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Prof. Fiona Gilbert (Cambridge, UK) gave the Arthur de Schepper Honorary Lecture at the European Congress of Radiology (ECR) 2017. The renowned UK breast radiologist talked about the recent breakthroughs in breast imaging, focusing on the efforts of breast imagers in moving from feature analysis to functional characterization of breast lesions.

The imaging phenotypes of breast cancer are routinely used to guide therapeutic decisions and treatment planning, and to decide the likelihood of a lesion being invasive or in situ disease, which affects the diagnostic approach. The morphological appearance already gives clues on tumor grade and aggressiveness of a cancer. Functional imaging provides further information about hallmarks processes in cancer development and progression such as neoangiogenesis, altered metabolism, sustained proliferation as well as information on the tumor microstructure/environment. Several functional magnetic resonance imaging (MRI) techniques such as dynamic contrast-enhanced (DCE) MRI, diffusion-weighted imaging (DWI), proton magnetic resonance spectroscopy (1H-MRSI), sodium imaging and blood oxygen level-dependent (BOLD) MRI have been introduced and enable visualization and quantification of functional processes at the cellular and molecular levels, which are beyond the scope of conventional imaging. Nuclear imaging using different radiolabeled tracers also interrogates different aspects of cancer biology such as tumor metabolism, proliferation or receptor status but lacks the required spatial resolution for high quality diagnostic imaging and is therefore usually performed as hybrid imaging with positron emission tomography/computed tomography (PET/CT) or PET/MRI .

Multiparametric and even multimodal functional breast imaging thus provides insights into the underlying oncogenic processes of cancer development, progression and response to treatment. Thus tackling the genomically heterogeneous nature of breast cancer by unraveling its metabolic towards personalized medicine in breast cancer.

Listen to the lecture via ECR Online here