Contrast-enhanced breast MRI has an established role in aiding in the detection, evaluation, and management of breast cancer. This article discusses MRI sequences, the clinical utility of MRI, and how MRI has been evaluated for use in breast radiotherapy treatment planning. We highlight the contribution of MRI in the decision-making regarding selecting appropriate candidates for breast conservation therapy and review the emerging role of MRI-guided breast radiotherapy.

Metastatic breast cancer (MBC) remains incurable because of tumor evolution. Despite advances in targeted therapies—CDK4/6 inhibitors, PIK3 inhibitors, HER2-directed agents, and antibody–drug conjugates—median overall survival is modest, with resistance emerging in nearly all patients. From an evolutionary perspective, standard continuous maximum tolerated dose (MTD) therapy may create intense selective pressure that reduces treatment-sensitive cells and, in some incurable and resistance-prone settings, could permit competitive release of resistant clones. While MTD remains the guideline-endorsed standard of care in many metastatic settings and has produced substantial survival gains, the eco-evolutionary framework highlights a potential trade-off rather than a categorical failure of MTD. Cancer is not just a genetic disease but an evolving ecosystem where cell populations compete for limited resources. Resistant cells typically carry a fitness cost—slower growth in the absence of treatment—creating an exploitable vulnerability. By preserving treatment-sensitive cells through dose modulation or treatment holidays (adaptive therapy), we can harness competitive suppression to control resistant populations and prolong disease control, potentially doubling time to progression compared to continuous MTD. This primer translates these ideas into plain language for clinical trial application. We explain four core eco-evolutionary principles every breast oncologist should know, review emerging evidence from adaptive therapy trials in breast and other cancers, and discuss practical implementation strategies to incorporate into future trials. The goal is not cure through eradication, but long-term control through evolutionary management. These evolution-informed strategies may, in selected contexts, help delay resistance and prolong disease control, and represent a complementary framework that warrants prospective testing.

Background parenchymal enhancement (BPE) on multi-parametric breast magnetic resonance imaging (mpMRI) reflects the volume and intensity of gadolinium uptake. We developed a semi-automated segmentation algorithm to extract and quantify measures of BPE and investigated the agreement of computed measures of BPE with radiologist-assigned categories. We retrospectively identified 123 high risk patients with breast mpMRI performed for screening indications. Pre- and post-gadolinium T1-weighted series with and without fat suppression were co-registered. Using Otsu’s method and an active contours method, the breast tissue was segmented from the chest wall and non-fat voxels were clustered to identify the amount of fibroglandular tissue. Median and inter-quartile ranges for the absolute volume of BPE (BPE cm3) and the percentage of BPE (BPE%) using a threshold PE of 30% were computed within the segmented FGT on the first post-contrast phase. Student’s t-test was used to evaluate BPE volume and BPE% by radiologist-assigned categories. Both BPE volume and BPE% differed significantly between minimal/mild and moderate/marked radiologist assigned categories (p=0.030 and 0.004, respectively). Using our newly developed semi-automated segmentation pipeline, we quantified fibroglandular tissue and BPE. The overlapping ranges of quantitative BPE corresponding to the radiologist-assigned BPE categories showcases the inter-reader variability with visual estimation of BPE.