Computed-aid radiographic measurements of cardiac silhouette in Poodle dogs with mitral valve insufficiency

Avaliaram-se os métodos de mensuração radiográficos, Vertebral Heart Size (VHS), o ângulo entre o eixo maior do coração e o esterno (ângulo) e a área cardíaca normalizada (ACN), na triagem Poodles portadores de insuficiência valvar mitral (IVM). Alocou-se um conjunto de 74 imagens radiográficas do tórax de Poodles em dois grupos: (I) estruturas cardiopulmonares normais (n = 18) e (II) portadores de doença cardíaca (n = 56), confirmada pelo ecocardiograma como sendo IVM. De acordo com a classificação do eco, o grupo II foi subdividido em quatro subgrupos: aumento atrial esquerdo (AAE) (IIa) leve (n = 4), (IIb) moderado (n = 7), (IIc) importante (n = 28) e (IId) ausente (n = 17). As mensurações foram realizadas na projeção laterolateral direita por um radiologista veterinário experiente (A) e por um iniciante (B). As mensurações de A foram consideradas referência. Para o VHS, houve diferenças significativas entre o grupo I e os grupos II (P &lt; 0,001), IIb (P &lt; 0,05) e IIc (P &lt; 0,001). O limiar ótimo médio foi de 9,85v e a precisão média de 78,34%. Houve diferenças significativas nas mensurações entre A e B nos grupos I (P &lt; 0,05) e II (P &lt; 0,001). Para o ângulo, houve diferenças significativas entre o grupo I e os grupos II (P &lt; 0,05) e IIc (P &lt; 0,05). O limiar ótimo médio foi de 60,57&ordm; e a precisão média de 77,57%. Houve diferenças significativas nas mensurações entre A e B nos grupos I (P &lt; 0,001) e II (P &lt; 0,001). Para a ACN, houve diferenças significativas entre o grupo I e os grupos II (P &lt 0,001), IIb (P &lt; 0,05), IIc (P &lt; 0,001) e IId (P &lt; 0,05). O limiar ótimo médio foi de 18,81v2 e a precisão média de 80.42%. Houve diferenças significativas nas mensurações entre A e B nos grupos I (P &lt; 0,05) e II (P &lt; 0,001). O desempenho do VHS na triagem de Poodles portadores de IVM foi regular. Identificou principalmente o aumento cardíaco generalizado. O desempenho do ângulo na triagem foi baixo. Reconheceu somente o aumento cardíaco generalizado. O desempenho da ACN na triagem foi bom. Identificou o AAE específico e alterações precoces na forma do coração. Para determinar o limiar ótimo, favoreceu-se a sensibilidade em detrimento da especificidade. A reprodutibilidade pareceu estar relacionada ao nível de experiência.Radiographic measurement methods, Vertebral Heart Size (VHS), angle between long axis of the heart and sternum (angle) and normalized cardiac area (NCA), were evaluated in clinical trials of Poodles with mitral valve insufficiency (MVI). Seventy four sets of thoracic radiographs of Poodles were allotted to two groups: (I) normal cardiopulmonary structures (n = 18) and (II) from patients with proven cardiac disease (n = 56), confirmed by echocardiography to be caused by MVI. According to ecocardiographic classification, group II was subdivided in four subgroups: (IIa) mild (n = 4), (IIb) moderate (n = 7), (IIc) severe (n = 28) and (IId) absent (n = 17) left atrial enlargement (LAE). Measurements were performed by one experienced veterinary radiologist (A) and one trainee (B) in right lateral view. The measurements of A were used as reference. For VHS, there were significant differences between group I and groups II (P &lt; 0.001), IIb (P &lt; 0.05) and IIc (P &lt; 0.001). The optimal threshold value mean was 9.85v and the median accuracy of 78.34%. There were significant differences in the measurements between A and B in groups I (P &lt; 0.05) and II (P &lt; 0.001). For angle, there were significant differences between group I and groups II (P &lt; 0.05) and IIc (P &lt; 0.05). The optimal threshold value mean was 60.57&ordm; and the median accuracy of 77.57%. There were significant differences in the measurements between A and B in groups I (P &lt; 0.001) and II (P &lt; 0.001). For NCA, there were significant differences between group I and groups II (P &lt; 0.001), IIb (P &lt; 0.05), IIc (P &lt; 0.001) and IId (P &lt; 0.05). The optimal threshold value mean was 18.81v2 and the median accuracy of 80.42%. There were significant differences in the measurements between A and B in groups I (P < 0.05) and II (P < 0.001). The VHS´ performance in clinical trials of Poodles with MVI was regular. It mainly identified generalized cardiac enlargement. The angle´s performance in clinical trials was low. It only recognized generalized cardiac enlargement. The NCAs performance in clinical trials was good. It identified specific LAE and early changes in heart shape. To determine optimal threshold, sensitivity was prioritized, to the detriment of specificity. The reproducibility seemed to be related to the level of experience

