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<article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:ali="http://www.niso.org/schemas/ali/1.0/" article-type="research-article" dtd-version="1.2" xml:lang="en"><front><journal-meta><journal-id journal-id-type="publisher-id">Digital Diagnostics</journal-id><journal-title-group><journal-title xml:lang="en">Digital Diagnostics</journal-title><trans-title-group xml:lang="ru"><trans-title>Digital Diagnostics</trans-title></trans-title-group><trans-title-group xml:lang="zh"><trans-title>Digital Diagnostics</trans-title></trans-title-group></journal-title-group><issn publication-format="print">2712-8490</issn><issn publication-format="electronic">2712-8962</issn><publisher><publisher-name xml:lang="en">Eco-Vector</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="publisher-id">628304</article-id><article-id pub-id-type="doi">10.17816/DD628304</article-id><article-categories><subj-group subj-group-type="toc-heading" xml:lang="en"><subject>Original Study Articles</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="ru"><subject>Оригинальные исследования</subject></subj-group><subj-group subj-group-type="toc-heading" xml:lang="zh"><subject>原创性科研成果</subject></subj-group><subj-group subj-group-type="article-type"><subject>Research Article</subject></subj-group></article-categories><title-group><article-title xml:lang="en">Prediction of the efficacy of neoadjuvant chemoradiotherapy in patients with rectal cancer based on a texture analysis of T2-weighted magnetic resonance tumor image obtained at primary staging</article-title><trans-title-group xml:lang="ru"><trans-title>Прогнозирование эффективности неоадъювантной химиолучевой терапии у больных раком прямой кишки на основе текстурного анализа Т2-взвешенного магнитно-резонансного изображения опухоли, полученного при первичном стадировании</trans-title></trans-title-group><trans-title-group xml:lang="zh"><trans-title>基于直肠癌患者初诊分期时获得的肿瘤加权T2核磁共振图像的纹理分析预测新辅助放化疗的效果</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4524-0839</contrib-id><contrib-id contrib-id-type="spin">1841-7759</contrib-id><name-alternatives><name xml:lang="en"><surname>Dayneko</surname><given-names>Yana A.</given-names></name><name xml:lang="ru"><surname>Дайнеко</surname><given-names>Яна Александровна</given-names></name><name xml:lang="zh"><surname>Dayneko</surname><given-names>Yana A.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>MD, Cand. Sci. (Medicine)</p></bio><bio xml:lang="ru"><p>канд. мед. наук</p></bio><bio xml:lang="zh"><p>MD, Cand. Sci. (Medicine)</p></bio><email>vorobeyana@gmail.com</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-3549-4499</contrib-id><contrib-id contrib-id-type="spin">5837-3465</contrib-id><name-alternatives><name xml:lang="en"><surname>Berezovskaya</surname><given-names>Tatiana P.</given-names></name><name xml:lang="ru"><surname>Березовская</surname><given-names>Татьяна Павловна</given-names></name><name xml:lang="zh"><surname>Berezovskaya</surname><given-names>Tatiana P.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>MD, Dr. Sci. (Medicine), Professor</p></bio><bio xml:lang="ru"><p>д-р мед. наук, профессор</p></bio><bio xml:lang="zh"><p>MD, Dr. Sci. (Medicine), Professor</p></bio><email>tberezovska@yahoo.com</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-5587-2795</contrib-id><contrib-id contrib-id-type="spin">3820-4320</contrib-id><name-alternatives><name xml:lang="en"><surname>Mirzeabasov</surname><given-names>Oleg A.</given-names></name><name xml:lang="ru"><surname>Мирзеабасов</surname><given-names>Олег Ахмедбекович</given-names></name><name xml:lang="zh"><surname>Mirzeabasov</surname><given-names>Oleg A.