Analysis of second-harmonic-generation microscopy in a mouse model of ovarian carcinoma

Abstract

Second-harmonic-generation (SHG) imaging of mouse ovaries ex vivo was used to detect collagen structure changes accompanying ovarian cancer development. Dosing with 4-vinylcyclohexene diepoxide and 7,12-dimethylbenz[a]anthracene resulted in histologically confirmed cases of normal, benign abnormality, dysplasia, and carcinoma. Parameters for each SHG image were calculated using the Fourier transform matrix and gray-level co-occurrence matrix (GLCM). Cancer versus normal and cancer versus all other diagnoses showed the greatest separation using the parameters derived from power in the highest-frequency region and GLCM energy. Mixed effects models showed that these parameters were significantly different between cancer and normal (P<0.008). Images were classified with a support vector machine, using 25% of the data for training and 75% for testing. Utilizing all images with signal greater than the noise level, cancer versus not-cancer specimens were classified with 81.2% sensitivity and 80.0% specificity, and cancer versus normal specimens were classified with 77.8% sensitivity and 79.3% specificity. Utilizing only images with greater than of 75% of the field of view containing signal improved sensitivity and specificity for cancer versus normal to 81.5% and 81.1%. These results suggest that using SHG to visualize collagen structure in ovaries could help with early cancer detection.

Fig. 1

Images from three ovaries of each diagnosis: normal (a–c), DMBA-effect (d–f), tubular adenoma (g–i), tubular adenoma with dysplasia (j–l), and carcinoma (m–o).

Fig. 2

Average values for parameters used to separate carcinoma from normal and carcinoma from noncarcinoma. $\mathrm{TA}=\text{tubular}$ adenoma, $\mathrm{TD}=\text{tubular}$ adenoma with dysplasia. Only positive standard deviations are shown.

Fig. 3

Average values for parameters used to separate tubular adenoma (TA) from tubular adenoma with dysplasia (TD). Only positive standard deviations are shown.

Fig. 4

Plot of power in the high-frequency region versus GLCM energy for carcinoma and normal diagnoses.

Fig. 5

Plot of contrast with 17-pixel separation vs. contrast with 25-pixel separation for tubular adenoma (TA) and tubular adenoma with dysplasia (TD).