<?xml version="1.0" encoding="UTF-8"?>
<!DOCTYPE root>
<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="other" 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">678877</article-id><article-id pub-id-type="doi">10.17816/DD678877</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></subject></subj-group></article-categories><title-group><article-title xml:lang="en">MRI-texture analysis in prediction of muscle invasive bladder cancer</article-title><trans-title-group xml:lang="ru"><trans-title>Текстурный анализ магнитно-резонансных томограмм в прогнозировании мышеч-ной инвазии при раке мочевого пузыря</trans-title></trans-title-group><trans-title-group xml:lang="zh"><trans-title/></trans-title-group></title-group><contrib-group><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0001-8276-3594</contrib-id><contrib-id contrib-id-type="spin">6158-0090</contrib-id><name-alternatives><name xml:lang="en"><surname>Kovalenko</surname><given-names>Anastasia A.</given-names></name><name xml:lang="ru"><surname>Коваленко</surname><given-names>Анастасия Андреевна</given-names></name><name xml:lang="zh"><surname>Kovalenko</surname><given-names>Anastasia A.</given-names></name></name-alternatives><address><country country="RU">Russian Federation</country></address><bio xml:lang="ru"><p>врач-рентгенолог отделения рентгеновской диагностики и томографии</p></bio><email>nastua_kovalenko@mail.ru</email><xref ref-type="aff" rid="aff1"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-5649-2193</contrib-id><contrib-id contrib-id-type="spin">8449-6590</contrib-id><name-alternatives><name xml:lang="en"><surname>Sinitsyn</surname><given-names>Valentin E.</given-names></name><name xml:lang="ru"><surname>Синицын</surname><given-names>Валентин Евгеньевич</given-names></name><name xml:lang="zh"><surname>Sinitsyn</surname><given-names>Valentin E.</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>vsini@mail.ru</email><xref ref-type="aff" rid="aff2"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8391-2771</contrib-id><contrib-id contrib-id-type="spin">7730-7420</contrib-id><name-alternatives><name xml:lang="en"><surname>Petrovichev</surname><given-names>Victor</given-names></name><name xml:lang="ru"><surname>Петровичев</surname><given-names>Виктор Cергеевич</given-names></name><name xml:lang="zh"><surname></surname><given-names></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>petrovi4ev@gmail.com</email><xref ref-type="aff" rid="aff3"/></contrib><contrib contrib-type="author"><contrib-id contrib-id-type="orcid">https://orcid.org/0000-0002-8314-9307</contrib-id><contrib-id contrib-id-type="spin">2384-2473</contrib-id><name-alternatives><name xml:lang="en"><surname>Kovalenko</surname><given-names>Zahar</given-names></name><name xml:lang="ru"><surname>Коваленко</surname><given-names>Захар</given-names></name><name xml:lang="zh"><surname></surname><given-names></given-names></name></name-alternatives><email>zahar_kovalenko@mail.ru</email><xref ref-type="aff" rid="aff4"/></contrib></contrib-group><aff-alternatives id="aff1"><aff><institution xml:lang="en">Central Clinical Hospital of the Management Affair</institution></aff><aff><institution xml:lang="ru">Центральная клиническая больница с поликлиникой</institution></aff><aff><institution xml:lang="zh">Central Clinical Hospital of the Management Affair</institution></aff></aff-alternatives><aff-alternatives id="aff2"><aff><institution xml:lang="en">Lomonosov Moscow State University</institution></aff><aff><institution xml:lang="ru">Московский государственный университета имени М.