Standard and Delayed Contrast-Enhanced MRI of Malignant and Benign Breast Lesions with Histological and Clinical Supporting Data (Advanced-MRI-Breast-Lesions)

The application of deep-learning methods to breast MRI has a potential to improve diagnosis as well as predict pathological features of the tumors and their response to therapy, and is currently widely investigated. Standard contrast-enhanced MRI of the breast provides high sensitivity but variable specificity in detecting breast cancer, and may lead to excessive benign biopsies. Large, well annotated datasets are needed to improve the current results in this field.
This dataset is a single-institutional, retrospective collection of 632 breast-MRI imaging sessions acquired on a 1.5T MR system between 2018-2021. Supporting data, collected for 200 patients from clinical notes, radiology report and pathology reports, is included: patient age, lesion location, malignant/benign outcome, pathology and grade (if applicable), receptor status and KI67 (if applicable). The main uniqueness of this data is that it contains the standard protocol series (T1-weighted DCE sequence with 5 time points- before and 4 time points after contrast injection, and T2-weighted MRI with/without fat suppression) as well as the delayed contrast T1-images acquired 20-28 minutes after contrast administration and the calculated treatment response assessment maps (TRAMs).