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<article article-type="research-article" dtd-version="1.3" 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" xml:lang="ru"><front><journal-meta><journal-id journal-id-type="publisher-id">medvis</journal-id><journal-title-group><journal-title xml:lang="ru">Медицинская визуализация</journal-title><trans-title-group xml:lang="en"><trans-title>Medical Visualization</trans-title></trans-title-group></journal-title-group><issn pub-type="ppub">1607-0763</issn><issn pub-type="epub">2408-9516</issn><publisher><publisher-name>RDS-Media Ltd.</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.24835/1607-0763-1372</article-id><article-id custom-type="elpub" pub-id-type="custom">medvis-1372</article-id><article-categories><subj-group subj-group-type="heading"><subject>Research Article</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="ru"><subject>БРЮШНАЯ ПОЛОСТЬ И ЗАБРЮШИННОЕ ПРОСТРАНСТВО</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ABDOMEN AND RETROPERITONEAL</subject></subj-group></article-categories><title-group><article-title>Воспроизводимость текстурных показателей КТ- и МРТ-изображений гепатоцеллюлярного рака</article-title><trans-title-group xml:lang="en"><trans-title>Reproducibility of CT and MRI texture features of hepatocellular carcinoma</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-9357-0998</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кармазановский</surname><given-names>Г. Г.</given-names></name><name name-style="western" xml:lang="en"><surname>Kаrmаzаnovsky</surname><given-names>G. G.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Кармазановский Григорий Григорьевич – академик РАН, доктор мед. наук, профессор, заведующий отделом лучевых методов диагностики, 117997 Москва, ул. Большая Серпуховская, д. 27;</p><p>профессор кафедры лучевой диагностики и терапии медикобиологического факультета, 117997 Москва, ул. Островитянова, д. 1</p></bio><bio xml:lang="en"><p>Grigory G. Kаrmаzаnovsky – Academician of the Russiаn Асаdemy of Sсienсes, Doct. of Sci. (Med.), Professor, Heаd of the Department of Radiation Methods of Diagnostics, 27, Bolshaya Serpukhovskaya str., Moscow 117997;</p><p>Professor of radiology department, 1, Ostrivityanova str., Moscow 117997</p></bio><email xlink:type="simple">karmazanovsky@ixv.ru</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4518-4451</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Шантаревич</surname><given-names>М. Ю.</given-names></name><name name-style="western" xml:lang="en"><surname>Shantarevich</surname><given-names>M. Y.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Шантаревич Мария Юрьевна – аспирант,</p><p>117997 Москва, ул. Большая Серпуховская, д. 27</p></bio><bio xml:lang="en"><p>Mariia Y. Shantarevich – Postgraduate studentm</p><p>27, Bolshaya Serpukhovskaya str., Moscow 117997</p></bio><email xlink:type="simple">mashantarevich@gmail.com</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-7349-1192</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Сташкив</surname><given-names>В. И.</given-names></name><name name-style="western" xml:lang="en"><surname>Stashkiv</surname><given-names>V. I.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Сташкив Владислава Ивановна – аспирант,</p><p>117997 Москва, ул. Большая Серпуховская, д. 27</p></bio><bio xml:lang="en"><p>Vladislava I. Stashkiv – Postgraduate student,</p><p>27, Bolshaya Serpukhovskaya str., Moscow 117997</p></bio><email xlink:type="simple">vladastashkiv@gmail.com</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-1791-9163</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Ревишвили</surname><given-names>А. Ш.</given-names></name><name name-style="western" xml:lang="en"><surname>Revishvili</surname><given-names>A. Sh.