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Krupinski, Johnson, Roehrig et al. (2003)

Reader and case sample combinations needed for 0.80 power based on the data of:

Krupinski EA, Johnson J, Roehrig H, Engstrom M, Fan J, Nafziger J, Lubin J, Dallas WJ. Using a human visual system model to optimize soft-copy mammography display: influence of MTF compensation. Academic Radiology 2003;10:1030-1035.

Goal: measure observer performance on soft-copy display of mammographic images that were either unprocessed or processed to compensate for modulation transfer function (MTF) deficiencies in the CRT display.

Readers: 6 radiologists

Cases: 250 mammographic regions of interest (256 x 256) with micro-calcification clusters with different contrast levels on a CRT monitor -- 50 lesion free (0% contrast) and 200 of which had lesions (50 at each contrast level 25%, 50%, 75%, and 100%).

Rating: confidence in the presence of a microcalcification cluster on a 6-point scale.

Conditions: (1) without image processing, (2) with processing to compensate for MTF deficiencies in the CRT monitor.

ROC Model = propROC, Parameter = AUC,

AUCs = 0.833, 0.805, respectively.

Readers = 6, Cases = 250,

MS( Treatment*Reader ) = 0.01148499,

MS( Treatment*Case ) = 0.11132085,

MS( Treatment*Reader *Case ) = 0.10809497.

 

AUC Difference = 0.03

Readers

Readers

and Cases

Random

Cases

Random

Readers

Random

3

246

640

253

4

220

483

223

5

197

389

199

6

179

326

179

7

165

281

163

8

152

247

150

9

142

221

139

10

133

200

129

11

125

183

121

12

118

169

114

13

112

157

107

14

106

146

101

15

101

138

96

 

 

AUC Difference = 0.05

Readers

Readers

and Cases

Random

Cases

Random

Readers

Random

3

208

232

215

4

161

175

164

5

130

142

131

6

109

119

109

7

95

103

94

8

83

91

82

9

75

81

73

10

68

74

66

11

62

68

60

12

57

62

55

13

53

58

51

14

50

54

48

15

47

51

45

 

 

AUC Difference = 0.10

Readers

Readers

and Cases

Random

Cases

Random

Readers

Random

3

122

60

127

4

72

46

73

5

50

37

51

6

39

32

39

7

32

28

32

8

27

25

27

9

24

22

23

10

21

20

20

11

20

20

20

12

20

20

20

13

20

20

20

14

20

20

20

15

20

20

20

 

Cautionary note:  For this data set the estimated required number of cases when only cases are treated as random sometimes considerably exceeds the required number when both cases and readers are treated as random. If the variance components were all known, this would not be possible. It happens here because we are using unbiased estimates of the variance components rather than the true unknown parameter values; in particular, it happens because the treatment-by-reader variance component estimate is negative.  In this situation a conservative approach is to rerun the program with the treatment-by-reader variance component estimate set to zero.  Alternatively, in this situation you may want to consider pooling information from several similar studies, resulting in more precise variance component estimates and hence more precise sample size estimates.  The reader is referred to the Details section of the MRMC Sample Size User's Guide for further information.

 


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