Image-based red blood cell counter for multiple species of wild and domestic animals / Contador de células vermelhas baseado em imagens para múltiplas espécies de animais silvestres e domésticos

RBC count plays an important role in animal diagnosis. Despite the many technologies available in different automated hematology analyzers, when it comes to the blood of wild animals it is still difficult to find an easy and affordable solution for multiple species. This study aims to evaluate the proposed automatic red blood cell counter. Blood samples (1 ocelot - Leopardus pardalis, 1 monkey - Cebus apella, 1 coati - Nasua nasua, 62 dogs - Canis familiaris, and 5 horses - Equus caballus) were analyzed using three methods: 1-manual count, 2-automatic count by image, and 3-semi-automatic count by image; blood from dogs and horses were also analyzed by a fourth method: 4-automatic count by impedance. The counts in methods 2 and 3 were produced by the proposed red blood cell counter. Results were compared using Pearson's correlation and plots with different methods as the criterion standard. RBC counts in methods 1, 2, and 3 correlated very well with those in the method 4 (r ≥ 0.94). RBC counts produced by method 2 were highly correlated with method 3 (r = 0.998). The results indicate that the proposed method can be used as an automatic or semi-automatic counting method in clinics that are currently using the manual method for RBC assessment.(AU)

A contagem de células vermelhas do sangue desempenha um papel importante no diagnóstico de animais. Apesar da existência de muitas tecnologias em diferentes contadores automatizados para análise de sangue, quando se trata do sangue de animais silvestres ainda é difícil encontrar uma solução simples e econômica para múltiplas espécies. O objetivo deste estudo é avaliar o contador de células vermelhas proposto. Amostras de sangue (uma jaguatirica - Leopardus pardalis, um macaco - Cebus apella, um quati - Nasua nasua, 62 cães - Canis familiaris e cinco cavalos - Equus caballus) foram analisadas por três métodos: 1 - contagem manual, 2 - contagem automática por imagem e 3 - contagem semiautomática por imagem; as amostras de cães e cavalos foram analisadas por um quarto método: 4 - contagem automática por impedância. As contagens dos métodos 2 e 3 foram obtidas usando-se o contador de células vermelhas proposto. Os resultados foram comparados por meio da correlação de Pearson e gráficos com diferentes métodos como valor de referência. As contagens dos métodos 1, 2 e 3 se correlacionaram muito bem com as contagens do método 4 (r ≥ 0.94). As contagens produzidas pelo método 2 apresentaram alta correlação com o método 3 (r = 0.998). Os resultados indicam que o contador proposto pode ser usado como um método de contagem automática ou semiautomática em clínicas que usam o método manual para contagem de células vermelhas do sangue de animais.(AU)

Image-based red blood cell counter for multiple species of wild and domestic animals / Contador de células vermelhas baseado em imagens para múltiplas espécies de animais silvestres e domésticos

RBC count plays an important role in animal diagnosis. Despite the many technologies available in different automated hematology analyzers, when it comes to the blood of wild animals it is still difficult to find an easy and affordable solution for multiple species. This study aims to evaluate the proposed automatic red blood cell counter. Blood samples (1 ocelot - Leopardus pardalis, 1 monkey - Cebus apella, 1 coati - Nasua nasua, 62 dogs - Canis familiaris, and 5 horses - Equus caballus) were analyzed using three methods: 1-manual count, 2-automatic count by image, and 3-semi-automatic count by image; blood from dogs and horses were also analyzed by a fourth method: 4-automatic count by impedance. The counts in methods 2 and 3 were produced by the proposed red blood cell counter. Results were compared using Pearson's correlation and plots with different methods as the criterion standard. RBC counts in methods 1, 2, and 3 correlated very well with those in the method 4 (r ≥ 0.94). RBC counts produced by method 2 were highly correlated with method 3 (r = 0.998). The results indicate that the proposed method can be used as an automatic or semi-automatic counting method in clinics that are currently using the manual method for RBC assessment.(AU)

A contagem de células vermelhas do sangue desempenha um papel importante no diagnóstico de animais. Apesar da existência de muitas tecnologias em diferentes contadores automatizados para análise de sangue, quando se trata do sangue de animais silvestres ainda é difícil encontrar uma solução simples e econômica para múltiplas espécies. O objetivo deste estudo é avaliar o contador de células vermelhas proposto. Amostras de sangue (uma jaguatirica - Leopardus pardalis, um macaco - Cebus apella, um quati - Nasua nasua, 62 cães - Canis familiaris e cinco cavalos - Equus caballus) foram analisadas por três métodos: 1 - contagem manual, 2 - contagem automática por imagem e 3 - contagem semiautomática por imagem; as amostras de cães e cavalos foram analisadas por um quarto método: 4 - contagem automática por impedância. As contagens dos métodos 2 e 3 foram obtidas usando-se o contador de células vermelhas proposto. Os resultados foram comparados por meio da correlação de Pearson e gráficos com diferentes métodos como valor de referência. As contagens dos métodos 1, 2 e 3 se correlacionaram muito bem com as contagens do método 4 (r ≥ 0.94). As contagens produzidas pelo método 2 apresentaram alta correlação com o método 3 (r = 0.998). Os resultados indicam que o contador proposto pode ser usado como um método de contagem automática ou semiautomática em clínicas que usam o método manual para contagem de células vermelhas do sangue de animais.(AU)

Image quality, threshold contrast and mean glandular dose in CR mammography.

In many countries, computed radiography (CR) systems represent the majority of equipment used in digital mammography. This study presents a method for optimizing image quality and dose in CR mammography of patients with breast thicknesses between 45 and 75 mm. Initially, clinical images of 67 patients (group 1) were analyzed by three experienced radiologists, reporting about anatomical structures, noise and contrast in low and high pixel value areas, and image sharpness and contrast. Exposure parameters (kV, mAs and target/filter combination) used in the examinations of these patients were reproduced to determine the contrast-to-noise ratio (CNR) and mean glandular dose (MGD). The parameters were also used to radiograph a CDMAM (version 3.4) phantom (Artinis Medical Systems, The Netherlands) for image threshold contrast evaluation. After that, different breast thicknesses were simulated with polymethylmethacrylate layers and various sets of exposure parameters were used in order to determine optimal radiographic parameters. For each simulated breast thickness, optimal beam quality was defined as giving a target CNR to reach the threshold contrast of CDMAM images for acceptable MGD. These results were used for adjustments in the automatic exposure control (AEC) by the maintenance team. Using optimized exposure parameters, clinical images of 63 patients (group 2) were evaluated as described above. Threshold contrast, CNR and MGD for such exposure parameters were also determined. Results showed that the proposed optimization method was effective for all breast thicknesses studied in phantoms. The best result was found for breasts of 75 mm. While in group 1 there was no detection of the 0.1 mm critical diameter detail with threshold contrast below 23%, after the optimization, detection occurred in 47.6% of the images. There was also an average MGD reduction of 7.5%. The clinical image quality criteria were attended in 91.7% for all breast thicknesses evaluated in both patient groups. Finally, this study also concluded that the use of the AEC of the x-ray unit based on the constant dose to the detector may bring some difficulties to CR systems to operate under optimal conditions. More studies must be performed, so that the compatibility between systems and optimization methodologies can be evaluated, as well as this optimization method. Most methods are developed for phantoms, so comparative studies including clinical images must be developed.