prostate bed, and within lymph nodes at 4.5 min (early) and 20 min (delayed), and correlated with clinical, imaging and pathologic follow-up. Time-activity curves were also generated for benign and malignant tissue. RESULTS: In the 8 patients with newly diagnosed prostate carcinoma who underwent dynamic scanning, visual analysis correctly identified the presence or absence of focal neoplastic involvement in 40 of 48 prostate sextants. Pelvic nodal status correlated with anti-(18)F-FACBC findings in 7 of 9 patients and was indeterminate in 2 of 9. In all 4 patients in whom there was proven recurrence, visual analysis was successful in identifying disease (1 prostate bed, 3 extraprostatic). In 3 of these patients, (111)In-capromab-pendetide had no significant uptake at nodal and skeletal foci. Malignant lymph node uptake in both the staging and restaging patients was significantly higher than benign nodal uptake. Though uptake faded with time, in all 6 patients with either lymph node metastases or recurrent prostate bed carcinoma, there was intense persistent uptake at 65 min. CONCLUSION: Anti-(18)F-FACBC is a promising radiotracer for imaging prostate carcinoma. Radiotracer uptake was demonstrated in primary and metastatic disease. Future research should investigate the mechanism of radiotracer uptake in normal and pathologic tissue and develop a clinical imaging strategy for initial staging and restaging.

Aged↗

PubMed2006

The neural processing of moral sensitivity to issues of justice and care.

The empirical and theoretical consideration of ethical decision making has focused on the process of moral judgment; however, a precondition to judgment is moral sensitivity, the ability to detect and evaluate moral issues [Rest, J. R. (1984). The major components of morality. In W. Kurtines & J. Gewirtz (Eds.), Morality, moral behaviour, and moral development (pp. 24-38). New York, NY: Wiley]. Using functional magnetic resonance imaging (fMRI) and contextually standardized, real life moral issues, we demonstrate that sensitivity to moral issues is associated with activation of the polar medial prefrontal cortex, dorsal posterior cingulate cortex, and posterior superior temporal sulcus (STS). These activations suggest that moral sensitivity is related to access to knowledge unique to one's self, supported by autobiographical memory retrieval and social perspective taking. We also assessed whether sensitivity to rule-based or "justice" moral issues versus social situational or "care" moral issues is associated with dissociable neural processing events. Sensitivity to justice issues was associated with greater activation of the left intraparietal sulcus, whereas sensitivity to care issues was associated with greater activation of the ventral posterior cingulate cortex, ventromedial and dorsolateral prefrontal cortex, and thalamus. These results suggest a role for access to self histories and identities and social perspectives in sensitivity to moral issues, provide neural representations of the subcomponent process of moral sensitivity originally proposed by Rest, and support differing neural information processing for the interpretive recognition of justice and care moral issues.

Adult↗

PubMed2006

Determining significant connectivity by 4D spatiotemporal wavelet packet resampling of functional neuroimaging data.

An active area of neuroimaging research involves examining functional relationships between spatially remote brain regions. When determining whether two brain regions exhibit significant correlation due to true functional connectivity, one must account for the background spatial correlation inherent in neuroimaging data. We define background correlation as spatiotemporal correlation in the data caused by factors other than neurophysiologically based functional associations such as scanner induced correlations and image preprocessing. We develop a 4D spatiotemporal wavelet packet resampling method which generates surrogate data that preserves only the average background spatial correlation within an axial slice, across axial slices, and through each voxel time series, while excluding the specific correlations due to true functional relationships. We also extend an amplitude adjustment algorithm which adjusts our surrogate data to closely match the amplitude distribution of the original data. Our method improves upon existing wavelet-based methods and extends them to 4D. We apply our resampling technique to determine significant functional connectivity from resting state and motor task fMRI datasets.

Adult↗

PubMed2006

The neural correlates of social anxiety disorder and response to pharmacotherapy.

