O linfoma alimentar é a forma anatômica mais frequente nos felinos e é o tipo de neoplasia que mais acomete o intestino delgado nessa espécie. É caracterizado pela infiltração de células linfóides neoplásicas em órgãos do trato gastrointestinal, com ou sem comprometimento de linfonodos mesentéricos. Seu diagnóstico pode ser considerado desafiador em muitos casos, devido às manifestações clínicas muitas vezes inespecíficas e às limitações da citologia e histopatologia. A imunoistoquímica, embora ainda pouco difundida, pode ser utilizada para confirmar o diagnóstico de linfoma alimentar, bem como determinar o tipo celular predominante. Objetivando-se caracterizar o linfoma alimentar felino, foi realizado estudo utilizando-se 40 casos de gatos com diagnóstico de linfoma alimentar (grupo 1), confirmados por meio da imunoistoquímica, no qual se avaliou os aspectos epidemiológicos, clínicos, citológicos, histológicos e imunoistoquímicos. Também foram avaliados 20 casos de felinos com doença inflamatória intestinal (grupo 2), confirmados segundo exame imunoistoquímico, quanto aos aspectos epidemiológicos e clínicos. E com o intuito de verificar a acurácia diagnóstica relativa dos exames de citologia, histologia e imunoistoquímica, foram utilizados os resultados dessas análises de ambos os grupos. Foi observado entre os felinos com linfoma alimentar estudados uma média de idade de 10,8 anos e as manifestações clínicas de maior ocorrência foram emagrecimento (55%), êmese (40%) e alterações nas fezes (40%). Entre as alterações ultrassonográficas observadas, as mais prevalentes foram linfonodomegalia mesentérica (86,11%) e espessamento de alças intestinais (80,55%). A maioria dos felinos estudados apresentou sorologia negativa tanto para FIV quanto para FeLV e apenas 14,28% e 8,57% foram positivos para FIV e FeLV, respectivamente. A correlação entre citologia e imunoistoquímica apontou sensibilidade, especificidade, valor preditivo positivo e negativo e razão de verossimilhança positiva e negativa de 93,3%, 65%, 66,6%, 92,85%, 2,65 e 0,10, respectivamente. O coeficiente de concordância Kappa de Cohen e a acurácia diagnóstica relativa foram de 0,55 e 77,14%, respectivamente. A correlação entre histopatologia e imunoistoquímica revelou sensibilidade, especificidade, valor preditivo positivo e negativo e razão de verossimilhança positiva e negativa de 89,74%, 60%, 81,39%, 75%, 2,22 e 0,18, respectivamente. O coeficiente de concordância Kappa de Cohen e a acurácia diagnóstica relativa foram de 0,52 e 79,66%, respectivamente. A associação entre sorologia para FIV e FeLV e tipo celular do linfoma alimentar não pode ser observada. O presente estudo permitiu concluir que a combinação de citologia, histopatologia e imunoistoquímica é necessária para o correto diagnóstico de linfoma alimentar, e o tipo celular de maior ocorrência foi o de células T. / Alimentary lymphoma is the most common anatomical form of feline lymphoma and is the neoplasm which more affects small intestine of this specie. It is characterized by infiltration of the gastrointestinal tract with neoplastic lymphocytes, with or without mesenteric lymph nodes involvement. The diagnosis of this illness can be challenger in several cases because of unspecific clinical signs and cytological and histopathological limitations. Immunohistochemistry is required where these evaluations were not definitive in addition to establish the cell phenotype T or B lymphocyte. The aim of this study was to characterize feline alimentary lymphoma. For these purpose, 40 cats with a diagnosis of alimentary lymphoma (Group 1) by immunohistochemistry were evaluated clinical, epidemiological, cytological and histologically, in addition to immunophenotype of the neoplasm tissues. Relative accuracy was performed using the results of cytology, histopathology and immunohistochemistry evaluation of 20 cats with inflammatory bowel disease diagnosis. The average age of the cats with alimentary lymphoma was 10.8 years and weight loss (55%), vomiting (40%) and fecal alteration (40%) were the most common clinical signs. The most prevalent ultrasonography abnormalities were mesenteric lymph nodes enlargement (86.11%) and intestinal wall thickening (80.55%). The majority of alimentary lymphoma cats were FIV and FeLV negative and 14.28% and 8.57% were FIV and FeLV positives, respectively. The cytology and immunohistochemistry correlation presents sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratio tests of 93.3%, 65%, 66.6%, 92.85%, 2.65 and 0.10, respectively. The Cohen´s kappa test and the relative accuracy were 0.55 and 77.14%, respectively. The histopathology and immunohistochemistry correlation presents sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratio tests of 89.74%, 60%, 81.39%, 75%, 2.22 and 0.18, respectively. The Cohen´s kappa test and the relative accuracy were 0.52 and 79.66%, respectively. Association of FIV and FeLV result tests and alimentary lymphoma phenotype was not observed. In conclusion, the results of the present study suggest that cytology, histology and immunohistochemistry combination is necessary for a correct diagnosis, and T cell alimentary lymphoma is the most common phenotype.