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>MD, Assistant Professor</p></bio><bio xml:lang="ru"><p>доцент</p></bio><bio xml:lang="zh"><p>MD, Assistant Professor</p></bio><email>oami@yandex.ru</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-0420-7856</contrib-id><name-alternatives><name xml:lang="en"><surname>Starkov</surname><given-names>Sergey O.</given-names></name><name xml:lang="ru"><surname>Старков</surname><given-names>Сергей Олегович</given-names></name><name xml:lang="zh"><surname>Starkov</surname><given-names>Sergey O.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>Dr. Sci. (Physical and Mathematical), Professor</p></bio><bio xml:lang="ru"><p>д-р физ.-мат. наук, профессор</p></bio><bio xml:lang="zh"><p>Dr. Sci. (Physical and Mathematical), Professor</p></bio><email>sergeystarkov56@mail.ru</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-6686-5419</contrib-id><contrib-id contrib-id-type="spin">9668-3834</contrib-id><name-alternatives><name xml:lang="en"><surname>Myalina</surname><given-names>Sofiya A.</given-names></name><name xml:lang="ru"><surname>Мялина</surname><given-names>София Анатольевна</given-names></name><name xml:lang="zh"><surname>Myalina</surname><given-names>Sofiya A.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>samyalina@mail.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-5961-2958</contrib-id><contrib-id contrib-id-type="spin">3787-6139</contrib-id><name-alternatives><name xml:lang="en"><surname>Nevolskikh</surname><given-names>Aleksey A.</given-names></name><name xml:lang="ru"><surname>Невольских</surname><given-names>Алексей Алексеевич</given-names></name><name xml:lang="zh"><surname>Nevolskikh</surname><given-names>Aleksey A.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>MD, Dr. Sci. (Medicine)</p></bio><bio xml:lang="ru"><p>д-р мед. наук</p></bio><bio xml:lang="zh"><p>MD, Dr. Sci. (Medicine)</p></bio><email>editor@omnidoctor.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-7689-6032</contrib-id><contrib-id contrib-id-type="spin">4264-5167</contrib-id><name-alternatives><name xml:lang="en"><surname>Ivanov</surname><given-names>Sergey А.</given-names></name><name xml:lang="ru"><surname>Иванов</surname><given-names>Сергей Анатольевич</given-names></name><name xml:lang="zh"><surname>Ivanov</surname><given-names>Sergey А.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>MD, Dr. Sci. (Medicine), Professor, corresponding member of the Russian Academy of Sciences</p></bio><bio xml:lang="ru"><p>д-р мед. наук, профессор, чл.-корр. РАН</p></bio><bio xml:lang="zh"><p>MD, Dr. Sci. (Medicine), Professor, corresponding member of the Russian Academy of Sciences</p></bio><email>oncourolog@gmail.com</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff3"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-8784-8415</contrib-id><contrib-id contrib-id-type="spin">1759-8101</contrib-id><name-alternatives><name xml:lang="en"><surname>Kaprin</surname><given-names>Andrey D.</given-names></name><name xml:lang="ru"><surname>Каприн</surname><given-names>Андрей Дмитриевич</given-names></name><name xml:lang="zh"><surname>Kaprin</surname><given-names>Andrey D.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>MD, Dr. Sci. (Medicine), Professor, academician of the Russian Academy of Sciences</p></bio><bio xml:lang="ru"><p>д-р мед. наук, профессор, академик РАН</p></bio><bio xml:lang="zh"><p>MD, Dr. Sci. (Medicine), Professor, academician of the Russian Academy of Sciences</p></bio><email>contact@nmicr.ru</email><xref ref-type="aff" rid="aff3"/><xref ref-type="aff" rid="aff4"/><xref ref-type="aff" rid="aff5"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">A.F. Tsyb Medical Radiology Research Centre, National Medical Research Radiological Center</institution></aff><aff><institution xml:lang="ru">Медицинский радиологический научный центр имени А.