This study attempted to define further the neural processing events underlying social anxiety in patients with social anxiety disorder (SAD) and their response to pharmacotherapy. Social anxiety-related changes in regional cerebral blood flow were defined by [15O]H2 positron emission tomography (PET) in medication-free individuals with generalized SAD (gSAD), and age- and sex-matched comparison subjects, and analyzed using a linear mixed effects model. PET studies were again acquired in the gSAD individuals following an 8-week, flexible dose treatment trial of nefazodone. Both script-guided mental imagery of an anxiogenic social situation and a confrontational mental arithmetic task were associated with marked increases in self-rated anxiety in both subject groups. For gSAD subjects, social anxiety induced by guided mental imagery was associated with increased activity in the left postcentral gyrus and lenticulate, and the right inferior frontal and middle temporal gyri. Social anxiety induced by the mental arithmetic task was associated with activation of the medial and left dorsolateral prefrontal cortex, cerebellum, thalamus, insula, and ventral striatum. Both tasks were associated with relative decreases in activity in the right amygdala and the hippocampus. A direct group comparison indicated that comparison subjects exhibited a differing pattern of social anxiety-related neural activations. Nefazodone treatment was associated with marked clinical improvement. Comparison of social anxiety-related neural activations prior to and after nefazodone administration indicated greater activity in the precentral gyrus, insula, midbrain/hypothalamus, and middle frontal and anterior cingulate gyrus prior to treatment, and greater activity in the left middle occipital and bilateral lingual gyri, postcentral gyrus, gyrus rectus, and hippocampus after treatment. The results of an analysis relating neural activity and treatment-related changes in symptom severity indicated differential neural responses associated with states of symptom remission vs partial response. The observed social anxiety-related changes in distributed neural activity are consistent with cognitive models of SAD and adaptive decreases in amygdala activity in response to social anxiogenics, and support the association of altered frontal cortical responses with treatment response.

Adult↗

PubMed2004

Modelling of cardiac imaging data with spatial correlation.

Cardiac imaging with single photon emission computed tomography (SPECT) is a common approach for quantifying myocardial perfusion. Fusing serial SPECT studies allows detection and quantification of changes in myocardial perfusion such as those resulting from disease progression or successful treatment therapy for patients with coronary artery disease. The abundance of data for each subject along with the inherent intra-subject correlation due to spatial proximity of multiple perfusion measurements present special analytical challenges. We utilize a standard physiological model of the left ventricle (LV) to construct a general statistical model for cardiac perfusion that incorporates spatial correlation. We illustrate the use of mixed effects models and linear models with correlated errors to estimate myocardial perfusion counts and to compare these counts across serial studies. We address different types of spatial correlation among perfusion measurements in the LV, and we consider various parametric structures for these correlations. We apply the model to data from serial SPECT studies conducted while subjects were in both restful and stressful states approximately two days and one year following a myocardial infarction.

Coronary Circulation↗

PubMed2004

Methods for detecting functional classifications in neuroimaging data.

Data-driven statistical methods are useful for examining the spatial organization of human brain function. Cluster analysis is one approach that aims to identify spatial classifications of temporal brain activity profiles. Numerous clustering algorithms are available, and no one method is optimal for all areas of application because an algorithm's performance depends on specific characteristics of the data. K-means and fuzzy clustering are popular for neuroimaging analyses, and select hierarchical procedures also appear in the literature. It is unclear which clustering methods perform best for neuroimaging data. We conduct a simulation study, based on PET neuroimaging data, to evaluate the performances of several clustering algorithms, including a new procedure that builds on the kth nearest neighbor method. We also examine three stopping rules that assist in determining the optimal number of clusters. Five hierarchical clustering algorithms perform best in our study, some of which are new to neuroimaging analyses, with Ward's and the beta-flexible methods exhibiting the strongest performances. Furthermore, Ward's and the beta-flexible methods yield the best performances for noisy data, and the popular K-means and fuzzy clustering procedures also perform reasonably well. The stopping rules also exhibit good performances for the top five clustering algorithms, and the pseudo-T2 and pseudo-F stopping rules are superior for noisy data. Based on our simulations for both noisy and unscaled PET neuroimaging data, we recommend the combined use of the pseudo-F or pseudo-T2 stopping rule along with either Ward's or the beta-flexible clustering algorithm.

Algorithms↗

PubMed2004

Identifying spatial relationships in neural processing using a multiple classification approach.

The application of statistical classification methods to in vivo functional neuroimaging data makes it possible to explore spatial patterns in task-related changes in neural processing. Cluster analysis is one group of descriptive statistical procedures that can assist in identifying classes of brain regions that exhibit similar task-related functionality. In practice, a limitation of cluster analysis is that the performances of clustering algorithms rely on unknown characteristics of the data, making it difficult to determine which procedure best suits a particular analysis. We present a multiple classification approach that incorporates numerous algorithms, evaluates the associated classifications, and either selects a plausible partition relative to the others considered or pools the results from the numerous methods. The multiple classification approach utilizes a new performance criterion, called the relative information (RI) measure, to evaluate the quality of the candidate partitions and as the basis for producing a composite classification image. Employing multiple classifications, rather than a single algorithm, our methodology increases the chance of detecting the functional relationships within the data and, therefore, produces more reliable results. We apply our methodology to a PET study to explore spatial relationships in measured brain function associated with increasing blood alcohol concentration levels, and we perform a simulation study to evaluate the performance of RI.

