Predicting Pathologic Bone Lesions Using Scout Computed Tomography (CT) Imaging
Table 1
Demographic characteristics of included patients, patients with unobserved lesions, and patients without unobserved lesions.
Demographics
All patients (n = 39)
Patients with missed lesions (n = 17)
Patients without missed lesions (n = 23)
value
Age in years (mean) (range)
61 (38, 79)
55 (38, 76)
65 (44, 79)
0.006
Gender
Male (n) (%)
13 (33.3%)
6
7
1.0
Female (n) (%)
26 (66.7%)
11
16
1.0
Ethnicity
Caucasian (n) (%)
36 (92.3%)
14
23
0.069
African American (n) (%)
3 (7.7%)
3
0
0.069
BMI (mean) (range)
27.0 (16.6, 71.2)
28.0 (16.6, 71.2)
26.1 (19.4, 36.5)
0.636
History of smoking (n) (%)
24 (61.5%)
9
15
0.522
Comorbidities
Cardiovascular disease (n) (%)
24 (61.5%)
9
16
0.336
Chronic kidney disease(n) (%)
3 (7.7%)
2
1
0.565
Chronic obstructive pulmonary disease (n) (%)
6 (15.4%)
1
5
0.216
Diabetes mellitus (n) (%)
6 (15.4%)
2
5
0.677
Rheumatoid arthritis (n) (%)
1 (2.6%)
1
0
0.425
Hypothyroidism (n) (%)
6 (15.4%)
1
6
0.205
Cancer type
Breast (n) (%)
16 (41.0%)
8
9
0.750
Lung (n) (%)
7 (17.9%)
2
5
0.677
Prostate (n) (%)
4 (10.3%)
0
4
0.123
Renal (n) (%)
4 (10.3%)
2
2
1.0
Multiple myeloma (n) (%)
3 (7.7%)
1
2
1.0
Colon (n) (%)
1 (2.6%)
1
0
0.425
Hepatocellular (n) (%)
1 (2.6%)
1
0
0.425
Melanoma (n) (%)
1 (2.6%)
1
0
0.425
Leiomyosarcoma (n) (%)
1 (2.6%)
1
0
0.425
Unknown (n) (%)
1 (2.6%)
0
1
1.0
Site of lesion
Femur (n) (%)
34 (87.2%)
15
19
1.0
Humerus (n) (%)
5 (12.8%)
2
4
1.0
One patient had both a lesion identified by authors on scout CT that was not reported on initial radiographic dictation and a separate lesion that was identified on the initial dictation; thus, this patient was included in analysis of both groups. BMI, body mass index; CT, computed tomography.
