Imagej's contribution to left ventricular segmentation in myocardial perfusion imaging

• Autor(a) principal: Sousa, Carlota Leonardo
• Data de Publicação: 2017
• Outros Autores: Carolino, Elisabete, Figueiredo, Sérgio, Vieira, Lina
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.21/7746
• topic: Nuclear medicine; Imagej; Myocardial perfusion imaging; Segmentation; Signal-to-noise ratio

Introduction: The Myocardial Perfusion Imaging (MPI) is a non-invasive image test that allows the assessment of perfusion, function, and viability of the Left Ventricle (LV). The quantitative parameters obtained post-reconstruction requires an accurate segmentation of the LV. ImageJ is an open-source software that provides segmentation techniques that may contribute to the segmentation of the LV in the MPI. The purpose of this study was to study the influence of the different segmentation methods provided by ImageJ, in MPI, depending on the administered activity. Material and methods: We carried out an experimental research with 4 MPI studies simulated with 275, 385, 500 and 750 Bq/voxel in the myocardium, whose short-axis (SA) slices were segmented with ImageJ by the threshold default, OTSU, and k-means Plugin Toolkit methods (k=2, k=3). To analyze the most appropriate segmentation method, the signal-to-noise ratio (SNR) for each short-axis (SA) slice was calculated, in accordance with the slices obtained from the software Quantitative Perfusion Single Photon Emission Computed Tomography® (QPS®) and by manual segmentation using ImageJ. To analyze the SNR with ImageJ and QPS® segmentation methods in the same simulated study, and to compare with the same segmentation method in different simulated studies, the Friedman and Kruskal-Wallis tests were applied. Results and discussion: The method k-means with k=3 is the most suitable method for the segmentation of the LV, regardless of the administered activity. Conclusion: This study may contribute to the clinical implementation of open-source based segmentation methods of the LV in MPI, according to the activity in the myocardium.