Artificial intelligence-based lung nodule detection for pulmonary arteriovenous fistulas on chest computed tomography

Table 3 Comparison of variables between successful and failed computer-aided detection

Characteristic	Factors	Overall (n = 26)	Detection success (n = 17)	Detection failure (n = 9)	P value
Location	Right upper lobe	7	3	4	-
	Right middle lobe	3	2	1
	Right lower lobe	4	3	1
	Left upper lobe	3	2	1
	Lingular segment	6	4	2
	Left lower lobe	3	3	0
Contact with adjacent structures	Present	19	13 (68)	6 (32)	0.63
	Absent	6	3 (50)	3 (50)
Morphology1	Simple type	22	13 (59)	9 (41)	0.26
	Complex type	4	4 (100)	0 (0)
Treatment indication2	Present	18	13 (72)	5 (28)	0.38
	Absent	8	4 (50)	4 (50)
Feeding artery diameter (mm)			3.4 (3.0, 4.0)	3.4 (2.4, 4.8)	0.47
Maximum lesion length (mm)			6.5 (4.9, 9.6)	5.5 (2.5, 11.0)	0.65

¹Simple type (single feeding artery and draining vein) or complex type (multiple feeding arteries).

²Treatment indication was defined as a feeding artery diameter of ≥ 3 mm.

Continuous variables are presented as median (interquartile range). No statistical comparison was performed for lesion location.