Digital Precision Surgery

Every person is anatomically unique. This is why, particularly in the case of complex surgical procedures, treatments must be tailored as precisely as possible to the individual circumstances of each patient.

The ‘Digital Precision Surgery’ innovation focus brings together expertise from various surgical specialities, including oral and maxillofacial surgery, orthopaedics and traumatology, neurosurgery, spinal surgery and other disciplines. Together, they are creating a digital ecosystem that integrates modern technologies throughout the entire treatment pathway.

From imaging through to analysis, planning and simulation, right through to treatment, aftercare and the systematic evaluation of results, a learning system is emerging that makes surgical procedures more precise, safer and more personalised.

Many of the technologies required for personalized surgery already exist today, including artificial intelligence, digital twins, surgical navigation, robotics, and 3D printing. However, these systems often operate independently and remain disconnected from one another.

Digital Precision Surgery integrates these technologies into a single ecosystem for the first time. Much like an orchestra, each technology fulfills a specific role. Only through their coordinated interaction can a new generation of personalized surgical care be realized.

The closed-loop ecosystem is being developed with a deliberate focus on interdisciplinary collaboration and is intended to support a wide range of surgical disciplines in the long term, from reconstructive surgery and oncology to other specialised procedures.

Using CT, MRI, and 3D surface imaging data, a patient-specific virtual model of the anatomy – a digital twin – is created. This digital twin enables surgeons to plan and simulate procedures virtually and personalised before entering the operating room.

When required, patient-specific surgical guides or implants can be designed and manufactured. During surgery, digital navigation systems, augmented reality technologies, and robotic assistance systems support the precise execution of the planned procedure.

Following treatment, outcomes are fed back into the ecosystem. This includes clinical outcomes, patient-reported outcome measures (PROMs), and clinician-reported outcome measures (CROMs). These data continuously inform future treatments and support ongoing refinement of clinical workflows and technologies.

The innovation does not lie in any single technology but in their intelligent integration.

For the first time, medical imaging, artificial intelligence, digital twins, 3D printing, surgical navigation, robotic assistance, and outcome evaluation are connected within a single, closed-loop ecosystem.

This creates a continuous digital treatment pathway, from diagnosis, analysis, planning, and simulation to treatment, follow-up, and systematic outcome assessment. The insights generated are continuously reintegrated into future care processes, enabling ongoing learning and improvement.

The result is a learning healthcare ecosystem that does not deploy technologies in isolation but combines them strategically to make surgical care more precise, safer, and increasingly personalized over time.

This innovation focus is aimed at patients with complex surgical conditions or malformations, where individualised planning and precise execution are particularly important.

Areas of application include, for example:

• Cleft lip and palate
• Skull malformations
• Defects following tumour surgery
• Complex bone or facial reconstructions
• Complex fractures and corrective procedures on the musculoskeletal system
• Neurosurgical procedures in anatomically challenging regions
• Complex spinal procedures

The Digital Precision Surgery is being developed as an interdisciplinary initiative from the outset. In collaboration with various surgical disciplines, digital treatment pathways are being created that enable more precise planning, personalised therapies and continuous improvement in treatment.

The innovation focus aims to:

• Improve the accuracy of surgical planning
• Reduce risks and complications
• Enhance patient understanding of proposed treatments
• Enable more personalized treatment strategies
• Improve the quality and safety of surgical care over the long term

Patients can often visualize and better understand their individual condition before surgery through patient-specific 3D models and simulations. This facilitates informed discussions and shared decision-making with the clinical team.

Importantly, people remain at the center of care. Technology supports healthcare professionals, it does not replace them.

The innovation focus builds on many years of clinical experience in virtual surgical planning, patient-specific implants, and medical 3D printing.

Its goal is to translate innovative technologies from research into routine clinical care in a safe, validated, and sustainable manner.

Over time, the learning ecosystem is intended to become not only a solution for highly specialized cases but a standardized, scalable, and trusted component of modern surgical care.