Performance of diagnostic centers in the classification of opportunistic screening mammograms from the Brazilian public health system (SUS)

Objective To evaluate the performance of diagnostic centers in the classification of mammography reports from an opportunistic screening undertaken by the Brazilian public health system (SUS) in the municipality of Goiânia, GO, Brazil in 2010. Materials and Methods The present ecological study analyzed data reported to the Sistema de Informação do Controle do Câncer de Mama (SISMAMA) (Breast Cancer Management Information System) by diagnostic centers involved in the mammographic screening developed by the SUS. Based on the frequency of mammograms per BI-RADS® category and on the limits established for the present study, the authors have calculated the rate of conformity for each diagnostic center. Diagnostic centers with equal rates of conformity were considered as having equal performance. Results Fifteen diagnostic centers performed mammographic studies for SUS and reported 31,198 screening mammograms. The performance of the diagnostic centers concerning BI-RADS classification has demonstrated that none of them was in conformity for all categories, one center presented conformity in five categories, two centers, in four categories, three centers, in three categories, two centers, in two categories, four centers, in one category, and three centers with no conformity. Conclusion The results of the present study demonstrate unevenness in the diagnostic centers performance in the classification of mammograms reported to SISMAMA from the opportunistic screening undertaken by SUS.

Classification of chronic obstructive pulmonary disease based on chest radiography

Objective Quantitative analysis of chest radiographs of patients with and without chronic obstructive pulmonary disease (COPD) determining if the data obtained from such radiographic images could classify such individuals according to the presence or absence of disease. Materials and Methods For such a purpose, three groups of chest radiographic images were utilized, namely: group 1, including 25 individuals with COPD; group 2, including 27 individuals without COPD; and group 3 (utilized for the reclassification /validation of the analysis), including 15 individuals with COPD. The COPD classification was based on spirometry. The variables normalized by retrosternal height were the following: pulmonary width (LARGP); levels of right (ALBDIR) and left (ALBESQ) diaphragmatic eventration; costophrenic angle (ANGCF); and right (DISDIR) and left (DISESQ) intercostal distances. Results As the radiographic images of patients with and without COPD were compared, statistically significant differences were observed between the two groups on the variables related to the diaphragm. In the COPD reclassification the following variables presented the highest indices of correct classification: ANGCF (80%), ALBDIR (73.3%), ALBESQ (86.7%). Conclusion The radiographic assessment of the chest demonstrated that the variables related to the diaphragm allow a better differentiation between individuals with and without COPD.

Bosniak classification of renal cystic lesions according to multidetector computed tomography findings

Renal cystic lesions are usually diagnosed in the radiologists' practice and therefore their characterization is crucial to determine the clinical approach to be adopted and prognosis. The Bosniak classification based on computed tomography findings has allowed for standardization and categorization of lesions in increasing order of malignancy (I, II, IIF, III and IV) in a simple and accurate way. The present iconographic essay developed with multidetector computed tomography images of selected cases from the archives of the authors' institution, is aimed at describing imaging findings that can help in the diagnosis of renal cysts.

Renal cell carcinoma: histological classification and correlation with imaging findings

AbstractRenal cell carcinoma (RCC) is the seventh most common histological type of cancer in the Western world and has shown a sustained increase in its prevalence. The histological classification of RCCs is of utmost importance, considering the significant prognostic and therapeutic implications of its histological subtypes. Imaging methods play an outstanding role in the diagnosis, staging and follow-up of RCC. Clear cell, papillary and chromophobe are the most common histological subtypes of RCC, and their preoperative radiological characterization, either followed or not by confirmatory percutaneous biopsy, may be particularly useful in cases of poor surgical condition, metastatic disease, central mass in a solitary kidney, and in patients eligible for molecular targeted therapy. New strategies recently developed for treating renal cancer, such as cryo and radiofrequency ablation, molecularly targeted therapy and active surveillance also require appropriate preoperative characterization of renal masses. Less common histological types, although sharing nonspecific imaging features, may be suspected on the basis of clinical and epidemiological data. The present study is aimed at reviewing the main clinical and imaging findings of histological RCC subtypes.

Receiver operating characteristic (ROC) curve for classification of18F-NaF uptake on PET/CT

Abstract Objective: To assess the cutoff values established by ROC curves to classify18F-NaF uptake as normal or malignant. Materials and Methods: PET/CT images were acquired 1 hour after administration of 185 MBq of18F-NaF. Volumes of interest (VOIs) were drawn on three regions of the skeleton as follows: proximal right humerus diaphysis (HD), proximal right femoral diaphysis (FD) and first vertebral body (VB1), in a total of 254 patients, totalling 762 VOIs. The uptake in the VOIs was classified as normal or malignant on the basis of the radiopharmaceutical distribution pattern and of the CT images. A total of 675 volumes were classified as normal and 52 were classified as malignant. Thirty-five VOIs classified as indeterminate or nonmalignant lesions were excluded from analysis. The standardized uptake value (SUV) measured on the VOIs were plotted on an ROC curve for each one of the three regions. The area under the ROC (AUC) as well as the best cutoff SUVs to classify the VOIs were calculated. The best cutoff values were established as the ones with higher result of the sum of sensitivity and specificity. Results: The AUCs were 0.933, 0.889 and 0.975 for UD, FD and VB1, respectively. The best SUV cutoffs were 9.0 (sensitivity: 73%; specificity: 99%), 8.4 (sensitivity: 79%; specificity: 94%) and 21.0 (sensitivity: 93%; specificity: 95%) for UD, FD and VB1, respectively. Conclusion: The best cutoff value varies according to bone region of analysis and it is not possible to establish one value for the whole body.

