Performance assessment of the single photon emission microscope: high spatial resolution SPECT imaging of small animal organs

The single photon emission microscope (SPEM) is an instrument developed to obtain high spatial resolution single photon emission computed tomography (SPECT) images of small structures inside the mouse brain. SPEM consists of two independent imaging devices, which combine a multipinhole collimator, a high-resolution, thallium-doped cesium iodide [CsI(Tl)] columnar scintillator, a demagnifying/intensifier tube, and an electron-multiplying charge-coupling device (CCD). Collimators have 300- and 450-µm diameter pinholes on tungsten slabs, in hexagonal arrays of 19 and 7 holes. Projection data are acquired in a photon-counting strategy, where CCD frames are stored at 50 frames per second, with a radius of rotation of 35 mm and magnification factor of one. The image reconstruction software tool is based on the maximum likelihood algorithm. Our aim was to evaluate the spatial resolution and sensitivity attainable with the seven-pinhole imaging device, together with the linearity for quantification on the tomographic images, and to test the instrument in obtaining tomographic images of different mouse organs. A spatial resolution better than 500 µm and a sensitivity of 21.6 counts·s-1·MBq-1 were reached, as well as a correlation coefficient between activity and intensity better than 0.99, when imaging 99mTc sources. Images of the thyroid, heart, lungs, and bones of mice were registered using 99mTc-labeled radiopharmaceuticals in times appropriate for routine preclinical experimentation of <1 h per projection data set. Detailed experimental protocols and images of the aforementioned organs are shown. We plan to extend the instrument's field of view to fix larger animals and to combine data from both detectors to reduce the acquisition time or applied activity.

Prediction of soil orders with high spatial resolution: response of different classifiers to sampling density

The objective of this work was to evaluate sampling density on the prediction accuracy of soil orders, with high spatial resolution, in a viticultural zone of Serra Gaúcha, Southern Brazil. A digital elevation model (DEM), a cartographic base, a conventional soil map, and the Idrisi software were used. Seven predictor variables were calculated and read along with soil classes in randomly distributed points, with sampling densities of 0.5, 1, 1.5, 2, and 4 points per hectare. Data were used to train a decision tree (Gini) and three artificial neural networks: adaptive resonance theory, fuzzy ARTMap; self‑organizing map, SOM; and multi‑layer perceptron, MLP. Estimated maps were compared with the conventional soil map to calculate omission and commission errors, overall accuracy, and quantity and allocation disagreement. The decision tree was less sensitive to sampling density and had the highest accuracy and consistence. The SOM was the less sensitive and most consistent network. The MLP had a critical minimum and showed high inconsistency, whereas fuzzy ARTMap was more sensitive and less accurate. Results indicate that sampling densities used in conventional soil surveys can serve as a reference to predict soil orders in Serra Gaúcha.

Methodological approaches to planar and volumetric scintigraphic imaging of small volume targets with high spatial resolution and sensitivity

Single-photon emission computed tomography (SPECT) is a non-invasive imaging technique, which provides information reporting the functional states of tissues. SPECT imaging has been used as a diagnostic tool in several human disorders and can be used in animal models of diseases for physiopathological, genomic and drug discovery studies. However, most of the experimental models used in research involve rodents, which are at least one order of magnitude smaller in linear dimensions than man. Consequently, images of targets obtained with conventional gamma-cameras and collimators have poor spatial resolution and statistical quality. We review the methodological approaches developed in recent years in order to obtain images of small targets with good spatial resolution and sensitivity. Multipinhole, coded mask- and slit-based collimators are presented as alternative approaches to improve image quality. In combination with appropriate decoding algorithms, these collimators permit a significant reduction of the time needed to register the projections used to make 3-D representations of the volumetric distribution of target’s radiotracers. Simultaneously, they can be used to minimize artifacts and blurring arising when single pinhole collimators are used. Representation images are presented, which illustrate the use of these collimators. We also comment on the use of coded masks to attain tomographic resolution with a single projection, as discussed by some investigators since their introduction to obtain near-field images. We conclude this review by showing that the use of appropriate hardware and software tools adapted to conventional gamma-cameras can be of great help in obtaining relevant functional information in experiments using small animals.