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Ревишвили Амиран Шотаевич – академик РАН, доктор мед. наук, профессор, директор, 117997 Москва, ул. Большая Серпуховская, д. 27;;</p><p>заведующий кафедрой ангиологии, сердечно-сосудистой, эндоваскулярной хирургии и аритмологии, 125993 Москва, ул. Баррикадная, д. 2/1, стр. 1</p></bio><bio xml:lang="en"><p>Amiran Sh. Revishvili – Academician of the Russian Academy of Science, Doct. of Sci. (Med.), Professor, Director, 27, Bolshaya Serpukhovskaya str., Moscow 117997;</p><p>Head of the Department of Angiology, Cardiovascular, Endovascular Surgery and Arrhythmology, 2/1, bld. 1, Barrikadnaya str., Moscow 125993</p></bio><email xlink:type="simple">amirevi@mail.ru</email><xref ref-type="aff" rid="aff-3"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ФГБУ “Национальный медицинский исследовательский центр хирургии им. А.В. Вишневского” Минздрава России;&#13;
ФГБОУ ВО “РНИМУ им. Н.И. Пирогова” Минздрава России</institution><country>Россия</country></aff><aff xml:lang="en"><institution>A.V. Vishnevsky National Medical Research Center of Surgery of the Ministry of Healthcare of the Russian Federation; &#13;
Pirogov Russian National Research Medical University of the Ministry of Healthcare of the Russian Federation</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>ФГБУ “Национальный медицинский исследовательский центр хирургии им. А.В. Вишневского” Минздрава России</institution><country>Россия</country></aff><aff xml:lang="en"><institution>A.V. Vishnevsky National Medical Research Center of Surgery of the Ministry of Healthcare of the Russian Federation</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-3"><aff xml:lang="ru"><institution>ФГБУ “Национальный медицинский исследовательский центр хирургии им. А.В. Вишневского” Минздрава России;&#13;
ФГБОУ ДПО “Российская медицинская академия непрерывного профессионального образования” Минздрава России</institution><country>Россия</country></aff><aff xml:lang="en"><institution>A.V. Vishnevsky National Medical Research Center of Surgery of the Ministry of Healthcare of the Russian Federation;&#13;
Russian Medical Academy of Continuous Professional Education of the Ministry of Healthcare of the Russian Federation</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2023</year></pub-date><pub-date pub-type="epub"><day>31</day><month>07</month><year>2023</year></pub-date><volume>27</volume><issue>3</issue><fpage>84</fpage><lpage>93</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Кармазановский Г.Г., Шантаревич М.Ю., Сташкив В.И., Ревишвили А.Ш., 2023</copyright-statement><copyright-year>2023</copyright-year><copyright-holder xml:lang="ru">Кармазановский Г.Г., Шантаревич М.Ю., Сташкив В.И., Ревишвили А.Ш.</copyright-holder><copyright-holder xml:lang="en">Kаrmаzаnovsky G.G., Shantarevich M.Y., Stashkiv V.I., Revishvili A.S.</copyright-holder><license xml:lang="ru" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>Данная работа распространяется под лицензией Creative Commons Attribution 4.0.</license-p></license><license xml:lang="en" license-type="creative-commons-attribution" xlink:href="https://creativecommons.org/licenses/by/4.0/" xlink:type="simple"><license-p>This work is licensed under a Creative Commons Attribution 4.0 License.</license-p></license></permissions><self-uri xlink:href="https://medvis.rdsmedia.ru/jour/article/view/1372">https://medvis.rdsmedia.ru/jour/article/view/1372</self-uri><abstract><p>Цель исследования: сравнить воспроизводимость текстурных показателей при сегментации двумя рентгенологами КТ- и МРТ-изображений гепатоцеллюлярного рака (ГЦР). Оценить возможность предварительной обработки изображений для повышения воспроизводимости текстурных показателей. Материал и методы. В исследование было включено 66 пациентов с данными предоперационных КТи МРТ-исследований, которым была выполнена хирургическая резекция печени по поводу ГЦР с указанием степени дифференцировки опухоли по данным послеоперационного патоморфологического исследования. Два рентгенолога с опытом абдоминальной визуализации 3 и 6 лет независимо друг от друга проводили сегментацию всего объема опухоли на КТ- и МРТ-изображениях. Расчет текстурных признаков выполнялся