MA Parameters Research Articles

Analisis Image Noise dan Nilai Dosis Radiasi Penggunaan Aplikasi Care Dose 4D dan Non Care Dose 4D pada Pesawat MSCT Siemens

Background : One effective technique is contained in a CT Scan to decrease the amount of radiation dose that is received in the use of automatic exposure control (AEC). AEC system of Siemens equipment is called Care Dose 4D. The research is based on unused of the application Care Dose 4D on CT Scan Imaging. The purpose of the research is to determine the differences of image noise and the differences of radiation doses (CTDI) using care dose 4D and Non Care Dose 4D in Siemens MSCT.Methods :The research was quantitative study with experimental approaches that is tested on four water phantom size type. Analysts data is done by statistical tests of Paired T-Test Samples to test the hypothesis and the level difference image information. In this statistical analysis is determined the level of confidence (level of Significance) with a value of α = 0.05.Results : On the using of Nasopharing protocol for children with 130 kV and 130 mAs parameters, using of Care Dose 4D has ability to decrease the image noise value is compared with non Care Dose 4D application. While the adult Nasopharing protocol with 130 kV and 220 mAs parameters, Care Dose 4D doesn’t provide enough impact in the reduction of image noise value if compared with conventional techniques or without using Care Dose 4D applications. Using of children nasopharing protocol application Care Dose 4D even increase radiation closes high enough value in CTDI vol that is 5,03 mGy, but using Nasopharing Care Dose 4D applications for adult can decrease radiation doses high enough value in CTDIvol, that is 2,64 mGy.Conclusion : On the use of children nasopharing protocol application Care Dose 4D even increase radiation closes high enough value in CTDI vol that is 5,03 mGy, while the adult Nasopharing using Care Dose 4D applications can decrease radiation doses high enough value in CTDIvol, that is 2,64 mGy.

Bias reduction of the maximum-likelihood estimator for a conditional Gaussian MA(1) model

ABSTRACTIn this paper, we consider an estimation for the unknown parameters of a conditional Gaussian MA(1) model. In the majority of cases, a maximum-likelihood estimator is chosen because the estimator is consistent. However, for small sample sizes the error is large, because the estimator has a bias of O(n− 1). Therefore, we provide a bias of O(n− 1) for the maximum-likelihood estimator for the conditional Gaussian MA(1) model. Moreover, we propose new estimators for the unknown parameters of the conditional Gaussian MA(1) model based on the bias of O(n− 1). We investigate the properties of the bias, as well as the asymptotical variance of the maximum-likelihood estimators for the unknown parameters, by performing some simulations. Finally, we demonstrate the validity of the new estimators through this simulation study.

A Comprehensive Clinical Decision Support Application Software for dose Optimisation Procedure in CT

CT images are the most common imaging modality after conventional X-ray imaging. There are used in order to determine organ position, location and size in relation to treatment area for treatment planning and for diagnoses of diseases. The general aims of the study is to design a comprehensive clinical decision support application software for patients' dose optimization. The design of the GUI involve the use of mathematical modeling procedure where the modeled equations reduces the data from empirical measurements to real clinical application process for implementation. The final component of the modeling process is the GUI applications. This was done in two different process and procedures. The first was the coding process where a software was developed with written C++ code and integrated on the data capturing application platform for clinical application. The second was the visual indicators where the shape and size were modeled to represent the variation in age and gender that exist between the various model equations. The GUI are then used by radiographers to predict and plan the choice of input parameters for effective managements of doses to patient undergoing abdominal CT examination. Finally, a GUI and CAD models were designed to adequately reflect the comfortable working process of all the mathematical model equations. Reference effective abdominal and renal dose parameters have been established and developed in a data base for clinical application. In addition, the displayed interface on the DICOM interface enable the prediction of CTDI and DLP parameters with known kVp and mAs parameters before imaging.

