Table 1 Characteristics of all enrolled patients.

From: Classification of malignant tumours in breast ultrasound using unsupervised machine learning approaches

Characteristics

Benign

Malignant

Age of patients (years in mean ± SD)

43.70 (42.23–45.18)

55.88 (54.39–57.38)

Lesion size of US (cm in mean ± SD)

1.56 (1.44–1.73)

2.28 (2.14–2.42)

BI-RADS category: patients in percentage (%)

1

–

–

2

7 (2.24%)

–

3

63 (20.19%)

11 (3.01%)

4A

222 (71.15%)

130 (35.62%)

4B

14 (4.49%)

46 (12.60%)

4C

3 (0.96%)

43 (11.78%)

5

1 (0.32%)

106 (29.04%)

6

1 (0.32%)

29 (7.95%)

Malignant tissue: patients in percentage (%)

DCIS

–

76 (20.82%)

IDC

–

289 (79.18%)

Benign tumour: patients in percentage (%)

LCIS

14 (4.49%)

–

Fibroadenoma

78 (25.00%)

–

Fibrocystic change

105 (33.65%)

–

Intraductal papilloma

14 (4.49%)

–

Stromal fibrosis

5 (1.60%)

–

Fibroadenomatoid mastopathy

1 (0.32%)

–

Adenosis

6 (1.92%)

–

Fibroepithelial lesion

72 (23.08%)

–

Morphological features of carcinoma

17 (5.45%)

–

  1. Basic characteristics of all enrolled patients and the proportions of benign (n = 312) and malignant (n = 365) cases include the age of patients (mean ± SD), size of lesions in the US and the BI-RADS category / benign and malignant tissue of patients. US: ultrasound; DCIS: ductal carcinoma in situ; LCIS: lobular carcinoma in situ; IDC: invasive ductal carcinoma; Morphological features of carcinoma: it showing morphological features of carcinoma in the US image, and confirmed to be benign tissue after a biopsy.
Back to article page