Predicting suitable nesting sites for the Black caiman (Melanosuchus niger Spix 1825) in the Central Amazon basin

After many years of illegal hunting and commercialization, the populations of the Black caiman (Melanosuchus niger) have been recovering during the last four decades due to the enforcement of a legislation that inhibits their international commercialization. Protecting nesting sites, in which vulnerable life forms (as reproductive females, eggs, and neonates) spend considerable time, is one of the most appropriate conservation actions aimed at preserving caiman populations. Thus, identifying priority areas for this activity should be the primary concern of conservationists. As caiman nesting sites are often found across the areas with difficult access, collecting nest information requires extensive and costly fieldwork efforts. In this context, species distribution modeling can be a valuable tool for predicting the locations of caiman nests in the Amazon basin. In this work, the maximum entropy method (MaxEnt) was applied to model the M. niger nest occurrence in the Mamirauá Sustainable Development Reserve (MSDR) using remotely sensed data. By taking into account the M. niger nesting habitat, the following predictor variables were considered: conditional distance to open water, distance to bare soil, expanded contributing area from drainage, flood duration, and vegetation type. The threshold-independent prediction performance and binary prediction based on the threshold value of 0.9 were evaluated by the area under the curve (AUC) and performing a binomial test, respectively. The obtained results (AUC = 0.967 (Formula presented.) 0.006 and a highly significant binomial test (Formula presented.)) indicated excellent performance of the proposed model in predicting the M. niger nesting occurrence in the MSDR. The variables related to hydrological regimes (conditional distance to open water, expanded contributing area from drainage, and flood duration) most strongly affected the model performance. MaxEnt can be used for developing community-based sustainable management programs to provide socio-economic benefits to local communities and promote species conservation in a much larger area within the Amazon basin. © 2019, © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group

A review on crocodilian nesting habitats and their characterisation via remote sensing

Crocodilians usually remain inside or near their nests during most vulnerable life stages (as eggs, neonates and reproductive females). Thus, protection of nesting sites is one of the most appropriate conservation actions for these species. Nesting sites are often found across areas with difficult access, making remote sensing a valuable tool used to derive environmental variables for characterisation of nesting habitats. In this study, we (i) review crocodilian nesting habitats worldwide to identify key variables for nesting site distribution: Proximity to open-water, open-water stability, vegetation, light, precipitation, salinity, soil properties, temperature, topography, and flooding status, (ii) present a summary of the relative importance of these variables for each crocodilian species, (iii) identify knowledge gaps in the use of remote sensing methods currently used to map potential crocodilian nesting sites, and (iv) provide insight into how these remotely sensed variables can be derived to promote research on crocodilian ecology and conservation. We show that few studies have used remote sensing and that the range of images and methods used comprises a tiny fraction of what is available at little to no cost. Finally, we discuss how the combined use of remote sensing methods-optical, radar, and laser-may help overcome difficulties routinely faced in nest mapping (e.g., cloud cover, flooding beneath the forest canopy, or complicated relief) in a relevant way to crocodilians and to other semiaquatic vertebrates in different environments. Keywords © 2019 Copyright 2019 by Koninklijke Brill NV, Leiden, The Netherlands

Predicting suitable nesting sites for the black caiman (melanosuchus niger Spix 1825) in the central Amazon basin

