Application of subject-specific adaptive mechanical loading for bone healing in a mouse tail vertebral defect

Area of Science:

• Biomaterials Science
• Orthopedic Engineering
• Computational Mechanics

Background:

• Bone defect repair remains a significant clinical challenge.
• Mechanical loading influences bone remodeling, but ineffective or damaging loading can hinder healing.
• Current methods often lack patient-specific mechanical considerations for bone defect sites.

Purpose of the Study:

• To explore real-time finite element (rtFE) methods for optimizing mechanical stimulation in bone defect healing.
• To investigate subject-specific and time-dependent estimation of effective peak cyclic loads.
• To assess the efficacy of rtFE-driven adaptive mechanical loading in a preclinical model.

Main Methods:

• Utilized micro-computed tomography (micro-CT) for 3D structural analysis of bone defects.
• Developed and applied real-time finite element (rtFE) analysis for subject-specific load estimation.
• Implemented adaptive mechanical loading based on rtFE predictions in a mouse caudal vertebral bone defect model.

Main Results:

• rtFE analysis enabled estimation of effective peak cyclic loads tailored to individual bone defects.
• Adaptive mechanical loading significantly enhanced bone healing compared to non-loaded controls.
• No vertebral fractures occurred, indicating the safety and efficacy of the loading strategy.

Conclusions:

• rtFE-driven adaptive loading regimes can improve bone defect healing efficacy.
• This approach accounts for unique initial defect conditions and spatio-temporal healing processes.
• The demonstrated methodology holds potential for patient-specific and more effective clinical bone defect treatments.