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Optimization of OSEM parameters in myocardial perfusion imaging reconstruction as a function of body mass index: a clinical approach

OBJECTIVE: The present study is aimed at contributing to identify the most appropriate OSEM parameters to generate myocardial perfusion imaging reconstructions with the best diagnostic quality, correlating them with patients’ body mass index. MATERIALS AND METHODS: The present study included 28 adul...

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Detalles Bibliográficos
Autores principales: de Barros, Pietro Paolo, Metello, Luis F., Camozzato, Tatiane Sabriela Cagol, Vieira, Domingos Manuel da Silva
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Colégio Brasileiro de Radiologia e Diagnóstico por Imagem 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4633075/
https://www.ncbi.nlm.nih.gov/pubmed/26543282
http://dx.doi.org/10.1590/0100-3984.2014.0084
Descripción
Sumario:OBJECTIVE: The present study is aimed at contributing to identify the most appropriate OSEM parameters to generate myocardial perfusion imaging reconstructions with the best diagnostic quality, correlating them with patients’ body mass index. MATERIALS AND METHODS: The present study included 28 adult patients submitted to myocardial perfusion imaging in a public hospital. The OSEM method was utilized in the images reconstruction with six different combinations of iterations and subsets numbers. The images were analyzed by nuclear cardiology specialists taking their diagnostic value into consideration and indicating the most appropriate images in terms of diagnostic quality. RESULTS: An overall scoring analysis demonstrated that the combination of four iterations and four subsets has generated the most appropriate images in terms of diagnostic quality for all the classes of body mass index; however, the role played by the combination of six iterations and four subsets is highlighted in relation to the higher body mass index classes. CONCLUSION: The use of optimized parameters seems to play a relevant role in the generation of images with better diagnostic quality, ensuring the diagnosis and consequential appropriate and effective treatment for the patient.