New methods to estimate the observed noise variance for an ARMA model

Abstract For an ARMA model with an observed noise, the observed noise variance estimation is not only a part of the model identification, but also its estimation accuracy affects the following MA parameter estimation accuracy directly. However, it is difficult to improve the estimation accuracy of the observed noise variance, especially when the observed noise variance is small. In this paper, two new methods are proposed to estimate the observed noise variance accurately. In the first method, the lower lags of the auto-covariance function are used to estimate the observed noise variance with high estimation accuracy, but it is valid only when the AR order is greater than the MA order. In the second method, the ARMA model is approximated as a high-order AR model so that it is effective even though the AR order is equal to or less than the MA order. If the observed noise variance is too small, its estimation error may be too large to valid the estimate. An empirical criterion is proposed to judge the necessity of estimating the observed noise variance. The proposed methods are verified by simulations and applied to the random noise modeling for gyroscopes tentatively.

Fractional Integration in Short Samples: Parametric Versus Semiparametric Methods

The finite sample properties of various parametric and semiparametric estimators of fractional integration are determined using Monte Carlo simulations. Previous work investigating the performance of fractional estimators relied on large sample sizes typical of economic and finance data sets. Here, the simulations are run with sample sizes representative of data sets commonly found in political science - between 40 and 100. Simulations are run on three different data generating processes (0, d, 0), (1, d, 0), and (0,d,1), with the AR and MA parameters and the order of fractional integration, d, varying with the order of fractional integration. The results indicate that semiparametric methods and the parametric frequency domain Whittle estimator are consistent across all ranges of observations with a purely fractional, (0,d,0) process, while the parametric time domain estimator exhibits a negative bias in its estimates. In the presence of a higher-order process the time domain estimator suffers dramatically and the semiparamteric estimators also exhibit bias that is potentially alleviated with proper choice of bandwidth. Throughout, the frequency domain maximum likelihood estimator outperforms other estimators, even in the presence of significant higher frequencies. The results indicate that fractional integration can be reliably estimated with lag lengths of 80 observations, but caution is still urged, particularly with the time domain estimator.

A simple example of an indirect estimator with discontinuous limit theory in the MA(1) model

SUMMARYIndirect estimators usually emerge from two‐step optimization procedures. Each step in such a procedure may induce complexities in the asymptotic theory of the estimator. In this note, we are occupied with a simple example in which the estimator defined by the inversion of the binding function has a ‘discontinuous’ limit theory even in cases where the auxiliary one does not. This example lives in the framework of estimation of the MA (1) parameter. The ‘discontinuities’ involve the dependence of the rate of convergence on the parameter, the non‐continuity of the limit distribution w.r.t. the parameter and the estimator's non‐regularity. We are also occupied with a more complex example where the discontinuities occur because of complexities induced in any step of the defining procedure. We present some Monte Carlo evidence on the quality of the approximations from the limit distributions. Copyright © 2014 Wiley Publishing Ltd

Comparison of low contrast sensitivity among multi-slice CT units using various mAs setting for the potential benefit of non-MRI compatible, stereotactic radiosurgery (SRS) patients