PREDICTING THE BOILING POINT OF PCDD/Fs BY THE QSPR METHOD BASED ON THE MOLECULAR DISTANCE-EDGE VECTOR INDEX

The quantitative structure property relationship (QSPR) for the boiling point (Tb) of polychlorinated dibenzo-p-dioxins and polychlorinated dibenzofurans (PCDD/Fs) was investigated. The molecular distance-edge vector (MDEV) index was used as the structural descriptor. The quantitative relationship between the MDEV index and Tb was modeled by using multivariate linear regression (MLR) and artificial neural network (ANN), respectively. Leave-one-out cross validation and external validation were carried out to assess the prediction performance of the models developed. For the MLR method, the prediction root mean square relative error (RMSRE) of leave-one-out cross validation and external validation was 1.77 and 1.23, respectively. For the ANN method, the prediction RMSRE of leave-one-out cross validation and external validation was 1.65 and 1.16, respectively. A quantitative relationship between the MDEV index and Tb of PCDD/Fs was demonstrated. Both MLR and ANN are practicable for modeling this relationship. The MLR model and ANN model developed can be used to predict the Tb of PCDD/Fs. Thus, the Tb of each PCDD/F was predicted by the developed models.

Identification of Races of Selected Isolates of Uromyces appendiculatus from Minas Gerais (Brazil) Based on the new international classification system

Twelve single-pustule isolates of Uromyces appendiculatus, the etiological agent of common bean rust, were collected in the state of Minas Gerais, Brazil, and classified according to the new international differential series and the binary nomenclature system proposed during the 3rd Bean Rust Workshop. These isolates have been used to select rust-resistant genotypes in a bean breeding program conducted by our group. The twelve isolates were classified into seven different physiological races: 21-3, 29-3, 53-3, 53-19, 61-3, 63-3 and 63-19. Races 61-3 and 63-3 were the most frequent in the area. They were represented by five and two isolates, respectively. The other races were represented by just one isolate. This is the first time the new international classification procedure has been used for U. appendiculatus physiological races in Brazil. The general adoption of this system will facilitate information exchange, allowing the cooperative use of the results obtained by different research groups throughout the world. The differential cultivars Mexico 309, Mexico 235 and PI 181996 showed resistance to all of the isolates that were characterized. It is suggested that these cultivars should be preferentially used as sources for resistance to rust in breeding programs targeting development lines adapted to the state of Minas Gerais.

Does the edge effect influence plant community structure in a tropical dry forest?

Edge effects are considered a key factor in regulating the structure of plant communities in different ecosystems. However, regardless to few studies, edge influence does not seem to be decisive in semiarid regions such as the Brazilian tropical dry forest known as Caatinga but this issue remains inconclusive. The present study tests the null hypothesis that the plant community of shrubs and trees does not change in its structure due to edge effects. Twenty-four plots (20 x 20 m) were set up in a fragment of Caatinga, in which 12 plots were in the forest edges and 12 plots were inside the fragment. Tree richness, abundance and species composition did not differ between edge and interior plots. The results of this study are in agreement with the pattern previously found for semiarid environments and contrasts with previous results obtained in different environments such as Rainforests, Savanna and Forest of Araucaria, which indicate abrupt differences between the border and interior of the plant communities in these ecosystems, and suggest that the community of woody plants of the Caatinga is not ecologically affected by the presence of edges.

CLASSIFICATION OF FOREST ROADS AND DETERMINATION OF ROUTE USING GEOGRAPHIC INFORMATION SYSTEM

ABSTRACT Geographic Information System (GIS) is an indispensable software tool in forest planning. In forestry transportation, GIS can manage the data on the road network and solve some problems in transportation, such as route planning. Therefore, the aim of this study was to determine the pattern of the road network and define transport routes using GIS technology. The present research was conducted in a forestry company in the state of Minas Gerais, Brazil. The criteria used to classify the pattern of forest roads were horizontal and vertical geometry, and pavement type. In order to determine transport routes, a data Analysis Model Network was created in ArcGIS using an Extension Network Analyst, allowing finding a route shorter in distance and faster. The results showed a predominance of horizontal geometry classes average (3) and bad (4), indicating presence of winding roads. In the case of vertical geometry criterion, the class of highly mountainous relief (4) possessed the greatest extent of roads. Regarding the type of pavement, the occurrence of secondary coating was higher (75%), followed by primary coating (20%) and asphalt pavement (5%). The best route was the one that allowed the transport vehicle travel in a higher specific speed as a function of road pattern found in the study.

