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MRI based 3D reconstruction of the spine from a new perspective. Optimized for digital planning and guide system.

Reference number
Coordinator Västra Götalandsregionen - Ortopedi, område 3, Sahlgrenska universitetssjukhuset
Funding from Vinnova SEK 900 000
Project duration May 2023 - April 2025
Status Ongoing
Venture Swelife and Medtech4Health - Collaborative Projects for Improved Health
Call Swelife and Medtech4Health - Collaborative projects for better health autumn 2022

Purpose and goal

The aim is to develop and validate a new non-radiation-loading precision medicine method for bone imaging in surgical orthopedics where MRI technology is used in clinical routine diagnostics and for surgical planning and navigation systems for surgery in combination with artificial intelligence (AI).

Expected effects and result

The method makes large parts of the detailed information created during an MRI examination, which is now hidden, available to both radiologists and orthopedic surgeons. The information can then be uploaded to the planning and navigation tools that are becoming increasingly important for care. Thanks to the use of AI, the different tissues and structures will be able to be identified and presented automatically, increasing the possibilities of making accurate assessments and safer operations. The method has excellent conditions for creating improvements in surgical orthopedics.

Planned approach and implementation

The project is divided into four work packages. AP1: evaluate and analyze imaging of the lumbar spine with DT and MRI experimentally. AP2: Identify possibilities and limitations of MRI for bone imaging and compare 3D reconstruction models produced with MRI vs. DT. AP3: image data processes are adapted for existing MRI equipment used in the diagnosis of back problems and apply this to a clinical material. AP4: diagnosis and treatment of patients with back problems with support of MRI-based image information implemented in a planning and guidance system.

The project description has been provided by the project members themselves and the text has not been looked at by our editors.

Last updated 16 June 2023

Reference number 2022-03472