Abstract
Nowadays, liver radioembolization with 90Y microscpheres represents an innovative treatment for unresectable hepatic tumors. 90Y radioembolization treatment planning is performed by means of 99mTc-MAA SPECT imaging. However, photons interaction within human tissues and, in particular, 99mTc \(\gamma \)-rays attenuation, may significantly compromise the quantitative accuracy of SPECT images. The aim of this study was to validate a patient-specific and Computed Tomography (CT)-based attenuation correction of SPECT images, by employing and analyzing, both phantom models and clinical liver SPECT images. The results observed suggested that the implementation of attenuation corrections, during the iterative process of SPECT images reconstruction, resulted in qualitatively and quantitatively visually improved images, with higher contrast and increased count density profiles. Moreover, as compared to uncorrected images, attenuation corrected SPECT images presented a counts distribution more proportional to the real radiopharmaceutical concentration, both in phantom model and in human liver. Thus, the methodology implemented will permit to improve the liver radioembolization treatment planning, based on 99mTc-MAA SPECT imaging and its efficacy, while minimizing the complications.
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Acknowledgments
We gratefully acknowledge the technical staff at the Nuclear Medicine - Radiopharmacology Department, Champalimaud Foundation, Center for the Unknown, Lisbon, for their availability, dedication and without whom all data would have not been possible to acquire, process and analyze. Moreover, we wish to thank Professors Maria G. Signorini (Politecnico di Milano, Milan), Lidia S. Ferreira (Instituto Superior Técnico, Lisbon) and Enrico Maglione (Instituto Superior Técnico, Lisbon) for their sincere advice and guidance.
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Demino, L., Ferreira, P., Oliveira, F.P.M., Costa, D.C. (2018). The Importance of SPECT Imaging Attenuation Correction During Treatment Planning for 90Y-labeled Glass Microspheres Liver Radioembolization. In: Tavares, J., Natal Jorge, R. (eds) VipIMAGE 2017. ECCOMAS 2017. Lecture Notes in Computational Vision and Biomechanics, vol 27. Springer, Cham. https://doi.org/10.1007/978-3-319-68195-5_29
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DOI: https://doi.org/10.1007/978-3-319-68195-5_29
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