Generalized eMC implementation for Monte Carlo dose calculation of electron beams from different machine types

The electron Monte Carlo (eMC) dose calculation algorithm available in the Eclipse treatment planning system (Varian Medical Systems) is based on the macro MC method and uses a beam model applicable to Varian linear accelerators. This leads to limitations in accuracy if eMC is applied to non-Varian machines. In this work eMC is generalized to also allow accurate dose calculations for electron beams from Elekta and Siemens accelerators. First, changes made in the previous study to use eMC for low electron beam energies of Varian accelerators are applied. Then, a generalized beam model is developed using a main electron source and a main photon source representing electrons and photons from the scattering foil, respectively, an edge source of electrons, a transmission source of photons and a line source of electrons and photons representing the particles from the scrapers or inserts and head scatter radiation. Regarding the macro MC dose calculation algorithm, the transport code of the secondary particles is improved. The macro MC dose calculations are validated with corresponding dose calculations using EGSnrc in homogeneous and inhomogeneous phantoms. The validation of the generalized eMC is carried out by comparing calculated and measured dose distributions in water for Varian, Elekta and Siemens machines for a variety of beam energies, applicator sizes and SSDs. The comparisons are performed in units of cGy per MU. Overall, a general agreement between calculated and measured dose distributions for all machine types and all combinations of parameters investigated is found to be within 2% or 2 mm. The results of the dose comparisons suggest that the generalized eMC is now suitable to calculate dose distributions for Varian, Elekta and Siemens linear accelerators with sufficient accuracy in the range of the investigated combinations of beam energies, applicator sizes and SSDs.

Rapid downregulation of innate immune cells, interleukin-12 and interleukin-23 in generalized pustular psoriasis with infliximab in combination with acitretin

Generalized pustular psoriasis (GPP) is a severe inflammatory disease characterized by recurrent eruptions of sterile pustules on erythematous skin. Although tumor necrosis factor (TNF) antagonists may lead to a rapid resolution of GPP, the mechanism of action of these agents remains to be investigated. Here, we sought to evaluate markers of immune response in the skin of a patient who experienced a rapid amelioration of GPP after treatment with infliximab and acitretin.

Oral prednisolone induced acute generalized exanthematous pustulosis due to corticosteroids of group A confirmed by epicutaneous testing and lymphocyte transformation tests

BACKGROUND: Acute generalized exanthematous pustulosis (AGEP) is a rare cutaneous eruption which is often provoked by drugs. CASE REPORT: We report 2 cases of AGEP which showed rapidly spreading pustular eruptions accompanied by malaise, fever and neutrophilia after the administration of systemic prednisolone (corticosteroid of group A, hydrocortisone type). The histological examination showing neutrophilic subcorneal spongiform pustules was consistent with the diagnosis of AGEP. In both cases the rash cleared within a week upon treatment with topical steroids (corticosteroid of group D1, betamethasonedipropionate type and corticosteroid of group D2, hydrocortisone-17-butyrate type). Three months after recovery, the sensitization to corticosteroids of group A was confirmed by epicutaneous testing and positive lymphocyte transformation tests. CONCLUSION: These cases show that systemic corticosteroids can induce AGEP and demonstrate that epicutaneous testing and lymphocyte transformation tests may be helpful in identifying the causative drug. Our data support previous reports indicating an important role for drug-specific T cells in inducing neutrophil inflammation in this disease.

Asymptotics for Marginal Generalized Linear Models With Sparse Correlations

Marginal generalized linear models can be used for clustered and longitudinal data by fitting a model as if the data were independent and using an empirical estimator of parameter standard errors. We extend this approach to data where the number of observations correlated with a given one grows with sample size and show that parameter estimates are consistent and asymptotically Normal with a slower convergence rate than for independent data, and that an information sandwich variance estimator is consistent. We present two problems that motivated this work, the modelling of patterns of HIV genetic variation and the behavior of clustered data estimators when clusters are large.

