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Digital PET compliance to EARL accreditation specifications
- Source :
- EJNMMI Physics, EJNMMI physics, 4(9). Springer
- Publisher :
- Springer Nature
-
Abstract
- Background Our aim was to evaluate if a recently introduced TOF PET system with digital photon counting technology (Philips Healthcare), potentially providing an improved image quality over analogue systems, can fulfil EANM research Ltd (EARL) accreditation specifications for tumour imaging with FDG-PET/CT. Findings We have performed a phantom study on a digital TOF PET system using a NEMA NU2-2001 image quality phantom with six fillable spheres. Phantom preparation and PET/CT acquisition were performed according to the European Association of Nuclear Medicine (EANM) guidelines. We made list-mode ordered-subsets expectation maximization (OSEM) TOF PET reconstructions, with default settings, three voxel sizes (4 × 4 × 4 mm3, 2 × 2 × 2 mm3 and 1 × 1 × 1 mm3) and with/without point spread function (PSF) modelling. On each PET dataset, mean and maximum activity concentration recovery coefficients (RCmean and RCmax) were calculated for all phantom spheres and compared to EARL accreditation specifications. The RCs of the 4 × 4 × 4 mm3 voxel dataset without PSF modelling proved closest to EARL specifications. Next, we added a Gaussian post-smoothing filter with varying kernel widths of 1–7 mm. EARL specifications were fulfilled when using kernel widths of 2 to 4 mm. Conclusions TOF PET using digital photon counting technology fulfils EARL accreditation specifications for FDG-PET/CT tumour imaging when using an OSEM reconstruction with 4 × 4 × 4 mm3 voxels, no PSF modelling and including a Gaussian post-smoothing filter of 2 to 4 mm.
- Subjects :
- Point spread function
Image quality
Short Communication
Biomedical Engineering
computer.software_genre
Tumour imaging
Imaging phantom
030218 nuclear medicine & medical imaging
EANM guidelines
03 medical and health sciences
0302 clinical medicine
Voxel
Expectation–maximization algorithm
Medicine
Radiology, Nuclear Medicine and imaging
Computer vision
FDG-PET
Instrumentation
EARL accreditation
Radiation
business.industry
Filter (signal processing)
Photon counting
030220 oncology & carcinogenesis
Kernel (statistics)
Artificial intelligence
business
Nuclear medicine
computer
Digital PET
Subjects
Details
- Language :
- English
- ISSN :
- 21977364
- Volume :
- 4
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- EJNMMI Physics
- Accession number :
- edsair.doi.dedup.....6a31a8741753f87253966f1f843686b2
- Full Text :
- https://doi.org/10.1186/s40658-017-0176-5