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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">633802</article-id><article-id pub-id-type="doi">10.17816/DD633802</article-id><article-id pub-id-type="edn">WDZWBY</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">Possibilities of Dixon sequences in magnetic resonance imaging for fat fraction quantification: a phantom study Possibilities of Dixon sequences in magnetic resonance imaging for fat fraction quantification: a phantom study</article-title><trans-title-group xml:lang="ru"><trans-title>Возможности DIXON последовательностей в магнитно-резонансной томографии для количественной оценки жировой фракции: фантомное исследование</trans-title></trans-title-group><trans-title-group xml:lang="zh"><trans-title>DIXON序列在磁共振成像中用于脂肪分数定量评估的潜力：一项体模研究</trans-title></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8684-775X</contrib-id><contrib-id contrib-id-type="spin">5504-8136</contrib-id><name-alternatives><name xml:lang="en"><surname>Panina</surname><given-names>Olga Yu.</given-names></name><name xml:lang="ru"><surname>Панина</surname><given-names>Ольга Юрьевна</given-names></name><name xml:lang="zh"><surname>Panina</surname><given-names>Olga Yu.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>MD</p></bio><bio xml:lang="zh"><p>MD</p></bio><email>olgayurpanina@gmail.com</email><xref ref-type="aff" rid="aff1"/><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-9014-9022</contrib-id><contrib-id contrib-id-type="spin">6842-8684</contrib-id><name-alternatives><name xml:lang="en"><surname>Gromov</surname><given-names>Alexander I.</given-names></name><name xml:lang="ru"><surname>Громов</surname><given-names>Александр Игоревич</given-names></name><name xml:lang="zh"><surname>Gromov</surname><given-names>Alexander I.</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>gai8@mail.ru</email><xref ref-type="aff" rid="aff3"/><xref ref-type="aff" rid="aff4"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8235-9361</contrib-id><contrib-id contrib-id-type="spin">5891-4384</contrib-id><name-alternatives><name xml:lang="en"><surname>Ahkmad</surname><given-names>Ekaterina S.</given-names></name><name xml:lang="ru"><surname>Ахмад</surname><given-names>Екатерина Сергеевна</given-names></name><name xml:lang="zh"><surname>Ahkmad</surname><given-names>Ekaterina S.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><email>akhmades@zdrav.mos.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-4293-2514</contrib-id><contrib-id contrib-id-type="spin">2278-7290</contrib-id><name-alternatives><name xml:lang="en"><surname>Semenov</surname><given-names>Dmitry S.</given-names></name><name xml:lang="ru"><surname>Семёнов</surname><given-names>Дмитрий Сергеевич</given-names></name><name xml:lang="zh"><surname>Semenov</surname><given-names>Dmitry S.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>Cand. Sci. (Engineering)</p></bio><bio xml:lang="ru"><p>канд. техн. наук</p></bio><bio xml:lang="zh"><p>Cand. Sci. (Engineering)</p></bio><email>semenovds4@zdrav.mos.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-1160-5905</contrib-id><contrib-id contrib-id-type="spin">9883-3406</contrib-id><name-alternatives><name xml:lang="en"><surname>Kivasev</surname><given-names>Stanislav A.</given-names></name><name xml:lang="ru"><surname>Кивасёв</surname><given-names>Станислав Александрович</given-names></name><name xml:lang="zh"><surname>Kivasev</surname><given-names>Stanislav A.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="en"><p>MD</p></bio><bio xml:lang="zh"><p>MD</p></bio><email>Kivasev@yahoo.com</email><xref ref-type="aff" rid="aff5"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0003-1694-4682</contrib-id><contrib-id contrib-id-type="spin">6193-1656</contrib-id><name-alternatives><name xml:lang="en"><surname>Petraikin</surname><given-names>Alexey V.</given-names></name><name xml:lang="ru"><surname>Петряйкин</surname><given-names>Алексей Владимирович</given-names></name><name xml:lang="zh"><surname>Petraikin</surname><given-names>Alexey V.</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>PetryajkinAV@zdrav.mos.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-6716-5593</contrib-id><contrib-id contrib-id-type="spin">2527-0130</contrib-id><name-alternatives><name xml:lang="en"><surname>Nechaev</surname><given-names>Valentin A.