Radarsat backscattering from an agricultural scene

Orbital remote sensing in the microwave electromagnetic region has been presented as an important tool for agriculture monitoring. The satellite systems in operation have almost all-weather capability and high spatial resolution, which are features appropriated for agriculture. However, for full exploration of these data, an understanding of the relationships between the characteristics of each system and agricultural targets is necessary. This paper describes the behavior of backscattering coefficient (sigma°) derived from calibrated data of Radarsat images from an agricultural area. It is shown that in a dispersion diagram of sigma° there are three main regions in which most of the fields can be classified. The first one is characterized by low backscattering values, with pastures and bare soils; the second one has intermediate backscattering coefficients and comprises well grown crops mainly; and a third one, with high backscattering coefficients, in which there are fields with strong structures causing a kind of double bounce effect. The results of this research indicate that the use of Radarsat images is optimized when a multitemporal analysis is done making the best use of the agricultural calendar and of the dynamics of different cultures.

Land use/cover classification in the Brazilian Amazon using satellite images

Land use/cover classification is one of the most important applications in remote sensing. However, mapping accurate land use/cover spatial distribution is a challenge, particularly in moist tropical regions, due to the complex biophysical environment and limitations of remote sensing data per se. This paper reviews experiments related to land use/cover classification in the Brazilian Amazon for a decade. Through comprehensive analysis of the classification results, it is concluded that spatial information inherent in remote sensing data plays an essential role in improving land use/cover classification. Incorporation of suitable textural images into multispectral bands and use of segmentation‑based method are valuable ways to improve land use/cover classification, especially for high spatial resolution images. Data fusion of multi‑resolution images within optical sensor data is vital for visual interpretation, but may not improve classification performance. In contrast, integration of optical and radar data did improve classification performance when the proper data fusion method was used. Among the classification algorithms available, the maximum likelihood classifier is still an important method for providing reasonably good accuracy, but nonparametric algorithms, such as classification tree analysis, have the potential to provide better results. However, they often require more time to achieve parametric optimization. Proper use of hierarchical‑based methods is fundamental for developing accurate land use/cover classification, mainly from historical remotely sensed data.

Magnetic resonance imaging of the vagina: an overview for radiologists with emphasis on clinical decision making

AbstractMagnetic resonance imaging is a method with high contrast resolution widely used in the assessment of pelvic gynecological diseases. However, the potential of such method to diagnose vaginal lesions is still underestimated, probably due to the scarce literature approaching the theme, the poor familiarity of radiologists with vaginal diseases, some of them relatively rare, and to the many peculiarities involved in the assessment of the vagina. Thus, the authors illustrate the role of magnetic resonance imaging in the evaluation of vaginal diseases and the main relevant findings to be considered in the clinical decision making process.

Cromatografia gasosa ultrarrápida: uma visão geral sobre parâmetros, instrumentação e aplicações

Since the introduction of GC there has been an ongoing interest in reducing time of analysis resulting in new terms and definitions such as ultra fast gas chromatography (UF-GC). One of the most used definitions describes UF-GC as a technique that combines the employment of short narrow bore column with very fast temperature programming rates producing chromatographic peaks in the range of 50 ms and allowing separations times in 1-2 min or less. This paper summarizes the analytical approaches, the main parameters involved and the instrumentation towards UF-GC.

A quimiometria nos cursos de graduação em química: proposta do uso da análise multivariada na determinação de pkª

An experiment was proposed applying the Chemometric approach of Multivariate Analysis for inclusion in undergraduate Chemistry courses to promote and expand the use of this analytical-statistical tool. The experiment entails the determination of the acid dissociation constant of dyes via UV-Vis electronic spectrophotometry. The dyes used show from simple equilibrium to very complex systems involving up to four protolytic species with high spectral overlap. The Chemometric methodology was more efficient than univariate methods. For use in classes, it is up to the teacher to decide which systems should be utilized given the time constraints and laboratory conditions.

