Optimization of oncological 18F-FDG PET/CT imaging based on a multiparameter analysis

Submitted by Ana Maria Fiscina Sampaio ([email protected]) on 2016-05-12T19:05:36Z No. of bitstreams: 1 Menezes VO Optimization....pdf: 2748103 bytes, checksum: 8446733e75e4b2c0c251d96a9269ffdd (MD5)Approved for entry into archive by Ana Maria Fiscina Sampaio ([email protected]) on 2016-05-12T19:23:57Z (GMT) No. of bitstreams: 1 Menezes VO Optimization....pdf: 2748103 bytes, checksum: 8446733e75e4b2c0c251d96a9269ffdd (MD5)Made available in DSpace on 2016-05-12T19:23:57Z (GMT). No. of bitstreams: 1 Menezes VO Optimization....pdf: 2748103 bytes, checksum: 8446733e75e4b2c0c251d96a9269ffdd (MD5) Previous issue date: 2016São Rafael Hospital. Nuclear Medicine Department. Salvador, BA, Brasil / Universidade Federal de Pernambuco. Hospital das Clínicas. Nuclear Medicine Department. Recife, PE, BrasilSão Rafael Hospital. Nuclear Medicine Department. Salvador, BA, Brasil / Hospital das Clínicas da Universidade Federal de Bahia/Ebserh, Salvador 40110-060, BrazilSão Rafael Hospital. Nuclear Medicine Department. Salvador, BA, Brasil / Hospital Universitário Professor Alberto Antunes/Ebserh. Nuclear Medicine Department. Maceió, AL, BrasilUniversidade Federal de Sergipe. Department of Physics. São Cristóvão, SE, BrasilYale University School of Medicine. Department of Diagnostic Radiology. New Haven, Connecticut / University of Pisa. School of Engineering. Pisa, ItalyFundación Centro Diagnóstico Nuclear, Buenos Aires, ArgentinaSão Rafael Hospital. Centro de Biotecnologia e Terapia Celular. Salvador, BA, BrasilSão Rafael Hospital. Centro de Biotecnologia e Terapia Celular. Salvador, BA, Brasil / Fundação Oswaldo Cruz. Centro de Pesquisas Gonçalo Moniz. Salvador, BA, BrasilPurpose: This paper describes a method to achieve consistent clinical image quality in 18F-FDG scans accounting for patient habitus, dose regimen, image acquisition, and processing techniques. Methods: Oncological PET/CT scan data for 58 subjects were evaluated retrospectively to derive analytical curves that predict image quality. Patient noise equivalent count rate and coefficient of variation (CV) were used as metrics in their analysis. Optimized acquisition protocols were identified and prospectively applied to 179 subjects. Results: The adoption of different schemes for three body mass ranges (90 kg) allows improved image quality with both point spread function and ordered-subsets expectation maximization-3D reconstruction methods. The application of this methodology showed that CV improved significantly (p < 0.0001) in clinical practice. Conclusions: Consistent oncological PET/CT image quality on a high-performance scanner was achieved from an analysis of the relations existing between dose regimen, patient habitus, acquisition, and processing techniques. The proposed methodology may be used by PET/CT centers to develop protocols to standardize PET/CT imaging procedures and achieve better patient management and cost-effective operations