From: Artificial intelligence in mammographic phenotyping of breast cancer risk: a narrative review
Study | Image format | Time from exam to breast cancer diagnosis | # images (# women) | Vendors (# sites) | Model architecture | Model performance |
---|---|---|---|---|---|---|
Long-term risk assessment | ||||||
Yala et al. [46] | FFDM (processed) | 1–5 years | 295,002 images (91,520 women) | Hologic (3 sites) | ResNet-18* | AUC = 0.84, 1-year risk AUC = 0.76, 5-year risk |
Dembrower et al. [43] | FFDM (processed) | 3.6 ± 2.2 years | 150,502 images (1188 cases; 10,563 controls) | Hologic (N/R) | Inception-ResNet* | OR = 1.55 ORadj = 1.56 AUC = 0.65 |
Arefan et al. [45] | FFDM (processed) | 1–4 years | 452 images (113 cases; 113 controls) | Hologic (1 site) | GoogleLeNet | AUC = 0.68, CC AUC = 0.60, MLO |
Yala et al. [44] | FFDM (processed) | 1–5 years | 88,994 images (1821 cases; 38,284 controls) | Hologic (1 site) | ResNet-18* | AUC = 0.68 for image only DL AUC = 0.70 for hybrid DL + risk factors |
Ha et al. [47] | FFDM (processed) | 2–5.3 years | N/R (210 cases; 527 controls) | GE (1 site) | CNN | OR = 4.42 Acc = 72% |
Short-term risk assessment | ||||||
Lotter et al. [48] | FFDM (processed) DBT (MSP) | 1–2 years | N/R (> 1000 cases; 62 K controls) | GE, Hologic (7 databases/sites) | RetinaNet* | AUC = 0.75–0.76 |
Eriksson et al. [49] | FFDM (processed) | 3 months–2 years | N/R (974 cases, 9376 controls) | GE, Philips, Sectra, Hologic, Siemens (4 sites) | CNN** | HR = 7.9 AUC = 0.73 |
McKinney et al. [50] | FFDM (processed) | 0 months–3.25 years | N/R (> 105 k women) | Hologic, GE, Siemens (4 sites) | RetinaNet MobileNetV2 ResNet-v2-50 ResNet-v1-50 | AUC = 0.76–0.89 |