Luiz Otávio Murta Junior

Influences of surface and solvent on retention of HEMA/mixture components after evaporation

OBJECTIVES This study examined the retention of solvents within experimental HEMA/solvent primers after two conditions for solvent evaporation: from a free surface or from dentine surface. METHODS Experimental primers were prepared by mixing 35% HEMA with 65% water, methanol, ethanol or acetone (v/v). Aliquots of each primer (50 microl) were placed on glass wells or they were applied to the surface of acid-etched dentine cubes (2mm x 2mm x 2mm) (n=5). For both conditions (i.e. from free surface or dentine cubes), change in primers mass due to solvent evaporation was gravimetrically measured for 10min at 51% RH and 21 degrees C. The rate of solvent evaporation was calculated as a function of loss of primers mass (%) over time. Data were analysed by two-way ANOVA and Student-Newman-Keuls (p<0.05). RESULTS There were significant differences between solvent retention (%) and evaporation rate (%/min) depending on the solvent present in the primer and the condition for evaporation (from free surface or dentine cubes) (p<0.05). For both conditions, the greatest amount of retained solvent was observed for HEMA/water primer. The rate of solvent evaporation for HEMA/acetone primer was almost 2- to 10-times higher than for HEMA/water primer depending whether evaporation occurred, respectively, from a free surface or dentine cubes. The rate of solvent evaporation varied with time, being in general highest at the earliest periods. CONCLUSIONS The rate of solvent evaporation and its retention into HEMA/solvent primers was influenced by the type of the solvent and condition allowed for their evaporation.

Isotropic anomalous filtering in Diffusion-Weighted Magnetic Resonance Imaging

Noise is inherent to Diffusion-Weighted Magnetic Resonance Imaging (DWI) and noise reduction methods are necessary. Although process based on classical diffusion is one of the most used approaches for digital image, anomalous diffusion has the potential for image enhancement and it has not been tested for DWI noise reduction. This study evaluates Anomalous Diffusion (AD) filter as DWI enhancement method. The proposed method was applied to magnetic resonance diffusion weighted images (DW-MRI) with different noise levels. Results show better performance for anomalous diffusion when compared to classical diffusion approach. The proposed method has shown potential in DWI enhancement and can be an important process to improve quality in DWI for neuroimage-based diagnosis.Noise is inherent to Diffusion-Weighted Magnetic Resonance Imaging (DWI) and noise reduction methods are necessary. Although process based on classical diffusion is one of the most used approaches for digital image, anomalous diffusion has the potential for image enhancement and it has not been tested for DWI noise reduction. This study evaluates Anomalous Diffusion (AD) filter as DWI enhancement method. The proposed method was applied to magnetic resonance diffusion weighted images (DW-MRI) with different noise levels. Results show better performance for anomalous diffusion when compared to classical diffusion approach. The proposed method has shown potential in DWI enhancement and can be an important process to improve quality in DWI for neuroimage-based diagnosis.

Use of the q-Gaussian Function in Radial Basis Function Networks

Radial Basis Function Networks (RBFNs) have been successfully employed in several function approximation and pattern recognition problems. In RBFNs, radial basis functions are used to compute the activation of artificial neurons. The use of different radial basis functions in RBFN has been reported in the literature. Here, the use of the q-Gaussian function as a radial basis function in RBFNs is investigated. An interesting property of the q-Gaussian function is that it can continuously and smoothly reproduce different radial basis functions, like the Gaussian, the Inverse Multiquadratic, and the Cauchy functions, by changing a real parameter q. In addition, the mixed use of different shapes of radial basis functions in only one RBFN is allowed. For this purpose, a Genetic Algorithm is employed to select the number of hidden neurons, and center, width and q parameter of the q-Gaussian radial basis function associated with each radial unit. The RBF Network with the q-Gaussian RBF is compared to RBF Networks with Gaussian, Cauchy, and Inverse Multiquadratic RBFs in problems in the Medical Informatics domain.

Changes in the Complexity of Heart Rate Variability with Exercise Training Measured by Multiscale Entropy-Based Measurements

Quantifying complexity from heart rate variability (HRV) series is a challenging task, and multiscale entropy (MSE), along with its variants, has been demonstrated to be one of the most robust approaches to achieve this goal. Although physical training is known to be beneficial, there is little information about the long-term complexity changes induced by the physical conditioning. The present study aimed to quantify the changes in physiological complexity elicited by physical training through multiscale entropy-based complexity measurements. Rats were subject to a protocol of medium intensity training (n=13) or a sedentary protocol (n=12). One-hour HRV series were obtained from all conscious rats five days after the experimental protocol. We estimated MSE, multiscale dispersion entropy (MDE) and multiscale SDiffq from HRV series. Multiscale SDiffq is a recent approach that accounts for entropy differences between a given time series and its shuffled dynamics. From SDiffq, three attributes (q-attributes) were derived, namely SDiffqmax, qmax and qzero. MSE, MDE and multiscale q-attributes presented similar profiles, except for SDiffqmax. qmax showed significant differences between trained and sedentary groups on Time Scales 6 to 20. Results suggest that physical training increases the system complexity and that multiscale q-attributes provide valuable information about the physiological complexity.

