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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">10.24835/1607-0763-2020-1-39-47</article-id><article-id custom-type="elpub" pub-id-type="custom">medvis-884</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</subject></subj-group><subj-group subj-group-type="section-heading" xml:lang="en"><subject>ABDOMEN</subject></subj-group></article-categories><title-group><article-title>Сравнительный анализ плотности печени по данным КТ и низкодозной КТ органов грудной клетки</article-title><trans-title-group xml:lang="en"><trans-title>Liver density in routine and low-dose computed tomography: the effect of image noise on measurement accuracy</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-5161-6540</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гончар</surname><given-names>А. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Gonchar</surname><given-names>A. P.</given-names></name></name-alternatives><bio xml:lang="ru"><p>младший научный сотрудник  125124 Москва, ул. Расковой, 16/26, стр. 1, Российская Федерация</p><p>Тел.: +7 (962) 967 50 71  </p></bio><bio xml:lang="en"><p>Junior Researcher125124 Moscow, Raskovoy str., 16/26, bld. 1, Russian Federation</p><p>Phone: +7-962-967-50-71 </p></bio><email xlink:type="simple">anne.gonchar@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/0000-0003-1816-1315</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Гомболевский</surname><given-names>В. А.</given-names></name><name name-style="western" xml:lang="en"><surname>Gombolevskij</surname><given-names>V. A.</given-names></name></name-alternatives><bio xml:lang="ru"/><bio xml:lang="en"/><email xlink:type="simple">g_viktor@mail.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/0000-0003-3786-4171</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Елизаров</surname><given-names>А. Б.</given-names></name><name name-style="western" xml:lang="en"><surname>Elizarov</surname><given-names>A. B.</given-names></name></name-alternatives><bio xml:lang="ru"/><bio xml:lang="en"/><email xlink:type="simple">a.elizarov@npcmr.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/0000-0001-7046-7157</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кульберг</surname><given-names>Н. С.</given-names></name><name name-style="western" xml:lang="en"><surname>Kulberg</surname><given-names>N. S.</given-names></name></name-alternatives><bio xml:lang="ru"><p>канд. физ.-мат. наук, руководитель отдела разработки средств медицинской визуализации 125124 Москва, ул. Расковой, 16/26, стр. 1, Российская Федерация</p><p>119333 Москва, ул. Вавилова, д. 44, корп. 2, Российская Федерация</p></bio><bio xml:lang="en"><p>44/2, Vavilova str., Moscow, 119333, Russian Federation</p></bio><email xlink:type="simple">kulberg@npcmr.ru</email><xref ref-type="aff" rid="aff-2"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-7385-5032</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Кляшторный</surname><given-names>В. Г.</given-names></name><name name-style="western" xml:lang="en"><surname>Klyashtorny</surname><given-names>V. G.</given-names></name></name-alternatives><bio xml:lang="ru"/><bio xml:lang="en"/><email xlink:type="simple">v.klyashtornyy@npcmr.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/0000-0002-0302-293X</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Чернина</surname><given-names>В. Ю.</given-names></name><name name-style="western" xml:lang="en"><surname>Chernina</surname><given-names>V. Yu.</given-names></name></name-alternatives><bio xml:lang="ru"/><bio xml:lang="en"/><xref ref-type="aff" rid="aff-1"/></contrib><contrib contrib-type="author" corresp="yes"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4619-2744</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Босин</surname><given-names>В. Ю.</given-names></name><name name-style="western" xml:lang="en"><surname>Bosin</surname><given-names>V. Yu.</given-names></name></name-alternatives><bio xml:lang="ru"/><bio xml:lang="en"/><email xlink:type="simple">sandal05@list.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/0000-0001-6545-6170</contrib-id><name-alternatives><name name-style="eastern" xml:lang="ru"><surname>Морозов</surname><given-names>С. П.</given-names></name><name name-style="western" xml:lang="en"><surname>Morozov</surname><given-names>S. P.</given-names></name></name-alternatives><bio xml:lang="ru"/><bio xml:lang="en"/><email xlink:type="simple">morozov@npcmr.ru</email><xref ref-type="aff" rid="aff-1"/></contrib></contrib-group><aff-alternatives id="aff-1"><aff xml:lang="ru"><institution>ГБУЗ “Научно-практический клинический центр диагностики и телемедицинских технологий Департамента здравоохранения города Москвы”</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow</institution><country>Russian Federation</country></aff></aff-alternatives><aff-alternatives id="aff-2"><aff xml:lang="ru"><institution>ГБУЗ “Научно-практический клинический центр диагностики и телемедицинских технологий Департамента здравоохранения города Москвы”;&#13;
