Infrared Spectroscopy for Determining Bone Graft Healing and Readiness in Tissue Models

Area of Science:

• Biomaterials science
• Spectroscopy
• Dental regenerative medicine

Background:

• Dental implant success depends on bone graft (BG) integration.
• Current radiographic methods offer limited quantitative assessment of BG maturation.
• Accurate assessment is crucial for determining optimal implant placement timing.

Purpose of the Study:

• To investigate visible near-infrared (VNIR) spectroscopy for quantitative assessment of intraoral bone graft healing.
• To evaluate VNIR spectroscopy's potential as a noninvasive tool for monitoring compositional changes during BG maturation.
• To correlate spectral data with progressive stages of bone graft healing in novel tissue models.

Main Methods:

• Developed six tissue models simulating progressive bone graft (BG) healing stages.
• Collected spectra using VNIR spectroscopy (ASD LabSpec4).
• Applied preprocessing, principal component analysis (PCA), and machine learning (LDA, KNN) for compositional analysis and stage classification.

Main Results:

• VNIR spectroscopy differentiated bone graft from native bone and detected spectral changes during graft maturation.
• Increased C-H absorbances correlated with advanced healing stages, resembling healthy bone spectra.
• Machine learning classification achieved 97% accuracy in predicting BG healing stages.

Conclusions:

• VNIR spectroscopy shows significant potential as a noninvasive, quantitative tool for monitoring intraoral bone graft healing.
• Identification of compositional markers (e.g., C-H absorbances) can guide optimal dental implant timing.
• Further pre-clinical validation is necessary to support clinical trials and enhance treatment planning.