Over the past decade, increasing digitisation and the development of technological infrastructures have fostered the emergence of innovative concepts such as Digital Twin (DT), which has been considered a major strategic technology trend since 2017. However, despite its potential, the application of DT in the healthcare sector has remained limited. The ‘Methods and tools to support definition of a Digital Twin of the Human Brain’ project in collaboration between the AVR Lab and the Universidad Nacional Autónoma de México (UNAM) now aims to fill this gap by developing a Digital Twin of the Human Brain, a promising technology for neurosurgery, one of the most complex and risky medical fields.

The brain DT aims to offer advanced support to neurosurgeons at all stages of treatment. Thanks to its ability to accurately model brain complexity, the digital twin will allow surgical interventions to be simulated in order to identify the most effective and customised strategies for each patient. In addition, it will be useful for preoperative planning, intraoperative management and postoperative monitoring, thus improving the quality of care and reducing the risks associated with interventions.

The strength of DT lies in its predictive capabilities, achieved through advanced computational models that integrate different temporal and biological scales. These models make it possible to link short-term events with broader biological dynamics, providing a detailed and evolving clinical picture. Predictive efficacy is constantly evaluated and refined, providing real-time feedback on the patient's clinical progress. 

The project involves the combined use of computational models and machine learning tools to create a reliable predictive system. Pre-operative data, collected from heterogeneous sources, will be harmonised and securely interpreted to ensure an accurate understanding of the patient's condition. During surgery, the data will be continuously updated in real time, allowing surgeons to quickly adapt to changes and optimise ongoing procedures.
This technology represents a significant step forward in healthcare, offering not only a detailed view of the brain structure, but also a dynamic system capable of improving the accuracy and effectiveness of neurosurgical care.