Relationship between microvascular changes, autonomic denervation, and myocardial fibrosis in Chagas cardiomyopathy: Evaluation by MRI and SPECT imaging

Background The relationship between microvasculopathy, autonomic denervation, and myocardial fibrosis, in Chagas cardiomyopathy is incompletely understood. The aim of this study was to explore the relative extent and anatomic distribution of myocardial hypoperfusion, autonomic denervation, and myocardial scarring using Single-Photon Emission Computerized Tomography (SPECT) imaging and Magnetic Resonance Imaging (MRI). Methods Thirteen patients with Chagas disease all had Iodine-123-metaiodobenzylguanidine (MIBG) SPECT, 99m Tc-Sestamibi (MIBI) rest-stress SPECT, and gadolinium late enhancement MRI imaging within a 2-month interval. The anatomic location and extent of denervation, of stress-induced hypoperfusion and fibrosis, were assessed through image co-registration and quantification of abnormal tissue areas as a percent of total myocardium. Results The results showed a strong general anatomic concordance between areas of hypoperfusion, denervation, and fibrosis, suggesting that the three abnormal features may be correlated. Myocardial denervation was anatomically and quantitatively closely associated areas of stress hypoperfusion. Conclusion Combined myocardial analysis of the extent and location of autonomic denervation, hypoperfusion, and scarring may allow for better understanding of the pathophysiology of Chagas cardiomyopathy. Autonomic myocardial denervation may be a more sensitive marker of cardiac involvement in Chagas Disease than finding by other imaging modalities.

The impact of artifact correction methods of RR series on heart rate variability parameters.

Heart rate variability (HRV) analysis is widely used to investigate the autonomic regulation of the cardiovascular system. HRV is often analyzed using RR time series, which can be affected by different types of artifacts. Although there are several artifact correction methods, there is no study that compares their performances in actual experimental contexts. This work aimed to evaluate the impact of different artifact correction methods on several HRV parameters. Initially, 36 ECG recordings of control rats or rats with heart failure or hypertension were analyzed to characterize artifact occurrence rates and distributions, to be mimicked in simulations. After a rigorous analysis, only 16 recordings ( n = 16) with artifact-free segments of at least 10,000 beats were selected. RR interval losses were then simulated in the artifact-free (reference) time series according to real observations. Correction methods applied to simulated series were deletion, linear interpolation, cubic spline interpolation, modified moving average window, and nonlinear predictive interpolation. Linear (time- and frequency-domain) and nonlinear HRV parameters were calculated from corrupted-corrected time series, as well as for reference series to evaluate the accuracy of each correction method. Results show that NPI provides the overall best performance. However, several correction approaches, for example the simple deletion procedure, can provide good performance in some situations, depending on the HRV parameters under consideration. NEW & NOTEWORTHY This work analyzes the performance of some correction techniques commonly applied to the missing beats problem in RR time series. From artifact-free RR series, spurious values were inserted based on actual data of experimental settings. We intend our work to be a guide to show how artifacts should be corrected to preserve as much as possible the original heart rate variability properties.

Effects of changing blood viscosity and heart rate on vena contracta width as evaluated by color Doppler flow mapping. An in vitro study with a pulsatile flow model.

Background: There is only limited knowledge on how the quantification of valvular regurgitation by color Doppler is affected by changing blood viscosity. This study was designed to evaluate the effect of changing blood viscosity on the vena contracta width using an in vitro model of valvular insufficiency capable of providing ample variation in the rate and stroke volume. Methods: We constructed a pulsatile flow model filled with human blood at varying hematocrit (15%, 35%, and 55%) and corresponding blood viscosity (blood/water viscosity: 2.6, 4.8, 9.1) levels in which jets were driven through a known orifice (7 mm2) into a 110 mL compliant receiving chamber (compliance: 2.2 mL/mmHg) by a pulsatile pump. In addition, we used variable pump stroke volumes (5, 7.5, and 10 mL) and rates (40, 60, and 80 ppm). Vena contracta region was imaged using a 3.5 MHz transducer. Pressure and volume in the flow model were kept constant during each experimental condition, as well as ultrasound settings. Results: Blood viscosity variation in the experimental range did not induce significant changes in vena contracta dimensions. Also, vena contracta width did not change from normal to low hematocrit and viscosity levels. A very modest increase only in vena contracta dimension was observed at very high level of blood viscosity when hematocrit was set to 55% . Pump rate, in the evaluated range, did not influence vena contracta width. These results in controlled experimental settings suggest that the vena contracta is an accurate quantitative method for quantifying valvular regurgitation even when this condition is associated with anemia, a frequent finding in patients with valvular heart disease.

