Voxel-wise analysis of dynamic 18 F-FET PET: a novel approach for non-invasive glioma characterisation

EJNMMI Research

Table 3 Data shown as in Table 2, separated according to molecular genetic grading

Tumour VOI, post-filtering	Parameter	IDH-mut non-codel (45)	IDH-mut codel (39)	IDH-wt (78)	H-test P; r	Post hoc
90% isocontour	TTP	25 ± 8	23 ± 9	16 ± 8	< 0.001; 0.45	∆x
90% isocontour	Slope_15–40	− 0.2 ± 1.5	− 0.2 ± 1.0	− 1.1 ± 1.3	< 0.001; 0.44	∆x
TBR_20–40 > 1.6	TBR_5–15,max	3.3 ± 1.5	3.5 ± 1.7	4.2 ± 1.3	< 0.001; 0.37	∆x
	TBR_5–15,mean	2.0 ± 0.5	2.0 ± 0.5	2.4 ± 0.4	< 0,001; 0.45	∆x
	TBR_20–40,max	3.2 ± 1.2	3.2 ± 1.4	3.5 ± 1.1	0.060; 0.19
	TBR_20–40,mean	2.0 ± 0.3	2.1 ± 0.4	2.1 ± 0.3	0.074; 0.18
	BTV_20–40	21 ± 22	28 ± 32	26 ± 24	0.347; 0.11
	PVH_{TBR,5–15 > 2}	32 ± 27	32 ± 26	62 ± 23	< 0.001; 0.52	∆x
	PVH_{TBR,20–40 > 2}	33 ± 23	33 ± 25	41 ± 22	0.071; 0.18
	PVH_TTP > 30	47 ± 21	50 ± 18	23 ± 20	< 0.001; 0.57	∆x
	PVH_TTP < 15	12 ± 13	10 ± 9	34 ± 22	< 0.001; 0.56	∆x
	PVH_TTP < 20	26 ± 20	24 ± 14	56 ± 25	< 0.001; 0.58	∆x
	PVH_{Slope < 0}	27 ± 20	25 ± 14	55 ± 23	< 0.001; 0.58	∆x
TBR_20–40 > 1.6, 10 mm Gauss	PVH_{GaussTTP > 30}	62 ± 30	67 ± 24	29 ± 28	< 0.001; 0.55	∆x
	PVH_{Gauss TTP < 20}	17 ± 22	12 ± 13	50 ± 31	< 0.001; 0.56	∆x
	PVH_{Gauss,Slope < 0}	21 ± 26	15 ± 16	56 ± 32	< 0.001; 0.57	∆x

Post hoc P < 0.05: ⁺IDH-mut non-codel vs. IDH-mut codel, ^∆IDH-mut non-codel vs. IDH-wt, ^xIDH-mut codel vs. IDH-wt