medsovetМедицинский СоветMeditsinskiy sovet = Medical Council2079-701X2658-5790REMEDIUM GROUP Ltd.10.21518/ms2025-116medsovet-9086Research ArticleТРУДНЫЙ ДИАГНОЗDIFFICULT DIAGNOSISПерспективное направление автоматизации выявления врожденных аномалий внутреннего ухаA promising direction of automating the detection of congenital anomalies of the inner earhttps://orcid.org/0000-0003-3309-4683ПопадюкВ. И.PopadyukV. I.

Попадюк Валентин Иванович - д.м.н., профессор, заведующий кафедрой оториноларингологии медицинского института.

117198, Москва, ул. Миклухо-Маклая, д. 6

Valentin I. Popadyuk - Dr. Sci. (Med.), Professor, Head of the Department of Otorhinolaryngology Medical Institute, RUDN University.

6, Miklukho-Maklai St., Moscow, 117198

lorval04@mail.ruhttps://orcid.org/0000-0002-2790-7900ДиабХ. М.DiabH. M.

Диаб Хассан Мохамад Али - д.м.н., главный научный сотрудник научно-клинического отдела патологии уха и основания черепа, заместитель директора по международной деятельности.

123182, Москва, Волоколамское шоссе, д. 30, к. 2

Hassan M. Diab - Dr. Sci. (Med.), Chief Researcher of the Scientific and Clinical Department of Ear and Skull Base Pathology, Deputy Director for International Activities, The National Medical Research Center for Otorhinolaryngology of the Federal Medico-Biological Agency of Russia.

30, Bldg. 2, Volokolamskoe Shosse, Moscow, 123182

hasandiab@mail.ruhttps://orcid.org/0000-0002-3608-2744ПащининаО. А.PashchininaO. A.

Пащинина Ольга Александровна - к.м.н., руководитель научно-клинического отдела патологии уха и основания черепа, врач-оториноларинголог.

123182, Москва, Волоколамское шоссе, д. 30, к. 2

Olga A. Pashchinina - Cand. Sci. (Med.), Branch Manager of Clinical Research Department of Diseases of the Ear and Skull Base, The National Medical Research Center for Otorhinolaryngology of the Federal Medico-Biological Agency of Russia.

30, Bldg. 2, Volokolamskoe Shosse, Moscow, 123182

olgaP83@mail.ruhttps://orcid.org/0000-0002-9081-6016МихалевичА. Е.MikhalevichA. E.

Михалевич Антон Евгеньевич - к.м.н., старший научный сотрудник отдела патологии уха и основания черепа.

123182, Москва, Волоколамское шоссе, д. 30, к. 2

Anton E. Mikhalevich - Cand. Sci. (Med.), Senior Researcher, The National Medical Research Center for Otorhinolaryngology of the Federal Medico-Biological Agency of Russia.

30, Bldg. 2, Volokolamskoe Shosse, Moscow, 123182

MikhalevichAE@mail.ruhttps://orcid.org/0009-0004-5778-7446ХаририМ.HaririM.

Харири Мостаафа - аспирант кафедры оториноларингологии медицинского института.

117198, Москва, ул. Миклухо-Маклая, д. 6

Mostafa Hariri - Postgraduate Student of the Department of Otorhinolaryngology at the Medical Institute, RUDN University.

6, Miklukho-Maklai St., Moscow, 117198

hariri.mostafa@mail.ruhttps://orcid.org/0009-0001-9884-4070ШукурянМ. А.ShukuryanM. A.

Шукурян Микаел Артурович - врач-оториноларинголог, младший научный сотрудник.

0025, Ереван, ул. Корюна, д. 2

Mikayel A. Shukuryan - Otolaryngologist, Junior Research Fellow, Yerevan State Medical University after Mkhitar Herasti.

2, Koryun St., Yerevan, 0025

mikashukuryan@yahoo.comhttps://orcid.org/0000-0001-6966-8656КириченкоИ. М.KirichenkoI. M.

Кириченко Ирина Михайловна - д.м.н, профессор кафедры оториноларингологии медицинского института.

117198, Москва, ул. Миклухо-Маклая, д. 6

Irina M. Kirichenko - Dr. Sci. (Med.), Professor of the Department of Otorhinolaryngology Medical Institute, RUDN University.

