Table 1 Patient and aneurysm characteristics of training and test sets. WFNS = World Federation of Neurosurgical Societies. SD = standard deviation.

From: Fully automated detection and segmentation of intracranial aneurysms in subarachnoid hemorrhage on CTA using deep learning

Characteristic

Training set

(n = 68)

Test set

(n = 185)

P value

Patient age (years; mean ± SD)

53.0 ± 12.8

55.1 ± 13.8

.31

Gender

  

.75

Female

47 (69.1%)

124 (67%)

 

Male

21 (30.9%)

61 (33%)

 

WFNS grade

  

.46

1

21 (30.9%)

54 (29.2%)

 

2

12 (17.6%)

23 (12.4%)

 

3

6 (8.8%)

27 (14.6%)

 

4

6 (8.8%)

26 (14.1%)

 

5

23 (33.8%)

55 (29.7%)

 

Fisher grade

  

.18

1

2 (2.9%)

0 (0%)

 

2

3 (4.4%)

13 (7%)

 

3

24 (35.3%)

83 (44.9%)

 

4

39 (57.4%)

89 (48.1%)

 

Aneurysm volume (mm3; mean ± SD)

187.1 ± 296.3

145.6 ± 223.5

.26

Aneurysm location

  

.64

Internal carotid artery

20 (25.3%)

46 (21.4%)

 

Anterior cerebral artery

24 (30.4%)

80 (37.2%)

 

Middle cerebral artery

24 (30.4%)

66 (30.7%)

 

Posterior circulation

11 (13.9%)

23 (10.7%)