Abstract

Digital Twins hold immense promise in oncology, particularly in their ability to personalize care through dynamic, patient-specific modelling.   This talk will highlight the development of the Digital Twin Assisted Surgery (DTAS) for kidney cancer surgeries, an initiative that bridges clinical practice, engineering, and data science. The project centres around integrating multimodal data such as radiological imaging, tumour complexity scores, surgical variables, and post-operative outcomes into a digital framework designed to inform surgical planning.   Beyond the technical architecture, our work is fundamentally shaped by clinical questions: How do we personalise surgery for anatomical and pathological variability? How do we ensure the kidney tumour has been fully resected?   The talk will reflect how clinicians and patients are involved at every stage of the model development, and how this work reflects a broader shift toward precision surgery. The ethical and practical considerations of embedding such tools in a high-stakes environment of cancer surgery will also be considered. Ultimately, this talk will present DTAS as the future of surgery, from theoretical principles to actual surgeries where the digital twin becomes a guide, enhancing rather than replacing surgical judgement.