EVALUATION OF DIAGNOSTIC ALGORITHM BASED ON COLLAGEN ORGANIZATION PARAMETERS FOR BREAST TUMORS.

Q3 Medicine

Experimental oncology Pub Date : 2022-12-01 DOI:10.32471/exp-oncology.2312-8852.vol-44-no-4.19137

N Lukianova, T Zadvornyi, О Mushii, T Pyatchanina, V Chekhun

{"title":"EVALUATION OF DIAGNOSTIC ALGORITHM BASED ON COLLAGEN ORGANIZATION PARAMETERS FOR BREAST TUMORS.","authors":"N Lukianova, T Zadvornyi, О Mushii, T Pyatchanina, V Chekhun","doi":"10.32471/exp-oncology.2312-8852.vol-44-no-4.19137","DOIUrl":null,"url":null,"abstract":"The changes in the quantitative parameters and spatial structure of collagen are considered a key diagnostic and prognostic factor associated with the development of many malignant neoplasms, including breast cancer (BCa). The aim of the work was to develop and test an algorithm for the assessment of collagen organization parameters as informative attributes associated with BCa for developing technology of machine learning and building an intelligent system of cancer diagnostics.Materials and methods: Tumor tissue samples of 5 patients with breast fibroadenomas and 20 patients with stage I-II BCa were studied. Collagen was identified histochemically by Mallory method. Photomicrographs of the studied preparations were obtained using a digital microscopy complex AxioScope A1. Morphometric studies were performed using the software CurveAlign v. 4.0. beta and ImageJ.Results: The algorithm for determining the quantitative characteristics and spatial organization of the collagen matrix in tumor tissue samples has been developed and tested. We showed that collagen fibers in the BCa tissue are characterized by significantly lower values of length (p < 0.001) and width (p < 0.001) as well as higher values of straightness (p < 0.001) and angle (p < 0.05) compared to these in the fibroadenoma tissue. No significant difference was found in the density of collagen fibers in the tissue of benign and malignant neoplasms of the mammary gland.Conclusion: The algorithm allows assessing a wide range of parameters of collagen fibers in tumor tissue, including their spatial orientation and mutual arrangement, parametric characteristics and density of the three-dimensional fibrillar network.","PeriodicalId":12287,"journal":{"name":"Experimental oncology","volume":"44 4","pages":"281-286"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Experimental oncology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.32471/exp-oncology.2312-8852.vol-44-no-4.19137","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Medicine","Score":null,"Total":0}

引用次数: 1

Abstract

The changes in the quantitative parameters and spatial structure of collagen are considered a key diagnostic and prognostic factor associated with the development of many malignant neoplasms, including breast cancer (BCa). The aim of the work was to develop and test an algorithm for the assessment of collagen organization parameters as informative attributes associated with BCa for developing technology of machine learning and building an intelligent system of cancer diagnostics.

Materials and methods: Tumor tissue samples of 5 patients with breast fibroadenomas and 20 patients with stage I-II BCa were studied. Collagen was identified histochemically by Mallory method. Photomicrographs of the studied preparations were obtained using a digital microscopy complex AxioScope A1. Morphometric studies were performed using the software CurveAlign v. 4.0. beta and ImageJ.

Results: The algorithm for determining the quantitative characteristics and spatial organization of the collagen matrix in tumor tissue samples has been developed and tested. We showed that collagen fibers in the BCa tissue are characterized by significantly lower values of length (p < 0.001) and width (p < 0.001) as well as higher values of straightness (p < 0.001) and angle (p < 0.05) compared to these in the fibroadenoma tissue. No significant difference was found in the density of collagen fibers in the tissue of benign and malignant neoplasms of the mammary gland.

Conclusion: The algorithm allows assessing a wide range of parameters of collagen fibers in tumor tissue, including their spatial orientation and mutual arrangement, parametric characteristics and density of the three-dimensional fibrillar network.

查看原文本刊更多论文

基于胶原组织参数的乳腺肿瘤诊断算法评价。

胶原定量参数和空间结构的变化被认为是许多恶性肿瘤(包括乳腺癌)发展的关键诊断和预后因素。这项工作的目的是开发和测试一种算法，用于评估胶原蛋白组织参数，作为与BCa相关的信息属性，用于开发机器学习技术和构建智能癌症诊断系统。材料与方法:对5例乳腺纤维腺瘤患者和20例I-II期BCa患者的肿瘤组织样本进行研究。用Mallory法组织化学鉴定胶原蛋白。使用数字显微镜AxioScope A1获得所研究制剂的显微照片。使用CurveAlign v. 4.0软件进行形态计量学研究。beta和ImageJ。结果:开发并测试了用于确定肿瘤组织样品中胶原基质的数量特征和空间组织的算法。我们发现，与纤维腺瘤组织相比，BCa组织中的胶原纤维的长度(p < 0.001)和宽度(p < 0.001)明显较低，直线度(p < 0.001)和角度(p < 0.05)值较高。乳腺良恶性肿瘤组织中胶原纤维密度差异无统计学意义。结论:该算法可以评估肿瘤组织中胶原纤维的广泛参数，包括它们的空间取向和相互排列，三维纤维网络的参数特征和密度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Experimental oncology Medicine-Oncology

CiteScore

1.40

自引率

0.00%

发文量

期刊介绍： The Experimental Oncology is an English-language journal that publishes review articles, original contributions, short communications, case reports and technical advances presenting new data in the field of experimental and fundamental oncology. Manuscripts should be written in English, contain original work, which has not been published or submitted for publication elsewhere. It also implies the transfer of the Copyright from the author to “Experimental Oncology”. No part of journal publications may be reproduced, stored in a retrieval system or transmitted in any form or by any means without the prior permission of the publisher.