Classification Using Generalized Partial Least Squares

The advances in computational biology have made simultaneous monitoring of thousands of features possible. The high throughput technologies not only bring about a much richer information context in which to study various aspects of gene functions but they also present challenge of analyzing data with large number of covariates and few samples. As an integral part of machine learning, classification of samples into two or more categories is almost always of interest to scientists. In this paper, we address the question of classification in this setting by extending partial least squares (PLS), a popular dimension reduction tool in chemometrics, in the context of generalized linear regression based on a previous approach, Iteratively ReWeighted Partial Least Squares, i.e. IRWPLS (Marx, 1996). We compare our results with two-stage PLS (Nguyen and Rocke, 2002A; Nguyen and Rocke, 2002B) and other classifiers. We show that by phrasing the problem in a generalized linear model setting and by applying bias correction to the likelihood to avoid (quasi)separation, we often get lower classification error rates.

Posterior Simulation in the Generalized Linear Model with Semiparmetric Random Effects

Generalized linear mixed models with semiparametric random effects are useful in a wide variety of Bayesian applications. When the random effects arise from a mixture of Dirichlet process (MDP) model, normal base measures and Gibbs sampling procedures based on the Pólya urn scheme are often used to simulate posterior draws. These algorithms are applicable in the conjugate case when (for a normal base measure) the likelihood is normal. In the non-conjugate case, the algorithms proposed by MacEachern and Müller (1998) and Neal (2000) are often applied to generate posterior samples. Some common problems associated with simulation algorithms for non-conjugate MDP models include convergence and mixing difficulties. This paper proposes an algorithm based on the Pólya urn scheme that extends the Gibbs sampling algorithms to non-conjugate models with normal base measures and exponential family likelihoods. The algorithm proceeds by making Laplace approximations to the likelihood function, thereby reducing the procedure to that of conjugate normal MDP models. To ensure the validity of the stationary distribution in the non-conjugate case, the proposals are accepted or rejected by a Metropolis-Hastings step. In the special case where the data are normally distributed, the algorithm is identical to the Gibbs sampler.

Gauss-Seidel Estimation of Generalized Linear Mixed Models with Application to Poisson Modeling of Spatially Varying Disease Rates

Generalized linear mixed models (GLMMs) provide an elegant framework for the analysis of correlated data. Due to the non-closed form of the likelihood, GLMMs are often fit by computational procedures like penalized quasi-likelihood (PQL). Special cases of these models are generalized linear models (GLMs), which are often fit using algorithms like iterative weighted least squares (IWLS). High computational costs and memory space constraints often make it difficult to apply these iterative procedures to data sets with very large number of cases. This paper proposes a computationally efficient strategy based on the Gauss-Seidel algorithm that iteratively fits sub-models of the GLMM to subsetted versions of the data. Additional gains in efficiency are achieved for Poisson models, commonly used in disease mapping problems, because of their special collapsibility property which allows data reduction through summaries. Convergence of the proposed iterative procedure is guaranteed for canonical link functions. The strategy is applied to investigate the relationship between ischemic heart disease, socioeconomic status and age/gender category in New South Wales, Australia, based on outcome data consisting of approximately 33 million records. A simulation study demonstrates the algorithm's reliability in analyzing a data set with 12 million records for a (non-collapsible) logistic regression model.

Generalized dilating diathesis in patients with popliteal arterial aneurysm

BACKGROUND: Aim of this study was to analyse the relationship between popliteal artery aneurysm (PAA) and generalized arteriomegaly. PATIENTS AND METHODS: In this consecutive serie, thirty-three patients (1 woman, mean age 69.7 +/- 9.6 years) undergoing PAA repair between 1996 and 2000 agreed to participate in a duplex screening program to assess the diameters of the infrarenal abdominal aorta, common and external iliac, common and superficial femoral and contralateral popliteal arteries as well as common carotid and brachial arteries. RESULTS: The prevalence of arteriomegaly and aneurysmal disease, respectively, was as follows: abdominal aorta 15/33 (45.5%) and 8/33 (24.2%), common iliac artery 34/66 (51.5%) and 23/66 (34.8%), common femoral artery 55/66 (83.3%) and 7/66 (10.6%) as well as contralateral popliteal artery 7/33 (21.2%) 15/33 (45.5%). Significantly larger carotid artery diameters were found comparing PAA patients with age- and body surface adjusted healthy controls (p < 0.001). Furthermore, patients with multiple peripheral arterial aneurysms had significantly larger diameters of the brachial (p < 0.02) and external iliac (p < 0.005). CONCLUSIONS: Our findings support the hypothesis of a diathesis for a generalized arteriomegaly with a predilection for further aneurysms of the abdominal aorta, iliac arteries, femoral and contralateral popliteal arteries in patients with PAA.