Connexin hemichannels and cell-cell channels: comparison of properties

Connexin46 (Cx46) forms functional hemichannels in the absence of contact by an apposed hemichannel and we have used these hemichannels to study gating and permeation at the single channel level with high time resolution. Using both cell-attached and -excised patch configurations, we find that single Cx46 hemichannels exhibit some properties expected of half of a gap junction channel, as well as novel properties. Cx46 hemichannels have a large unitary conductance (~300 pS) and a relatively large pore as inferred from permeability to TEA. Both monovalent cations and anions can permeate, but cations are substantially more permeable. The open channel conductance shows marked inward rectification in symmetric salts. We find that the conductance and permeability properties of Cx46 cell-cell channels can be explained by the series addition of two hemichannels. These data suggest that the pore structures of unapposed hemichannels and cell-cell channels are conserved. Also like cell-cell channels, unapposed Cx46 hemichannels are closed by elevated levels of H+ or Ca2+ ions on the cytoplasmic face. Closure occurs in excised patches indicating that the actions of these agents do not require a soluble cytoplasmic factor. Fast (<0.5 ms) application of H+ to either side of the open hemichannel causes an immediate small reduction in unitary conductance followed by complete closure with latencies that are dependent on H+ concentration and side of application; sensitivity is much greater to H+ on the cytoplasmic side. Closure by cytoplasmic H+ does not require that the hemichannel be open. Thus, H+ ions readily permeate Cx46 hemichannels, but at high enough concentration close them by acting at a cytoplasmic site(s) that causes a conformational change resulting in complete closure. Extracellular H+ may permeate to act on the cytoplasmic site or act on a lower affinity extracellular site. Thus, the unapposed hemichannel is a valuable tool in addressing fundamental questions concerning the operation of gap junction channels that are difficult to answer by existing methods. The ability of Cx46, and perhaps other connexins, to form functional unapposed hemichannels that are opened by moderate depolarization may represent an unexplored role of connexins as mediators of transport across the plasma membrane.

EEG spike source localization before and after surgery for temporal lobe epilepsy: a BOLD EEG-fMRI and independent component analysis study

Simultaneous measurements of EEG-functional magnetic resonance imaging (fMRI) combine the high temporal resolution of EEG with the distinctive spatial resolution of fMRI. The purpose of this EEG-fMRI study was to search for hemodynamic responses (blood oxygen level-dependent - BOLD responses) associated with interictal activity in a case of right mesial temporal lobe epilepsy before and after a successful selective amygdalohippocampectomy. Therefore, the study found the epileptogenic source by this noninvasive imaging technique and compared the results after removing the atrophied hippocampus. Additionally, the present study investigated the effectiveness of two different ways of localizing epileptiform spike sources, i.e., BOLD contrast and independent component analysis dipole model, by comparing their respective outcomes to the resected epileptogenic region. Our findings suggested a right hippocampus induction of the large interictal activity in the left hemisphere. Although almost a quarter of the dipoles were found near the right hippocampus region, dipole modeling resulted in a widespread distribution, making EEG analysis too weak to precisely determine by itself the source localization even by a sophisticated method of analysis such as independent component analysis. On the other hand, the combined EEG-fMRI technique made it possible to highlight the epileptogenic foci quite efficiently.

Mathematical equation correction to spectral and transport interferences in high-resolution continuum source flame atomic absorption spectrometry: determination of lead in phosphoric acid

In this work, a new mathematical equation correction approach for overcoming spectral and transport interferences was proposed. The proposal was applied to eliminate spectral interference caused by PO molecules at the 217.0005 nm Pb line, and the transport interference caused by variations in phosphoric acid concentrations. Correction may be necessary at 217.0005 nm to account for the contribution of PO, since Atotal217.0005 nm = A Pb217.0005 nm + A PO217.0005 nm. This may be easily done by measuring other PO wavelengths (e.g. 217.0458 nm) and calculating the relative contribution of PO absorbance (A PO) to the total absorbance (Atotal) at 217.0005 nm: A Pb217.0005 nm = Atotal217.0005 nm - A PO217.0005 nm = Atotal217.0005 nm - k (A PO217.0458 nm). The correction factor k is calculated from slopes of calibration curves built up for phosphorous (P) standard solutions measured at 217.0005 and 217.0458 nm, i.e. k = (slope217.0005 nm/slope217.0458 nm). For wavelength integrated absorbance of 3 pixels, sample aspiration rate of 5.0 ml min-1, analytical curves in the 0.1 - 1.0 mg L-1 Pb range with linearity better than 0.9990 were consistently obtained. Calibration curves for P at 217.0005 and 217.0458 nm with linearity better than 0.998 were obtained. Relative standard deviations (RSD) of measurements (n = 12) in the range of 1.4 - 4.3% and 2.0 - 6.0% without and with mathematical equation correction approach were obtained respectively. The limit of detection calculated to analytical line at 217.0005 nm was 10 µg L-1 Pb. Recoveries for Pb spikes were in the 97.5 - 100% and 105 - 230% intervals with and without mathematical equation correction approach, respectively.