Ф. Цыба ― филиал ФГБУ «Национальный медицинский исследовательский центр радиологии»</institution></aff><aff><institution xml:lang="zh">A.F. Tsyb Medical Radiology Research Centre, National Medical Research Radiological Center</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)</institution></aff><aff><institution xml:lang="ru">Обнинский институт атомной энергетики — филиал ФГАОУ ВПО «Национальный исследовательский ядерный университет МИФИ»</institution></aff><aff><institution xml:lang="zh">National Research Nuclear University MEPhI (Moscow Engineering Physics Institute)</institution></aff></aff-alternatives><aff-alternatives id="aff3"><aff><institution xml:lang="en">Peoples’ Friendship University of Russia</institution></aff><aff><institution xml:lang="ru">Российский университет дружбы народов имени Патриса Лумумбы</institution></aff><aff><institution xml:lang="zh">Peoples’ Friendship University of Russia</institution></aff></aff-alternatives><aff-alternatives id="aff4"><aff><institution xml:lang="en">P.A. Herzen Moscow Research Institute of Oncology, National Medical Research Radiological Center</institution></aff><aff><institution xml:lang="ru">Московский научно-исследовательский онкологический институт имени П.А. Герцена ― филиал ФГБУ «Национальный медицинский исследовательский центр радиологии»</institution></aff><aff><institution xml:lang="zh">P.A. Herzen Moscow Research Institute of Oncology, National Medical Research Radiological Center</institution></aff></aff-alternatives><aff-alternatives id="aff5"><aff><institution xml:lang="en">National Medical Research Radiological Centre</institution></aff><aff><institution xml:lang="ru">Национальный медицинский исследовательский центр радиологии</institution></aff><aff><institution xml:lang="zh">National Medical Research Radiological Centre</institution></aff></aff-alternatives><pub-date date-type="preprint" iso-8601-date="2024-09-04" publication-format="electronic"><day>04</day><month>09</month><year>2024</year></pub-date><pub-date date-type="pub" iso-8601-date="2024-12-04" publication-format="electronic"><day>04</day><month>12</month><year>2024</year></pub-date><volume>5</volume><issue>3</issue><issue-title xml:lang="en"/><issue-title xml:lang="ru"/><issue-title xml:lang="zh"/><fpage>421</fpage><lpage>435</lpage><history><date date-type="received" iso-8601-date="2024-03-03"><day>03</day><month>03</month><year>2024</year></date><date date-type="accepted" iso-8601-date="2024-04-24"><day>24</day><month>04</month><year>2024</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2024, Eco-Vector</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2024, Эко-вектор</copyright-statement><copyright-statement xml:lang="zh">Copyright ©; 2024, Eco-Vector</copyright-statement><copyright-year>2024</copyright-year><copyright-holder xml:lang="en">Eco-Vector</copyright-holder><copyright-holder xml:lang="ru">Эко-вектор</copyright-holder><copyright-holder xml:lang="zh">Eco-Vector</copyright-holder><ali:free_to_read xmlns:ali="http://www.niso.org/schemas/ali/1.0/"/><license><ali:license_ref xmlns:ali="http://www.niso.org/schemas/ali/1.0/">https://creativecommons.org/licenses/by-nc-nd/4.0</ali:license_ref></license></permissions><self-uri xlink:href="https://jdigitaldiagnostics.com/DD/article/view/628304">https://jdigitaldiagnostics.com/DD/article/view/628304</self-uri><abstract xml:lang="en"><p><bold>BACKGROUND</bold>: Recently, significant efforts have been undertaken to find potential noninvasive biomarkers for predicting the response of locally advanced rectal cancer to neoadjuvant chemoradiotherapy.