Chronic stimulation of the globus pallidus internus for treatment of non-dYT1 generalized dystonia and choreoathetosis: 2-year follow up

OBJECT: The authors studied the long-term efficacy of deep brain stimulation (DBS) of the posteroventral lateral globus pallidus internus up to 2 years postoperatively in patients with primary non-DYT1 generalized dystonia or choreoathetosis. The results are briefly compared with those reported for DBS in DYT1 dystonia (Oppenheim dystonia), which is caused by the DYT1 gene. METHODS: Enrollment in this prospective expanded pilot study was limited to adult patients with severely disabling, medically refractory non-DYT1 generalized dystonia or choreoathetosis. Six consecutive patients underwent follow-up examinations at defined intervals of 3 months, 1 year, and 2 years postsurgery. There were five women and one man, and their mean age at surgery was 45.5 years. Formal assessments included both the Burke-Fahn-Marsden dystonia scale and the recently developed Unified Dystonia Rating Scale. Two patients had primary generalized non-DYT1 dystonia, and four suffered from choreoathetosis secondary to infantile cerebral palsy. Bilateral quadripolar DBS electrodes were implanted in all instances, except in one patient with markedly asymmetrical symptoms. There were no adverse events related to surgery. The Burke-Fahn-Marsden scores in the two patients with generalized dystonia improved by 78 and 71% at 3 months, by 82 and 69% at 1 year, and by 78 and 70% at 2 years postoperatively. This was paralleled by marked amelioration of disability scores. The mean improvement in Burke-Fahn-Marsden scores in patients with choreoathetosis was 12% at 3 months, 29% at 1 year, and 23% at 2 years postoperatively, which was not significant. Two of these patients thought that they had achieved marked improvement at 2 years postoperatively, although results of objective evaluations were less impressive. In these two patients there was a minor but stable improvement in disability scores. All patients had an improvement in pain scores at the 2-year follow-up review. Medication was tapered off in both patients with generalized dystonia and reduced in two of the patients with choreoathetosis. All stimulation-induced side effects were reversible on adjustment of the DBS settings. Energy consumption of the batteries was considerably higher than in patients with Parkinson disease. CONCLUSIONS: Chronic pallidal DBS is a safe and effective procedure in generalized non-DYT1 dystonia, and it may become the procedure of choice in patients with medically refractory dystonia. Postoperative improvement of choreoathetosis is more modest and varied, and subjective ratings of outcome may exceed objective evaluations.

LOCAL DIGITAL CONTROL OF POWER ELECTRONIC CONVERTERS IN A DC MICROGRID BASED ON A-PRIORI DERIVATION OF SWITCHING SURFACES

In power electronic basedmicrogrids, the computational requirements needed to implement an optimized online control strategy can be prohibitive. The work presented in this dissertation proposes a generalized method of derivation of geometric manifolds in a dc microgrid that is based on the a-priori computation of the optimal reactions and trajectories for classes of events in a dc microgrid. The proposed states are the stored energies in all the energy storage elements of the dc microgrid and power flowing into them. It is anticipated that calculating a large enough set of dissimilar transient scenarios will also span many scenarios not specifically used to develop the surface. These geometric manifolds will then be used as reference surfaces in any type of controller, such as a sliding mode hysteretic controller. The presence of switched power converters in microgrids involve different control actions for different system events. The control of the switch states of the converters is essential for steady state and transient operations. A digital memory look-up based controller that uses a hysteretic sliding mode control strategy is an effective technique to generate the proper switch states for the converters. An example dcmicrogrid with three dc-dc boost converters and resistive loads is considered for this work. The geometric manifolds are successfully generated for transient events, such as step changes in the loads and the sources. The surfaces corresponding to a specific case of step change in the loads are then used as reference surfaces in an EEPROM for experimentally validating the control strategy. The required switch states corresponding to this specific transient scenario are programmed in the EEPROM as a memory table. This controls the switching of the dc-dc boost converters and drives the system states to the reference manifold. In this work, it is shown that this strategy effectively controls the system for a transient condition such as step changes in the loads for the example case.