Prediction of Breast Cancer Histological Outcome by Radiomics and Artificial Intelligence Analysis in Contrast-Enhanced Mammography.
Antonella PetrilloRoberta FuscoElio Di BernardoTeresa PetrosinoMaria Luisa BarrettaAnnamaria PortoVincenza GranataMaurizio Di BonitoAnnarita FanizziRaffaella MassafraNicole PetruzzellisFrancesca ArezzoLuca BoldriniDaniele La ForgiaPublished in: Cancers (2022)
The results confirm that the identification of malignant breast lesions and the differentiation of histological outcomes and some molecular subtypes of tumors (mainly positive hormone receptor tumors) can be obtained with satisfactory accuracy through both univariate and multivariate analysis of textural features extracted from Contrast-Enhanced Mammography images.
Keyphrases
- contrast enhanced
- artificial intelligence
- deep learning
- diffusion weighted
- magnetic resonance imaging
- magnetic resonance
- computed tomography
- machine learning
- big data
- diffusion weighted imaging
- convolutional neural network
- optical coherence tomography
- type diabetes
- skeletal muscle
- dual energy
- adipose tissue
- metabolic syndrome
- weight loss