Tecnologias da informação e métodos computacionais para gerenciamento, otimização e medicina de precisão em departamentos de imagens médicas


  • Marcos Machado Radtec


Tecnologia médica, Padronização, Protocolos, Biomarcadores, Inteligência artificial, Radiologia


A área da saúde demanda por tecnologias da informação e métodos computacionais para melhorar a produtividade dos serviços e oferecer assistência personalizada aos pacientes. Este trabalho buscou desenvolver e explorar sistemas e métodos computacionais para implementar melhorarias no gerenciamento, otimizar os exames, e acessar novos biomarcadores e assinaturas com inteligência artificial para apoio à decisão. Foram desenvolvidos e implementados softwares com o conceito Workflow Based Approach (WBA) e métodos computacionais escritos em linguagem Python para melhorar a gestão e otimizar os protocolos de exames. Um workflow para acesso a novos biomarcadores e assinaturas IA foi desenvolvido e validado em pacientes com CT de COVID-19, 18F-FDG-PET/CT de câncer de colo do útero e 18F-FDG-PET/CT de linfoma Hodgkin. O workflow demonstrou-se válido em análises de robustez: repetitividade (erro < 5%), reprodutibilidade (coeficiente de correlação intraclasse, ICC > 90%) e correlação clínica (p < 0,05). Os modelos preditivos para 18F-FDG-PET/CT de câncer de colo do útero e 18F-FDG-PET/CT de linfoma Hodgkin apresentaram desempenho geral de AUC=0,74 e AUC=0,96, respectivamente. Um novo software que utiliza métodos de IA para apoio ao diagnóstico da COVID-19 em CT de tórax de pacientes com pneumonia foi disponibilizado e validado em um PACS/Viewer. Sem apoio do software, os médicos tiveram desempenho médio de 83,4% de sensibilidade, e 64,3% de especificidade. Com o apoio do software, o desempenho melhorou para 87,1% de sensibilidade, e 91,1% de especificidade. Adicionalmente, o software melhorou a concordância entre observadores, de moderado para substancial, em uma escala construída a partir do coeficiente de concordância Cohen’s Kappa.


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ACR accreditation. Disponível em: . Acesso em: 19/09/2022.

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Como Citar

Machado, M. (2023). Tecnologias da informação e métodos computacionais para gerenciamento, otimização e medicina de precisão em departamentos de imagens médicas. Revista Brasileira De Física Médica, 17, 723. Recuperado de https://www.rbfm.org.br/rbfm/article/view/723



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