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Presentation
Presentation
This course unit focuses on veterinary histopathological diagnosis, with particular emphasis on neoplastic diseases. Its field of action includes the microscopic evaluation of tissues, tumour classification, and the application of histological grading systems with diagnostic and prognostic relevance. It also introduces digital pathology, promoting technical and analytical skills in veterinary histopathological diagnosis. Within the context of the study cycle, this course unit strengthens knowledge in pathology and fosters the development of fundamental competencies in diagnostic oncologic pathology, providing a solid foundation for professional practice and scientific research.
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Class from course
Class from course
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Degree | Semesters | ECTS
Degree | Semesters | ECTS
Bachelor; Master Degree | Semestral | 2
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Year | Nature | Language
Year | Nature | Language
4 | Optional | Português
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Code
Code
ULHT478-27268
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Prerequisites and corequisites
Prerequisites and corequisites
Not applicable
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Professional Internship
Professional Internship
Não
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Syllabus
Syllabus
Sample preparation for histopathological diagnosis (trimming, margin assessment) Production of high-quality macroscopic photographs in pathology for publication purposes Preparation of histopathological reports Classification and diagnosis of the benign and malignant neoplasms most frequently diagnosed in animals: Benign epithelial tumours Malignant epithelial tumours Benign mesenchymal tumours Malignant mesenchymal tumours Round cell tumours Application of histological grading criteria, including specific criteria for cutaneous and subcutaneous mast cell tumours and soft tissue sarcomas, as well as immunohistochemistry techniques Introduction to the software "QuPath": interpretation and quantification of tissue images obtained through microscopy (Ki-67)
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Objectives
Objectives
Recognise and classify the main benign and malignant tumours of epithelial, mesenchymal and round cell origin, based on histological criteria. Identify histological patterns associated with neoplastic processes and evaluate criteria relevant to diagnosis and prognosis. Apply histological grading systems, particularly those specific to mast cell tumours and soft tissue sarcomas. Prepare histopathological reports of tumour processes in a clear, structured and scientifically rigorous manner, recognising and communicating situations of diagnostic uncertainty. Use digital pathology and image analysis tools, including the QuPath software, for the interpretation and quantification of histological parameters.
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Teaching methodologies
Teaching methodologies
The course unit promotes active learning through the analysis of digitised slides, preparation of reports, and tumour classification. The use of clinical cases, real examples, and digital pathology tools, such as the QuPath software, enables the development of technical, analytical, and image interpretation skills.
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References
References
Gross, T. L., Ihrke, P. J., Walder, E. J., & Affolter, V. K. (2005). Skin diseases of the dog and cat: Clinical and histopathologic diagnosis (2nd ed.). Wiley-Blackwell. Meuten, D. J. (Ed.). (2017). Tumors in domestic animals (5th ed.). John Wiley & Sons Inc.
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Assessment
Assessment
- Avaliação contínua em aula. A aprovação é obtida com um mínimo de 9,5 valores. Em cada aula será avaliado a assiduidade, interesse, capacidade de trabalho e participação.
A atribuição de 14 valores será distribuída ao longo de 7 aulas, da semana 5 à semana 11, correspondendo a 2 valores por aula - 1 valor pelo trabalho individual e 1 valor pelo trabalho em grupo realizado em sala de aula. Estes valores contemplam a descrição microscópica da lesão observada, o diagnóstico final, bem como a participação e a capacidade de trabalho autónomo de cada aluno.
A atribuição de 6 valores inclui uma avaliação individual realizada no final do semestre, na qual será fornecida uma lâmina digitalizada. O aluno deverá elaborar a descrição microscópica da lesão observada, bem como apresentar o diagnóstico final.
É obrigatória a presença ao mínimo de 2/3 das aulas. Exceto alunos com estatuto trabalhador-estudante e outros aplicáveis. Para estes casos, é aplicado um regime suplementar de avaliação, para aferição de conhecimentos, que pode incluir trabalhos adicionais, prova escrita e/ou oral, definido pelo docente.
Para a aprovação na unidade curricular, o aluno deve obter, na média ponderada de todos os momentos de avaliação, a classificação mínima de 9,5 valores.
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Mobility
Mobility
No