Purpose: To evaluate the low contrast detectability sensitivity among 4-slice, 8-slice and 16-slice CT units using various mAs settings. Findings of the study may elucidate the most optimal imaging parameter for stereotactic radiosurgery (SRS) patients who are not MRI compatible. Methods and Materials : Low contrast targets in the CATPHAN phantom (model: CTP 504, The Phantom Laboratory) were imaged on a 4-slice LightSpeed Advantage™ GE CT scanner (GE Healthcare, WI) and a 16- slice LightSpeed Advantage™ GE CT scanner (GE Healthcare, WI) in 8-slice and 16-slice mode. The CATPHAN CTP515 low contrast targets of size 15, 9, 8, 7, 6, 5, 4, 3 and 2 mm for each contrast difference of 1%, 0.5% and 0.3% from the water-equivalent background was imaged using a SRS protocol. Two image sets per setting were acquired for mAs parameters of 300, 350 and 440. Images were evaluated in a blind study by three independent reviewers. Results: Using 300,350 and 440mAs settings on the 4-slice scanner, the average smallest diameters recorded at 1% contrast were 5 ± 1 mm, 5 ± 1 mm and 5 ± 0 mm and at 0.5% were 7 ± 2 mm, 7 ± 1 mm and 6 ± 1 mm. For the 8 - slice scanner, the average smallest diameters recorded at 1% contrast were 7 ± 0 mm, 6 ± 0 mm and 5 ± 0 mm, and at 0.5% were 12 ± 3 mm, 9 ± 1 mm and 6 ± 1 mm. For the 16 - slice scanner, the average smallest diameters recorded at 1% contrast were 7 ± 1 mm, 7 ± 1 mm and 6 ± 1 mm, and at 0.5% were 11 ± 3 mm, 8 ± 1 mm and 8 ± 1 mm. A difference was observed between the 4 and 8 - slice scanners at 300mAs (p < 0.01) for each contrast level as well as the 4 and 16 slice at 440 (p < 0.01) and 350 (p < 0.01) mAs. Additionally, a difference was observed between each mAs for the 8 slice at 1% (p < 0.01) and 0.5% (p < 0.01) contrast. Conclusion : Results demonstrate consistently improved low contrast detectability as mAs was increased. CT simulation imaging parameters can be optimized to improve low contrast sensitivity for non MRI compatible SRS patients. ---------------- Cite this article as : Stanley D, Narayanasamy G, Breton C, Papanikolaou N, Gutierrez AN. Comparison of low contrast sensitivity among multi-slice CT units using various mAs setting for the potential benefit of non-MRI compatible, stereotactic radiosurgery (SRS) patients. Int J Cancer Ther Oncol 2014; 2(2):020237. DOI: 10.14319/ijcto.0202.37

Guidelines for Applying Statistical Quality Control Method to Monitor Autocorrelated Prcoesses

The implementation of statistical control charts under autocorrelated situations is a critical issue since it has a significant impact on the monitoring capability of manufacturing processes. The objective of this study is to assess the performance of control charts under different scenarios and to optimize the design of control charts to best deal with autocorrelated processes. To achieve the proposed objective, two autoregressive integrated moving average models, ARIMA (1, 0, 1) and ARIMA (0, 1, 1), are utilized to characterize stationary and non-stationary processes. These process models were simulated to achieve the response, average run length (ARL), which is the performance measure of this study. The factorial design of experiment was conducted to quantify the effect of critical factors, i.e., ARIMA coefficients, types of charts (exponentially weighted moving average: EWMA and moving range: MR) and shift sizes on the ARL. The experimental results show that EWMA chart is the most appropriate control chart to monitor autocorrelated observations. Additionally, both AR and MA parameters along with shift sizes have a significant effect on the performance of control charts. Therefore, this study has pointed out a suitable tool for use under the different scenarios of autocorrelation. The validation of the above experimental results was conducted on another ARIMA model, ARIMA (1, 0, 0). If the performance of control charts under autocorrelated disturbances is correctly characterized, practitioners will have guidelines for achieving the highest possible performance potential when deploying SPC.

WE‐C‐103‐04: The Optimization of CT Protocols Using Plots of CTDIvol and of Max and Min MA Versus Patient Size for Actual Clinical Scans Using Automatic Exposure Control (AEC)

