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1.
Lasers Surg Med ; 52(10): 993-1009, 2020 12.
Article in English | MEDLINE | ID: mdl-32311117

ABSTRACT

BACKGROUND AND OBJECTIVES: To determine the efficacy of targeted fluorescent biomarkers and multiphoton imaging to characterize early changes in ovarian tissue with the onset of cancer. STUDY DESIGN/MATERIALS AND METHODS: A transgenic TgMISIIR-TAg mouse was used as an animal model for ovarian cancer. Mice were injected with fluorescent dyes to bind to the folate receptor α, matrix metalloproteinases, and integrins. Half of the mice were treated with 4-vinylcyclohexene diepoxide (VCD) to simulate menopause. Widefield fluorescence imaging (WFI) and multiphoton imaging of the ovaries and oviducts were conducted at 4 and 8 weeks of age. The fluorescence signal magnitude was quantified, and texture features were derived from multiphoton imaging. Linear discriminant analysis was then used to classify mouse groups. RESULTS: Imaging features from both fluorescence imaging and multiphoton imaging show significant changes (P < 0.01) with age, VCD treatment, and genotype. The classification model is able to classify different groups to accuracies of 75.53%, 69.53%, and 86.76%, for age, VCD treatment, and genotype, respectively. Building a classification model using features from multiple modalities shows marked improvement over individual modalities. CONCLUSIONS: This study demonstrates that using WFI with targeted biomarkers, and multiphoton imaging with endogenous contrast shows promise for detecting early changes in ovarian tissue with the onset of cancer. The results indicate that multimodal imaging can provide higher sensitivity for classifying tissue types than using single modalities alone. Lasers Surg. Med. © 2020 Wiley Periodicals, Inc.


Subject(s)
Ovarian Neoplasms , Postmenopause , Animals , Disease Models, Animal , Female , Humans , Mice , Optical Imaging , Ovarian Neoplasms/diagnostic imaging
2.
J Biomed Opt ; 24(9): 1-16, 2019 09.
Article in English | MEDLINE | ID: mdl-31571434

ABSTRACT

Ovarian cancer is the deadliest gynecologic cancer due predominantly to late diagnosis. Early detection of ovarian cancer can increase 5-year survival rates from 40% up to 92%, yet no reliable early detection techniques exist. Multiphoton microscopy (MPM) is a relatively new imaging technique sensitive to endogenous fluorophores, which has tremendous potential for clinical diagnosis, though it is limited in its application to the ovaries. Wide-field fluorescence imaging (WFI) has been proposed as a complementary technique to MPM, as it offers high-resolution imagery of the entire organ and can be tailored to target specific biomarkers that are not captured by MPM imaging. We applied texture analysis to MPM images of a mouse model of ovarian cancer. We also conducted WFI targeting the folate receptor and matrix metalloproteinases. We find that texture analysis of MPM images of the ovary can differentiate between genotypes, which is a proxy for disease, with high statistical significance (p < 0.001). The wide-field fluorescence signal also changes significantly between genotypes (p < 0.01). We use the features to classify multiple tissue groups to over 80% accuracy. These results suggest that MPM and WFI are promising techniques for the early detection of ovarian cancer.


Subject(s)
Early Detection of Cancer/methods , Image Interpretation, Computer-Assisted/methods , Microscopy, Fluorescence, Multiphoton/methods , Optical Imaging/methods , Ovarian Neoplasms/diagnostic imaging , Algorithms , Animals , Disease Models, Animal , Female , Mice , Ovary/diagnostic imaging
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