O linfoma alimentar é a forma anatômica mais frequente nos felinos e é o tipo de neoplasia que mais acomete o intestino delgado nessa espécie. É caracterizado pela infiltração de células linfóides neoplásicas em órgãos do trato gastrointestinal, com ou sem comprometimento de linfonodos mesentéricos. Seu diagnóstico pode ser considerado desafiador em muitos casos, devido às manifestações clínicas muitas vezes inespecíficas e às limitações da citologia e histopatologia. A imunoistoquímica, embora ainda pouco difundida, pode ser utilizada para confirmar o diagnóstico de linfoma alimentar, bem como determinar o tipo celular predominante. Objetivando-se caracterizar o linfoma alimentar felino, foi realizado estudo utilizando-se 40 casos de gatos com diagnóstico de linfoma alimentar (grupo 1), confirmados por meio da imunoistoquímica, no qual se avaliou os aspectos epidemiológicos, clínicos, citológicos, histológicos e imunoistoquímicos. Também foram avaliados 20 casos de felinos com doença inflamatória intestinal (grupo 2), confirmados segundo exame imunoistoquímico, quanto aos aspectos epidemiológicos e clínicos. E com o intuito de verificar a acurácia diagnóstica relativa dos exames de citologia, histologia e imunoistoquímica, foram utilizados os resultados dessas análises de ambos os grupos. Foi observado entre os felinos com linfoma alimentar estudados uma média de idade de 10,8 anos e as manifestações clínicas de maior ocorrência foram emagrecimento (55%), êmese (40%) e alterações nas fezes (40%). Entre as alterações ultrassonográficas observadas, as mais prevalentes foram linfonodomegalia mesentérica (86,11%) e espessamento de alças intestinais (80,55%). A maioria dos felinos estudados apresentou sorologia negativa tanto para FIV quanto para FeLV e apenas 14,28% e 8,57% foram positivos para FIV e FeLV, respectivamente. A correlação entre citologia e imunoistoquímica apontou sensibilidade, especificidade, valor preditivo positivo e negativo e razão de verossimilhança positiva e negativa de 93,3%, 65%, 66,6%, 92,85%, 2,65 e 0,10, respectivamente. O coeficiente de concordância Kappa de Cohen e a acurácia diagnóstica relativa foram de 0,55 e 77,14%, respectivamente. A correlação entre histopatologia e imunoistoquímica revelou sensibilidade, especificidade, valor preditivo positivo e negativo e razão de verossimilhança positiva e negativa de 89,74%, 60%, 81,39%, 75%, 2,22 e 0,18, respectivamente. O coeficiente de concordância Kappa de Cohen e a acurácia diagnóstica relativa foram de 0,52 e 79,66%, respectivamente. A associação entre sorologia para FIV e FeLV e tipo celular do linfoma alimentar não pode ser observada. O presente estudo permitiu concluir que a combinação de citologia, histopatologia e imunoistoquímica é necessária para o correto diagnóstico de linfoma alimentar, e o tipo celular de maior ocorrência foi o de células T. / Alimentary lymphoma is the most common anatomical form of feline lymphoma and is the neoplasm which more affects small intestine of this specie. It is characterized by infiltration of the gastrointestinal tract with neoplastic lymphocytes, with or without mesenteric lymph nodes involvement. The diagnosis of this illness can be challenger in several cases because of unspecific clinical signs and cytological and histopathological limitations. Immunohistochemistry is required where these evaluations were not definitive in addition to establish the cell phenotype T or B lymphocyte. The aim of this study was to characterize feline alimentary lymphoma. For these purpose, 40 cats with a diagnosis of alimentary lymphoma (Group 1) by immunohistochemistry were evaluated clinical, epidemiological, cytological and histologically, in addition to immunophenotype of the neoplasm tissues. Relative accuracy was performed using the results of cytology, histopathology and immunohistochemistry evaluation of 20 cats with inflammatory bowel disease diagnosis. The average age of the cats with alimentary lymphoma was 10.8 years and weight loss (55%), vomiting (40%) and fecal alteration (40%) were the most common clinical signs. The most prevalent ultrasonography abnormalities were mesenteric lymph nodes enlargement (86.11%) and intestinal wall thickening (80.55%). The majority of alimentary lymphoma cats were FIV and FeLV negative and 14.28% and 8.57% were FIV and FeLV positives, respectively. The cytology and immunohistochemistry correlation presents sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratio tests of 93.3%, 65%, 66.6%, 92.85%, 2.65 and 0.10, respectively. The Cohen´s kappa test and the relative accuracy were 0.55 and 77.14%, respectively. The histopathology and immunohistochemistry correlation presents sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratio tests of 89.74%, 60%, 81.39%, 75%, 2.22 and 0.18, respectively. The Cohen´s kappa test and the relative accuracy were 0.52 and 79.66%, respectively. Association of FIV and FeLV result tests and alimentary lymphoma phenotype was not observed. In conclusion, the results of the present study suggest that cytology, histology and immunohistochemistry combination is necessary for a correct diagnosis, and T cell alimentary lymphoma is the most common phenotype.

