14 February 2018 Pulsed terahertz imaging of breast cancer in freshly excised murine tumors
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Abstract
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.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)
Tyler Bowman, Tyler Bowman, Tanny Chavez, Tanny Chavez, Kamrul Khan, Kamrul Khan, Jingxian Wu, Jingxian Wu, Avishek Chakraborty, Avishek Chakraborty, Narasimhan Rajaram, Narasimhan Rajaram, Keith Bailey, Keith Bailey, Magda O. El-Shenawee, Magda O. El-Shenawee, } "Pulsed terahertz imaging of breast cancer in freshly excised murine tumors," Journal of Biomedical Optics 23(2), 026004 (14 February 2018). https://doi.org/10.1117/1.JBO.23.2.026004 . Submission: Received: 18 November 2017; Accepted: 23 January 2018
Received: 18 November 2017; Accepted: 23 January 2018; Published: 14 February 2018
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