</p> <p><bold>AIM</bold>: To assess the texture characteristics of locally advanced rectal cancer in primary T2-weighted imaging (T2-WI) as a potential predictor for the efficacy of standard neoadjuvant chemoradiotherapy and develop a prediction system for the efficacy of neoadjuvant chemoradiotherapy based on them.</p> <p><bold>MATERIALS AND METHODS</bold>:<italic> </italic>The retrospective study enrolled 82 patients with locally advanced rectal cancer who received combination treatment with neoadjuvant chemoradiotherapy. Patient data were divided into the training (<italic>n</italic>=58) and control (<italic>n</italic>=24) sets. For texture analysis, primary high-resolution T2-WI at the level of the tumor center, oriented perpendicular to the intestinal wall, was used. The texture analysis was performed by second-order statistics based on the gray-level co-occurrence matrices using MAZDA ver. 4.6 featuring the calculation of 11 texture parameters. In the training set, based on the morphological assessment of surgical specimens, significantly different texture analysis parameters were found for two groups of patients: neoadjuvant chemoradiotherapy responders (good prognosis group) and nonresponders (poor prognosis group). Accordingly, a scoring system was created for assessing the efficacy of neoadjuvant chemoradiotherapy. The system was tested on the control set, and diagnostic efficacy parameters were determined.</p> <p><bold>RESULTS</bold>:<italic> </italic>In the training set, the good and poor prognosis groups differed significantly in five texture parameters: AngScMom (<italic>p</italic>=0.021), SumofSqs (<italic>p</italic>=0.003), SumEntrp (<italic>p</italic>=0.003), Entropy (<italic>p</italic>=0.038), and SumVarnc (<italic>p</italic>=0.015), for which the cutoff points were found. These parameters were applied to create the scoring system (excluding the Entropy parameter, which had a strong direct correlation with SumEntrp and the lowest area under the curve, and SumofSqs, which had low reproducibility). The diagnostic efficiency of the scoring system for predicting the response had sensitivity, specificity, positive-predictive value, and negative- predictive value of 72%, 69%, 70%, and 71% for the training set and 80%, 64%, 62%, and 82% for the control set, respectively. The areas under the ROC curve were 0.77 and 0.72 for the training and control sets, respectively.</p> <p><bold>CONCLUSIONS</bold>: Texture analysis of the primary T2-WI of tumors in patients with locally advanced rectal cancer allows for predicting the efficacy of neoadjuvant chemoradiotherapy with moderate diagnostic efficiency. The results suggest good prospects for further research in this area.</p></abstract><trans-abstract xml:lang="ru"><p><bold>Обоснование</bold>.<bold> </bold>В последнее время прилагаются значительные усилия по поиску потенциальных неинвазивных биомаркёров для прогнозирования ответа местно распространённого рака прямой кишки на неоадъювантную химиолучевую терапию.</p> <p><bold>Цель исследования </bold>― оценить текстурные характеристики местно распространённого рака прямой кишки на первичном Т2-взвешенном изображении (Т2-ВИ) в качестве потенциального фактора прогноза эффективности стандартной неоадъювантной химиолучевой терапии и разработать на их основе систему прогнозирования эффективности такого лечения.</p> <p><bold>Материалы и методы</bold>. Включённые в ретроспективное исследование пациенты с местно распространённым раком прямой кишки, получившие комбинированное лечение с неоадъювантной химиолучевой терапией (<italic>n</italic>=82), были разделены на обучающую (<italic>n</italic>=58) и контрольную (<italic>n</italic>=24) выборку. Для текстурного анализа использовали первичное Т2-ВИ высокого разрешения на уровне центра опухоли, ориентированное перпендикулярно стенке кишки. Текстурный анализ выполняли статистическим методом второго порядка на основе матрицы совместной встречаемости уровней серого (GLCM) с помощью компьютерной программы MAZDAver. 