В. Ломоносова</institution></aff><aff><institution xml:lang="zh">Lomonosov Moscow State University</institution></aff></aff-alternatives><aff-alternatives id="aff3"><aff><institution xml:lang="en">National Medical Research Centre “Treatment and Rehabilitation Centre”</institution></aff><aff><institution xml:lang="ru">Национальный медицинский исследовательский центр «Лечебно-реабилитационный центр»</institution></aff><aff><institution xml:lang="zh">National Medical Research Centre “Treatment and Rehabilitation Centre”</institution></aff></aff-alternatives><aff id="aff4"><institution></institution></aff><pub-date date-type="preprint" iso-8601-date="2026-06-05" publication-format="electronic"><day>05</day><month>06</month><year>2026</year></pub-date><volume>7</volume><issue>2</issue><issue-title xml:lang="ru"/><history><date date-type="received" iso-8601-date="2025-04-24"><day>24</day><month>04</month><year>2025</year></date><date date-type="accepted" iso-8601-date="2026-04-03"><day>03</day><month>04</month><year>2026</year></date></history><permissions><copyright-statement xml:lang="en">Copyright ©; , Eco-Vector</copyright-statement><copyright-statement xml:lang="ru">Copyright ©; , Эко-вектор</copyright-statement><copyright-statement xml:lang="zh">Copyright ©; , Eco-Vector</copyright-statement><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/678877">https://jdigitaldiagnostics.com/DD/article/view/678877</self-uri><abstract xml:lang="en"><p><bold>Background: </bold>Bladder cancer (VMC) is the most common disease among malignant neoplasms of the urinary system. The mean age at diagnosis is 73 years old, which suggests a high frequency of comorbidity and clinical risks in invasive diagnostic procedures. Infiltration of the muscle layer is present is a key factor in determining treatment. The factor affecting the overall quality of a histological study include quality of biopsy. <ext-link ext-link-type="uri" xlink:href="https://context.reverso.net/%D0%BF%D0%B5%D1%80%D0%B5%D0%B2%D0%BE%D0%B4/%D0%B0%D0%BD%D0%B3%D0%BB%D0%B8%D0%B9%D1%81%D0%BA%D0%B8%D0%B9-%D1%80%D1%83%D1%81%D1%81%D0%BA%D0%B8%D0%B9/In+view+of+the+above">In view of the above</ext-link>, the development of new radiology methods to predict muscle invasion in bladder cancer is still relevant. Nowadays, radiomics is an interesting field of research. Тexture analysis is a new analytical tool that allows to obtain information about the pathophysiological characteristics of tissues by computer analysis of medical images by specialized software. Тhe essence of radiomics is transformation of signal intensity distribution and pixel interrelations in the field of interest.</p> <p><bold>Aim: </bold>To study the possibility of MRI-texture analysis in distinguish between muscle-invasive and nonmuscle-invasive bladder cancer.</p> <p><bold>Material and methods: </bold>This retrospective multicenter study included 84 patients. We randomly choose 80% samples as training set and 20% as test data. Standart MRI exams were performed with intravenous contrast agents using a 1.5/3T scanners. All images were normalized prior to the radiomics analysis, using spatial resampling with fixed voxel size of 1х1х1 mm. The radiomic features were extracted from three pulse sequences (T2, DWI b=800/1000 s/mm<sup>2</sup>, ADC). One radiologist segmented the lesion on the slice with maximum diameter (2D-ROI).</p> <p><bold>Results: </bold>A сlinical-based model was based on 6 parameters - VI-RADS_4-5, grade, maximum tumor size, age, VI-RADS_1-2, number of tumors. Despite satisfactory specificity (78.6%) and accuracy (72.2%) in the test data, the sensitivity of the model was only 50%. A radiomics-based model was based on 4 texture features and yielded higher values of accuracy (77.8%) and sensitivity (75.0%) in muscle invasive prediction compared to the clinical model.</p> <p><bold>Conclusion: </bold>MRI-based texture analysis could potentially be used as a radiological method in discrimination of muscle invasive bladder cancer.</p></abstract><trans-abstract xml:lang="ru"><p><bold>Актуальность:</bold> Рак мочевого пузыря (РМП) – наиболее распространенное заболевание среди злокачественных новообразований мочевыделительной системы. По данным литературы, средний возраст постановки диагноза соответствует 73 годам, что предполагает высокую частоту коморбидной патологии и возможные клинические риски при применении инвазивных диагностических процедур.</p> <p>Инвазия опухоли в мышечный слой является важным фактором, определяющим лечебную тактику. На информативности гистологического исследования, применяемого с целью выявления мышечной инвазии, сказывается целый ряд факторов, связанных прежде всего с качеством забора материала.