Purpose: To determine the usefulness of the knowledge of CTDIvol and mA variations as a function of patient size for optimizing scan parameters in CT imaging using AEC. Methods: Data was collected from actual patient scans for a number of different CT protocols such as standard chest, body, head, vascular imaging, and pediatric body. A GE LightSpeed VCT scanner was used in Smart mA mode in which the user can select the Noise Index, and the maximum and minimum mA allowed during mA modulation. For each different protocol the CTDIvol, minimum mA, maximum mA and patient size where determined for at least 40 patients, along with information on when the mA had reached its specified minimum or maximum value. Plots were made of the CTDIvol versus patient size and of the maximum and minimum mA versus patient size. Results: Initial results demonstrated a significant variation in CTDIvol over the range of adult patient sizes of more than a factor of ten for abdominal imaging. The observation that clinical scans frequently reached the minimum allowed mA indicated that reduction of the rotation time and lowering of the minimum mA parameter would allow lower patient dose and better operation of the AEC system. These results also led us to create separate protocols for small, medium, and large patients, each with a different optimized Noise Index, kV, rotation time, and mA range. These were created in consultation with our radiologists in determining the lowest dose that would provide a clinically acceptable image after the AEC was deemed to be operating optimally. Conclusion: The above analysis can provide significant help in improving CT protocols and lowering patient dose. The plots of CTDIvol versus patient size also helped to educate radiologists in the dose variations to be expected for a range of patient sizes. Equipment grant from GE healthcare.

Edgeworth and Moment Approximations: The Case of MM and QML Estimators for the MA(1) Models

Extending the results in Sargan (1976) and Tanaka (1984), we derive the asymptotic expansions of the distribution, the bias and the mean squared error of the MM and QML estimators of the first-order autocorrelation and the MA parameter for the MA(1) model. It turns out that the asymptotic properties of the estimators depend on whether the mean of the process is known or estimated. A comparison of the moment expansions, either in terms of bias or MSE, reveals that there is not uniform superiority of neither of the estimators, when the mean of the process is estimated. This is also confirmed by simulations. In the zero-mean case, and on theoretical grounds, the QMLEs are superior to the MM ones in both bias and MSE terms. We also discuss how the approximations are affected by moderate deviations from the unit root case. The results presented here are important for bias correction and increasing the efficiency of the estimators.

Wavelet Power: Wavelet Energy Ratio Unit Root Tests

This paper uses wavelet theory to propose a frequency domain nonparametric and tuning parameter free family of unit root tests indexed by the fractional parameter d. The proposed test exploits the wavelet power spectrum of the observed series and its fractional partial sum to construct a test of the unit root based on the ratio of the resulting scaling energies. The construction takes its inspiration from the variance ratio (VR) unit root test of Nielsen (2009) and Fan and Gen cay (2010) (FG). The result is a statistic whose power properties virtually mimic that of the VR statistics but which drastically reduces the severe size distortions suffered by both the VR and FG test in the presence of serially correlated MA(1) errors when the MA parameter is close to negative unity. Any remaining size distortions are virtually eliminated using a modern wavelet resampling technique called wavestrapping. Finally, the test is visibly more robust to size distortions arising from lowering d than its VR counterpart and unlike the FG test, requires no estimation for construction.

Review of Nacim Pak-Shiraz, Shi’i Islam in Iranian Cinema: Religion and Spirituality in Film

Nacim Pak-Shiraz’s monograph on the relation between Iranian Shi’ism and the cinema under the rule of the Islamic Republic aims to unpack religion as a category of analysis in the study of film. Her study raises a number of interesting questions. What constitutes religion in the scholarship about film both inside and outside Iran? How is Shi’ism understood by various factions of Iranian society? How does Shi’ism find expression in Iranian film? One could say that the book is premised on an event: the addition to the annual Fajr International Film Festival of a new category in 2005 of ‘spiritual cinema’ or ‘sinama-ye ma’nagara.’ Fajr, itself, is a much anticipated event celebrating the anniversary of the Iranian Revolution, and a festival in which Iranian and international entries compete for prizes, for best ‘Asian Cinema’ and best ‘International Cinema,’ among other awards. As Pak-Shiraz notes, the addition of the category ‘spiritual cinema’ generated a heated debate amongst journalists, film critics and film fans around the meanings and parameters of the sinama-ye ma’nagara. Intriguing in Pak-Shiraz’s text are the detailed descriptions scattered in every chapter, of interviews she conducted with these constituents, as well as filmmakers and clerics, to determine the spiritual or religious markers of Iranian film. Here she provides records of her own ethnography of several film-related events including the Fajr festival itself and sheds light on the interpretive chasm within Iran of what does and what does not belong under a rubric that is so personal and yet so deeply associated with the theocratic regime itself. A caricature from the first issue of the official newsletter of the festival and translated on page 39 of Pak-Shiraz’s text humorously reveals the difficulties in defining these parameters in film: ‘rain’ as a symbol of the rain of love in film; the ‘wind’ as a symbol of giving oneself over to the wind; the ‘child’ as a symbol of wisdom; the ‘Afghan’ as a symbol of misery; the ‘apple’ as a symbol of love; the ‘camcorder’ as a symbol of innovation in seeing. These presences in film Cont Islam (2014) 8:79–80 DOI 10.1007/s11562-012-0204-0

