medvisМедицинская визуализацияMedical Visualization1607-07632408-9516RDS-Media Ltd.10.24835/1607-0763-2020-1-13-28medvis-850Research ArticleБРЮШНАЯ ПОЛОСТЬABDOMENНовый и простой онлайн-инструмент для дифференциации нейроэндокринных и солидных псевдопапиллярных опухолей поджелудочной железыA new and simple on-line tool to differentiate neuroendocrine and solid pseudopapillary pancreatic tumorshttps://orcid.org/0000-0002-0302-293XЧернинаВ. Ю.CherninaV. Yu.

ординатор отделения рентгенологии и магнитно-резонансных исследований с кабинетом ультразвуковой диагностики; младший научный сотрудник отдела развития качества радиологии

117997 Москва, ул. Большая Серпуховская, д. 27, Российская Федерация

125124 Москва, ул. Расковой, д. 16/26, Российская Федерация

Тел.: +7-964-636-99-92 

resident of the Diagnostic Rаdiology depаrtment; researcher of Department of quality of radiology

117997 Moscow, Russia, Bol'shaya Serpukhovskaia str., 27

125124, Moscow, Raskovoy str., 16/26, Russian Federation

Phone: +7-964- 636-99-92

chernina909@gmail.comhttps://orcid.org/0000-0002-2681-9378БлохинИ. А.BlokhinI. A.

117997 Москва, ул. Большая Серпуховская, д. 27, Российская Федерация

125124 Москва, ул. Расковой, д. 16/26, Российская Федерация 

graduate student of the Diagnostic Rаdiology depаrtment; researcher of Department of quality of radiology

117997 Moscow, Russia, Bol'shaya Serpukhovskaia str., 27

125124, Moscow, Raskovoy str., 16/26, Russian Federation

blokhin.ioann@gmail.comhttps://orcid.org/0000-0003-2583-0599МараповД. И.MarapovD. I.

Butlerova str., 49, Kazan, Russian Federation

damirov@list.ruhttps://orcid.org/0000-0003-4539-9943КригерА. Г.KrigerA. G.

27, Bol'shaya Serpukhovskaia str., Moscow, 117997, Russian Federation

kriger@ixv.ruhttps://orcid.org/0000-0001-6247-9481КалининД. В.KalininD. V.

27, Bol'shaya Serpukhovskaia str., Moscow, 117997, Russian Federation

dmitry.v.kalinin@gmail.comhttps://orcid.org/0000-0001-6054-4737ШимаВольфгангSchimaW.

Prim. Univ. Professor, Head of the Department of Diagnostic and Interventional Radiology 

Dornbacher Str. 20-28, Vienna, 1170, Austria

wolfgang.schima@khgh.athttps://orcid.org/0000-0002-9357-0998КармазановскийГ. Г.KarmazanovskyG. G.

 117997 Москва, ул. Островитянова, д. 1, Российская Федерация

сorresponding member of the Russiаn Асаdemy of Sсienсes, Dr. of Sci. (Med.), Professor, Heаd of the Diagnostic Rаdiology depаrtment; Professor of radiology department

27, Bol'shaya Serpukhovskaia str., Moscow, 117997, Russian Federation

house 1, Ostrivityanova str., Moscow, 117997, Russian Federation

karmazanovsky@yandex.ruФГБУ “Национальный медицинский исследовательский центр хирургии имени А.В. Вишневского” Минздрава России; ГБУЗ “Научно-практический клинический центр диагностики и телемедицинских технологий Департамента здравоохранения города Москвы”РоссияA.V. Vishnevsky National Medical Research Center of Surgery; Research and Practical Clinical Center of Diagnostics and Telemedicine Technologies, Department of Health Care of MoscowRussian FederationФедеральное государственное бюджетное образовательное учреждение высшего образования «Казанский государственный медицинский университет» Министерства здравоохранения Российской Федерации,РоссияKazan State Medical UniversityRussian FederationФедеральное государственное бюджетное учреждение «Национальный медицинский исследовательский центр хирургии имени А.В. Вишневского» Министерства здравоохранения Российской ФедерацииРоссияA.V. Vishnevsky National Medical Research Center of SurgeryRussian FederationБольница Goettlicher Heiland Krankenhaus, больница Barmherzige Schwestern Krankenhaus и больница Sankt Josef Krankenhaus, ВинценцгруппеАвстрияGoettlicher Heiland Krankenhaus, Barmherzige Schwestern Krankenhaus, and Sankt Josef Krankenhaus, VinzenzgruppeAustriaФедеральное государственное бюджетное учреждение «Национальный медицинский исследовательский центр хирургии имени А.В. Вишневского» Министерства здравоохранения Российской Федерации; ФГАОУ ВО “Российский национальный исследовательский медицинский университет имени Н.И. Пирогова” Минздрава РоссииРоссияA.V. Vishnevsky National Medical Research Center of Surgery; Pirogov Russian National Research Medical University of the Ministry of Health of RussiaRussian Federation202029042020241Медицинская визуализация 2020№11328Copyright © Чернина В.Ю., Блохин И.А., Марапов Д.И., Кригер А.Г., Калинин Д.В., Шима В., Кармазановский Г.Г., 20202020Чернина В.Ю., Блохин И.А., Марапов Д.И., Кригер А.Г., Калинин Д.В., Шима В., Кармазановский Г.Г.Chernina V.Y., Blokhin I.A., Marapov D.I., Kriger A.G., Kalinin D.V., Schima W., Karmazanovsky G.G.This work is licensed under a Creative Commons Attribution 4.0 License.https://medvis.vidar.ru/jour/article/view/850Цель исследования

