Premium
Optimization of oncological 18 F‐FDG PET/CT imaging based on a multiparameter analysis
Author(s) -
Menezes Vinicius O.,
Machado Marcos A. D.,
Queiroz Cleiton C.,
Souza Susana O.,
d'Errico Francesco,
Namías Mauro,
Larocca Ticiana F.,
Soares Milena B. P.
Publication year - 2016
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4940354
Subject(s) - image quality , iterative reconstruction , nuclear medicine , pet ct , image processing , medical imaging , scanner , medicine , dosimetry , quality assurance , positron emission tomography , medical physics , radiology , computer science , artificial intelligence , image (mathematics) , external quality assessment , pathology
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.