Admission rapid thrombelastography predicts development of pulmonary embolism in trauma patients

Injury leads to dramatic disturbances in coagulation with increased risk of bleeding followed by a hypercoagulable state. A comprehensive assessment of these coagulation abnormalities can be measured and described by thrombelastography. The purpose of this study was to identify whether admission rapid-thrombelastography (r-TEG) could identify patients at risk of developing pulmonary embolism (PE) during their hospital stay. Patients admitted between September 2009 to February 2011 who met criteria for our highest-level trauma activation and were transported directly from the scene were included in the study. PE defined as clinically suspected and computed tomography angiography confirmed PE. We evaluated r-TEG values with particular attention to the maximal amplitude (mA) parameter that is indicative of overall clot strength. Demographics, vital signs, injury severity, and r-TEG values were then evaluated. In addition to r-TEG values, gender and injury severity score (ISS) were chosen a priori for developing a multiple logistic regression model predicting development of PE. r-TEG was obtained on 2,070 consecutive trauma activations. Of these, 2.5% (53) developed PE, 97.5% (2,017) did not develop PE. Patients in the PE group were older (median age, 41 vs. 33 years, p = 0.012) and more likely to be white (69% vs. 54%, p = 0.036). None of the patients in the PE group sustained penetrating injury (0% vs. 25% in the no-PE group, p < 0.001). The PE group also had admission higher mA values (66 vs. 63, p = 0.050) and higher ISS (median, 31 vs. 19, p = 0.002). When controlling for gender, race, age, and ISS, elevated mA at admission was an independent predictor of PE with an odds ratio of 3.5 for mA > 65 and 5.8 for mA > 72. Admission r-TEG mA values can identify patients with an increased risk of in-hospital PE. Further studies are needed to determine whether alternative anticoagulation strategies should be used for these high-risk patients. Prognostic study, level III.

Implementing option pricing models when asset returns follow an autoregressive moving average process

Motivated by the empirical findings that asset returns or volatilities are predictable, this paper studies the pricing of European options on stock or volatility, the instantaneous changes of which depend upon an autoregressive moving average (ARMA) process. The pricing formula of an ARMA-type option is similar to that of Black and Scholes, except that the total volatility input depends upon the AR and MA parameters. From numerical analyses, the option values are increasing functions of the levels of AR or MA parameters across all moneyness levels. Specifically, the AR effect is more significant than the MA effect. Finally, based on the daily closing prices of TAIEX options from 2004 to 2008, the ad hoc ARMA(1,1) model provides the best in-sample fit and the second best out-of-sample fit, whereas the variance gamma model provides the second best in-sample fit and the best out-of-sample fit. Therefore, both variance gamma model and ad hoc ARMA model are superior models for pricing TAIEX options.