Machine learning can provide insight and support for a variety of decisions. In some areas of medicine, decision-support models are capable of assisting healthcare practitioners in making accurate diagnoses. In this work we explored the application of these techniques to distinguish between two diseases in veterinary medicine; inflammatory bowel disease (IBD) and alimentary lymphoma (ALA). Both disorders are common gastrointestinal (GI) diseases in humans and animals that share very similar clinical and pathological outcomes. Because of these similarities, distinguishing between these two diseases can sometimes be challenging. In order to identify patterns that may help with this differentiation, we retrospectively mined medical records from dogs and cats with histopathologically diagnosed GI diseases. Since the pathology report is the key conveyer of this information in the medical records, our first study focused on its information structure. Other groups have had a similar interest. In 2008, to help insure consistent reporting, the World Small Animal Veterinary Association (WSAVA) GI International Standardization Group proposed standards for recording histopathological findings (HF) from GI biopsy samples. In our work, we extend WSAVA efforts and propose an information model (composed of information structure and terminology mapped to the Systematized Nomenclature of Medicine - Clinical Terms) to be used when recording histopathological diagnoses (HDX, one or more HF from one or more tissues). Next, our aim was to identify free-text HF not currently expressed in the WSAVA format that may provide evidence for distinguishing between IBD and ALA in cats. As part of this work, we hypothesized that WSAVA-based structured reports would have higher classification accuracy of GI disorders in comparison to use of unstructured free-text format. We trained machine learning models in 60 structured, and independently, 60 unstructured reports. Results show that unstructured information-based models using two machine learning algorithms achieved higher accuracy in predicting the diagnosis when compared to the structured information-based models, and some novel free-text features were identified for possible inclusion in the WSAVA-reports. In our third study, we tested the use of machine learning algorithms to differentiate between IBD and ALA using complete blood count and serum chemistry data. Three models (using naïve Bayes, neural networks, and C4.5 decision trees) were trained and tested on laboratory results for 40 Normal, 40 IBD, and 40 ALA cats. Diagnostic models achieved classification sensitivity ranging between 63% and 71% with naïve Bayes and neural networks being superior. These models can provide another non-invasive diagnostic tool to assist with differentiating between IBD and ALA, and between diseased and non-diseased cats. We believe that relying on our information model for histopathological reporting can lead to a more complete, consistent, and computable knowledgebase in which machine learning algorithms can more efficiently identify these and other disease patterns. / Ph. D. / Computational models play an important role in supporting the decision making process. In some areas of medicine, decision-support models assist healthcare practitioners to make accurate diagnoses. In this work, we explored the application of computational techniques to distinguish between two diseases; inflammatory bowel disease (IBD) and alimentary lymphoma (ALA). These are common gastrointestinal (GI) diseases in humans and animals that share very similar laboratory findings. Because of these similarities, distinguishing between these two diseases can sometimes be challenging. In order to identify patterns that may help with this differentiation, we mined medical records from dogs and cats diagnosed with GI diseases. Since the pathology report is a key source of information for the diagnosis of these two diseases, in our first study we focused on its information structure. Others with similar interest have also examined reports of this type. In 2008, a group proposed standards for recording histopathological findings (HF) from GI biopsy samples. In our work, we extend the group’s efforts and propose an information model (composed of information structure and terminology) to be used when recording histopathological diagnoses (HDX, one or more HF from one or more tissues). Next, our aim was to identify free-text HF not currently expressed in the standardization group’s format that may provide evidence for distinguishing between IBD and ALA in cats. We trained computational models in 60 structured, and independently, 60 unstructured reports. Results show that unstructured information-based models using two computational models achieved higher accuracy in predicting the diagnosis when compared to the structured information-based models. As a result, novel free text features, which improved the performance of the structured reports, were identified. In our third study, we tested the use of computational models to differentiate between IBD and ALA using routine laboratory results. Three models were trained and tested on laboratory results from 40 Normal, 40 IBD, and 40 ALA cats. Diagnostic models achieved classification sensitivity ranging between 63% and 71%. These models can provide another noninvasive diagnostic tool to assist with differentiating between IBD and ALA, and between diseased and non-diseased cats. We believe that relying on our information model for histopathological reporting can lead to a more complete, consistent, and computable knowledgebase for the identification of these two diseases.