</given-names></name><name xml:lang="ru"><surname>Нечаев</surname><given-names>Валентин Александрович</given-names></name><name xml:lang="zh"><surname>Nechaev</surname><given-names>Valentin 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>NechaevVA1@zdrav.mos.ru</email><xref ref-type="aff" rid="aff2"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies</institution></aff><aff><institution xml:lang="ru">Научно-практический клинический центр диагностики и телемедицинских технологий</institution></aff><aff><institution xml:lang="zh">Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Moscow City Hospital named after S.S. Yudin</institution></aff><aff><institution xml:lang="ru">Городская клиническая больница имени С.С. Юдина</institution></aff><aff><institution xml:lang="zh">Moscow City Hospital named after S.S. Yudin</institution></aff></aff-alternatives><aff-alternatives id="aff3"><aff><institution xml:lang="en">Russian University of Medicine</institution></aff><aff><institution xml:lang="ru">Российский университет медицины</institution></aff><aff><institution xml:lang="zh">Russian University of Medicine</institution></aff></aff-alternatives><aff-alternatives id="aff4"><aff><institution xml:lang="en">National Medical Research Radiological Center</institution></aff><aff><institution xml:lang="ru">Национальный медицинский исследовательский центр радиологии</institution></aff><aff><institution xml:lang="zh">National Medical Research Radiological Center</institution></aff></aff-alternatives><aff-alternatives id="aff5"><aff><institution xml:lang="en">Central Clinical Hospital “RZD-Medicine”</institution></aff><aff><institution xml:lang="ru">Центральный клинический госпиталь «РЖД-Медицина»</institution></aff><aff><institution xml:lang="zh">Central Clinical Hospital “RZD-Medicine”</institution></aff></aff-alternatives><pub-date date-type="preprint" iso-8601-date="2025-06-04" publication-format="electronic"><day>04</day><month>06</month><year>2025</year></pub-date><pub-date date-type="pub" iso-8601-date="2025-07-08" publication-format="electronic"><day>08</day><month>07</month><year>2025</year></pub-date><volume>6</volume><issue>2</issue><issue-title xml:lang="ru"/><fpage>191</fpage><lpage>202</lpage><history><date date-type="received" iso-8601-date="2024-06-26"><day>26</day><month>06</month><year>2024</year></date><date date-type="accepted" iso-8601-date="2024-12-06"><day>06</day><month>12</month><year>2024</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; 2025, Eco-Vector</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; 2025, Эко-вектор</copyright-statement><copyright-statement xml:lang="zh">Copyright ©; 2025, Eco-Vector</copyright-statement><copyright-year>2025</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/633802">https://jdigitaldiagnostics.com/DD/article/view/633802</self-uri><abstract xml:lang="en"><p><bold><italic>BACKGROUND: </italic></bold>The accuracy of quantitative parameters obtained using magnetic resonance imaging is of scientific and practical interest. Monitoring of scan parameters and standardization of commonly used approaches to assess fat fraction remain challenging in radiology.</p> <p><bold><italic>AIM: </italic></bold>This study aimed to evaluate the possibility of fat fraction quantification using standard Dixon pulse sequences through phantom modeling.</p> <p><bold><italic>METHODS: </italic></bold>This multicenter, cross-sectional, nonblinded experimental study used direct oil-in-water emulsions to model substances with varying fat concentrations. Test tubes containing these emulsions were placed in a cylindrical phantom. The emulsions were prepared with mixtures of vegetable oils, with fat fraction values of 10%–60%. Several tests were conducted using scanners from different manufacturers and with varying magnetic field strengths: Optima MR450w, 1.5 T; MAGNETOM Skyra, 3 T; Ingenia, 1.5 T; and Ingenia Achieva dStream, 3.0 T at different medical centers. Fat fraction was obtained using standard formulas based on signal intensity measurements. A regression analysis was conducted to assess the linear relationship between the measured and predefined fat fraction concentrations and an F-test to evaluate variability.</p> <p><bold><italic>RESULTS: </italic></bold>Phantom modeling was employed to determine the performance of Dixon pulse sequences across different magnetic resonance imaging scanners for quantitative fat fraction estimation using relevant formulas. In assessing the accuracy of fat fraction quantification, a weak linear correlation was found between the obtained values and predefined fat fraction concentrations. Additionally, significant deviations &gt;5% were observed for certain scanners. Reproducibility analysis demonstrated variability in fat fraction concentration across different scanner models and within the same model.</p> <p><bold><italic>CONCLUSION: </italic></bold>Obtained results confirm that fat fraction quantification using Dixon pulse sequences and relevant formulas should be performed only after preliminary phantom scanning. The use of a phantom ensures adequate quality control and calibration of the magnetic resonance imaging scanner, making accurate quantitative fat measurement more reliable and widely accessible.