Combined reflectance spectroscopy and coherent light backscattering measurement differentiate cervical cancer from normal epithelial tissue in a xenograft mouse model.

Cervical cancer is a type of slow-growing cancer associated with high mortality rates. Early detection can enable lifesaving early intervention. Current cervical premalignant lesion detection methods suffer from both high miss rates and excessive referrals for unnecessary biopsies. Herein, coherent light backscatter and modifications in reflected white-light spectra were measured to specifically discriminate between cervical tumors and normal squamous epithelial tissues resected from a mouse xenograft model. The combined measurements resulted in 92% sensitivity and 93% specificity in discrimination between the two tissues. These methods can be used to develop a noninvasive portable optical probe for sensitive and objective detection of precancer and cancer epithelial lesions in the cervix and other accessible epithelial tissues.

The Use of a Novel Optical Algorithm in the Diagnosis of Cervical Pre-Invasive Pathology - A Preliminary Proof of Principal Study.

OBJECTIVE: To develop a novel optical probe monitoring cervical tissues in real-time and to compare the new imaging technique to actual cervical pathologic findings on resected cone biopsy specimens. METHODS: A loop electro-excisional procedure was performed on 15 women with a biopsy diagnosis of dysplasia. The conization specimen was then assessed with the novel optical system and results recorded. The 'normal' and 'abnormal' areas were tested by the optical setup at several points. Extracted parameters were used as the input of the classifier function of a logistic regression algorithm model to assess for system accuracy vs. clinical examination. RESULTS: Ninety-seven samples were taken - forty-five samples from 'abnormal zones' and 42 samples from 'normal zones', as defined by the surgeon. The pathologist diagnosed 58 samples as dysplastic and 39 samples as normal. The novel optical method predicted 58 sample points as abnormal and 39 points as normal. The sensitivity of the system was 90% with a specificity of 77%. The probability of correct differentiation of dysplastic cervical tissue from normal cervical tissue was 85%. CONCLUSIONS: The optical probe and the algorithms of image processing in combination with the logistic regression algorithm correlated well with pathology results for cervical dysplasia ex-vivo.