2022
DOI: 10.3389/fonc.2022.853755
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Focal Serous Tubal Intra-Epithelial Carcinoma Lesions Are Associated With Global Changes in the Fallopian Tube Epithelia and Stroma

Abstract: ObjectiveSerous tubal intra-epithelial carcinoma (STIC) lesions are thought to be precursors to high-grade serous ovarian cancer (HGSOC), but HGSOC is not always accompanied by STIC. Our study was designed to determine if there are global visual and subvisual microenvironmental differences between fallopian tubes with and without STIC lesions.MethodsComputational image analyses were used to identify potential morphometric and topologic differences in stromal and epithelial cells in samples from three age-match… Show more

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Cited by 6 publications
(5 citation statements)
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“…Interestingly, their findings suggest that STIC coexists with other morphological and topological changes which could be used as potential markers of STIC presence and indicate further pathological evaluation [17].…”
Section: Discussionmentioning
confidence: 99%
“…Interestingly, their findings suggest that STIC coexists with other morphological and topological changes which could be used as potential markers of STIC presence and indicate further pathological evaluation [17].…”
Section: Discussionmentioning
confidence: 99%
“…As terminally differentiated cells with low proliferative potential, ciliated cells themselves might be less prone to the accumulation of DNA damage [ 17 ]. The loss of ciliated cells is also associated with menopause and aging, which are known risk factors for EOC [ 20 , 21 ].…”
Section: Discussionmentioning
confidence: 99%
“…Image tiles were analyzed for differences in texture patterns using the blue and red channels that were digitally separated from Masson’s trichrome-stained image by a color-deconvolution algorithm [ 15 ]. Staining texture patterns were characterized by our previously applied feature panel [ 16 , 17 ] comprising: 1 average staining intensity, 45 segmentation-based fractal texture features (SFTA) [ 18 ], 30 Gabor mean-squared energy, and 30 Gabor mean amplitude features [ 19 ]. We chose these features because they are invariant to image rotation and can extract image intensities, stained area size, fractal dimension, and texture energy.…”
Section: Methodsmentioning
confidence: 99%