</p> <p> В связи с вышеуказанным, сохраняет свою актуальность разработка и внедрение новых маркеров, в том числе на основе современных методов лучевой диагностики, уточняющих Т-стадию и прогноз РМП. С этих позиций активно обсуждаются возможности использования текстурного анализа магнитно-резонансных томограмм (МРТ).</p> <p>Текстурный анализ - это новый аналитический инструмент, позволяющий путем компьютерного анализа медицинских изображений c помощью специализированного программного обеспечения получать информацию о патофизиологических особенностях тканей. Суть текстурного анализа сводится к математическому преобразованию распределения интенсивности сигналов и взаимосвязей пикселей в области интереса.</p> <p><bold>Цель: </bold>изучить возможность текстурного анализа магнитно-резонансных томограмм в дифференциальной диагностике мышечноинвазивных и мышечнонеинвазивных форм РМП.</p> <p><bold>Материал и методы:</bold> В ретроспективное многоцентровое исследование включено 84 пациента. Для реализации цели исследования обследованные были разделены случайным образом на обучающую и тестовую выборки в соотношении 80:20. Проанализированы МРТ органов малого таза, выполненные с внутривенным контрастированием по стандартному протоколу на томографах с индукцией магнитного поля 1,5/3 Тл. Для всех изображений была применена предварительная обработка, заключающаяся в использовании заданного размера вокселя 1х1х1 мм. Выполнялся текстурный анализ трех импульсных последовательностей (Т2-ВИ, ДВИ с b-фактором 800/1000 c/мм<sup>2</sup>, ИКД). Сегментация изображений проводилась с использованием двухмерной области интереса (2D ROI).</p> <p><bold>Результаты: </bold>В клиническую модель прогноза наличия мышечной инвазии вошло 6 переменных – VI-RADS_4-5, grade, максимальный размер опухоли, возраст, VI-RADS_1-2, количество опухолей. На тестовой выборке при удовлетворительных показателях специфичности (78,6%) и точности (72,2%) чувствительность модели составляла только 50%. При пошаговом отборе с включением показателей в Lasso-регрессию в радиомическую модель отобрано 4 текстурных предиктора мышечной инвазии. Показано, что радиомическая модель обладает большей точностью (77,8%) и чувствительностью (75,0%) в выявлении мышечной инвазии в сравнении с клинической моделью.</p> <p><bold>Заключение:</bold> Текстурный анализ МРТ может использоваться для дифференциальной диагностики мышечноинвазивных и мышечнонеинвазивных форм РМП.</p></trans-abstract><trans-abstract xml:lang="zh"><p/></trans-abstract><kwd-group xml:lang="en"><kwd>radiomics, texture analysis, bladder cancer, MRI</kwd></kwd-group><kwd-group xml:lang="ru"><kwd>радиомика (radiomics), текстурный анализ (texture analysis), рак мочевого пузыря (bladder cancer), МРТ (MRI)</kwd></kwd-group><funding-group/></article-meta></front><body></body><back><ref-list><ref id="B1"><label>1.</label><mixed-citation>1.	Cancer Today (n.d.). http://gco.iarc.fr/today/home. Accessed April 13, 2022</mixed-citation></ref><ref id="B2"><label>2.</label><citation-alternatives><mixed-citation xml:lang="en">2.	Halaseh SA, Halaseh S, Alali Y, Ashour ME, Alharayzah MJ. A Review of the Etiol-ogy and Epidemiology of Bladder Cancer: All You Need To Know. Cureus. 2022;14(7):e27330. doi:10.7759/cureus.27330</mixed-citation><mixed-citation xml:lang="ru">2.	Halaseh S.A., Halaseh S., Alali Y., et al. A Review of the Etiology and Epidemiology of Bladder Cancer: All You Need To Know // Cureus. 2022.Vol. 14, N. 7. doi: 10.7759/cureus.27330</mixed-citation></citation-alternatives></ref><ref id="B3"><label>3.</label><citation-alternatives><mixed-citation xml:lang="en">3.	Richters A, Aben KKH, Kiemeney LALM. The global burden of urinary bladder can-cer: an update. World J Urol. 2020;38(8):1895-1904. doi:10.1007/s00345-019-02984-4</mixed-citation><mixed-citation xml:lang="ru">3.	Richters A., Aben K.K.H., Kiemeney L.A.L.M. The global burden of urinary bladder cancer: an update // World J Urol. 2020.Vol. 38, N. 8. doi: 10.1007/s00345-019-02984-4</mixed-citation></citation-alternatives></ref><ref id="B4"><label>4.</label><citation-alternatives><mixed-citation xml:lang="en">4.	Zhang Y, Rumgay H, Li M, Yu H, Pan H, Ni J. The global landscape of bladder can-cer incidence and mortality in 2020 and projections to 2040. J Glob Health. 