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Breast cancer continues to be the most commonly diagnosed cancer among women with over 2 million new cases per year worldwide. One important independent risk factor for developing breast cancer is breast density (BD). Epidemiological studies show that women with dense tissue may have an increased risk of developing breast cancer by 2-6 times when compared to women with less dense tissue. In this retrospective single-centre study, the authors aimed to evaluate the differences in radiomics features in different BD levels and to determine whether features derived from texture analysis (TA) are able to predict BD in spiral photon-counting computed tomography (PC-BCT). The authors were able to show that TA can in fact predict BD with high accuracy, resulting in TA possibly being a useful quantitative tool in the classification of BD in spiral PC-BCT.

Key points

  • Analysis of texture features on spiral photon-counting breast computed tomography is useful in the assessment of breast density.
  • Texture analysis may provide as an observer-independent, objective tool for breast density assessment and serve as quality control tool.
  • Texture analysis may complement breast cancer risk estimation, reflecting parenchymal tissue characteristics more precisely.

Article: Radiomics in photon-counting dedicated breast CT: potential of texture analysis for breast density classification

Authors: Anna Landsmann, Carlotta Ruppert, Jann Wieler, Patryk Hejduk, Alexander Ciritsis, Karol Borkowski, Moritz C. Wurnig, Cristina Rossi & Andreas Boss

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