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

Olawade, David; Oisakede, Emmanuel O.; Fidelis, Sandra Chinaza; Ogunbona, Muyiwa Ademola; Makanjuola, Babajide David; Daniel, Raphael Igbarumah Ayo

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

Olawade, David ORCID: https://orcid.org/0000-0003-0188-9836, Oisakede, Emmanuel O. ORCID: https://orcid.org/0009-0000-5791-301X, Fidelis, Sandra Chinaza, Ogunbona, Muyiwa Ademola ORCID: https://orcid.org/0009-0001-8384-7455, Makanjuola, Babajide David and Daniel, Raphael Igbarumah Ayo (2026) Digital twins in urological oncology and surgery: A review of emerging applications. European Journal of Surgical Oncology, 52 (6). p. 111849.

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Official URL: https://doi.org/10.1016/j.ejso.2026.111849

Abstract

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.