как без применения предварительной обработки изображений, так и с применением заданного размера вокселя 1 мм3 (RES) фильтром Лапласа Гаусса, а для КТ-изображений также с ограничением по плотности от 0 до 300 HU (0–300 HU). Согласованность измерений рентгенологами в отношении текстурных показателей была оценена с помощью коэффициента внутриклассовой корреляции 2-го типа (ICC). Результаты. Наибольший процент воспроизводимых текстурных признаков при применении предварительной обработки изображений отмечался при КТ в артериальную фазу сканирования (0–300 HU + RES) (89,1%), а при МРТ в гепатобилиарную фазу с приведением изображений к изотропному вокселю (86,6%). При этом приведение изображения к изотропному вокселю 1 мм3 повышало процент воспроизводимых текстурных показателей в нативную, артериальную и отсроченную фазы при КТ, а также для Т2ВИ, ДВИ и в гепатобилиарную фазу при МРТ. Заключение. Обе методики (КТ и МРТ) позволяют выявить воспроизводимые текстурные признаки, особенно с приведением изображения к изотропному вокселю. При этом предпочтение стоит отдавать постконтрастным изображениям, в том числе гепатобилиарной фазе. При КТ также целесообразно использовать ограничение по плотности для выделенной области интереса, что позволит избежать влияния на получаемые текстурные признаки прилежащих органов и жировой клетчатки и, таким образом, повысит процент воспроизводимых текстурных признаков. </p></abstract><trans-abstract xml:lang="en"><p>Purpose: To compare the reproducibility of texture features during segmentation of CT and MR images of hepatocellular cancer (HCC) by two radiologists. Evaluate the possibility of images pre-processing to improve the reproducibility of texture features. Material and methods. We included 66 patients with preoperative CT and MR images, followed by surgical liver resection for HCC, indicating the tumor histologic grade. Two radiologists with 3 and 6 years of abdominal imaging experience independently segmented the entire tumor volume on CT and MR images. The calculation of texture features was performed without the use of images pre-processing and using a spatial resampling with fixed voxel size of 1 mm3 (RES), a Laplace Gaussian filter, and for CT images, also with a density threshold from 0 to 300 HU (0–300 HU). The agreement between measurements of radiologists in relation to texture features was carried out using the type 2 intra-class correlation coefficient (ICC). Results. The highest percentage of reproducible texture features with the use of image preprocessing was observed with CT in the arterial phase (0–300 HU + RES) (89.1%), and with MRI in the hepatobiliary phase (RES) (86.6%). At the same time, spatial resampling with fixed voxel size of 1 mm3 increased the percentage of reproducible texture features in the native, arterial, and delayed phases in CT, as well as in T2-WI, DWI, and in the hepatobiliary phase for MRI. Conclusion. Thus, both techniques, CT and MRI, make it possible to extract reproducible texture features, especially with the use of spatial resampling with fixed voxel size. In this case, preference should be given to a postcontrast images, including the hepatobiliary phase. In CT, it is also advisable to use a density threshold from 0 to 300 HU for the selected area of interest, which will avoid affecting the texture features of adjacent organs and adipose tissue and increase the reproducibility of textural features. </p></trans-abstract><kwd-group xml:lang="ru"><kwd>гепатоцеллюлярный рак</kwd><kwd>КТ</kwd><kwd>МРТ</kwd><kwd>текстурный анализ</kwd><kwd>радиомика</kwd></kwd-group><kwd-group xml:lang="en"><kwd>hepatocellular carcinoma</kwd><kwd>CT</kwd><kwd>MRI</kwd><kwd>texture analysis</kwd><kwd>radiomics</kwd></kwd-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Allemani C., Matsuda T., Di Carlo V. et al. CONCORD Working Group. Global surveillance of trends in cancer survival 2000-14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. 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