Purpose: To identify key radiomic features in pretreatment peritumoral breast tissue associated with high response to neoadjuvant chemotherapy.

Methods: In this retrospective study, we identified 27 biopsy-proven invasive breast cancer cases (BIRADS 6) with dynamic contrast-enhanced MR (DCE-MRI) studies performed prior to neoadjuvant chemotherapy. Segmentation of pretreatment MR images was completed using the image-processing software 3D Slicer. For each case, a tumor label map and five masks were created by thresholding subtracted pre and 1st post-contrast images and dilating the tumor label map to voxel-equivalent distances of 2.5mm, 5mm, 10mm, 15mm and 20mm beyond the tumor border. A total of 57 metrics including distribution statistics, shape, morphology and texture were computed from each mask using the 3D Slicer HeterogeneityCAD module. Cases were then separated into 2 groups using Miller-Payne scores acquired from final surgical pathology reports. Scores of 1-3 were placed into a “low-response” group while scores of 4-5, indicating reduction of tumor cells greater than 90%, were placed into a “high-response” group. Statistical correlation was performed using univariate Mann-Whitney tests to compare low-response and high-response groups at the tumor and individual peritumoral levels.

Results: Six metrics showed significant difference between the low-response and high-response groups at the tumor level, 2.5 mm peritumoral level, and 5mm peritumoral level. Among these metrics were Volume, Maximum 3D Diameter, Sphericity, Long Run Enhancement (indicative of coarseness), Surface Area (in mm^2), and Compactness 2.

Conclusions: Our study showed that radiomic features of peritumoral breast tissue extracted from DCE-MRI, such as greater sphericity and compactness and lower coarseness, volume, and surface area are associated with a higher response to neoadjuvant chemotherapies.