posted on 2021-04-08, 17:26authored byYifan Yang, Yinlong Yang, Zhijie Liu, Li Guo, Shiping Li, Xiangjie Sun, Zhiming Shao, Minbiao Ji
Precise evaluation
of breast tumor malignancy based on tissue calcifications
has important practical value in the disease diagnosis, as well as
the understanding of tumor development. Traditional X-ray mammography
provides the overall morphologies of the calcifications but lacks
intrinsic chemical information. In contrast, spontaneous Raman spectroscopy
offers detailed chemical analysis but lacks the spatial profiles.
Here, we applied hyperspectral stimulated Raman scattering (SRS) microscopy
to extract both the chemical and morphological features of the microcalcifications,
based on the spectral and spatial domain analysis. A total of 211
calcification sites from 23 patients were imaged with SRS, and the
results were analyzed with a support vector machine (SVM) based classification
algorithm. With optimized combinations of chemical and geometrical
features of microcalcifications, we were able to reach a precision
of 98.21% and recall of 100.00% for classifying benign and malignant
cases, significantly improved from the pure spectroscopy or imaging
based methods. Our findings may provide a rapid means to accurately
evaluate breast tumor malignancy based on fresh tissue biopsies.