Persistent asthma in adults: comparison of high resolution computed tomography of the lungs after one year of follow-up

OBJECTIVE: The aims of this study were to evaluate the role of high resolution computed tomography of the torax in detecting abnormalities in chronic asthmatic patients and to determine the behavior of these lesions after at least one year. METHOD: Fourteen persistent asthmatic patients with a mean forced expiratory volume in 1-second that was 63% of predicted and a mean forced expiratory volume in 1-second /forced vital capacity of 60% had two high resolution computed tomographys separated by an interval of at least one year. RESULTS: All 14 patients had abnormalities on both scans. The most common abnormality was bronchial wall thickening, which was present in all patients on both computed tomographys. Bronchiectasis was suggested on the first computed tomography in 5 of the 14 (36%) patients, but on follow-up, the bronchial dilatation had disappeared in 2 and diminished in a third. Only one patient had any emphysematous changes; a minimal persistent area of paraseptal emphysema was present on both scans. In 3 patients, a "mosaic" appearance was observed on the first scan, and this persisted on the follow-up computed tomography. Two patients had persistent areas of mucoid impaction. In a third patient, mucus plugging was detected only on the second computed tomography. CONCLUSIONS: We conclude that there are many abnormalities on the high resolution computed tomography of patients with persistent asthma. Changes suggestive of bronchiectasis, namely bronchial dilatation, frequently resolve spontaneously. Therefore, the diagnosis of bronchiectasis by high resolution computed tomography in asthmatic patients must be made with caution, since bronchial dilatation can be reversible or can represent false dilatation. Nonsmoking chronic asthmatic subjects in this study had no evidence of centrilobular or panacinar emphysema.

Evaluation of geostatistical techniques to estimate the spatial distribution of aboveground biomass in the Amazon rainforest using high-resolution remote sensing data

ABSTRACT The spatial distribution of forest biomass in the Amazon is heterogeneous with a temporal and spatial variation, especially in relation to the different vegetation types of this biome. Biomass estimated in this region varies significantly depending on the applied approach and the data set used for modeling it. In this context, this study aimed to evaluate three different geostatistical techniques to estimate the spatial distribution of aboveground biomass (AGB). The selected techniques were: 1) ordinary least-squares regression (OLS), 2) geographically weighted regression (GWR) and, 3) geographically weighted regression - kriging (GWR-K). These techniques were applied to the same field dataset, using the same environmental variables derived from cartographic information and high-resolution remote sensing data (RapidEye). This study was developed in the Amazon rainforest from Sucumbíos - Ecuador. The results of this study showed that the GWR-K, a hybrid technique, provided statistically satisfactory estimates with the lowest prediction error compared to the other two techniques. Furthermore, we observed that 75% of the AGB was explained by the combination of remote sensing data and environmental variables, where the forest types are the most important variable for estimating AGB. It should be noted that while the use of high-resolution images significantly improves the estimation of the spatial distribution of AGB, the processing of this information requires high computational demand.

Sensitivity of the Amazon biome to high resolution climate change projections

ABSTRACT: Despite the reduction in deforestation rate in recent years, the impact of global warming by itself can cause changes in vegetation cover. The objective of this work was to investigate the possible changes on the major Brazilian biome, the Amazon Rainforest, under different climate change scenarios. The dynamic vegetation models may simulate changes in vegetation distribution and the biogeochemical processes due to climate change. Initially, the Inland dynamic vegetation model was forced with initial and boundary conditions provided by CFSR and the Eta regional climate model driven by the historical simulation of HadGEM2-ES. These simulations were validated using the Santarém tower data. In the second part, we assess the impact of a future climate change on the Amazon biome by applying the Inland model forced with regional climate change projections. The projections show that some areas of rainforest in the Amazon region are replaced by deciduous forest type and grassland in RCP4.5 scenario and only by grassland in RCP8.5 scenario at the end of this century. The model indicates a reduction of approximately 9% in the area of tropical forest in RCP4.5 scenario and a further reduction in the RCP8.5 scenario of about 50% in the eastern region of Amazon. Although the increase of CO2 atmospheric concentration may favour the growth of trees, the projections of Eta-HadGEM2-ES show increase of temperature and reduction of rainfall in the Amazon region, which caused the forest degradation in these simulations.

Evaluation of a linear spectral mixture model and vegetation indices (NDVI and EVI) in a study of schistosomiasis mansoni and Biomphalaria glabrata distribution in the state of Minas Gerais, Brazil

This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.