Использование искусственного интеллекта в цистоскопической диагностике рака мочевого пузыря

Введение. На современном этапе развития науки и техники происходят активная разработка и постепенное внедрение в систему здравоохранения технологий искусственного интеллекта (ИИ).
Цель работы – обзор литературы для оценки диагностического значения ИИ в выявлении рака мочевого пузыря на этапе цистоскопии.
Материалы и методы. Проведен библиографический поиск статей в базах данных Medline и Embase с использованием ключевых слов “artificial intelligence”, “cystoscopy”, “TURBT”.
Результаты. Автоматизированная обработка изображений на основе ИИ может повысить точность диагностики рака при цистоскопии. По данным представленных исследований чувствительность цистоскопии при использовании ИИ достигает 89,7–95,4 %, специфичность – 87,8–98,6 %, что превосходит диагностические возможности стандартной цистоскопии в белом свете, чувствительность и специфичность которой составляют примерно 60 и 70 % соответственно. Несмотря на многообещающие результаты данных исследований, современная наука находится лишь на стадии разработки и оценки производительности различных методов ИИ, используемых для анализа цистоскопических изображений. На сегодняшний день рано говорить о внедрении и широком применении данных технологий в здравоохранении, так как отсутствуют проспективные клинические исследования оценки эффективности цистоскопической диагностики и трансуретральной резекции рака мочевого пузыря в сопровождении ИИ.
Заключение. Цистоскопия на основе ИИ – перспективное направление (согласно немногочисленным данным литературы) в вопросе повышения качества медицинской помощи при раке мочевого пузыря. Для усовершенствования диагностических возможностей ИИ и внедрения в клиническую практику полученных технологических данных необходимо проведение дальнейших исследований.

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