Phantom criteria for qualification of brain FDG and amyloid PET across different cameras

Ikari, Yasuhiko; Akamatsu, Go; Nishio, Tomoyuki; Ishii, Kenji; Ito, Kengo; Iwatsubo, Takeshi; Senda, Michio

doi:10.1186/s40658-016-0159-y

EJNMMI Physics

Table 4 Phantom image performances acquired with reconstruction parameters optimized for each PET camera and for each PET drug

From: Phantom criteria for qualification of brain FDG and amyloid PET across different cameras

Vendor, model	PET drug	Reconstruction parameters	Spatial resolution (mm)	%contrast (%)	Uniformity (SD)	Image noise (CV [%])
GE, Advance	FDG	FORE + OSEM, subset = 20, iteration = 4, Z-axis; none	7.0	61.0	0.0245	13.7
	Florbetapir	FORE + OSEM, subset = 20, iteration = 4, Z-axis; none, Gaussian 4 mm	7.0	56.2	0.0245	10.7
	Flutemetamol	FORE + OSEM, subset = 20, iteration = 4, Z-axis; none, Gaussian 4 mm	7.0	58.0	0.0245	13.7
	PiB	FORE + OSEM, subset = 20, iteration = 4, Z-axis; none, Gaussian 4.5 mm	7.0	55.5	0.0245	14.1
GE, Discovery 600^a	FDG	3D-iteration, subset = 16, iteration = 5	5.3	72.9	0.0103	7.7
	Florbetapir	3D-iteration, subset = 16, iteration = 5	5.3	73.3	0.0103	12.0
	Flutemetamol	3D-iteration, subset = 16, iteration = 5, Gaussian (XxYxZ = 4 mm)	6.7	68.8	0.0103	9.1
	PiB	3D-iteration, subset = 16, iteration = 5, Gaussian (XxYxZ = 4 mm)	6.7	67.9	0.0103	12.3
GE, Discovery 690/710^a	FDG	3D-iteration, subset = 16, iteration = 4	5.3	65.6	0.0107	7.8
	Florbetapir	3D-iteration, subset = 16, iteration = 4	5.3	65.0	0.0115	12.3
	Flutemetamol	3D-iteration, subset = 16, iteration = 4, Gaussian (XxYxZ = 4 mm)	6.3	61.2	0.0107	9.2
	PiB	3D-iteration, subset = 16, iteration = 4, Gaussian (XxYxZ = 5 mm)	6.2	56.9	0.0110	8.2
GE, Discovery ST Elite	FDG	3D-iteration, subset = 35, iteration = 2, Z-axis; standard	5.5	68.9	0.0140	7.8
	Florbetapir	3D-iteration, subset = 35, iteration = 2, Z-axis; standard	5.5	70.5	0.0140	12.2
	Flutemetamol	3D-iteration, subset = 35, iteration = 2, Z-axis; standard, Gaussian (XxYxZ = 4 mm)	6.0	67.2	0.0140	9.9
	PiB	3D-iteration, subset = 35, iteration = 2, Z-axis; standard, Gaussian (XxYxZ = 4 mm)	6.0	67.0	0.0140	13.3
GE, Discovery ST (upgraded for 3D-IR)	FDG	3D-iteration, subset = 21, iteration = 4, Z-axis; standard	6.0	73.0	0.0120	7.1
	Florbetapir	3D-iteration, subset = 21, iteration = 4, Z-axis; standard	6.0	75.0	0.0120	10.8
	Flutemetamol	3D-iteration, subset = 21, iteration = 4, Z-axis; standard, Gaussian (XxYxZ = 4 mm)	6.0	67.6	0.0120	9.6
	PiB	3D-iteration, subset = 21, iteration = 4, Z-axis; standard, Gaussian (XxYxZ = 4 mm)	6.0	65.8	0.0120	13.2
Shimadzu, HeadtomeV^b	FDG	FORE + OSEM, subset = 16, iteration = 4, Ramp × BW cf = 8 o = 2	7.0	63.6	0.0215	9.7
	Florbetapir	FORE + OSEM, subset = 16, iteration = 4, Ramp × BW cf = 8 o = 2	7.0	63.1	0.0215	11.5
