Biomedical subjects

Donald B Twieg

Publications and source records attributed to Donald B Twieg.

6 recordsLinked to original sources

PubMed2006

Rapid mapping of flow velocity using a new PARSE method.

A new method for flow velocity mapping is presented here. Instead of the conventional approach of employing two images (velocity sensitive and control) to generate velocity information, in the new method one determines the velocity directly from a single-shot acquisition by solving an inverse problem. This technique is a variant of single-shot parameter assessment by retrieval from signal encoding (SS-PARSE). The results of simulation and phantom studies show strong agreement with the actual velocities. The prototype method can measure velocities in the range of -50 to 50 cm/s, which is roughly appropriate for future applications in dynamic blood flow measurement in carotid arteries.

Algorithms↗

PubMed2006

Developing functional magnetic resonance imaging techniques for alert macaque monkeys.

Functional magnetic resonance imaging (fMRI) has developed rapidly into a major non-invasive tool for studying the human brain. However, due to a variety of technical difficulties, it has yet to be widely adopted for use in alert, trained non-human primates. Our laboratory has been developing techniques for such fMRI studies. As background, we first consider basic principles of fMRI imaging, experimental design, and post-processing. We discuss appropriate MRI system hardware and components for conducting fMRI studies in alert macaques, and the animal preparation and behavior necessary for optimal experiments. Finally, we consider alternative fMRI techniques using exogenous contrast agents, arterial spin labeling, and more direct measures of neural activation.

Animals↗

PubMed2005

Study of temporal stationarity and spatial consistency of fMRI noise using independent component analysis.

Spatial independent component analysis (ICA) was used to study the temporal stationarity and spatial consistency of structured functional MRI (fMRI) noise. Spatial correlations have been used in the past to generate filters for the removal of structured noise for each time-course in an fMRI dataset. It would be beneficial to produce a multivariate filter based on the same principles. ICA is examined to determine if it has properties that are beneficial for this type of filtering. Six fMRI baseline datasets were decomposed via spatial ICA. The time-courses associated with each component were tested for wide-sense stationarity using the wide sense stationarity quotient (WSS). Each dataset was divided into three subsets and each subset was decomposed. The components of first and third subset were matched by the strength of their correlation. The components produced by ICA were found to have largely nonstationary time-courses. Despite the temporal nonstationarity in the data, ICA was found to produce consistent spatial components. The degree of correlation among components differed depending on the amount of dimension reduction performed on the data. It was found that a relatively small number of dimensions produced components that are potentially useful for generating a spatial fMRI filter.

Algorithms↗

PubMed2004

Assessment of brain tumor angiogenesis inhibitors using perfusion magnetic resonance imaging: quality and analysis results of a phase I trial.

PURPOSE: To determine thresholds of quality for a T2*-weighted perfusion magnetic resonance imaging (MRI) study and evaluate the effects of an angiogenesis inhibitor on relative blood flow and volume changes in brain tumor patients in a multi-institution setting. MATERIALS AND METHODS: A total of 36 volunteers from four participating institutions with clinically diagnosed malignant gliomas were studied using perfusion MRI protocols. These included a baseline study and follow-up studies every eight weeks to evaluate the effect of an anti-angiogenic agent on tumor perfusion. Quality tests were performed on the perfusion imaging data by defining statistical thresholds of acceptance. Region of interest (ROI) analysis was performed on tumors and kinetic parameters were normalized with respect to normal tissue. RESULTS: Statistical thresholds for goodness of the gamma variate fit, T2* recovery, and mean signal full-width half-minimum (FWHMin) were computed for our data sets with a 99% one-sided confidence interval; these were 6.91%, 79.48%, and 23.35 seconds, respectively. Decreases in-blood volume and flow measurements were observed in patients with documented clinical response. CONCLUSION: Malignant brain tumors have altered perfusion parameters that may be used to understand and monitor neovascularization. This permits non-invasive assessment of the efficacy of angiogenesis inhibiting drugs.

Angiogenesis Inhibitors↗

PubMed2003

Parsing local signal evolution directly from a single-shot MRI signal: a new approach for fMRI.

In this work a new single-shot MRI method, single-shot parameter assessment by retrieval from signal encoding (SS-PARSE), is introduced. This method abandons a fundamental simplifying assumption that is used in conventional MRI methods. Established MRI methods implicitly assume that the local intrinsic signal does not change its amplitude or phase during signal acquisition, even though these changes may be substantial, especially during the relatively long signals used in single-shot image acquisitions. SS-PARSE, on the other hand, acknowledges local decay and phase evolution, and models each signal datum as a sample from (k,t)-space rather than k-space. Because of this more accurate signal model, SS-PARSE promises improved performance in terms of accuracy and robustness, but requires more intensive reconstruction computations. The theoretical properties of the method are discussed, and simulation results are presented that demonstrate more robust and accurate measurements of relaxation rate changes associated with brain activation in functional MRI (fMRI), freedom from geometric errors due to off-resonance frequencies, and better tolerance of the large susceptibility gradients that occur naturally in parts of the brain. In addition, this technique has the potential to assess nonexponential relaxation behavior during a single-shot signal.

Algorithms↗

PubMed2003

Improved depiction of small anatomic structures in MR images using Gaussian-weighted spirals and zero-filled interpolation.

Partial-volume artifacts reduce the contrast and continuity of small structures in magnetic resonance images. Zero-filled interpolation (ZFI) has been known for some time as a useful technique to reduce partial-volume artifacts and improve the appearance of small structures and edges. However, its use is limited by the fact that ZFI can exacerbate image artifacts. For example, it can exacerbate Gibbs ringing, also known as the truncation artifact, which manifests itself as spurious ringing around sharp edges. Currently, the most common technique to address this problem is post-acquisition filtering, which causes blurring in the image. Using ZFI in conjunction with a variable-density sampling method designed to reduce ringing is proposed as a possible solution to this problem. This approach is demonstrated with a Gaussian-weighted spiral and is compared to conventional spiral sampling both with and without the application of a filter used to reduce ringing. The two spiral sampling techniques are compared using simulations, phantom images, and in vivo brain images. The Gaussian-weighted spiral demonstrates reduced ringing without the loss of spatial resolution commonly associated with post-acquisition filtering. Additionally, this sampling technique is shown to work well in conjunction with ZFI to reduce partial-volume artifacts without the apparent increase in Gibbs ringing usually associated with zero-filled reconstruction. This approach will be most useful for imaging techniques such as MR angiography which are known to be sensitive to partial-volume effects, as well as when imaging anatomic regions associated with more severe Gibbs ringing.

Brain↗