Changes in AI mammogram risk scores over time help predict future breast cancer

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Images in a 75-year-old woman who underwent routine screening mammography in 2022. Left mediolateral oblique views shown from prior screening mammograms: (A) 2015, (B) 2018, (C) 2019, and (D) 2021. In (E) 2022, a new mass developed in the left breast at the 6-o’clock position (arrow), with a (F) corresponding irregular mass at US (arrow). Subsequent US-guided core needle biopsy yielded invasive ductal carcinoma, grade 2. The deep learning 5-year risk scores gradually increased from 2.0 (2015) to 2.1 (2018), 3.4 (2019), 3.6 (2021), and 15.3 (2022). CMFN = centimeters from nipple, LT = left, TRANS = transverse.

Credit: Radiological Society of North America (RSNA)

OAK BROOK, Ill. – Using artificial intelligence (AI), researchers found that image-based risk scores for breast cancer derived from screening mammograms evolve over time and differ between women who develop cancer and those who do not, opening the door to a new era of dynamic breast cancer risk assessment. The new research was published today in Radiology, a journal of the Radiological Society of North America (RSNA).

Deep learning models can now generate breast cancer risk scores directly from screening mammograms, using the entire image rather than a limited, predetermined feature such as density. These models have demonstrated better performance than traditional risk models and breast density alone in estimating a woman’s five-year breast cancer risk.

Most women diagnosed with breast cancer have no known genetic mutations or reported family…

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