Doctor of Philosophy

dissertationWe present a method for absolutely quantifying pharmacokinetic parameters in dynamic contrast-enhanced (DCE)-MRI. This method, known as alternating mini-mization with model (AMM), involves jointly estimating the arterial input function (AIF) and pharmacokinetic parameters from a characteristic set of measured tissue concentration curves. By blindly estimating the AIF, problems associated with AIF measurement in pharmacokinetic modeling, such as signal saturation, flow and partial volume eff ects, and small arterial lumens can be ignored. The blind estimation method described here introduces a novel functional form for the AIF, which serves to simplify the estimation process and reduce the deleterious e ffects of noise on the deconvolution process. Computer simulations were undertaken to assess the performance of the estimation process as a function of the input tissue curves. A con fidence metric for the estimation quality, based on a linear combination of the SNR and diversity of the input curves, is presented. This con fidence metric is then used to allow for localizing the region from which input curves are drawn. Local blood supply to any particular region can then be blindly estimated, along with some measure of con fidence for that estimation. Methods for evaluating the utility of the blind estimation algorithm on clinical data are presented, along with preliminary results on quantifying tissue parameters in soft-tissue sarcomas. The AMM method is applied to in vivo data from both cardiac perfusion and breast cancer scans. The cardiac scans were conducted using a dual-bolus protocol, which provides a measure of truth for the AIF. Twenty data sets were processed with this method, and pharmacokinetic parameter values derived from the blind AIF were compared with those derived from the dual-bolus measured AIF. For seventeen of the twenty datasets there were no statistically signifi cant differences in Ktrans estimates. The cardiac AMM method presented here provides a way to quantify perfusion of myocardial tissue with a single injection of contrast agent and without a special pulse sequence. The resulting parameters are similar to those given by the dual bolus method. The breast cancer scans were processed with the AMM method and the results were compared to an analysis done with the semiquantitative DCE-MRI scans. The e ffects of the temporal sampling rate of the data on the AMM method are examined. The ability of the AMM-derived parameters to distinguish benign and malignant tumors is compared to more conventional methods

A Comparison of Theory-Based and Experimentally Determined Myocardial Signal Intensity Correction Methods in First-Pass Perfusion Magnetic Resonance Imaging

Objectives. To evaluate the impact of correcting myocardial signal saturation on the accuracy of absolute myocardial blood flow (MBF) measurements. Materials and Methods. We performed 15 dual bolus first-pass perfusion studies in 7 dogs during global coronary vasodilation and variable degrees of coronary artery stenosis. We compared microsphere MBF to MBF calculated from uncorrected and corrected MRI signal. Four correction methods were tested, two theoretical methods (Th1 and Th2) and two empirical methods (Em1 and Em2). Results. The correlations with microsphere MBF (n=90 segments) were: uncorrected (y=0.47x+1.1, r=0.70), Th1 (y=0.53x+1.0, r=0.71), Th2 (y=0.62x+0.86, r=0.73), Em1 (y=0.82x+0.86, r=0.77), and Em2 (y=0.72x+0.84, r=0.75). All corrected methods were not significantly different from microspheres, while uncorrected MBF values were significantly lower. For the top 50% of microsphere MBF values, flows were significantly underestimated by uncorrected SI (31%), Th1 (25%), and Th2 (19%), while Em1 (1%), and Em2 (9%) were similar to microsphere MBF. Conclusions. Myocardial signal saturation should be corrected prior to flow modeling to avoid underestimation of MBF by MR perfusion imaging

Using Dynamic Contrast-Enhanced Magnetic Resonance Imaging Data to Constrain a Positron Emission Tomography Kinetic Model: Theory and Simulations

We show how dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) data can constrain a compartmental model for analyzing dynamic positron emission tomography (PET) data. We first develop the theory that enables the use of DCE-MRI data to separate whole tissue time activity curves (TACs) available from dynamic PET data into individual TACs associated with the blood space, the extravascular-extracellular space (EES), and the extravascular-intracellular space (EIS). Then we simulate whole tissue TACs over a range of physiologically relevant kinetic parameter values and show that using appropriate DCE-MRI data can separate the PET TAC into the three components with accuracy that is noise dependent. The simulations show that accurate blood, EES, and EIS TACs can be obtained as evidenced by concordance correlation coefficients >0.9 between the true and estimated TACs. Additionally, provided that the estimated DCE-MRI parameters are within 10% of their true values, the errors in the PET kinetic parameters are within approximately 20% of their true values. The parameters returned by this approach may provide new information on the transport of a tracer in a variety of dynamic PET studies

Open Problems on Central Simple Algebras

We provide a survey of past research and a list of open problems regarding central simple algebras and the Brauer group over a field, intended both for experts and for beginners.Comment: v2 has some small revisions to the text. Some items are re-numbered, compared to v

The effect of obesity on regadenoson-induced myocardial hyperemia: a quantitative magnetic resonance imaging study

The A2(A) receptor agonist, regadenoson, is increasingly used as a vasodilator during nuclear myocardial perfusion imaging. Regadenoson is administered as a single, fixed dose. Given the frequency of obesity in patients with symptoms of heart disease, it is important to know whether the fixed dose of regadenoson produces maximal coronary hyperemia in subjects of widely varying body size. Thirty subjects (12 female, 18 male, mean BMI 30.3 ± 6.5, range 19.6–46.6) were imaged on a 3T magnetic resonance scanner. Imaging with a saturation recovery radial turboFLASH sequence was done first at rest, then during adenosine infusion (140 μg/kg/min) and 30 min later with regadenoson (0.4 mg/5 ml bolus). A 5 cc/s injection of Gd-BOPTA was used for each perfusion sequence, with doses of 0.02, 0.03 and 0.03 mmol/kg, respectively. Analysis of the upslope of myocardial time-intensity curves and quantitative processing to obtain myocardial perfusion reserve (MPR) values were performed for each vasodilator. The tissue upslopes for adenosine and regadenoson matched closely (y = 1.1x + 0.03, r = 0.9). Mean MPR was 2.3 ± 0.6 for adenosine and 2.4 ± 0.9 for regadenoson (p = 0.14). There was good agreement between MPR measured with adenosine and regadenoson (y = 1.1x − 0.06, r = 0.7). The MPR values measured with both agents tended to be lower as BMI increased. There were no complications during administration of either agent. Regadenoson produced fewer side effects. Fixed dose regadenoson and weight adjusted adenosine produce similar measures of MPR in patients with a wide range of body sizes. Regadenoson is a potentially useful vasodilator for stress MRI studies