Table 1 Patient data of all twenty-three patients collected for clinical study at Rochester General Hospital including the patient’s age, breast with tumor (BWT), breast density, tumor grade, and cancer type.

From: Breast cancer detection using enhanced IRI-numerical engine and inverse heat transfer modeling: model description and clinical validation

Patient

Age

BWT

Breast density

Tumor grade

Cancer type

1

60

R

HD

2

DCIS

2

70

R

SF

2

IDC

3

71

R

PF

1

IDC

4

68

R

SF

3

IDC

4

68

L

SF

1

ILC

5

51

R

SF

2

IDC

6

67

L

SF

1

IDC

7

67

L

SF

1

IDC

8

62

L

PF

3

ILC

9

46

R

HD

2

IDC

10

48

R

SF

1

IDC

11

64

R

PF

1

IDC

12

68

L

HD

1

ADH

13

68

L

SF

3

IDC

14

70

R

SF

3

IDC

15

42

R

HD

3

IDC

16

49

R

SF

3

IDC

17

70

L

SF

2

ILC

18

67

L

ED

X

LCIS

19

72

R

SF

2

IDC

20

72

L

SF

3

IDC

21

64

L

SF

2

IDC

22

63

L

SF

2

IDC

23

57

L

SF

2

IDC

  1. The letters R and L represent the right and left breast, respectively. Patient 4 has bilateral breast cancer and appears twice in the table, but with each breast having distinct tumor grades and cancer types. Patient 18 is the only one with an undetermined tumor grade that is represented by X. The breast density types are predominantly fatty (PF), scattered fibroglandular (SF), heterogeneously dense (HD), and extremely dense (ED). The cancer types are ductal carcinoma in situ (DCIS), invasive ductal carcinoma (IDC), invasive lobular carcinoma (ILC), lobular carcinoma in situ (LCIS), and atypical ductal hyperplasia (ADH).