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. Author manuscript; available in PMC: 2018 May 1.
Published in final edited form as: Eur Radiol. 2016 Sep 5;27(5):2055–2066. doi: 10.1007/s00330-016-4571-4

Table 1.

Per-patient pooled performance data by reconstruction algorithm

Performance Measure % [95% CI] (N/total N) Reconstruction Algorithm
SD-FBP RD-FBP RD-ASIR RD-MBIR
Sensitivity 0.91 [0.84–0.99] (52/57) 0.79 [0.68–0.90] (45/57) 0.84 [0.75–0.94] (48/57) 0.84 [0.75–0.94] (48/57)
Specificity 0.78 [0.71–0.84] (119/153) 0.75 [0.68–0.82] (115/153) 0.75 [0.68–0.82] (115/153) 0.68 [0.61–0.75] (104/153)
Positive Predictive Value 0.60 [0.50–0.71] (52/86) 0.54 [0.43–0.65] (45/83) 0.56 [0.45–0.66] (48/86) 0.49 [0.40–0.59] (48/97)
Negative Predictive Value 0.96 [0.93–0.99] (119/124) 0.91 [0.85–0.95] (115/127) 0.93 [0.88–0.97] (115/124) 0.92 [0.87–0.97] (104/113)
Accuracy 0.81 [0.76–0.87] (171/210) 0.76 [0.70–0.82] (160/210) 0.78 [0.72–0.83] (163/210) 0.72 [0.66–0.78] (152/210)