4.6 с расчётом 11 параметров текстуры. После морфологической оценки операционных препаратов в обучающей выборке выявлены достоверно различающиеся параметры текстурного анализа для групп пациентов, ответивших (группа хорошего прогноза) и не ответивших (группа плохого прогноза) на лечение, на основе чего создана балльная система оценки эффективности неоадъювантной химиолучевой терапии. Система протестирована на контрольной выборке с определением параметров диагностической эффективности.</p> <p><bold>Результаты</bold>.<bold> </bold>Группы хорошего и плохого прогноза в обучающей выборке достоверно различались по пяти параметрам текстуры, для которых найдены точки разделения: AngScMom (<italic>р</italic>=0,021), SumofSqs (<italic>р</italic>=0,003), SumEntrp (<italic>р</italic>=0,003), Entropy (<italic>р</italic>=0,038) и SumVarnc (<italic>р</italic>=0,015), из них исключены при создании балльной системы Entropy ,как имеющий сильную прямую корреляционную связь с SumEntrp и наименьшую AUC, и SumofSqs из-за низкой воспроизводимости. Диагностическая эффективность балльной системы прогнозирования ответа имела чувствительность, специфичность, прогностичность положительного и прогностичность отрицательного результата 72; 69; 70 и 71% для обучающей и 80; 64; 62 и 82% для контрольной выборки соответственно. Площадь под ROC-кривой для обучающей выборки составила 0,77, для контрольной ― 0,72.</p> <p><bold>Заключение</bold>.<bold> </bold>Текстурный анализ первичного Т2-ВИ опухоли у больных местно распространённым раком прямой кишки позволил спрогнозировать эффективность неоадъювантной химиолучевой терапии с умеренной диагностической эффективностью, что свидетельствует о перспективности дальнейших исследований в этом направлении.</p></trans-abstract><trans-abstract xml:lang="zh"><p>论证。为了预测局部晚期直肠癌对新辅助放化疗的反应，最近人们在寻找潜在无创生物标志物方面一直在做着巨大的努力。</p> <p>研究目的 — 评估局部晚期直肠癌在原发加权T2图像上的纹理特征，将其作为预测标准新辅助放化疗效果的潜在因素，并在此基础上开发一套预测此类治疗效果的系统。</p> <p>材料和方法。在回顾性研究中接受新辅助放化疗综合治疗的局部晚期直肠癌患者（n=82）被分为训练样本（n=58）和对照样本（n=24）。在肿瘤中心水平使用方向垂直于肠壁的高分辨率原始加权T2图像，用于纹理分析。纹理分析基于灰度级共生矩阵（GLCM），借助MAZDAver计算机程序执行了二阶统计法。 4.6和11个纹理参数的计算。在训练样本中进行手术制剂形态学评估后，查明治疗有反应（预后良好组）和无反应（预后不良组）患者组的纹理分析参数的真实差异，并在此基础上创建评估新辅助放化疗效果的评分系统。系统在对照样本上进行测试确定诊断效率的参数。</p> <p>结果。在训练样本的预后良好组和预后不良组中找到分离点，其五个纹理参数上存在真实差异：AngScMom（p=0.021）、SumofSqs（p=0.003）、SumEntrp（p=0.003）、Entropy（p=0.038）和 SumVarnc（p=0.015），在创建评分系统时排除了 Entropy，因其与 SumEntrp相比有很强的直接相关性，最低的AUC， 以及与SumofSqs相比重现性低。反应预测评分系统的诊断效率在训练样本中的灵敏度、特异性、阳性预测能力和阴性预测能力分别为 72%、69%、70% 和 71%，相应的在对照样本中分别为 80%、64%、62% 和 82%。曲线下面积在训练样本中为 ROC 为 0.77，在对照样本中为 0.72。</p> <p>结论。对局部晚期直肠癌患者原发肿瘤T2-VI的纹理分析可以预测诊断效率适中的新辅助放化疗效果，表明这个方向的进一步研究的前景性。</p></trans-abstract><kwd-group xml:lang="en"><kwd>rectal cancer</kwd><kwd>magnetic resonance imaging</kwd><kwd>radiomics</kwd><kwd>texture analysis</kwd><kwd>treatment efficacy assessment</kwd><kwd>primary staging</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>рак прямой кишки</kwd><kwd>магнитно-резонансная томография</kwd><kwd>радиомика</kwd><kwd>текстурный анализ</kwd><kwd>оценка эффективности лечения</kwd><kwd>первичное стадирование</kwd></kwd-group><kwd-group xml:lang="zh"><kwd>直肠癌</kwd><kwd>核磁共振成像</kwd><kwd>影像组学</kwd><kwd>纹理分析</kwd><kwd>疗效评估</kwd><kwd>初诊分期</kwd></kwd-group><funding-group/></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><citation-alternatives><mixed-citation xml:lang="en">Berdov BA, Erigin DV, Nevolskykh AA, et al. 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