Digital twins in urological oncology and surgery: A review of emerging applications

医学 转化式学习 限制 叙述性评论 数据共享 临床实习 数据科学 医学物理学 前提 功能(生物学) 钥匙(锁) 梅德林 计算机科学 斯科普斯 下尿路症状 病人护理 Web应用程序 系统回顾 多学科方法 新兴技术 信息基础设施 临床试验 生物医学技术
作者
David B. Olawade,Emmanuel O. Oisakede,Sandra Chinaza Fidelis,Muyiwa Ademola Ogunbona,Babajide David Makanjuola,Raphael Igbarumah Ayo Daniel
出处
期刊:Ejso [Elsevier BV]
卷期号:52 (6): 111849-111849
标识
DOI:10.1016/j.ejso.2026.111849
摘要

BACKGROUND: Digital twin technology represents a transformative approach in healthcare, creating virtual replicas of physical entities that enable real-time data integration, predictive modelling, and personalised treatment strategies. In urology, this emerging technology offers unprecedented opportunities to optimise patient care through simulation-based decision-making. AIM: This narrative review comprehensively examines current applications of digital twin technology in urology, evaluates its clinical utility across various urological conditions, and identifies key challenges limiting its widespread implementation. METHOD: A comprehensive search was conducted across PubMed, Web of Science, and Scopus databases for literature published between January 2020 and January 2026. Search terms included digital twin, virtual twin, urology, uro-oncology, prostate cancer, renal surgery, and bladder dysfunction. Studies focusing on the development, validation, and clinical implementation of digital twins in urological practice were included. RESULTS: Digital twin technology demonstrates significant potential in uro-oncology for treatment planning, surgical navigation, and disease progression monitoring. Key applications include patient-specific tumour growth simulation in prostate cancer, three-dimensional anatomical modelling for partial nephrectomy, and bladder function prediction in outlet obstruction. Integration with artificial intelligence enhances predictive accuracy and enables real-time surgical guidance. CONCLUSION: Digital twin technology represents a paradigm shift towards precision urology, though challenges in data integration, computational requirements, validation, and ethical considerations must be addressed before routine clinical implementation. Future developments should focus on standardisation, regulatory frameworks, and prospective clinical validation studies.
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