Федеральный исследовательский центр “Институт управления” РАН</institution><country>Россия</country></aff><aff xml:lang="en"><institution>Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of Moscow;&#13;
Federal Research Center Computer Science and Control of the Russian Academy of Sciences</institution><country>Russian Federation</country></aff></aff-alternatives><pub-date pub-type="collection"><year>2020</year></pub-date><pub-date pub-type="epub"><day>30</day><month>04</month><year>2020</year></pub-date><volume>24</volume><issue>1</issue><issue-title>Медицинская визуализация 2020№1</issue-title><fpage>39</fpage><lpage>47</lpage><permissions><copyright-statement>Copyright &amp;#x00A9; Гончар А.П., Гомболевский В.А., Елизаров А.Б., Кульберг Н.С., Кляшторный В.Г., Чернина В.Ю., Босин В.Ю., Морозов С.П., 2020</copyright-statement><copyright-year>2020</copyright-year><copyright-holder xml:lang="ru">Гончар А.П., Гомболевский В.А., Елизаров А.Б., Кульберг Н.С., Кляшторный В.Г., Чернина В.Ю., Босин В.Ю., Морозов С.П.</copyright-holder><copyright-holder xml:lang="en">Gonchar A.P., Gombolevskij V.A., Elizarov A.B., Kulberg N.S., Klyashtorny V.G., Chernina V.Y., Bosin V.Y., Morozov S.P.</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/884">https://medvis.rdsmedia.ru/jour/article/view/884</self-uri><abstract><p>Жировой гепатоз – распространенный вид патологии, своевременное выявление которой позволяет избежать прогрессирования заболевания и развития необратимых изменений. Известно, что по данным стандартной компьютерной томографии (КТ) и низкодозной КТ (НДКТ) можно достоверно выявлять стеатоз средней и тяжелой степеней, в том числе при исследовании органов грудной клетки (ОГК). Таким образом внедрение в клиническую практику скрининговых программ с помощью НДКТ позволяет проводить дополнительную оценку состояния печени.</p><sec><title>Цель исследования</title><p>Цель исследования: оценка возможностей корректного определения средней плотности печени при НДКТ ОГК для выявления признаков жирового гепатоза при проведении скрининговых исследований.</p></sec><sec><title>Материал и методы</title><p>Материал и методы. Проанализированы результаты КТ и НДКТ ОГК 30 000 пациентов, выполненных за период 2017–2019 гг. Критериями включения в разработку являлось наличие у пациента данных КТ и НДКТ в промежутке менее 27 дней между исследованиями. Исследования, при которых в печени выявлены образования, пациенты после операций на печени, с анемией, при снижении плотности крови менее 40 HU, с опущенными вдоль туловища руками во время исследования и при некорректной сегментации печени при обработке изображений не включались в анализ.Исследования НДКТ и КТ были выполнены на 64-срезовых томографах. Протяженность сканирования: от верхушки легких до плевральных синусов. Напряжение при низкодозном протоколе было равно 135 кВ, при стандартном – 120 кВ. Средняя лучевая нагрузка при НДКТ составила 0,6–0,8 мЗв, при стандартной КТ – 2,8–4,6 мЗв.Автоматический анализ изображений проводился с помощью разработанного ПО для автоматического измерения плотности печени, статистический анализ – с помощью программы Stata14 (StataCorp LLC, College Station, Texas, США).</p></sec><sec><title>Результаты</title><p>Результаты. Отобраны результаты исследований 61 пациента, которые соответствовали заданным критериям. Соотношение мужчин к женщинам составило 23:38, средний возраст – 53 года.При сравнительной оценке рентгенологической плотности печени при КТ и НДКТ на всей выборке  статистически значимых отличий не выявлено (p &lt; 0,480), при этом отмечалось незначительное повышение средних значений плотности при использовании низкодозных протоколов сканирования: 52,81 HU при НДКТ и 51,88 HU при КТ.