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Spine Surgery & Precision Technology

Minimally invasive, robotic-assisted and image-guided approaches for more precise spine surgery

Description

The Spine Surgery Research Program at INI Hannover focuses on advancing precise, safe and tissue-preserving surgical procedures for disorders of the spine.

Its central areas include minimally invasive and navigated surgical techniques, robotic-assisted procedures and the systematic integration of intraoperative imaging into surgical planning and execution.

A particular scientific focus is the objective analysis of the accuracy of spinal instrumentation—from the anatomically demanding upper cervical spine, including C1/C2, to thoracic, lumbar and lumbosacral instrumentation.

In addition, the program investigates motion-preserving and dynamic stabilization concepts, sagittal balance and increasingly AI-based methods for individualized surgical planning.

Key Research Areas

Development and evaluation of tissue-preserving surgical approaches designed to reduce surgical trauma while providing safe decompression and stabilization.
Scientific analysis of the accuracy of navigated screw placement in the cervical, thoracic and lumbar spine. Particular attention is given to anatomically demanding regions such as C1/C2.
Integration of robotic assistance into the planning and execution of spinal procedures. Research addresses accuracy, reproducibility, safety and surgical workflow.
Use of intraoperative three-dimensional imaging for immediate assessment of anatomy, decompression, implant position and surgical results.
Advancement of image-guided and navigated techniques for the upper cervical spine and craniovertebral junction, including patient-specific trajectory planning.
Development of individualized surgical strategies for degenerative disease, instability, deformity and revision surgery.
Investigation of motion-preserving and dynamic stabilization concepts as alternatives or adjuncts to rigid fusion. Key areas include individualized indications, biomechanical effects, preservation of physiological mobility and potential effects on adjacent spinal segments.
Systematic postoperative analysis of implant positioning, radiological results, complications, revision rates and clinical outcomes.
Development of AI-based methods for automated analysis of sagittal and spinopelvic parameters. Radiological and clinical information will be integrated into predictive models to define patient-specific correction targets and virtually evaluate alternative surgical strategies.

The long-term objective is to develop models capable of using anatomy, balance, age, pathology and clinical parameters to predict which surgical strategy is most likely to achieve the optimal functional outcome for an individual patient.

If you would like to learn more about our research or are interested in scientific collaboration, please contact us at:

research@ini-hannover.de

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Spine Surgery & Precision Technology

Minimally invasive, robotic-assisted and image-guided approaches for more precise spine surgery

Description

Key Research Areas