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Table 2 Representative studies in AI-enabled direct breast risk assessment from mammographic images

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

  1. The table describes the development image dataset used in each study, including format of mammographic images, time window from mammographic exam to breast cancer diagnosis, sample size, and vendors, as well as model architecture and performance in breast cancer risk assessment
  2. FFDM full-field digital mammography, CNN convolutional neural network, AUC area under the ROC curve, Acc accuracy, OR odds ratio, HR hazard ratio
  3. *Indicates publicly available AI model. **Indicates commercial model. N/R not explicitly reported in the paper