A theoretical comparison of two optimization methods for radiofrequency drive schemes in high frequency MRI resonators

In this paper, numerical simulations are used in an attempt to find optimal Source profiles for high frequency radiofrequency (RF) volume coils. Biologically loaded, shielded/unshielded circular and elliptical birdcage coils operating at 170 MHz, 300 MHz and 470 MHz are modelled using the FDTD method for both 2D and 3D cases. Taking advantage of the fact that some aspects of the electromagnetic system are linear, two approaches have been proposed for the determination of the drives for individual elements in the RF resonator. The first method is an iterative optimization technique with a kernel for the evaluation of RF fields inside an imaging plane of a human head model using pre-characterized sensitivity profiles of the individual rungs of a resonator; the second method is a regularization-based technique. In the second approach, a sensitivity matrix is explicitly constructed and a regularization procedure is employed to solve the ill-posed problem. Test simulations show that both methods can improve the B-1-field homogeneity in both focused and non-focused scenarios. While the regularization-based method is more efficient, the first optimization method is more flexible as it can take into account other issues such as controlling SAR or reshaping the resonator structures. It is hoped that these schemes and their extensions will be useful for the determination of multi-element RF drives in a variety of applications.

Area-under-the-curve monitoring of prednisolone for dose optimization in a stable renal transplant population

Background: Renal transplant recipients were noted to appear cushingoid while on low doses of steroid as part of a triple therapy immunosuppression of cyclosporin A (CsA), prednisolone, and azathioprine. Methods: The study group comprised adult renal transplant recipients with stable graft function who had received their renal allograft a minimum of 1 year previously (43 studies undertaken in 22 men and 20 women) with median daily prednisone dose of 7 mg (range 3-10). The control group was healthy nontransplant subjects [median dose 10 mg (10-30)]. Prednisolone bioavailability was measured using a limited 6-hour area under the curve (AUC), with prednisolone measured using specific HPLC assay. Results: The median prednisolone AUC/mg dose for all transplant recipients was significantly greater than the control group by approximately 50% (316 nmol(.)h/L/mg prednisolone versus 218). AUC was significantly higher in female recipients (median 415 versus 297 for men) and in recipients receiving cyclospotin (348 versus 285). The highest AUC was in women on estrogen supplements who were receiving cyclosporin (median 595). A significantly higher proportion of patients on triple therapy had steroid side effects compared with those on steroid and azathioprine (17/27 versus 4/15), more women than men had side effects (14/16 versus 7/22), and the AUC/mg prednisone was greater in those with side effects than without (median 377 versus 288 nmol-h/L/mg). Discussion: The results are consistent with the hypothesis that CsA increases the bioavailability of prednisolone, most likely through inhibition of beta-glycoprotein. The increased exposure to steroid increased the side-effect profile of steroids in the majority of patients. Because the major contributor to AUC is the maximum postdose concentration, it may be possible to use single-point monitoring (2 hours postdose) for routine clinical studies.

Population-based continuous optimization, probabilistic modelling and mean shift

Evolutionary algorithms perform optimization using a population of sample solution points. An interesting development has been to view population-based optimization as the process of evolving an explicit, probabilistic model of the search space. This paper investigates a formal basis for continuous, population-based optimization in terms of a stochastic gradient descent on the Kullback-Leibler divergence between the model probability density and the objective function, represented as an unknown density of assumed form. This leads to an update rule that is related and compared with previous theoretical work, a continuous version of the population-based incremental learning algorithm, and the generalized mean shift clustering framework. Experimental results are presented that demonstrate the dynamics of the new algorithm on a set of simple test problems.

Multiresolution query optimization in an online environment

Multiresolution (or multi-scale) techniques make it possible for Web-based GIS applications to access large dataset. The performance of such systems relies on data transmission over network and multiresolution query processing. In the literature the latter has received little research attention so far, and the existing methods are not capable of processing large dataset. In this paper, we aim to improve multiresolution query processing in an online environment. A cost model for such query is proposed first, followed by three strategies for its optimization. Significant theoretical improvement can be observed when comparing against available methods. Application of these strategies is also discussed, and similar performance enhancement can be expected if implemented in online GIS applications.