</p></abstract><trans-abstract xml:lang="ru"><p><bold>Обоснование. </bold>Точность количественных показателей, полученных с помощью магнитно-резонансной томографии, представляет научный и практический интерес. Контроль параметров сканирования и стандартизация общеизвестных подходов к оценке жировой фракции является важной задачей лучевой диагностики.</p> <p><bold>Цель исследования.</bold> Оценить возможность количественного измерения жировой фракции с помощью стандартных диксоновских импульсных последовательностей посредством фантомного моделирования.</p> <p><bold>Методы. </bold>Проведено экспериментальное многоцентровое одномоментное неослеплённое исследование. Для моделирования веществ с разной концентрацией жировой фазы выбраны прямые эмульсии типа «масло в воде». Пробирки с эмульсиями помещали в специальный цилиндрический фантом. Эмульсии на основе смеси растительных масел представлены в диапазоне значений жировой фракции 10–60%. Проводили серию тестирований на сканерах разных производителей и с различной индукцией магнитного поля: Optima MR450w 1,5 Tл, MAGNETOM Skyra 3 Tл, а также на томографе Ingenia 1,5 Тл и Ingenia Achieva dStream 3,0 Tл в разных медицинских центрах. Фракцию жира определяли расчётным методом по общеизвестным формулам на основе измерения интенсивности сигнала. Провели регрессионный анализ линейной зависимости измеренных концентраций жировой фракций от заданных значений, а также F-тест для оценки вариативности.</p> <p><bold>Результаты. </bold>С использованием фантомного моделирования провели проверку работы импульсных диксоновских последовательностей на различных томографах с целью количественного определения жировой фракции по соответствующим формулам. При оценке точности её количественного измерения установлена слабая линейная зависимость между полученными значениями и заданными концентрациями жировой фракции. Кроме того, для некоторых томографов выявлено статистически значимое смещение, превышающее 5%. Оценка воспроизводимости измерений показала различия в вариабельности концентрации жировой фракции как между разными моделями томографов, так и внутри одной.</p> <p><bold>Заключение. </bold>Полученные результаты подтверждают, что расчёт жировой фракции с использованием импульсных диксоновских последовательностей по соответствующим формулам необходимо осуществлять только после предварительного фантомного сканирования. Применение фантома обеспечивает надлежащий контроль качества и калибровку магнитно-резонансного томографа, делая точное количественное измерение жира более надёжным и широкодоступным.</p></trans-abstract><trans-abstract xml:lang="zh"><p>论证。磁共振成像获得的定量指标的准确性具有重要的科学和实际意义。对扫描参数的控制以及脂肪分数评估通用方法的标准化，是当前影像诊断工作中的关键任务之一。</p> <p>目的： 通过体模建模实验，评估采用标准DIXON脉冲序列进行脂肪分数定量测量的可行性。</p> <p>方法。开展一项多中心、横断面、非盲实验研究。为模拟不同脂肪浓度的物质，选择了 “油包水”型直接乳液。将乳液装入试管后置于专用圆柱形体模中。乳液由植物油混合物制成，脂肪分数范围为10–60%。在多家医疗机构使用不同厂商和磁场强度的磁共振成像设备（Optima MR450w 1.5T、MAGNETOM Skyra 3T、Ingenia 1.5T和Ingenia Achieva dStream 3.0T）进行扫描。依据通用计算公式，通过信号强度计算脂肪分数。对测得的脂肪分数浓度与设定值之间的线性关系进行了回归分析，同时采用F检验评估测量结果的变异性。</p> <p>结果。利用体模建模，在不同型号的磁共振成像设备上，对DIXON脉冲序列按相关公式进行脂肪分数定量测量的性能进行了验证。对脂肪分数定量测量准确性的评估结果显示，其测得值与设定浓度之间仅存在较弱的线性关系。此外，在部分磁共振成像设备中发现了具有统计学显著性的偏倚，幅度超过5%。测量重现性评估显示，不同型号磁共振成像设备之间以及同一型号设备内部的脂肪分数变异性存在差异。</p> <p>结论。研究结果证实，只有在进行体模扫描验证之后，方可依据相关公式使用DIXON脉冲序列进行脂肪分数的定量计算。体模的应用可实现对磁共振成像设备的质量控制与校准，从而使脂肪的定量测量更加可靠且具备更广泛的适用性。</p></trans-abstract><kwd-group xml:lang="en"><kwd>magnetic resonance imaging</kwd><kwd>fat fraction quantification</kwd><kwd>fat fraction</kwd><kwd>phantom</kwd><kwd>Dixon sequences</kwd><kwd>quality control</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>магнитно-резонансная томография</kwd><kwd>количественная оценка жировой фракции</kwd><kwd>фракция жира</kwd><kwd>фантом</kwd><kwd>диксоновские последовательности</kwd><kwd>контроль качества</kwd></kwd-group><kwd-group xml:lang="zh"><kwd>磁共振成像</kwd><kwd>脂肪分数定量评估</kwd><kwd>脂肪分数</kwd><kwd>体模</kwd><kwd>DIXON序列</kwd><kwd>质量控制</kwd></kwd-group><funding-group><award-group><funding-source><institution-wrap><institution xml:lang="en">Moscow City Health Department</institution></institution-wrap><institution-wrap><institution xml:lang="ru">Департамент здравоохранения города Москвы</institution></institution-wrap><institution-wrap><institution xml:lang="zh">Moscow City Health Department</institution></institution-wrap></funding-source><award-id>1196</award-id></award-group></funding-group></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>Outwater EK, Blasbalg R, Siegelman ES, Vala M. 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