Tyler Bowman, Tanny Chavez, Kamrul Khan, Jingxian Wu, Avishek Chakraborty, Narasimhan Rajaram, Keith Bailey, Magda El-Shenawee,
https://www.spiedigitallibrary.org/journals/Journal-of-Biomedical-Optics/volume-23/issue-2/026004/Pulsed-terahertz-imaging-of-breast-cancer-in-freshly-excised-murine/10.1117/1.JBO.23.2.026004.short
This paper investigates terahertz (THz) imaging
and classification of freshly excised murine xenograft breast cancer tumors.
These tumors are grown via injection of E0771 breast adenocarcinoma cells into
the flank of mice maintained on high-fat diet. Within 1 h of excision, the
tumor and adjacent tissues are imaged using a pulsed THz system in the
reflection mode. The THz images are classified using a statistical Bayesian
mixture model with unsupervised and supervised approaches. Correlation with digitized
pathology images is conducted using classification images assigned by a modal
class decision rule. The corresponding receiver operating characteristic curves
are obtained based on the classification results. A total of 13 tumor samples
obtained from 9 tumors are investigated. The results show good correlation of
THz images with pathology results in all samples of cancer and fat tissues. For
tumor samples of cancer, fat, and muscle tissues, THz images show reasonable
correlation with pathology where the primary challenge lies in the overlapping
dielectric properties of cancer and muscle tissues. The use of a supervised
regression approach shows improvement in the classification images although not
consistently in all tissue regions. Advancing THz imaging of breast tumors from
mice and the development of accurate statistical models will ultimately
progress the technique for the assessment of human breast tumor margins.
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