Search academic texts

Information × Registration Number 0223U001011, 0121U110569 , R & D reports Title Verification of key pathomorphological characteristics of tumor growth as innovative elements of artificial intelligence in the optimiziation of breast cancer diagnostic technology popup.stage_title Head Chekhun Vasyl F., Доктор медичних наук Registration Date 24-01-2023 Organization R.E. Kavetsky Institute of Experimental Pathology, Oncology and Radiobiology National Academy of Sciences of Ukraine popup.description2 The algorithm for verifying key collagen parameters for assessing the degree of malignancy of breast neoplasms in routine practice has been tested. It was established that Malory's staining of samples provides the highest level of selective staining of collagen fibers in the tissue of breast neoplasms with a high level of contrast of such components relative to other structural elements of tumors. It has been shown that collagen fibers in breast cancer tissue are characterized by significantly lower values of length (p<0.001) and width (p<0.001), as well as greater indicators of straightness (p<0.001) and orientation (p<0.05) in comparison with similar ones in fibroadenomas. No significant difference was found in the density of collagen fibers in the tissue of benign and malignant neoplasms of the mammary gland. In order to create a database for the development of machine learning technology, a collection of tumor tissue samples from breast cancer patients with different clinical status and degree of malignancy (n=75) was selected. More than 1,600 photomicrographs (x400) of Malory-stained tumor tissue of breast cancer, accompanied by information on the degree of malignancy of neoplasms, were provided for the formation of the database, which is the basis for the development of approaches to computer prediction of breast cancer. Thus, signs of the structural organization of collagen fibers were identified, which reflect the aggressive potential of breast cancer cource. Product Description popup.authors Zadvornyi Taras V. Lukianova Nataliya Yu. Piatchanina Tetiana V. popup.nrat_date 2023-01-24 Close