Combined T-staging and locoregional staging (N-staging) was possible within one imaging session using the proposed protocol. Despite a minimal increase in examination time, high diagnostic accuracy and excellent interrater reliability were achieved.

This study demonstrates the significant relationship between semi-quantitative enhancement analysis in breast MRI and disease-related death of breast cancer patients. As results were extracted from a routine staging examination, MRI noninvasively provides not only diagnostic information but also outcome data at one step. Future studies should address the impact of these findings on patient management and therapeutic approach.

to investigate whether automated volumetric radiomic analysis of breast cancer vascularization (VAV) can improve survival prediction in primary breast cancer. 314 consecutive patients with primary invasive breast cancer received standard clinical MRi before the initiation of treatment according to international recommendations. Diagnostic work-up, treatment, and follow-up was done at one tertiary care, academic breast-center (outcome: disease specific survival/DSS vs. disease specific death/ DSD). the nottingham prognostic index (npi) was used as the reference method with which to predict survival of breast cancer. Based on the MRi scans, VAV was accomplished by commercially available, fDA-cleared software. DSD served as endpoint. integration of VAV into the npi gave npi VAV. prediction of DSD by npi VAV compared to standard npi alone was investigated (cox regression, likelihood-test, predictive accuracy: Harrell's C, Kaplan Meier statistics and corresponding hazard ratios/HR, confidence intervals/CI). DSD occurred in 35 and DSS in 279 patients. Prognostication of the survival outcome by npi (Harrell's c = 75.3%) was enhanced by VAV (NPI VAV : Harrell's c = 81.0%). Most of all, the NPI VAV identified patients with unfavourable outcome more reliably than NPI alone (hazard ratio/HR = 4.5; confidence interval/CI = 2.14-9.58; P = 0.0001). Automated volumetric radiomic analysis of breast cancer vascularization improved survival prediction in primary breast cancer. Most of all, it optimized the identification of patients at higher risk of an unfavorable outcome. Future studies should integrate MRi as a "gate keeper" in the management of breast cancer patients. Such a "gate keeper" could assist in selecting patients benefitting from more advanced diagnostic procedures (genetic profiling etc.) in order to decide whether are a more aggressive therapy (chemotherapy) is warranted. Breast cancer is the most common malignant neoplasm of women in the western world. Despite substantial advances in diagnosis and treatment, morbidity and mortality of breast cancer remain high 1. By adjusting the treatment to the individual cancer biology, precision medicine aims to both improve disease survival and to reduce the rate of unnecessary cytotoxic treatment 2,3. To achieve this goal, accurate biomarkers are essential tools for precision medicine. They help us to understand tumor biology and allow estimation of patient outcome 4. The Nottingham Prognostic Index (NPI) is a well-established and widely used method for the prediction of survival of primary breast cancer. It is based on three classic biomarkers of breast cancer: tumor size, tumor grade, and the number of metastatic loco-regional lymph nodes 5-8. Breast MRI (MRI) is a functional imaging method that has been validated in clinical practice for over 30 years 9. Objective semi-quantitative analysis of MRI by automated, FDA-cleared software has been intensely

Dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) is able to detect breast cancer with high sensitivity. Furthermore, this method provides functional information on tissue composition and vascularization. This study aims to identify the potential of DCE-MRI to predict distant metastasis in breast cancer patients using computer assisted interpretation of dynamic enhancement data. For this purpose, 59 consecutive patients with newly diagnosed invasive breast cancer received pretherapeutic DCE-MRI at 1.5 Tesla according to international recommendations. In all patients, follow up interval and occurrence of distant metastasis was documented. For DCE-MRI analysis dedicated software was used (Brevis, Siemens Healthcare, Erlangen, Germany). It allows semiautomatic identification of the most suspect curve in a lesion analyzed. Enhancement parameters assessed were "Initial Enhancement", "Washout", "Peak-Enhancement", and "Time to Peak Enhancement". Cox proportional hazards regression (CPHR) was used to analyze the effect of these parameters on the probability of metachronous distant metastasis. Median follow up period was 52.0 months. 6 patients developed distant metastases between 11 and 35 months after breast cancer diagnosis. In CPHR, Washout could be identified as significant and independent predictor for occurrence of distant metastasis (P = 0.0134). Our initial data demonstrate an association between computer measured enhancement parameters in DCE-MRI and occurrence of distant metastasis by quantification of Washout.

MR mammography was able to non-invasively assess tumor grading in a standard protocol. Since tumor grading is a surrogate for overall survival, these results provide further evidence to the clinical application of MR mammography as a noninvasive prognostic tool.