1. Influence of PET reconstruction technique and matrix size on qualitative and quantitative assessment of lung lesions on [18F]-FDG-PET: A prospective study in 37 cancer patients
- Author
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Wolfgang Marik, Georg Riegler, Ivo Rausch, Christopher Pivec, Georgios Karanikas, Helmut Prosch, Albert Hirtl, Karem El-Rabadi, Michael Weber, and Marius E. Mayerhoefer
- Subjects
medicine.medical_specialty ,Lung Neoplasms ,Logistic regression ,030218 nuclear medicine & medical imaging ,Lesion ,03 medical and health sciences ,0302 clinical medicine ,Fluorodeoxyglucose F18 ,Ordered subset expectation maximization ,Positron Emission Tomography Computed Tomography ,medicine ,Humans ,Radiology, Nuclear Medicine and imaging ,Prospective Studies ,Prospective cohort study ,Independent Rater ,PET-CT ,Lung ,business.industry ,Repeated measures design ,General Medicine ,medicine.anatomical_structure ,030220 oncology & carcinogenesis ,Radiology ,Radiopharmaceuticals ,medicine.symptom ,Nuclear medicine ,business ,Algorithms - Abstract
Purpose To evaluate the influence of point spread function (PSF)-based reconstruction and matrix size for PET on (1) lung lesion detection and (2) standardized uptake values (SUV). Methods This prospective study included oncological patients who underwent [18F]-FDG-PET/CT for staging. PET data were reconstructed with a 2D ordered subset expectation maximization (OSEM) algorithm, and a 2D PSF-based algorithm (TrueX), separately with two matrix sizes (168×168 and 336×336). The four PET reconstructions (TrueX-168; OSEM-168; TrueX-336; and OSEM-336) were read independently by two raters, and PET-positive lung lesions were recorded. Blinded to the PET findings, a third independent rater assessed lung lesions with diameters of >4mm on CT. Subsequently, PET and CT were reviewed side-by side in consensus. Multi-factorial logistic regression analyses and two-way repeated measures analyses of variance (ANOVA) were performed. Results Thirty-seven patients with 206 lung lesions were included. Lesion-based PET sensitivities differed significantly between reconstruction algorithms ( P 0.001) and between reconstruction matrices ( P =0.022). Sensitivities were 94.2% and 88.3% for TrueX-336; 88.3% and 85.9% for TrueX-168; 67.8% and 66.3% for OSEM-336; and 67.0% and 67.9% for OSEM-168; for rater 1 and rater 2, respectively. SUV max and SUV mean were significantly higher for images reconstructed with 336×336 matrices than for those reconstructed with 168×168 matrices ( P Conclusion Our results demonstrate that PSF-based PET reconstruction, and, to a lesser degree, higher matrix size, improve detection of metabolically active lung lesions. However, PSF-based PET reconstructions and larger matrix sizes lead to higher SUVs, which may be a concern when PET data from different institutions are compared.
- Published
- 2017