Vinicius O Menezes1, Marcos A D Machado2, Cleiton C Queiroz3, Susana O Souza4, Francesco d'Errico5, Mauro Namías6, Ticiana F Larocca7, Milena B P Soares8. 1. Nuclear Medicine Department, São Rafael Hospital, Salvador 41720-375, Brazil and Nuclear Medicine Department, Hospital das Clínicas da Universidade Federal de Pernambuco/Ebserh, Recife 50670-901, Brazil. 2. Nuclear Medicine Department, São Rafael Hospital, Salvador 41720-375, Brazil and Nuclear Medicine Department, Hospital das Clínicas da Universidade Federal de Bahia/Ebserh, Salvador 40110-060, Brazil. 3. Nuclear Medicine Department, São Rafael Hospital, Salvador 41720-375, Brazil and Nuclear Medicine Department, Hospital Universitário Professor Alberto Antunes/Ebserh, Maceió 57072-900, Brazil. 4. Department of Physics, Universidade Federal de Sergipe, São Cristóvão 49100-000, Brazil. 5. Department of Diagnostic Radiology, Yale University School of Medicine, New Haven, Connecticut 06520 and School of Engineering, University of Pisa, Pisa 56126, Italy. 6. Fundación Centro Diagnóstico Nuclear, Buenos Aires C1417CVE, Argentina. 7. Centro de Biotecnologia e Terapia Celular, São Rafael Hospital, Salvador 41253-190, Brazil. 8. Centro de Biotecnologia e Terapia Celular, São Rafael Hospital, Salvador 41253-190, Brazil and Fundação Oswaldo Cruz, Centro de Pesq. Gonçalo Moniz, Salvador 40296-710, Brazil.
Abstract
PURPOSE: This paper describes a method to achieve consistent clinical image quality in (18)F-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 (<60 kg, 60-90 kg, >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.
PURPOSE: This paper describes a method to achieve consistent clinical image quality in (18)F-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 (<60 kg, 60-90 kg, >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.
Authors: Christina P W Cox; Daniëlle M E van Assema; Frederik A Verburg; Tessa Brabander; Mark Konijnenberg; Marcel Segbers Journal: EJNMMI Res Date: 2021-07-19 Impact factor: 3.138