Digital DiagnosticsDigital DiagnosticsDigital DiagnosticsDigital Diagnostics2712-84902712-8962Eco-Vector62324010.17816/DD623240Systematic reviewsСистематические обзоры系统评价Review ArticlePriority radiomic parameters for computed tomography of head and neck malignancies: A systematic reviewПриоритетные параметры радиомического анализа для компьютерной томографии при злокачественных новообразованиях головы и шеи: систематический обзор头颈部恶性肿瘤计算机断层扫描的优先放射组学分析参数：系统综述https://orcid.org/0000-0002-0208-52184458-5608VasilevYuriy A.ВасильевЮрий АлександровичVasilevYuriy A.
Russian Federation

MD, Cand. Sci. (Medicine)

канд. мед. наук

MD, Cand. Sci. (Medicine)

npcmr@zdrav.mos.ruhttps://orcid.org/0000-0001-8886-36846135-4872NanovaOlga G.НановаОльга ГеннадьевнаNanovaOlga G.
Russian Federation

Cand. Sci. (Biology)

канд. биол. наук

Cand. Sci. (Biology)

NanovaOG@zdrav.mos.ruhttps://orcid.org/0000-0002-2681-93783306-1387BlokhinIvan A.БлохинИван АндреевичBlokhinIvan A.
Russian Federation
i.blokhin@npcmr.ruhttps://orcid.org/0000-0002-9661-02548592-0558ReshetnikovRoman V.РешетниковРоман ВладимировичReshetnikovRoman V.
Russian Federation

Cand. Sci. (Physics and Mathematics)

канд. физ.-мат. наук

Cand. Sci. (Physics and Mathematics)

reshetnikov@fbb.msu.ruhttps://orcid.org/0000-0002-2990-77363602-7120VladzymyrskyyAnton V.ВладзимирскийАнтон ВячеславовичVladzymyrskyyAnton V.
Russian Federation

MD, Dr. Sci. (Medicine), Professor

д-р мед. наук, профессор

MD, Dr. Sci. (Medicine), Professor

npcmr@zdrav.mos.ruhttps://orcid.org/0000-0002-0245-44318948-6152OmelyanskayaOlga V.ОмелянскаяОльга ВасильевнаOmelyanskayaOlga V.
Russian Federation
o.omelyanskaya@npcmr.ruResearch and Practical Clinical Center for Diagnostics and Telemedicine TechnologiesНаучно-практический клинический центр диагностики и телемедицинских технологийResearch and Practical Clinical Center for Diagnostics and Telemedicine Technologies2901202420092024522552681311202304122023Copyright ©; 2024, Eco-VectorCopyright ©; 2024, Эко-векторCopyright ©; 2024, Eco-Vector2024Eco-VectorЭко-векторEco-Vectorhttps://creativecommons.org/licenses/by-nc-nd/4.0https://jdigitaldiagnostics.com/DD/article/view/623240

BACKGROUND: Radiomics is the newest and most promising direction in modern radiographic diagnostics. The number of head and neck cancer studies employing radiomics is increasing annually. A systematic review of recent publications (2021–2023) on computed tomography (CT) of head and neck malignancies was performed.

AIM: To present systematized data on parameters for radiomic analysis for head and neck malignancies identified by CT data.

MATERIALS AND METHODS: The literature search was carried out in PubMed. The basic characteristics of the selected articles were extracted, and their quality was assessed using RQS 2.0 and the modified QUADAS-CAD questionnaire. The reproducibility level of radiomic parameters selected for predictive models in different studies was assessed. Eleven articles were selected for the review. In most cases, a high risk of systematic error associated with data imbalance in terms of demographic parameters and level of pathologies was noted.

RESULTS: The range of RQS 2.0 scores for the included articles varied from 19.44% to 50.00% of the maximum possible score. The decreasing research quality was mainly caused by the lack of external result validation (73% of the analyzed articles) and data accessibility and transparency (82%). Inter-study reproducibility of radiomic parameters was low owing to the wide variety of techniques used for image acquisition, image post-processing, extraction, and statistical processing of radiomic parameters.

CONCLUSION: A set of stable radiomic parameters must be successfully introduced into clinical practice. The standardization of radiomics method and creation of an open radiomics database are necessary for this purpose.

Обоснование. Радиомика — новейшее и многообещающее направление современной лучевой диагностики. Число исследований злокачественных новообразований головы и шеи с помощью этого метода увеличивается с каждым годом. Мы провели систематический обзор новейших публикаций (2021–2023) по злокачественным новообразованиям головы и шеи, выполненным на основе компьютерной томографии.

Цель — систематизация данных по используемым параметрам радиомического анализа при раке головы и шеи, выявленным по данным компьютерной томографии.

Материалы и методы. Поиск статей осуществлялся в базе PubMed. Произведены извлечение базовых характеристик отобранных статей и оценка их качества по RQS 2.0 и модифицированному опроснику QUADAS-CAD. Оценили уровень воспроизводимости радиомических параметров, отобранных для прогностических моделей, в разных исследованиях. Для обзора отобрано 11 статей. В большинстве случаев отмечался высокий риск систематической ошибки, связанный с несбалансированностью выборки по демографическим параметрам и уровню патологий.

Результаты. При оценке качества радиомики диапазон баллов для исследованных статей изменяется от 19,44% до 50,00% максимально возможной суммы. Основные проблемы, влекущие за собой снижение качества исследований, обусловлены отсутствием внешней валидации результатов (73% проанализированных статей), а также недоступностью или непрозрачностью исследовательских данных (82%). Воспроизводимость радиомических параметров между исследованиями низкая из-за большого разнообразия используемых методик получения и постобработки изображений, а также извлечения и статистической обработки радиомических параметров.

Заключение. Обсуждается необходимость выделения базового блока устойчивых радиомических параметров для внедрения метода в клиническую практику, что возможно сделать только при стандартизации методов радиомики и создания открытой базы радиомических данных.

论证。放射组学是现代放射治疗诊断中最新、最有前途的领域。使用这种方法对头颈部恶性肿瘤进行检查的数量每年都在增加。我们对基于计算机断层扫描的头颈部恶性肿瘤最新出版物（2021-2023 年）进行了系统综述。

目的是系统整理通过计算机断层扫描检测到的头颈部癌症的放射组学分析参数数据。

材料和方法。这些文章在 PubMed 数据库中进行了检索。我们提取了所选文章的基线特征，并使用 RQS 2.0 和修改后的 QUADAS-CAD 问卷对其质量进行了评估。我们评估了不同研究中预后模型所选放射组学参数的可重复性水平。我们选择了 11 篇文章进行审查。在大多数情况下，由于人口统计参数和病理学水平的取样不平衡，系统误差的风险很高。

结果。在评估放射组学的质量时，所分析文章的得分范围从最高可能得分的 19.44% 到 50.00% 不等。导致研究质量下降的主要问题是研究结果缺乏外部验证（占所分析文章的 73%），以及研究数据无法获取或缺乏透明度（占 82%）。由于所使用的图像采集和后处理技术种类繁多，以及对放射组学参数的提取和统计处理，不同研究之间放射组学参数的可重复性很低。

结论。讨论将该方法引入临床实践的基本稳定放射组学参数分配的必要性，这只有在放射组学方法标准化和建立开放的放射组学数据库的情况下才能实现。

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