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Table 1 Optimized parameters chosen according to the model of the scanner

From: Optimization of brain PET imaging for a multicentre trial: the French CATI experience

GE models Number Installation year Slice thickness (mm) Recons. method Number of iterations (iterations × subsets) Post-reconstruction filter type and FWHM if relevant (mm) Matrix Pixel spacing (mm × mm) Others
 Discovery 690 3 2009/2010/2011 3.27 VPHD 10 × 36 Gaussian 3.5 256 × 256 1.17 × 1.17 Z-filter: standard
 Discovery RX 2 2009 3.27 FORE + OSEM 2D 7 × 35 Gaussian 3.5 128 × 128 2.34 × 2.34 Loop filter: 2.34 mm
Z-filter: standard
 Discovery DST - E 1 2004 3.27 FORE + OSEM 2D 5 × 35 Gaussian 2.57 128 × 128 2.34 × 2.34 Loop filter: 2.34 mm
Z-filter: standard
 Discovery ST 4 1 2004 3.27 FORE + OSEM 2D 7 × 35 Gaussian 3 256 × 256 1.17 × 1.17 Loop filter: 2 mm
Z-filter: standard
 Discovery ST 2 2003/2004 3.27 FORE + OSEM 2D 7 × 32 Gaussian 2 or 2.57 128 × 128 2.34 × 2.34 Loop filter: 2.34 mm
Philips models Number Installation year Slice thickness (mm) Recons. method Number of iterations (iterations × subsets) Smoothing (mm) Matrix Pixel spacing (mm × mm) Others
 Gemini TF 2 2008/2010 2 LOR - RAMLA 10 × 33 Smooth B 128 × 128 2 × 2
 Gemini GXL 1 2006 2 LOR - RAMLA 10 × NA Smooth 128 × 128 2 × 2
Siemens models Number Installation year Slice thickness (mm) Recons. method Number of iterations (iterations × subsets) Post-reconstruction filter type and FWHM if relevant (mm) Matrix Pixel spacing (mm × mm) Others
 Biograph mCT 40/64 3 2009/2012 2.027 OSEM 3D 12 × 24 Gaussian 3 or 4 256 × 256 1.59 × 1.59
 Biograph Hirez TruePoint 1 2008 3 OSEM 3D 8 × 21 Gaussian 4 336 × 336 1.02 × 1.02
 Biograph 6 VB 20B True V 1 2006 2 FORE + OSEM 2D 8 × 21 Gaussian 4 256 × 256 1.34 × 1.34
 Biograph 6 2 2004/2005 2 FORE + OSEM 2D 8 × 24 Gaussian 2 or 3 256 × 256 1.33 × 1.33
 Biograph 16 VB40B 1 2004 2 FORE + OSEM 2D 8 × 24 Gaussian 3 336 × 336 1.02 × 1.02
 Biograph LSO DUO 2 2003/2004 3.375 FORE + OSEM 2D 8 × 16 Gaussian 2 256 × 256 1.33 × 1.33
  1. NA non applicable, OSEM Ordered Subset Expectation Maximization, VPHD VUE Point High Definition, LOR-RAMLA Line-of-Response Row-Action Maximum Likelihood Algorithm, FORE Fourier Rebinning