Identification of croplands of winter cereals in Rio Grande do Sul state, Brazil, through unsupervised classification of normalized difference vegetation index images

This study aimed to propose methods to identify croplands cultivated with winter cereals in the northern region of Rio Grande do Sul State, Brazil. Thus, temporal profiles of Normalized Difference Vegetation Index (NDVI) from MODIS sensor, from April to December of the 2000 to 2008, were analyzed. Firstly, crop masks were elaborated by subtracting the minimum NDVI image (April to May) from the maximum NDVI image (June to October). Then, an unsupervised classification of NDVI images was carried out (Isodata), considering the crop mask areas. According to the results, crop masks allowed the identification of pixels with greatest green biomass variation. This variation might be associated or not with winter cereals areas established to grain production. The unsupervised classification generated classes in which NDVI temporal profiles were associated with water bodies, pastures, winter cereals for grain production and for soil cover. Temporal NDVI profiles of the class winter cereals for grain production were in agree with crop patterns in the region (developmental stage, management standard and sowing dates). Therefore, unsupervised classification based on crop masks allows distinguishing and monitoring winter cereal crops, which were similar in terms of morphology and phenology.

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Montreal classification of patient operated for Crohn's disease and identification of surgical recurrence predictors

OBJECTIVE: to evaluate Crohn's disease recurrence and its possible predictors in patients undergoing surgical treatment. METHODS: We conducted a retrospective study with Crohn's disease (CD) patients undergoing surgical treatment between January 1992 and January 2012, and regularly monitored at the Bowel Clinic of the Hospital das Clínicas of the UFMG. RESULTS: we evaluated 125 patients, 50.4% female, with a mean age of 46.12 years, the majority (63.2%) diagnosed between 17 and 40 years of age. The ileum was involved in 58.4%, whereas stenotic behavior was observed in 44.8%, and penetrating, in 45.6%. We observed perianal disease in 26.4% of cases. The follow-up average was 152.40 months. Surgical relapse occurred in 29.6%, with a median time of 68 months from the first operation. CONCLUSION: The ileocolic location, penetrating behavior and perianal involvement (L3B3p) were associated with increased risk of surgical recurrence.

Diagnosis, classification and treatment of gestational trophoblastic neoplasia

Gestational trophoblastic neoplasia (GTN) is the term to describe a set of malignant placental diseases, including invasive mole, choriocarcinoma, placental site trophoblastic tumor and epithelioid trophoblastic tumor. Both invasive mole and choriocarcinoma respond well to chemotherapy, and cure rates are greater than 90%. Since the advent of chemotherapy, low-risk GTN has been treated with a single agent, usually methotrexate or actinomycin D. Cases of high-risk GTN, however, should be treated with multiagent chemotherapy, and the regimen usually selected is EMA-CO, which combines etoposide, methotrexate, actinomycin D, cyclophosphamide and vincristine. This study reviews the literature about GTN to discuss current knowledge about its diagnosis and treatment.

Classification of antimicrobial resistance using artificial neural networks and the relationship of 38 genes associated with the virulence of Escherichia coli isolates from broilers

Avian pathogenic Escherichia coli (APEC) is responsible for various pathological processes in birds and is considered as one of the principal causes of morbidity and mortality, associated with economic losses to the poultry industry. The objective of this study was to demonstrate that it is possible to predict antimicrobial resistance of 256 samples (APEC) using 38 different genes responsible for virulence factors, through a computer program of artificial neural networks (ANNs). A second target was to find the relationship between (PI) pathogenicity index and resistance to 14 antibiotics by statistical analysis. The results showed that the RNAs were able to make the correct classification of the behavior of APEC samples with a range from 74.22 to 98.44%, and make it possible to predict antimicrobial resistance. The statistical analysis to assess the relationship between the pathogenic index (PI) and resistance against 14 antibiotics showed that these variables are independent, i.e. peaks in PI can happen without changing the antimicrobial resistance, or the opposite, changing the antimicrobial resistance without a change in PI.

Changes in plant community diversity and composition across an edge between Araucaria forest and pasture in South Brazil

This work investigated how richness, abundance, composition and structure of woody and herbaceous vegetation were altered by the proximity of an edge between Araucaria forest and pasture in South Brazil. Herbaceous and woody species including seedlings were surveyed in 42 plots of 5 × 5 m randomly placed at the following distances: 5 and 50 m from the edge into the pasture and 0, 25, 50, 100 and 250 m from the edge into the forest. There was a significant increase in vegetation cover, richness and abundance of woody species, woody seedlings and herbaceous plants at the edge (0 m). These variables, in general, decreased from 25 to 50 m from the edge into the forest in comparison to the forest interior. Few seedlings of woody plants were able to establish themselves in the pasture. There were continuous changes in species composition that occurred in the studied gradient due to the invasion of light-demanding species and the disappearance of some shade-tolerant species at the edge. In conclusion, the forest edge studied generated changes in the plant community that extended up to 50 m into the forest.