After many years of illegal hunting and commercialization, the populations of the Black caiman (Melanosuchus niger) have been recovering during the last four decades due to the enforcement of a legislation that inhibits their international commercialization. Protecting nesting sites, in which vulnerable life forms (as reproductive females, eggs, and neonates) spend considerable time, is one of the most appropriate conservation actions aimed at preserving caiman populations. Thus, identifying priority areas for this activity should be the primary concern of conservationists. As caiman nesting sites are often found across the areas with difficult access, collecting nest information requires extensive and costly fieldwork efforts. In this context, species distribution modeling can be a valuable tool for predicting the locations of caiman nests in the Amazon basin. In this work, the maximum entropy method (MaxEnt) was applied to model the M. niger nest occurrence in the Mamirauá Sustainable Development Reserve (MSDR) using remotely sensed data. By taking into account the M. niger nesting habitat, the following predictor variables were considered: conditional distance to open water, distance to bare soil, expanded contributing area from drainage, flood duration, and vegetation type. The threshold-independent prediction performance and binary prediction based on the threshold value of 0.9 were evaluated by the area under the curve (AUC) and performing a binomial test, respectively. The obtained results (AUC = 0.967 ± 0.006 and a highly significant binomial test P<0.01) indicated excellent performance of the proposed model in predicting the M. niger nesting occurrence in the MSDR. The variables related to hydrological regimes (conditional distance to open water, expanded contributing area from drainage, and flood duration) most strongly affected the model performance. MaxEnt can be used for developing community-based sustainable management programs to provide socio-economic benefits to local communities and promote species conservation in a much larger area within the Amazon basin514759CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO - CNPQCOORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESFUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULO - FAPESPNão tem299340198–092016/13462–0G.P.R. Banon received a scholarship from the Coordination for the Improvement of Higher Education Personnel (CAPES) through the “Programa Nacional de Pós-Doutorado” (PNPD) (grant 299340198–09). L.C. Banon received a scholarship from the São Paulo Research Foundation (FAPESP) through the “Pesquisa Regular” (grant 2016/13462–0). G.M. Moulatlet was funded by the University of Turku Graduate School. F. Villamarín received a scholarship from the Brazilian Council for Scientific and Technological Development (CNPq) through the “Programa Estudantes Convênio de Pós-Graduação” (PECPG). Field data were obtained with the financial support from the St. Augustine Alligator Farm & Zoological Park provided by the Wildlife Conservation Society (WCS) and John Thorbjarnarso

Computed tomography in veterinary medicine: foundations and clinical indications

A tomografia computadorizada (TC) é uma técnica de diagnóstico por imagem que tem sido amplamente utilizada na medicina veterinária nos últimos anos, tanto em centros de ensino superior quanto por centros médicos veterinários de referência. Desde o surgimento do primeiro tomógrafo, a TC tem incorporado os avanços tecnológicos da informática e da área de diagnóstico por imagem. A TC utiliza raios-X para formar imagens em cortes de um objeto em diferentes planos, sem sobreposição das estruturas internas que o compõem. Essa modalidade de imagem tem sido utilizada na medicina veterinária especialmente na avaliação da cavidade nasal e dos seios paranasais, de neoformações musculoesqueléticas, alterações de bula timpânica, traumas e fraturas de crânio, afecções da articulação temporomandibular, degeneração ou hérnia de disco intervertebral, neoplasias pulmonares ou do mediastino e neoplasias cerebrais, entre outras. Este artigo revisa as bases da TC e sua utilização na medicina veterináriaComputed tomography (CT) is an imaging technique that has been widely used in veterinary medicine in recent years, both in veterinary schools and veterinary medical reference centers. Since the first scanner appeared, it has incorporated technological advances inherent to the use of computers and of diagnostic imaging. CT uses X-rays to form slice images of an object in different planes without overlapping of its internal structures. In veterinary medicine, this technique is currently used to evaluate the nasal cavity and paranasal sinuses, musculoskeletal tumors, tympanic bulla abnormalities, trauma and skull fractures, temporomandibular joint disorder, degeneration or herniated intervertebral discs, pulmonary and mediastinal neoplasms, brain tumors and others. This article reviews the basis of CT and its clinical applications in veterinary medicineLa tomografía computarizada (TC) es una técnica de diagnóstico por imagen utilizada con mayor frecuencia en medicina veterinaria en los últimos años, tanto por centros de enseñanza superior como por centros veterinarios de referencia. Desde la aparición del primer tomógrafo, la técnica de tomografía computarizada ha incorporado los avances tecnológicos de la computación y del diagnóstico por imagen. La TC utiliza rayos-X para formar imágenes en cortes de un objeto en diferentes planos sin sobreposición de las estructuras internas. Esta ha sido utilizada en medicina veterinaria especialmente para evaluación de afecciones de la cavidad nasal y senos paranasales, neoformaciones del sistema musculoesquelético, alteraciones de bulla timpánica, fracturas craneanas, afecciones de la articulación temporomandibular, degeneración o hernia de disco intervertebral, neoplasias pulmonares o del mediastino y neoplasias cerebrales, entre otras. Este artículo revisa las bases de la TC y su utilización en medicina veterinari