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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">10.24835/1607-0763-1049</article-id><article-id custom-type="elpub" pub-id-type="custom">medvis-1049</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>НОВЫЕ ТЕХНОЛОГИИ ЛУЧЕВЫХ ИССЛЕДОВАНИЙ</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>NEW TECHNOLOGIES IN RADIOLOGY</subject></subj-group></article-categories><title-group><article-title>Количественная компьютерная томография, современные данные. Обзор</article-title><trans-title-group xml:lang="en"><trans-title>Quantitative Computed Tomography, modern data. Review</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-1694-4682</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Петряйкин</surname><given-names>А. В.</given-names></name><name name-style="western" xml:lang="en"><surname>Petraikin</surname><given-names>A. V.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Петряйкин Алексей Владимирович – кандидат медицинских наук, ведущий научный сотрудник отдела инновационных технологий.</p><p>109029 Москва, Средняя Калитниковская ул., д. 28, стр. 1.</p><p>SPIN: 6193-1656</p></bio><bio xml:lang="en"><p>Alexey V. Petraikin – Cand. of Sci (Med.), leading researcher, of Innovative Technologies Department Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow.</p><p>28-1, Srednyaya Kalitnikovskaya str., Moscow, 109029.</p><p>SPIN-6193-1656</p></bio><email xlink:type="simple">alexeypetraikin@gmail.com</email><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-1763-0725</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Скрипникова</surname><given-names>И. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Skripnikova</surname><given-names>I. A.</given-names></name></name-alternatives><bio xml:lang="ru"><p>Скрипникова Ирина Анатольевна – доктор медицинских наук, профессор, руководитель отдела профилактики остеопороза.</p><p>101990 Москва, Петроверигский пер., 10, стр.3.</p><p>SPIN: 1514-0880.</p></bio><bio xml:lang="en"><p>Irina A. Skripnikova – Doct. of Sci. (Med.), Professor, Head of Osteoporosis prevention Department of National Medical Research Center for Therapy and Preventive Medicine, Ministry of Health Care of Russia.</p><p>10-3, Petroverigsky per., Moscow, 101990.</p><p>SPIN-1514-0880</p></bio><email xlink:type="simple">ISkripnikova@gnicpm.ru</email><xref ref-type="aff" rid="aff-2"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru">Научно-практический клинический центр диагностики и телемедицинских технологий Департамента здравоохранения города Москвы<country>Россия</country></aff><aff xml:lang="en">Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of Moscow Health Care Department<country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru">Национальный медицинский исследовательский центр терапии и профилактической медицины Минздрава России<country>Россия</country></aff><aff xml:lang="en">National Medical Research Center for Therapy and Preventive Medicine, Ministry of Health Care of Russia<country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2021</year></pub-date><pub-date pub-type="epub"><day>12</day><month>12</month><year>2021</year></pub-date><volume>25</volume><issue>4</issue><fpage>134</fpage><lpage>146</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Петряйкин А.В., Скрипникова И.А., 2022</copyright-statement><copyright-year>2022</copyright-year><copyright-holder xml:lang="ru">Петряйкин А.В., Скрипникова И.А.</copyright-holder><copyright-holder xml:lang="en">Petraikin A.V., Skripnikova I.A.</copyright-holder><license 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.vidar.ru/jour/article/view/1049">https://medvis.vidar.ru/jour/article/view/1049</self-uri><abstract><p>Обзор посвящен методике количественной компьютерной томографии (ККТ, QCT – quantitative computed tomography). При ККТ производится перевод рентгеновской плотности (HU) в минеральную плотность кости (МПК, мг/мл) с помощью линейных зависимостей, полученных при использования калибровочных стандартов (фантомов). При сопоставлении с нормативными возрастными данными возможна диагностика остеопороза (ОП). В обзоре представлены различные методики ККТ и их диагностические возможности в соответствии с позициями ISCD 2019 (International Society for Clinical Densitometry). Рассмотрены результаты сравнения ККТ и стандартной двухэнергетической рентгеновской абсорбциометрии (ДРА, DXA – dual-energy Х-ray absorptiometry). Отмечено, что при исследовании проксимального отдела бедра результаты методик хорошо сопоставимы, по результатам обеих методик возможна диагностика ОП по Т-критерию. Однако при исследовании позвоночника при ККТ оценивается объемная МПК губчатого вещества тел позвонков, а при ДРА оценивается проекционная МПК. Различны и подходы к интерпретации результатов – при постановке диагноза ОП при ДРА позвоночника используется Т-критерий, а при ККТ – критерии ACR (American College of Radiology).</p><p>В обзоре описаны фантомы, применяемые в ККТ, приведены данные по лучевой нагрузке при проведении ККТ и ДРА.</p><p>Описан подход к оппортунистическому скринингу ОП методом ККТ по результатам ранее проведенной КТ, включая автоматизированные его варианты с использованием технологий искусственного интеллекта. Эти перспективные методики привлекательны ввиду большого количества выполняемых КТ-исследований и исключения проведения дополнительных исследований.</p></abstract><trans-abstract xml:lang="en"><p>In the review we discussed about the method of quantitative computed tomography (QCT, quantitative computed tomography). In QCT, X-ray density (HU) is converted to bone mineral density (BMD mg / ml) using linear relationships obtained by scanning calibration standards (phantoms). When compared with the normative age data, it is possible to diagnose osteoporosis (OP). The review presents various QCT techniques and their diagnostic capabilities in accordance with the positions of ISCD 2019 - (International Society for Clinical Densitometry). The results of comparison of QCT and conventional dual-energy X-ray absorptiometry (DXA) are  considered.  It is noted that in the study of the proximal femur (PF), the results of the methods are well comparable, according to the results of both methods, it is possible to diagnose OP by the T-score. However, when examining the spine QCT, the volume BMD of the trabecular bone of the vertebral bodies is assessed, and with DXA, the projection BMD is assessed. The approaches to the interpretation of the results are also different - diagnosis of OP in DXA of the spine based on the T-score, but in QCT, the ACR (American College of Radiology) criteria are used.</p><p>We describe the phantoms used in QCT, as well as provide data on radiation exposure during QCT and DXA.</p><p>The article describes an approach to opportunistic screening of osteoporosis by the QCT based on the results of previously performed CT scans, including its automated work-flow using artificial intelligence technologies. These promising techniques are attractive due to the large number of CT examinations performed and the exclusion of additional examinations.</p></trans-abstract><kwd-group xml:lang="ru"><kwd>количественная компьютерная томография</kwd><kwd>КТ-денситометрия</kwd><kwd>остеоденситометрия</kwd><kwd>минеральная плотность кости</kwd><kwd>двухэнергетическая рентгеновская абсорбциометрия</kwd><kwd>остеопороз</kwd><kwd>фантомы</kwd></kwd-group><kwd-group xml:lang="en"><kwd>Quantitative Computed Tomography</kwd><kwd>QCT</kwd><kwd>bone mineral density</kwd><kwd>BMD</kwd><kwd>Osteoporosis</kwd><kwd>phantom</kwd></kwd-group><funding-group xml:lang="ru"><funding-statement>Исследование выполнено при финансовой поддержке РФФИ в рамках научного проекта № 20-015-00260</funding-statement></funding-group><funding-group xml:lang="en"><funding-statement>The reported study was funded by RFBR № 20-015-00260</funding-statement></funding-group></article-meta></front><back><ref-list><title>References</title><ref id="cit1"><label>1</label><citation-alternatives><mixed-citation xml:lang="ru">Beckmann E.C. 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