6, Miklukho-Maklai St., Moscow, 117198

loririna@yandex.ruРоссийский университет дружбы народов имени Патриса ЛумумбыРоссияRUDN UniversityRussian FederationНациональный медицинский исследовательский центр оториноларингологии Федерального медико-биологического агентстваРоссияThe National Medical Research Center for Otorhinolaryngology of the Federal Medico-Biological Agency of RussiaRussian FederationЕреванский государственный медицинский университет имени Мхитара ГерациАрменияYerevan State Medical University after Mkhitar HerastiArmenia20252405202507163176Copyright © Попадюк В.И., Диаб Х.М., Пащинина О.А., Михалевич А.Е., Харири М., Шукурян М.А., Кириченко И.М., 20252025Попадюк В.И., Диаб Х.М., Пащинина О.А., Михалевич А.Е., Харири М., Шукурян М.А., Кириченко И.М.Popadyuk V.I., Diab H.M., Pashchinina O.A., Mikhalevich A.E., Hariri M., Shukuryan M.A., Kirichenko I.M.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://www.med-sovet.pro/jour/article/view/9086Введение

Введение. По данным Всемирной организации здравоохранения, во всем мире насчитывается около 1,5 млрд людей с нарушением слуха, из которых 430 млн имеют тяжелые нарушения слуховой функции. Потеря слуха поражает 1–2 из каждых 1000 новорожденных. Выявление аномалий внутреннего уха является трудной задачей даже для опытных специалистов. Цель. Разработать полностью автоматизированную последовательность команд с конвейерной передачей данных для классификации дефектов внутреннего уха и обработка КТ-снимков аномалий внутреннего уха пациентов с использованием данного программного обеспечения.

Материалы и методы

Материалы и методы. В данном исследовании представлен первый автоматизированный метод классификации врожденных аномалий внутреннего уха. В экспериментальной части разработана трехмерная сеть строения улитки для 346 стандартных и 121 атипичных структур с помощью общей схемы сегментации, обученной исключительно на нормальной анатомии. В ФГБУ НМИЦО оториноларингологии ФМБА России за период с 2018 по 2024 г. проведено обследование 98 пациентов из них было 54 (55,5%) мальчика и 44 (44,5%) девочки в возрасте от 8 мес. до 6 лет (средний возраст 2,5 года) c аномалиями развития внутреннего уха и с тяжелыми нарушениями слуха, которым в последующем проводилась кохлеарная имплантация.

Результаты

Результаты. Получена обобщенная средняя точность – 77% по 7 различным патологическим подгруппам среди нарушений в сравнении с профессиональным диагнозом отохирурга, специализирующегося на врожденных дефектах внутреннего уха. Обсуждение. Несмотря на то что автоматическое обнаружение различных типов аномалий внутреннего уха по сути является задачей классификации, из-за отсутствия репрезентативных и разнородных наборов данных, которые точно представляют все разнообразие этих врожденных дефектов развития, приходится использовать параметрический подход (определение ориентиров). Этот метод используется при стандартных данных для получения неявной информации, которая может потенциально обнаружить аномалию в строении неконтролируемым образом.

Выводы

Выводы. Предложен первый метод автоматического определения врожденных аномалий развития внутреннего уха и продемонстрировано, что применение 3D-информации о форме улитки, извлеченной с помощью модели, обученной исключительно на стандартных структурах, достаточно для классификации дефектов развития, что имеет принципиальное значение для клинического применения.

Introduction

Introduction. Hearing loss affects 1 to 2 out of every 1000 newborns. Detecting anomalies in the inner ear is a challenging task even for experienced specialists.

Aim

Aim. To develop a fully automated sequence of commands with a pipeline data transfer for the classification of inner ear defects and processing of CT images of inner ear anomalies in patients using this program data.

Materials and мethods

Materials and мethods. This study presents the first automated method for classifying congenital inner ear anomalies. In the experimental part, a 3D cochlear structure network was developed for 346 standard and 121 atypical structures using a common segmentation scheme trained exclusively on normal anatomy. From 2018 to 2024, 98 patients were examined at the Federal State Budgetary Institution of Science, Otolaryngology, Federal Medical and Biological Agency of Russia, including 54 (55.5%) boys and 44 (44.5%) girls aged from 8 months to 6 years (average age 2.5 years) with inner ear developmental anomalies and severe hearing impairments, who subsequently underwent cochlear implantation.

Results

Results. We achieved a generalized average accuracy of 77% across 7 different pathological subgroups of disorders compared to the professional diagnosis of an otolaryngologist specializing in congenital inner ear defects.

Discussion

Discussion. Although automatic detection of various types of inner ear anomalies is essentially a classification task, the lack of representative and heterogeneous datasets that accurately represent the diversity of these congenital developmental defects necessitates the use of a parametric approach. This method is employed with standard data to extract implicit information that could potentially detect anomalies in a non-controlled manner.

Conclusions

Conclusions. We proposed the first method for the automatic detection of congenital anomalies of the inner ear and demonstrated that the use of 3D information about the shape of the cochlea, extracted using a model trained exclusively on standard structures, is sufficient for classifying developmental defects.

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