Оценка исследований, разбитых на подгруппы в зависимости от плотности печени, показала, что в подгруппе  40–50 HU полученные данные отличаются статистической значимостью (p &lt; 0,0003), тогда как в остальных группах подобная взаимосвязь не выявлена (p &lt; 0,753, p &lt; 0,269, p &lt; 0,077). При НДКТ отмечена средняя антикорреляция между плотностью и среднеквадратическим отклонением с коэффициентом -0,686 (p &lt; 0,0001).</p></sec><sec><title>Обсуждение</title><p>Обсуждение. Результат статистического анализа показал, что данные плотности печени при НДКТ сопоставимы с КТ. Это позволяет выявлять пациентов с жировым гепатозом средней и тяжелой степеней,не повышая дозу лучевой нагрузки.Анализ влияния шумовых помех на плотность печени при НДКТ показал, что чем выше уровень шума, тем интенсивнее снижаются данные плотности печени, что необходимо учитывать при трактовке результатов. Отсутствие единых значений плотности печени, различающих ее нормальные значения от сниженных, затрудняет интерпретацию данных, находящихся в диапазоне 40–50 HU, что требует проведения дальнейших исследований. </p></sec></abstract><trans-abstract xml:lang="en"><p>The introduction of LDCT-based screening programs into clinical practice allows an additional assessment of the liver. It is known that medium-to-severe steatosis can be detected using LDCT. However, taking into account the increased image noise level and the fact that the liver is always only partly in the scan area, the question arises as to how accurately the liver density can be determined in LDCT relative to routine CT.</p><sec><title>Purpose</title><p>Purpose. Thus, the following objectives of this study have been established:• To identify the differences between the mean density of the liver as measured by a CT and an LNDT.• To compare the mean density between CT and LDCT in different patient subgroups depending on the mean liver density (&lt;40 HU, 40–50 HU, 50–60 HU, and &gt;60 HU).• To determine the effect of image noise level on the mean liver density values on LDCT compared to CT.</p></sec><sec><title>Materials and methods</title><p>Materials and methods. We analyzed 30000 patient records from 2017 to 2019.Inclusion criteria: We included patients with both thoracic non-contrast CT and an LDCT and the time interval between the studies of less than 27 days.Exclusion criteria: The absence of CT-LDCT pair, presence of focal liver lesions, known liver diseases, operated liver, anemia with blood density decrease below 40 HU, hands along the body instead of overhead.Study protocol: LDCT was performed at 135 kV. The routine CT was at 120 kV. Scan length: from lung apex to pleural sinuses. The average radiation dose with LDCT was 0.6–0.8 mSv, and 2.8–4.6 mSv with routine CT. All scans were performed on two 64-detector units from the same manufacturer.We measured liver density with the CTLiverExam software algorithm for automatic liver densitometry.The statistical processing was done using the Stata14 program.</p></sec><sec><title>Results</title><p>Results. We used data from 61 patients for statistical analysis. The average age was 53 years. The ratio of men to women was 23:38.We did not observe statistically significant differences between CT and LDCT. With a breakdown by the initial liver density level, it turned out that in the subgroup 40-50 HU, the differences were statistically significant. No correlation between liver density and standard deviation for CT was revealed (p = 0.338). There was a mild anticorrelation for LDCT with a coefficient of -0.686 (p &lt; 0.0001).</p></sec><sec><title>Conclusion</title><p>Conclusion. Our study shows that liver density measurement in thoracic LDCT is valid. In the context of lung cancer screening programs. An analysis of the image noise/liver density ratio on the LDCT shows an inversely proportional relationship: the higher the noise level, the more significant a “decrease” in liver density. This factor must be taken into account when interpreting the results CT and LDCT. </p></sec></trans-abstract><kwd-group xml:lang="ru"><kwd>низкодозная компьютерная томография</kwd><kwd>стандартная компьютерная томография</kwd><kwd>стеатоз печени</kwd><kwd>автоматическое определение плотности печени</kwd></kwd-group><kwd-group xml:lang="en"><kwd>low-dose computed tomography</kwd><kwd>computed tomography</kwd><kwd>liver steatosis</kwd><kwd>automatic liver densitometry</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">Bedogni G., Miglioli L., Masutti F., Tiribelli C., Marchesini G., Bellentani S. Prevalence of and risk factors for nonalcoholic fatty liver disease: the Dionysos nutrition and liver study. 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