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Table 3 Lesion diagnostic performances parameters of different reconstruction and different BMI (n = 466)

From: Enhancing 18F-FDG PET image quality and lesion diagnostic performance across different body mass index using the deep progressive learning reconstruction algorithm

BMI categories

Parameters

Larger lesions (OSEM)

(n = 282)

Larger lesions (DPL)

(n = 282)

Sub-centimeter lesions (OSEM)

(n = 184)

Sub-centimeter lesions (DPL)

(n = 184)

Underweight (n = 118)

\(\:{\text{S}\text{U}\text{V}}_{\text{m}\text{a}\text{x}}^{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

12.2(9.9,16.7)

14.4(10.8,18.4)

6.1(4.9,7.6)

7.6(5.9,9.2)

\(\:{\text{S}\text{B}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

7.0(5.5,10.3)

7.6(6.2,10.9)

3.2(2.6,4.4)

4.1(3.2,5.4)

\(\:{\text{S}\text{N}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

79.4(54.7,118.5)

133.0(102.3,183.5)

36.9(30.2,43.3)

67.0(55.3,91.8)

\(\:{\text{C}\text{B}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

6.0(4.5,9.3)

6.6(5.2,9.9)

2.2(1.6,3.4)

3.1(2.2,4.4)

\(\:{\text{C}\text{N}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

68.3(43.3,106.9)

118.1(85.5,164.9)

25.4(18.6,31.0)

49.0(37.8,71.5)

Normal (n = 207)

\(\:{\text{S}\text{U}\text{V}}_{\text{m}\text{a}\text{x}}^{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

11.2(7.9,15.3)

12.1(8.8,17.1)

5.9(4.6,7.7)

7.5(6.0,9.9)

\(\:{\text{S}\text{B}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

6.1(4.1,8.2)

6.3(4.3,8.9)

3.0(2.4,4.5)

4.0(3.0,5.5)

\(\:{\text{S}\text{N}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

46.5(33.4,71.6)

88.5(63.0,141.0)

28.7(22.4,41.5)

60.5(46.5,91.0)

\(\:{\text{C}\text{B}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

5.1(3.1,7.2)

5.3(3.3,7.9)

2.0(1.4,3.5)

3.0(2.0,4.5)

\(\:{\text{C}\text{N}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

37.8(24.5,63.6)

72.8(48.0,121.3)

18.7(13.8,32.8)

43.5(30.8,73.8)

Overweight (n = 141)

\(\:{\text{S}\text{U}\text{V}}_{\text{m}\text{a}\text{x}}^{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

12.0(8.2,17.3)

12.9(9.3,20.5)

6.0(4.8,8.5)

7.8(6.0,10.8)

\(\:{\text{S}\text{B}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

5.0(3.1,7.1)

5.2(3.4,8.0)

2.4(2.0,3.7)

3.1(2.5,4.6)

\(\:{\text{S}\text{N}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

43.1(27.5,61.2)

84.8(49.5,123.7)

22.0(17.9,33.7)

47.1(37.3,69.6)

\(\:{\text{C}\text{B}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

4.0(2.1,6.1)

4.2(2.4,7.0)

1.4(1.0,2.7)

2.2(1.5,3.6)

\(\:{\text{C}\text{N}\text{R}}_{\text{L}\text{e}\text{s}\text{i}\text{o}\text{n}}\)

37.1(24.0,59.4)

74.8(44.2,109.9)

17.1(11.4,27.9)

39.4(28.6,63.9)