Thayer School of Engineering
High positive margin rates in oncologic breast-conserving surgery are a pressing clinical problem. Volumetric X-ray scanning is emerging as a powerful ex vivo specimen imaging technique for analyzing resection margins, but X-rays lack contrast between non-malignant and malignant fibrous tissues. In this study, combined micro-CT and wide-field optical image radiomics were developed to classify malignancy of breast cancer tissues, demonstrating that X-ray/optical radiomics improve malignancy classification. Ninety-two standardized features were extracted from co-registered micro-CT and optical spatial frequency domain imaging samples extracted from 54 breast tumors exhibiting seven tissue subtypes confirmed by microscopic histological analysis. Multimodal feature sets improved classification performance versus micro-CT alone when adipose samples were included (AUC = 0.88 vs. 0.90; p-value = 3.65e−11) and excluded, focusing the classification task on exclusively non-malignant fibrous versus malignant tissues (AUC = 0.78 vs. 0.85; p-value = 9.33e−14). Extending the radiomics approach to high-dimensional optical data—termed “optomics” in this study—offers a promising optical image analysis technique for cancer detection. Radiomic feature data and classification source code are publicly available.
Streeter, S.S., Hunt, B., Zuurbier, R.A. et al. Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures. Sci Rep 11, 21832 (2021). https://doi.org/10.1038/s41598-021-01414-z
Dartmouth Digital Commons Citation
Streeter, Samuel S.; Hunt, Brady; Zuurbier, Rebecca A.; Wells, Wendy A.; Paulsen, Keith D.; and Pogue, Brian W., "Developing diagnostic assessment of breast lumpectomy tissues using radiomic and optical signatures" (2021). Dartmouth Scholarship. 4119.