Kohn condition and exotic Newton–Hooke symmetry in the non-commutative Landau problem

N “exotic” [alias non-commutative] particles with masses ma, charges ea and non-commutative parameters θa, moving in a uniform magnetic field B, separate into center-of-mass and internal motions if Kohnʼs condition ea/ma=const is supplemented with eaθa=const. Then the center-of-mass behaves as a single exotic particle carrying the total mass and charge of the system, M and e, and a suitably defined non-commutative parameter Θ. For vanishing electric field off the critical case eΘB≠1, the particles perform the usual cyclotronic motion with modified but equal frequency. The system is symmetric under suitable time-dependent translations which span a (4+2)-parameter centrally-extended subgroup of the “exotic” [i.e., two-parameter centrally-extended] Newton–Hooke group. In the critical case B=Bc=(eΘ)−1 the system is frozen into a static “crystal” configuration. Adding a constant electric field, all particles perform, collectively, a cyclotronic motion combined with a drift perpendicular to the electric field when eΘB≠1. For B=Bc the cyclotronic motion is eliminated and all particles move, collectively, following the Hall law. Our time-dependent symmetries are reduced to the (2+1)-parameter Heisenberg group of centrally-extended translations.

Hybrid bootstrap aided unit root testing

In this paper, we propose a hybrid bootstrap procedure for augmented Dickey-Fuller (ADF) tests for the presence of a unit root. This hybrid proposal combines a time domain parametric autoregressive fit to the data and a nonparametric correction applied in the frequency domain to capture features that are possibly not represented by the parametric model. It is known that considerable size and power problems can occur in small samples for unit root testing in the presence of an MA parameter using critical values of the asymptotic Dickey-Fuller distribution. The benefit of the sieve bootstrap in this situation has been investigated by Chang and Park (J Time Ser Anal 24:379–400, 2003). They showed asymptotic validity as well as substantial improvements for small sample sizes, but the actual sizes of their bootstrap tests were still quite far away from the nominal size. The finite sample performances of our procedure are extensively investigated through Monte Carlo simulations and compared to the sieve bootstrap approach. Regarding the size of the tests, our results show that the hybrid bootstrap remarkably outperforms the sieve bootstrap.

Identification of autoregressive moving average systems based on noise compensation in the correlation domain

This study presents a new scheme for the identification of minimum-phase autoregressive moving average (ARMA) systems from noise-corrupted observations. From the autocorrelation function (ACF) of the observed data, exploiting the characteristics of the zero lag, the authors develop a set of equations containing the lower lags of the ACF and solve the corresponding quadratic eigenvalue problem in order to estimate simultaneously the AR parameters and the observation noise variance. In the proposed identification technique, both the white noise and the periodic impulse-train excitations are considered for the purpose of practical applications. In order to estimate the MA parameters, first, a residual signal is obtained by filtering the noisy observations via the estimated AR parameters. A noise-subtraction algorithm is proposed utilising the estimated noise variance and the AR parameters to reduce the effect of noise from the ACF of the residual signal. The MA parameters are then estimated by using the spectral factorisation corresponding to the noise-compensated ACF of the residual signal. In order to demonstrate the effectiveness of the proposed method, extensive experimentations are performed considering synthetic ARMA systems of different orders in the presence of noise and results are compared with those of some of the existing methods. Computer simulations demonstrate a superior identification results in terms of estimation accuracy and consistency even under heavy noisy conditions. Simulation results are also provided for the identification of a human vocal-tract system using natural speech signals showing a superior performance of the proposed technique in terms of the power spectral density of the synthesised speech signal.

A Markov regime-switching ARMA approach for hedging stock indices

This study considers the hedging effectiveness of applying the N-state Markov regime-switching autoregressive moving-average (MRS-ARMA) model to the S&P-500 and FTSE-100 markets. The distinguishingfeature of this study is to incorporate the observations of serially correlated stockreturns into the hedging analysis. To resolve the problem of NT possible routes induced by the presence of MA parameters associated with the algorithm of Hamilton JD (1989) and a sample of size T, we propose an algorithm by combining the ideas of Hamilton JD (1989) and Gray SF (1996). We find that the hedging performances of the three proposed MRS-MA(1) strategies herein are superior to their corresponding MRS counterparts considered in Alizadeh A and Nomikos N (2004) over the out-of-sample periods, even when we realistically track the transaction costs generated from rebalancing the hedged portfolios. © 2010 Wiley Periodicals, Inc. Jrl Fut Mark 31:165–191, 2011

