Assessment of Intracranial Arterial Stenosis with Multidetector Row CT Angiography: A Postprocessing Techniques Comparison

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Fig 1.
Sixty-three-year-old female patient: postprocessed VR (A), MIP (B), corona MPR (C), and CPR images (D, E).

Table 1:

Location of intracranial arterial stenosed segments detected by observers in consensus

	No. (%) of Lesions (n = 215)	No. (%) of Lesions (n = 215)
High cervical ICA right	7 (3.2)	54 (25)
High cervical ICA left	7 (3.2)
Petrous ICA right	9 (4.2)
Petrous ICA left	12 (6.7)
Cavernous ICA right	6 (2.8)
Cavernous ICA left	4 (1.9)
Supraclinoid ICA right	4 (1.9)
Supraclinoid ICA left	5 (2.3)
A1 right	2 (0.9)	7 (3)
A1 left	1 (0.5)
A2 right	2 (0.9)
A2 left	2 (0.9)
M1 right	9 (4.2)	31 (14)
M1 left	7 (3.2)
M2 right	8 (3.7)
M2 left	7 (3.2)
Intracranial vertebral right	23 (10.7)	49 (23)
Intracranial vertebral left	26 (12)
P1 right	12 (6.7)	47 (22)
P1 left	8 (3.7)
P2 right	11 (5.1)
P2 left	16 (7.4)
Proximal basilar	13 (6)	27 (13)
Distal basilar	14 (6.5)

Table 2:

Number of intracranial arterial stenosed segments according to observers and postprocessing techniques

	Number of Identified Lesions
	Observer 1				Observer 2
	MPR	CPR	MIP	VR	MPR	CPR	MIP	VR
High cervical ICA right	3	5	6	6	3	4	7	7
High cervical ICA left	3	4	7	7	4	5	7	7
Petrous ICA right	4	5	5	8	3	4	6	9
Petrous ICA left	5	6	7	11	2	5	8	11
Cavernous ICA right	2	8	5	5	4	4	4	4
Cavernous ICA left	3	2	4	3	4	3	4	5
Supraclinoid ICA right	3	3	4	4	4	2	4	5
Supraclinoid ICA left	3	4	5	5	2	3	5	4
A1 right	0	1	2	2	0	1	2	3
A1 left	0	0	1	1	1	0	2	1
A2 right	0	1	1	2	0	1	1	2
A2 left	0	0	1	2	0	0	2	2
M1 right	3	6	7	8	2	3	5	6
M1 left	2	4	6	7	3	2	4	7
M2 right	3	4	9	6	3	3	8	8
M2 left	2	1	10	6	2	1	11	7
Intracranial vertebral right	8	15	16	21	6	12	17	21
Intracranial vertebral left	12	14	21	24	9	19	22	25
P1 right	2	5	8	11	3	7	9	12
P1 left	3	6	6	9	4	8	7	7
P2 right	5	8	9	14	3	4	8	9
P2 left	6	12	14	13	8	14	13	13
Proximal basilar	7	9	12	14	9	8	10	10
Distal basilar	6	9	11	12	9	10	10	12
Total	85	132	177	201	88	123	176	197

Table 3:

Kappa value between observers in the identification of intracranial arterial segments according to different postprocessing techniques

Table 4:

Observer 1: Sensitivity, specificity, NPV, and PPV of the different reconstruction methods

	Sensitivity	Specificity	PPV	NPV
MPR	0.302 (95% CI = 0.241–0.364)	0.989 (95% CI = 0.984–0.994)	0.765 (95% CI = 0.675–0.885)	0.923 (95% CI = 0.911–0.935)
CPR	0.474 (95% CI = 0.408–0.541)	0.984 (95% CI = 0.978–0.989)	0.773 (95% CI = 0.701–0.844)	0.941 (95% CI = 0.930–0.951)
MIP	0.637 (95% CI = 0.573–0.701)	0.974 (95% CI = 0.967–0.982)	0.745 (95% CI = 0.682–0.808)	0.958 (95% CI = 0.949–0.967)
VR	0.888 (95% CI = 0.846–0.930)	0.995 (95% CI = 0.991–0.998)	0.950 (95% CI = 0.920–0.980)	0.987 (95% CI = 0.982–0.992)

Table 5:

Observer 2: Sensitivity, specificity, NPV, and PPV of the different reconstruction methods

	Sensitivity	Specificity	PPV	NPV
MPR	0.381 (95% CI = 0.316–0.446)	0.997 (95% CI = 0.994–0.999)	0.824 (95% CI = 0.734–0.894)	0.932 (95% CI = 0.921–0.943)
CPR	0.521 (95% CI = 0.454–0.588)	0.994 (95% CI = 0.990–0.998)	0.762 (95% CI = 0.670–0.884)	0.946 (95% CI = 0.936–0.956)
MIP	0.572 (95% CI = 0.506–0.638)	0.971 (95% CI = 0.963–0.979)	0.699 (95% CI = 0.631–0.767)	0.951 (95% CI = 0.941–0.960)
VR	0.916 (95% CI = 0.879–0.953)	0.999 (95% CI = 0.998–1)	0.995 (95% CI = 0.985–1)	0.990 (95% CI = 0.986–0.995)

Table 8:

Kappa value between observers in the quality image evaluation according to different postprocessing techniques