2023;13:04109. doi:10.7189/jogh.13.04109</mixed-citation><mixed-citation xml:lang="ru">4.	Zhang Y., Rumgay H., Li M., Yu H., et al. The global landscape of bladder cancer in-cidence and mortality in 2020 and projections to 2040 // J Glob Health. 2023. Vol. 13. doi: 10.7189/jogh.13.04109</mixed-citation></citation-alternatives></ref><ref id="B5"><label>5.</label><citation-alternatives><mixed-citation xml:lang="en">5.	Saginala K, Barsouk A, Aluru JS, Rawla P, Padala SA, Barsouk A. Epidemiology of Bladder Cancer. Med Sci (Basel). 2020;8(1):15. doi:10.3390/medsci8010015</mixed-citation><mixed-citation xml:lang="ru">5.	Saginala K., Barsouk A., Aluru J.S., et al. Epidemiology of Bladder Cancer // Med Sci (Basel). 2020. Vol. 8, N. 1. doi: 10.3390/medsci8010015</mixed-citation></citation-alternatives></ref><ref id="B6"><label>6.</label><citation-alternatives><mixed-citation xml:lang="en">6.	Tempo J, Yiu TW, Ischia J, Bolton D, O'Callaghan M. Global changes in bladder cancer mortality in the elderly. Cancer Epidemiol. 2023;82:102294. doi:10.1016/j.canep.2022.102294</mixed-citation><mixed-citation xml:lang="ru">6.	Tempo J., Yiu T.W., Ischia J., еt al. Global changes in bladder cancer mortality in the elderly // Cancer Epidemiol. 2023. doi: 10.1016/j.canep.2022.102294</mixed-citation></citation-alternatives></ref><ref id="B7"><label>7.</label><citation-alternatives><mixed-citation xml:lang="en">7.	Soukup V, Čapoun O, Cohen D, et al. Prognostic Performance and Reproducibility of the 1973 and 2004/2016 World Health Organization Grading Classification Systems in Non-muscle-invasive Bladder Cancer: A European Association of Urology Non-muscle Invasive Bladder Cancer Guidelines Panel Systematic Review. Eur Urol. 2017;72(5):801-813. doi:10.1016/j.eururo.2017.04.015</mixed-citation><mixed-citation xml:lang="ru">7.	Soukup V., Čapoun O., Cohen D., et al. Prognostic Performance and Reproducibility of the 1973 and 2004/2016 World Health Organization Grading Classification Sys-tems in Non-muscle-invasive Bladder Cancer: A European Association of Urology Non-muscle Invasive Bladder Cancer Guidelines Panel Systematic Review // Eur Urol. 2017. Vol. 72, N. 5. doi: 10.1016/j.eururo.2017.04.015</mixed-citation></citation-alternatives></ref><ref id="B8"><label>8.</label><citation-alternatives><mixed-citation xml:lang="en">8.	The All-Russian public organization «Russian Society of Oncourologists». The Russian national Union «Association of oncologists of Russia». The All-Russian public organization «Russian Society of Urologists». The All-Russian public organi-zation «Russian Society of Clinical Oncology». Clinical recommendations for the diagnosis and treatment of patients with bladder cancer, 2023</mixed-citation><mixed-citation xml:lang="ru">8.	Общероссийская общественная организация «Российское общество онкоуроло-гов». Общероссийский национальный союз «Ассоциация онкологов России». Общероссийская общественная организация «Российское общество урологов». Общероссийская общественная организация «Российское общество клиниче-ской онкологии». Клинические рекомендации Клинические рекомендации Минздрава России: Рак мочевого пузыря, 2023</mixed-citation></citation-alternatives></ref><ref id="B9"><label>9.</label><citation-alternatives><mixed-citation xml:lang="en">9.	Ark JT, Keegan KA, Barocas DA, et al. Incidence and predictors of understaging in patients with clinical T1 urothelial carcinoma undergoing radical cystectomy. BJU Int. 2014;113(6):894-899. doi:10.1111/bju.12245</mixed-citation><mixed-citation xml:lang="ru">9.	Ark J.T, Keegan K.A., Barocas D.A., et al. Incidence and predictors of understaging in patients with clinical T1 urothelial carcinoma undergoing radical cystectomy // BJU Int. 2014. Vol. 113, N. 6. doi: 10.1111/bju.12245</mixed-citation></citation-alternatives></ref><ref id="B10"><label>10.</label><citation-alternatives><mixed-citation xml:lang="en">10.	Rolevich AI. Impact of a surgeon on the relapse-free survival of patients with non-muscle-invasive bladder cancer. Cancer Urology. 2016;12(2):40-52. doi: 10.17650/1726-9776-2016-12-2-40-52</mixed-citation><mixed-citation xml:lang="ru">10.	