Developing optimized CT scan protocols: Phantom measurements of image quality

Purpose The increasing frequency of computerized tomography (CT) examinations is well documented, leading to concern about potential radiation risks for patients. However, the consequences of not performing the CT examination and missing injuries and disease are potentially serious, impacting upon correct patient management. The ALARA principle of dose optimization must be employed for all justified CT examinations. Dose indicators displayed on the CT console as either CT dose index (CTDI) and/or dose length product (DLP), are used to indicate dose and can quantify improvements achieved through optimization. Key scan parameters contributing to dose have been identified in previous literature and in previous work by our group. The aim of this study was to optimize the scan parameters of mA; kV and pitch, whilst maintaining image quality and reducing dose. This research was conducted using psychophysical image quality measurements on a CT quality assurance (QA) phantom establishing the impact of dose optimization on image quality parameters. Method Current CT scan parameters for head (posterior fossa and cerebrum), abdomen and chest examinations were collected from 57% of CT suites available nationally in Malta ( n = 4). Current scan protocols were used to image a Catphan ®600 CT QA phantom whereby image quality was assessed. Each scan parameter: mA; kV and pitch were systematically reduced until the contrast resolution (CR), spatial resolution (SR) and noise were significantly lowered. The Catphan ®600 images, produced by the range of protocols, were evaluated by 2 expert observers assessing CR, SR and noise. The protocol considered as the optimization threshold was just above the setting that resulted in a significant reduction in CR and noise but not affecting SR at the 95% confidence interval. Results The limit of optimization threshold was determined for each CT suite. Employing optimized parameters, CTDI and DLP were both significantly reduced ( p ≤ 0.001) by 0–49% and 0–51% respectively. Below the optimization threshold, CR and noise were significantly affected ( p ≤ 0.05) but not SR ( p ≥ 0.083). The threshold value is the value below which CR and noise were affected. Conclusion Optimization was effected through the establishment of the limits at which image quality is detrimentally reduced by dose reduction. This work established the mA, kV and pitch changes necessary to achieve the optimization thresholds, reducing the dose and the limit at which psychophysical image quality is significantly decreased. Further work will evaluate these settings in the clinical environment.

Estudo de fatores pró-trombóticos e pró-inflamatórios na cardiomiopatia chagásica

The relationship between inflammatory and prothrombotic activity in chagas cardiomyopathy and in other etiologies is unclear. To study the profile of pro-thrombotic and pro-inflammatory markers in patients with Chagas' heart failure and compare them with patients of non-chagas etiology. Cross-sectional cohort. left ventricle ejection fraction (LVEF) < 45% and onset time to symptoms > one month. The patients were divided into two groups: group 1 (G1) - seropositive for Chagas - and group 2 (G2) - seronegative for Chagas. Pro-inflammatory factor: Ultra-sensitive CRP. Pro-thrombotic factors: thrombin-antithrombin factor, fibrinogen, von Willebrand factor antigen, plasma P-selectin and thromboelastography. Sample calculated for 80% power, assuming a standard deviation difference of 1/3; significant p if it is < 0.05. Fisher's exact test for categorical variables; unpaired Student's t-test for parametric continuous variables and Mann-Whitney test for nonparametric continuous variables. Between January and June 2008, 150 patients were included, 80 in G1 and 70 in G2. Both groups maintained the averages of high sensitivity CRP above baseline values, however, there was no significant difference (p = 0.328). The fibrinogen levels were higher in G2 than in G1 (p = 0.015). Among the thromboelastography variables, the parameters MA (p=0.0013), G (p=0.0012) and TG (p =0.0005) were greater in G2 than in G1. There is no evidence of greater pro-thrombotic status among patients with Chagas disease. The levels of fibrinogen and the MA, G and TG parameters of the thromboelastography point to pro-thrombotic status among non-chagas patients. Both groups had increased inflammatory activity.