Mass Spectrometry Imaging for Predicting Bone Fracture Healing and Cartilage Repair Outcomes
Non-union occurs in 5-10% of bone fractures and post-traumatic osteoarthritis develops in up to 75% of cartilage injuries, yet outcome prediction remains impossible with current tools. This review explores how mass spectrometry imaging can detect molecular signatures in hard tissues that may serve as predictive biomarkers for impaired healing. The potential for real-time, in-situ MS during surgery to guide intraoperative decisions represents a novel application that could transform orthopaedic care.
The original study
Clinical use of mass spectrometry (imaging) for hard tissue analysis in abnormal fracture healing.
- Authors
- Nauta SP, Poeze M, Heeren RMA, Porta Siegel T
- Journal
- Clinical chemistry and laboratory medicine
- Type
- Journal Article, Review
- PMID
- 32049645
Original abstract
Common traumas to the skeletal system are bone fractures and injury-related articular cartilage damage. The healing process can be impaired resulting in non-unions in 5-10% of the bone fractures and in post-traumatic osteoarthritis (PTOA) in up to 75% of the cases of cartilage damage. Despite the amount of research performed in the areas of fracture healing and cartilage repair as well as non-unions and PTOA, still, the outcome of a bone fracture or articular cartilage damage cannot be predicted. Here, we discuss known risk factors and key molecules involved in the repair process, together with the main challenges associated with the prediction of outcome of these injuries. Furthermore, we review and discuss the opportunities for mass spectrometry (MS) - an analytical tool capable of detecting a wide variety of molecules in tissues - to contribute to extending molecular understanding of impaired healing and the discovery of predictive biomarkers. Therefore, the current knowledge and challenges concerning MS imaging of bone and cartilage tissue as well as in vivo MS are discussed. Finally, we explore the possibilities of in situ, real-time MS for the prediction of outcome during surgery of bone fractures and injury-related articular cartilage damage.