High-voltage electric stimulation of the donor site of skin grafts accelerates the healing process. A randomized blinded clinical trial

INTRODUCTION Severe burns benefit from skin grafting, and grafting surgery is of great importance in the treatment of these injuries. As a result, there is formation of an additional wound at the donor site, which is painful and susceptible to infection. However, the therapeutic approach to these problems at donor sites for skin grafting is insufficiently explored in the literature. AIM To evaluate electrical stimulation of the donor sites of burn patients treated by grafting surgery. METHODS This work evaluated 30 donor sites of cutaneous graft burn patients treated with high-voltage electrical stimulation. Subjects were randomized into two groups: electrical stimulation (GES), treated with electrostimulation (50min, 100Hz, twin pulses 15 us, monophasic), and the sham group (GS), treated by the same procedures but without current. Pain was assessed by visual analog scale daily before and after the electrical stimulation. The time elapsed until complete epithelization was evaluated (time of primary dressing detached spontaneously). Skin temperature was measured by thermography. The characteristics of donor sites were qualitatively evaluated using images and the plug-in CaPAS® (Carotid Plaque Analysis Software). RESULTS The results showed a significant decrease in pain, which was absent on the third day in the GES and the sixth day in the GS. The time the primary dressing detached spontaneously in days decreased (p<0.05) (4.7±0.2) compared to the GS group (7.0±1.3). Donor site healing characteristics such as vascularization, pigmentation, height, the quantity of crust formed, irregularities, and the quality of healing was better in the GES; moreover, homogeneity and inertia of the images confirmed higher healing quality. CONCLUSION As a result of the study, the technology shows promise and merits a larger study with objective assessments and different physical variables.

Enhancing quality in Diffusion Tensor Imaging with anisotropic anomalous diffusion filter

Introduction: Diffusion tensor imaging (DTI) is an important medical imaging modality that has been useful to the study of microstructural changes in neurological diseases. However, the image noise level is a major practical limitation, in which one simple solution could be the average signal from a sequential acquisition. Nevertheless, this approach is time-consuming and is not often applied in the clinical routine. In this study, we aim to evaluate the anisotropic anomalous diffusion (AAD) filter in order to improve the general image quality of DTI. Methods: A group of 20 healthy subjects with DTI data acquired (3T MR scanner) with different numbers of averages (N=1,2,4,6,8, and 16), where they were submitted to 2-D AAD and conventional anisotropic diffusion filters. The Relative Mean Error (RME), Structural Similarity Index (SSIM), Coefficient of Variation (CV) and tractography reconstruction were evaluated on Fractional Anisotropy (FA) and Apparent Diffusion Coefficient (ADC) maps. Results: The results point to an improvement of up to 30% of CV, RME, and SSIM for the AAD filter, while up to 14% was found for the conventional AD filter (p<0.05). The tractography revealed a better estimative in fiber counting, where the AAD filter resulted in less FA variability. Furthermore, the AAD filter showed a quality improvement similar to a higher average approach, i.e. achieving an image quality equivalent to what was seen in two additional acquisitions. Conclusions: In general, the AAD filter showed robustness in noise attenuation and global image quality improvement even in DTI images with high noise level.

Populational brain models of diffusion tensor imaging for statistical analysis: a complementary information in common space

Abstract Introduction : The search for human brain templates has been progressing in the past decades and in order to understand disease patterns a need for a standard diffusion tensor imaging (DTI) dataset was raised. For this purposes, some DTI templates were developed which assist group analysis studies. In this study, complementary information to the most commonly used DTI template is proposed in order to offer a patient-specific statistical analysis on diffusion-weighted data. Methods : 131 normal subjects were used to reconstruct a population-averaged template. After image pre processing, reconstruction and diagonalization, the eigenvalues and eigenvectors were used to reconstruct the quantitative DTI maps, namely fractional anisotropy (FA), mean diffusivity (MD), relative anisotropy (RA), and radial diffusivity (RD). The mean absolute error (MAE) was calculated using a voxel-wise procedure, which informs the global error regarding the mean intensity value for each quantitative map.