Ролевич А.И. Влияние хирурга на безрецидивную выживаемость пациентов, страдающих раком мочевого пузыря без мышечной инвазии // Онкоурология. 2016. Vol. 12. N. 2. doi: 10.17650/1726-9776-2016-12-2-40-52</mixed-citation></citation-alternatives></ref><ref id="B11"><label>11.</label><citation-alternatives><mixed-citation xml:lang="en">11.	Lai AL, Law YM. VI-RADS in bladder cancer: Overview, pearls and pitfalls. Eur J Radiol. 2023;160:110666. doi:10.1016/j.ejrad.2022.110666</mixed-citation><mixed-citation xml:lang="ru">11.	Lai A.L., Law Y.M. VI-RADS in bladder cancer: Overview, pearls and pitfalls // Eur J Radiol. 2023. doi: 10.1016/j.ejrad.2022.110666</mixed-citation></citation-alternatives></ref><ref id="B12"><label>12.</label><citation-alternatives><mixed-citation xml:lang="en">12.	Mayerhoefer ME, Materka A, Langs G, et al. Introduction to Radiomics. J Nucl Med. 2020;61(4):488-495. doi:10.2967/jnumed.118.222893</mixed-citation><mixed-citation xml:lang="ru">12.	Mayerhoefer M.E, Materka A., Langs G., et al. Introduction to Radiomics // J Nucl Med. 2020. Vol. 61, N. 4. doi: 10.2967/jnumed.118.222893</mixed-citation></citation-alternatives></ref><ref id="B13"><label>13.</label><citation-alternatives><mixed-citation xml:lang="en">13.	van Timmeren JE, Cester D, Tanadini-Lang S, et al. Radiomics in medical imaging-"how-to" guide and critical reflection. Insights Imaging.2020; 11(1):91. doi:10.1186/s13244-020-00887-2</mixed-citation><mixed-citation xml:lang="ru">13.	van Timmeren J.E., Cester D., Tanadini-Lang S., et al. Radiomics in medical imag-ing-"how-to" guide and critical reflection // Insights Imaging. 2020. Vol.11. N 1. P 91. doi:10.1186/s13244-020-00887-2</mixed-citation></citation-alternatives></ref><ref id="B14"><label>14.</label><mixed-citation>14.	Lim C.S, Tirumani S., van der Pol C.B., et al. Use of Quantitative T2-Weighted and Apparent Diffusion Coefficient Texture Features of Bladder Cancer and Extravesical Fat for Local Tumor Staging After Transurethral Resection // AJR Am J Roentgenol. 2019. Vol. 212. N 5. P. 1060-1069. doi:10.2214/AJR.18.20718</mixed-citation></ref><ref id="B15"><label>15.</label><citation-alternatives><mixed-citation xml:lang="en">15.	Nioche C, Orlhac F, Boughdad S, et al. LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characteriza-tion of Tumor Heterogeneity. Cancer Res. 2018;78(16):4786-4789. doi:10.1158/0008-5472.CAN-18-0125</mixed-citation><mixed-citation xml:lang="ru">15.	Nioche C., Orlhac F., Boughdad S., et al. LIFEx: A Freeware for Radiomic Feature Calculation in Multimodality Imaging to Accelerate Advances in the Characteriza-tion of Tumor Heterogeneity. Cancer Res. 2018. Vol. 78, N. 16. doi: 10.1158/0008-5472.CAN-18-0125</mixed-citation></citation-alternatives></ref><ref id="B16"><label>16.</label><citation-alternatives><mixed-citation xml:lang="en">16.	Xu X, Liu Y, Zhang X, et al. Preoperative prediction of muscular invasiveness of bladder cancer with radiomic features on conventional MRI and its high-order de-rivative maps // AbdomRadiol (NY). 2017. 42(7):1896-1905. doi:10.1007/s00261-017-1079-6</mixed-citation><mixed-citation xml:lang="ru">16.	Xu X., Liu Y., Zhang X., et al. Preoperative prediction of muscular invasiveness of bladder cancer with radiomic features on conventional MRI and its high-order de-rivative maps // AbdomRadiol (NY). 2017. Vol. 42. N 7. P. 1896-1905. doi:10.1007/s00261-017-1079-6</mixed-citation></citation-alternatives></ref><ref id="B17"><label>17.</label><citation-alternatives><mixed-citation xml:lang="en">17.	Razik A, Das CJ, Sharma R,et sl.Utility of first order MRI-Texture analysis parame-ters in the prediction of histologic grade and muscle invasion in urinary bladder can-cer: a preliminary study. Br J Radiol.2021.94(1122). doi: 10.1259/bjr.20201114</mixed-citation><mixed-citation xml:lang="ru">17.	Razik A., Das C.J., Sharma R.,etsl.Utility of first order MRI-Texture analysis pa-rameters in the prediction of histologic grade and muscle invasion in urinary bladder cancer: a preliminary study // Br J Radiol. 2021. Vol. 94. N 1122. doi: 10.1259/bjr.20201114</mixed-citation></citation-alternatives></ref></ref-list></back></article>
