Biomedical subjects

Timothy D Johnson

Publications and source records attributed to Timothy D Johnson.

24 records · Page 2Linked to original sources

PubMed2003

Clonus after human spinal cord injury cannot be attributed solely to recurrent muscle-tendon stretch.

Clonus, presented behaviorally as rhythmic distal joint oscillation, is a common pathology that occurs secondary to spinal cord injury (SCI) and other neurological disabilities. There are two predominant theories as to the underlying mechanism of clonus. The prevailing one is that clonus results from recurrent activation of stretch reflexes. An alternative hypothesis is that clonus results from the action of a central oscillator. We present evidence that the mechanism underlying clonus in individuals with SCI is not solely related to muscle stretch. We studied electromyography (EMG) of the soleus (SOL), medial gastrocnemius (MG), tibialis anterior (TA), medial and lateral hamstrings, vastus medialis, vastus lateralis, and rectus femoris from subjects with clinically complete and clinically incomplete SCI during stretch-induced ankle clonus, stepping, and non-weight-bearing standing. Clonic EMG of the SOL, MG, and TA occurred synchronously and were not consistently related to muscle-tendon stretch in any of the conditions studied. Further, EMG activity during stretch-induced ankle clonus, stepping, and non-weight-bearing standing had similar burst frequency, burst duration, silent period duration, and coactivation among muscles, indicating that clonic EMG patterns occurred over a wide range of kinematic and kinetic conditions, and thus proprioceptive inputs. These results suggest that the repetitive clonic bursts could not be attributable solely to immediate afferent feedback such as recurrent muscle stretch. However, these results support the theory that the interaction of central mechanisms and peripheral events may be responsible for clonus.

Adult↗

PubMed2003

A Bayesian change-point analysis of electromyographic data: detecting muscle activation patterns and associated applications.

Many facets of neuromuscular activation patterns and control can be assessed via electromyography and are important for understanding the control of locomotion. After spinal cord injury, muscle activation patterns can affect locomotor recovery. We present a novel application of reversible jump Markov chain Monte Carlo simulation to estimate activation patterns from electromyographic data. We assume the data to be a zero-mean, heteroscedastic process. The variance is explicitly modeled using a step function. The number and location of points of discontinuity, or change-points, in the step function, the inter-change-point variances, and the overall mean are jointly modeled along with the mean and variance from baseline data. The number of change-points is considered a nuisance parameter and is integrated out of the posterior distribution. Whereas current methods of detecting activation patterns are deterministic or provide only point estimates, ours provides distributional estimates of muscle activation. These estimates, in turn, are used to estimate physiologically relevant quantities such as muscle coactivity, total integrated energy, and average burst duration and to draw valid statistical inferences about these quantities.

Bayes Theorem↗

PubMed2003

Bayesian deconvolution analysis of pulsatile hormone concentration profiles.

Many hormones are secreted into the circulatory system in a pulsatile manner and are cleared exponentially. The most common method of analyzing these systems is to deconvolve the hormone concentration into a secretion function and a clearance function. Accurate estimation of the model parameters depends on the number and location of the secretion pulses. To date, deconvolution analysis assumes the number and approximate location of these pulses are known a priori. In this article, we present a novel Bayesian approach to deconvolution that jointly models the number of pulses along with all other model parameters. Our method stochastically searches for the secretion pulses. This is accomplished by viewing the set of parameters that define the pulses as a point process. Pulses are determined by a birth-death process which is embedded in Markov chain Monte Carlo algorithm. This idea originated with Stephens (2000, Annals of Statistics 28, 40-74) in the context of finite mixture model density estimation, where the number of mixture components is unknown. There are several advantages that our model enjoys over the traditional frequentist approaches. These advantages are highlighted with four datasets consisting of serum concentration levels of luteinizing hormone obtained from ovariectomized ewes.

Animals↗

PubMed2003

Evaluation of cancer therapy using diffusion magnetic resonance imaging.

Assessment of the effectiveness of cancer therapy traditionally relies on comparison of tumor images acquired before and after therapeutic intervention by inspection of gross anatomical images to evaluate changes in tumor size. The potential for imaging to provide additional insights related to the therapeutic impact would be enhanced if a specific parameter or combination of parameters could be identified that reflect tissue changes at the cellular or physiological level. This information could also provide a more sensitive and earlier indicator of treatment response in an individual animal or patient. Diffusion magnetic resonance imaging can detect relatively small changes in tissue structure at the cellular level and thus provides an opportunity to quantitatively and serially follow therapeutic-induced changes in solid tumors. This article provides an overview of the use of diffusion magnetic resonance imaging as a surrogate marker for quantitating treatment responsiveness in both preclinical and clinical studies.

Animals↗

PubMed2002

Diffusion MRI: a new strategy for assessment of cancer therapeutic efficacy.

The use of anatomical imaging in clinical oncology practice traditionally relies on comparison of patient scans acquired before and following completion of therapeutic intervention. Therapeutic success is typically determined from inspection of gross anatomical images to assess changes in tumor size. Imaging could provide significant additional insight into therapeutic impact if a specific parameter or combination of parameters could be identified which reflect tissue changes at the cellular or physiologic level. This would provide an early indicator or treatment response/outcome in an individual patient before completion of therapy. Moreover, response of a tumor to therapeutic intervention may be heterogeneous. The use of imaging could assist in delineating therapeutic-induced spatial heterogeneity within a tumor mass by providing information related to specific regions that are resistant or responsive to treatment. Largely untapped potential resides in exploratory methods such as diffusion MRI, which is a nonvolumetric intravoxel measure of tumor response based upon water molecular mobility. Alterations in water mobility reflect changes in tissue structure at the cellular level. While the clinical utility of diffusion MRI for oncologic practice is still under active investigation, this overview on the use of diffusion MRI for the evaluation of brain tumors will serve to introduce how this approach may be applied in the future for the management of patients with solid tumors.

Brain Neoplasms↗

PubMedDate not supplied

A methodology for registration of a histological slide and in vivo MRI volume based on optimizing mutual information.

We present a method for registering histology and in vivo imaging that requires minimal microtoming and is automatic following the user's initialization. In this demonstration, we register a single hematoxylin-and-eosin-stained histological slide of a coronal section of a rat brain harboring a 9L gliosarcoma with an in vivo 7T MR image volume of the same brain. Because the spatial resolution of the in vivo MRI is limited, we add the step of obtaining a high spatial resolution, ex vivo MRI in situ for intermediate registration. The approach taken was to maximize mutual information in order to optimize the registration between all pairings of image data whether the sources are MRI, tissue block photograph, or stained sample photograph. The warping interpolant used was thin plate splines with the appropriate basis function for either 2-D or 3-D applications. All registrations were implemented by user initialization of the approximate pose between the two data sets, followed by automatic optimization based on maximizing mutual information. Only the higher quality anatomical images were used in the registration process; however, the spatial transformation was directly applied to a quantitative diffusion image. Quantitative diffusion maps from the registered location appeared highly correlated with the H&E slide. Overall, this approach provides a robust method for coregistration of in vivo images with histological sections and will have broad applications in the field of functional and molecular imaging.

Animals↗