Elasticity-guided tumor resection: applying biomechanical information to neurosurgical practice.
Authors
Affiliations (10)
Affiliations (10)
- Department of Neurosurgery, Odense University Hospital, Odense, Denmark. [email protected].
- Brain Research Interdisciplinary Guided Excellence (BRIDGE), University of Southern Denmark, Odense, Denmark. [email protected].
- Department of Neurosurgery, Odense University Hospital, Odense, Denmark.
- Brain Research Interdisciplinary Guided Excellence (BRIDGE), University of Southern Denmark, Odense, Denmark.
- Department of Radiology, Odense University Hospital, Odense, Denmark.
- Research Unit of Radiology, Department of Clinical Research, University of Southern Denmark, Odense, Denmark.
- Department of Radiology, Mayo Clinic, Rochester, MN, USA.
- Division of Biomedical Imaging, Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology, Stockholm, Sweden.
- MedTechLabs, Karolinska University Hospital, BioClinicum, Solna, Sweden.
- Faculty of Health Sciences, Department of Radiography, Oslo Metropolitan University, Oslo, Norway.
Abstract
Tumor stiffness and adhesion are decisive factors in neurosurgical strategy, yet they remain absent from standard planning and navigation. Advances in biomechanics allow these properties to be measured and mapped across modalities: magnetic resonance elastography for preoperative stiffness and adhesion, intraoperative ultrasound elastography for real-time updates, and rheometry as biological ground truth. Emerging frameworks could integrate these measurements with artificial intelligence and multimodal neuroimaging to produce probabilistic maps of tumor consistency and brain-tumor interface quality. We define this concept as elasticity-guided neurosurgery: the incorporation of biomechanical parameters into surgical decision-making to improve safety, efficiency, and personalization. By transforming tactile impressions into actionable data, elasticity-guided neurosurgery could represent a paradigm shift toward more information-driven neurosurgical oncology.