ArticleMaedica2024
Evaluation of Clinicopathological Features in Breast Cancer Patients Using Cytonuclear Morphometry.
Article in Maedica, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
7 authors.
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Abstract
As breast cancer is one of the leading causes of death worldwide, we aim to correlate cytonuclear morphometric parameters with clinicopathological features in order to emphasize their importance to prognostication. Following the pathological processing of tumor specimens, representative areas throughout the tumor mass were selected. These areas have been scanned using an Olympus VS200 slide scanner and analyzed using QuPath v0.4.4. Nine cytonuclear morphometric parameters have been calculated and correlated with clinicopathological features. P values were determined through regression analysis and a p-value <0.05 was considered significant. Many significant correlations have been obtained between cytonuclear morphometric parameters and clinicopathological features. There have been elaborated mathematical criteria-based algorithms by selecting cut-off values for tubular differentiation score, nuclear pleomorphism score, mitotic rate score, Nottingham score, lymph node status, lymphovascular invasions, perineural invasion, presence of necrosis, presence of in situ carcinoma and presence of microcalcifications. The cytonuclear morphometric parameters show great promise for prognostication in breast cancer patients, as many of them were significantly correlated with clinicopathological features. The values of these parameters have allowed the development of algorithms to predict these features.
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