Цель исследования: предложить удобный онлайн-калькулятор для количественной дифференциальной диагностики солидно-псевдопапиллярной опухоли (СППО) и нейроэндокринной неоплазии (НЭН) по данным МСКТ с внутривенным контрастированием.

Материал и методы

Материал и методы. Ретроспективное исследование включало 76 пациентов в период с января 2014 г. по март 2018 г. Окончательная группа из 62 пациентов была разделена на 2 подгруппы: СППО и НЭН. Два рентгенолога независимо друг от друга проанализировали данные МСКТ. Посредством бинарной логистической регрессии были выведены две многопараметрические прогностические модели для дифференциальной диагностики между гиперваскулярными НЭН и СППО, гиповаскулярными НЭН и СППО. Для оценки прогностического значения количественных характеристик и определения оптимальных пороговых значений для дифференциальной диагностики были использованы ROC-кривые.

Результаты

Результаты. 30 пациентов с НЭН составили 1-ю группу. 32 пациента с СППО составили 2-ю группу. Для I прогностической модели выбор порогового значения 34% дал максимальную чувствительность и специфичность 96,7% и 93,8% соответственно. Значения, превышающие пороговое значение, коррелируют с НЭН, равные и меньше порогового значения коррелируют с СППО. Для II прогностической модели выбор порогового значения в 50% дал максимальную чувствительность и специфичность 100% и 100%. Значения, превышающие пороговое значение, коррелируют с НЭН, равные и меньше порогового значения коррелируют с СППО.

Заключение

Заключение. Были разработаны две диагностические модели для дифференциальной диагностики между гиперваскулярными, гиповаскулярными НЭН и СППО. Модели позволяют провести дифференциальную диагностику с помощью оценки количественных значений плотности по данным МСКТ с внутривенным контрастированием. Был создан онлайн-калькулятор для рутинного использования в практике. Калькулятор доступен по ссылке http://pancreas-alculator.com.

Objectives

Objectives. To propose an multidetector computed tomography-based tool for quantitative differentiation between pancreatic neuroendocrine tumour (PNET) and solid pseudopapillary neoplasm (SPN) in clinical practice.

Methods

Methods. The retrospective study included 76 patients from January 2014 to March 2018. The final cohort of sixty-two patients was divided into two groups: PNET and SPN. Two radiologists independently analyzed MDCT data. We constructed two multivariable prognostic models for differential diagnosis between hypervascular PNETs and SPN, nonhypervascular PNETs and SPN via binary logistic regression. We used the receiver operating characteristic (ROC) curves to evaluate the prognostic value of any quantitative characteristics and to determine optimal cut- off values for differential diagnosis.

Results

Results. Thirty patients with PNET comprised the first group. Thirty-two patients with SPN comprised the second group. For the first prognostic model selecting a cut-off value of 34% yielded the maximum sensitivity and specificity of 96.7% and 93.8%, respectively. Values larger than the cut-off value correlated with PNET. For the second prognostic model, selecting a cut-off value of 50% yielded the maximum sensitivity and specificity of 100% and 100%. Values larger than the cut-off value correlated with PNET.

Conclusion

Conclusion. We developed two diagnostic models for differential diagnosis between hypervascular, nonhypervascular PNETs and SPN. The models allow for increased confidence in the diagnosis. Finally, we created an on-line calculator for easy routine use http://pancreas-calculator.com).

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The authors declare that there are no conflicts of interest present.