Alcoholic Intoxication↗

PubMed2004

Making inferences about projected completors in longitudinal studies.

In this article, we present methodology for making inferences about projected completors in the presence of attrition. The approach is motivated by a clinical trial that investigates a treatment for disability among individuals who sustain severe head injuries. Although most studies attempt to make inferences about the entire study population, our application poses important scientific questions targeting individuals who are likely to complete the study or to remain on protocol for a specified time period. We propose using measures of each individual's dropout inclination to identify projected completors and then building a stratified response model based on projected completion status. We present several prediction measures along with procedures for evaluating accuracy with respect to observed dropout. Estimation of model parameters proceeds using maximum likelihood and restricted maximum likelihood methods. We illustrate the utility of our proposed analysis by using the motivating disability data example.

Algorithms↗

PubMed2003

Modeling intra-subject correlation among repeated scans in positron emission tomography (PET) neuroimaging data.

Many in vivo positron emission tomography (PET) neuroimaging studies record correlates of regional cerebral blood flow (rCBF) in a series of scans for each individual, usually under different experimental conditions. Typical methods for statistical analysis involve fitting voxel-specific general linear models (GLM) that assume spherical normal errors, implying that all voxel-specific rCBF measurements are independent and arise from identical normal probability distributions. While the spherical GLM provides a unified and computationally efficient approach to estimation, the likely correlations among an individual's repeated scans and heteroscedasticity between conditions prompt the use of extended statistical methodology. We outline a more general method to analyze PET data using random effects and correlated errors to model unequal variances across conditions as well as covariances (correlations) among the repeated scans for each individual. We introduce correlation maps to display intra-subject correlations between an individual's rCBF measurements from different scans. We illustrate the application of our model using data from a study of social anxiety and highlight analytical advantages over the spherical GLM.

Cerebrovascular Circulation↗

PubMed2003

Interaction of isoflurane with the dopamine transporter.

BACKGROUND: Isoflurane administration is known to increase extracellular dopamine (DA) concentration. Because the dopamine transporter (DAT) is a key regulator of DA, it is likely affected by isoflurane. This study investigates the hypothesis that isoflurane inhibits DA reuptake by causing DAT to be trafficked into the cell. METHODS: Rhesus monkeys were scanned with positron emission tomography (PET) using [18F]FECNT (a highly specific DAT ligand) while anesthetized with 1% isoflurane. The isoflurane was increased to 2%, and the animals were rescanned. Uptake was analyzed with the tissue reference method using the cerebellum as the reference tissue to determine the binding potential in the putamen. Immunohistochemistry and Western blot analyses were performed in rats to determine if isoflurane administration would change the total amount of DAT. Rats breathed air plus 2% isoflurane for 30 min, and then striatal DAT assays were rapidly performed. immunocytochemistry experiments were performed using human embryonic kidney (HEK) cells stably transfected with human DAT. The cells were exposed to 4% isoflurane for 1 h while the location of DAT was observed with fluorescent confocal microscopy. RESULTS: The [18F]FECNT binding potential in rhesus monkeys decreased by 63 +/- 6% (SEM, n = 5) when isoflurane was increased from 1 to 2% as compared with no significant change (0.7 +/- 2.5%; SEM, n = 5) when the isoflurane concentration was not changed (P < 0.001). No difference in DAT staining between isoflurane-treated and control rats was apparent from visual inspection, and quantitative Western blot analyses showed no significant change in total DAT protein. After isoflurane treatment, focal puncta of intense fluorescence was visible inside the HEK cells. CONCLUSIONS: The experiments indicate that DAT is trafficked into the cell by isoflurane without changing the total amount of DAT in the striatum. The PET data are consistent with this finding, provided that intracellular DAT acquires a conformation that has low affinity for [18F]FECNT. Thus, [18F]FECNT appears to be an excellent agent for measuring plasma membrane-expressed DAT and evaluating DAT trafficking.

Anesthetics, Inhalation↗