	Flutemetamol	FORE + OSEM, subset = 16, iteration = 4, Ramp × BW cf = 8 o = 2, Gaussian (XxYxZ = 4 mm)	7.5	56.3	0.0215	13.2
	PiB	FORE + OSEM, subset = 16, iteration = 4, Ramp × BW cf = 8 o = 2, Gaussian (XxYxZ = 4 mm)	7.5	55.7	0.0215	17.3
Shimadzu, Eminence BX	FDG	HDE, FORE-DRAMA, filter cycle = 0, iteration = 4	6.0	72.4	0.0180	6.5
	Florbetapir	HDE, FORE-DRAMA, filter cycle = 0, iteration = 4	6.0	72.3	0.0180	9.7
	Flutemetamol	HDE, FORE-DRAMA, filter cycle = 0, iteration = 4, Gaussian (XxYxZ = 4 mm)	7.0	66.0	0.0180	8.5
	PiB	HDE, FORE-DRAMA, filter cycle = 0, iteration = 4, Gaussian (XxYxZ = 4 mm)	7.0	65.4	0.0180	11.3
Shimadzu, Eminence GM	FDG	HDE, FORE-DRAMA, filter cycle = 0, iteration = 4	7.0	55.0	0.0249	8.8
	Florbetapir	HDE, FORE-DRAMA, filter cycle = 0, iteration = 4	7.0	56.0	0.0249	13.4
	Flutemetamol	HDE, FORE-DRAMA, filter cycle = 0, iteration = 4, Gaussian (XxYxZ = 4 mm)	8.0	50.0	0.0249	10.5
	PiB	HDE, FORE-DRAMA, filter cycle = 0, iteration = 4, Gaussian (XxYxZ = 4 mm)	8.0	51.0	0.0249	13.7
SIEMENS, biograph Hi-Rez^a	FDG	FORE + OSEM, subset = 14 (16), iteration = 4	7.0	64.0	0.0140	6.5
	Florbetapir	FORE + OSEM, subset = 14 (16), iteration = 4	7.0	63.6	0.0140	10.0
	Flutemetamol	FORE + OSEM, subset = 14 (16), iteration = 4, Gaussian (XxYxZ = 4 mm)	8.0	57.8	0.0135	9.7
	PiB	FORE + OSEM, subset = 14 (16), iteration = 4, Gaussian (XxYxZ = 4 mm)	8.0	58.2	0.0140	12.2
SIEMENS, biograph mCT-X 3R	FDG	3D-iterative, subset = 12, iteration = 4	6.0	71.0	0.0150	9.8
	Florbetapir	3D-iterative, subset = 12, iteration = 4	6.0	71.0	0.0150	14.9
	Flutemetamol	3D-iterative, subset = 12, iteration = 4, Gaussian (XxYxZ = 4 mm)	7.0	64.0	0.0150	8.5
	PiB	3D-iterative, subset = 12, iteration = 4, Gaussian (XxYxZ = 4 mm)	7.0	64.0	0.0150	11.5
SIEMENS, biograph truePoint	FDG	FORE + OSEM, subset = 14, iteration = 4	6.0	61.3	0.0100	7.1
	Florbetapir	FORE + OSEM, subset = 14, iteration = 4	6.0	61.3	0.0100	10.1
	Flutemetamol	FORE + OSEM, subset = 14, iteration = 4, Gaussian (XxYxZ = 4 mm)	8.0	56.4	0.0100	8.1
	PiB	FORE + OSEM, subset = 14, iteration = 4, Gaussian (XxYxZ = 4 mm)	8.0	56.4	0.0100	10.9
SIEMENS, ECAT Accel	FDG	FORE + OSEM, subset = 16, iteration = 6	7.0	56.0	0.0210	6.6
	Florbetapir	FORE + OSEM, subset = 16, iteration = 6	7.0	55.3	0.0210	9.9
	Flutemetamol	FORE + OSEM, subset = 16, iteration = 6, Gaussian (XxYxZ = 4 mm)	8.0	50.5	0.0210	11.4
	PiB	FORE + OSEM, subset = 16, iteration = 6, Gaussian (XxYxZ = 4 mm)	8.0	49.4	0.0210	16.2

Italic numbers represent performances deviated from the proposed criteria of phantom test for the specific PET drug condition
^aThe parameters are the mean values of three cameras of the same model
^bThe parameters are the mean values of two cameras of the same model

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