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. 2021 May 4;22(8):1225–1239. doi: 10.3348/kjr.2020.1210

Table 3. Summary of Studies Using AI-CAD for DBT Interpretation.

References No. of Readers No. of DBT Exams Software Used Reading Time AUC Sensitivity (%) Specificity (%) Recall Rates (%)
Without CAD With CAD Without CAD With CAD Without CAD With CAD Without CAD With CAD
Balleyguier et al. 2017 [39] 6 80 (23 cancers) PowerLook Tomo Detection, iCAD ↓ 48.2 sec 0.854 0.850 86.5 86.5 57.6 56.2 42.7 45.2
↓ 23.5%
Benedikt et al. 2018 [40] 20 240 (60 cancers) PowerLook Tomo Detection, iCAD* ↓ 19.6 sec 0.841 0.850 84.7 87.1 52.7 50.9 47.4 49.2
↓ 29%
Chae et al. 2019 [41] 4 100 (70 cancers) In-house DBT CAD system ↓ 10.04 sec 0.778 0.776 77.5 78.6 66.7 66.7 - -
↓ 14%
Conant et al. 2019 [35] 24 260 (65 cancers) PowerLook Tomo Detection, iCAD ↓ 34.7 sec 0.795 0.852 77.0 85.0† 62.7 69.6† 38.0 30.9
↓ 52.7%

*CAD system focuses on detecting soft tissue lesions and does not detect calcifications, With statistical significance. AI = artificial intelligence, AUC = area under the receiving operator characteristics curve, CAD = computer-aided detection/diagnosis, DBT = digital breast tomosynthesis