O presente artigo teve como objetivo identificar os principais artefatos que podem ser gerados na cintilografia de perfusão miocárdica executada em gama câmara dedicada ao estudo cardíaco com detectores CZT através da análise de exames de cintilografia de perfusão miocárdica realizados no nosso serviço. Dentre os possíveis artefatos que podem ser gerados na CZT durante a cintilografia de perfusão miocárdica destacam-se os artefatos de movimentação do paciente, posicionamento inadequado no aparelho, atenuações, captações extra cardíacas e artefatos causados por condições cardíacas préexistentes. Na prática diária é essencial saber os tipos de artefatos que podem ocorrer na cintilografia de perfusão miocárdica, para que os mesmos possam ser reconhecidos e corrigidosquando possívelvisando a melhoria na qualidade do nosso exame.

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Foram analisados 25 pacientes com achados de COVID-19 ao PET/CT, dos quais 11 (44%) eram do sexo masculino e 14 (66%) do sexo feminino. A idade variou entre 36 e 88 anos. As indicações dos exames de acordo com os tumores primários eram: pulmão (5), mama (3), próstata (2), pâncreas (2), linfoma (2), nódulo pulmonar a/e (2), leucemia (1), orofaringe (1), hipofaringe (1), lesão mediastinal a/e (1), pelve renal (1), bexiga (1), cólon (1), reto (1) e sem localização (1). Selecionamos os pacientes com câncer de pulmão. Dentre eles, o SUV máximo das alterações pulmonares com captação pelo 18F-FDG variou entre 2,3 – 4,06 com a média de 3,3.

The sensitivity of mammography as a screening method is low in dense breasts, which are associated with a high risk of developing tumors. Thus, molecular breast imaging (MBI) with background uptake (BPU) of fibroglandular tissue can be used as a complementary method. The aim of this review was to synthesize the existing evidence on these important diagnostic imaging tools. Three electronic databases were searched to identify original articles, including publications dating from September 2010 and September 2020, in English, conducted in any location, and addressing at least one aspect related to dense breasts and Breast-specific gamma-imaging (BSGI). In total, 22 studies were reviewed. Several advantages of MBI and BPU as complementary methods of screening for dense breasts were found. Among them, we can mention the increase in breast cancer detection rate, easy implementation in clinical practice, high patient satisfaction, low cost and good reproducibility. In view of the good results found in our review, we can conclude that the implementation of MBI, especially with BPU, can be a promising complementary tool for screening of dense breasts.

The aim of this article is to analyze the current overview of machine learning applied to cardiac imaging in nuclear medicine through a review of the recent literature. In recent years, new highly efficient artificial intelligence tools are revolutionizing the field of image analysis, being developed with the purpose of integrating the large volume of clinical and image information to improve the diagnosis of the disease and the risk estimate. The integration of artificial intelligence in daily clinical practice is being evaluated on several fronts and nuclear cardiology can benefit from the improvement in sensitivity, specificity, and diagnostic accuracy that the incorporation of these technologies can provide.