RESUMO
The precise identification and differentiation of peri-implant diseases, without the need for intrusive procedures, is crucial for the successful clinical treatment and overall durability of dental implants. This work introduces a novel approach that combines surface-enhanced Raman scattering (SERS) spectroscopy with advanced chemometrics to analyse peri-implant crevicular fluid (PICF) samples. The primary purpose is to offer an unbiased evaluation of implant health. A detailed investigation was performed on PICF samples obtained from a cohort of patients exhibiting different levels of peri-implant health, including those with healthy implants, implants impacted by peri-implantitis, and implants with peri-implant mucositis. The obtained SERS spectra were analysed using canonical-powered partial least squares (CPPLS) to identify unique chemical characteristics associated with each inflammatory state. Significantly, our research findings unveil the presence of a common inflammatory SERS spectral pattern in cases of peri-implantitis and peri-implant mucositis. Furthermore, the SERS-based scores obtained from CPPLS were combined with established clinical scores and subjected to a linear discriminant analysis (LDA) classifier. Repeated double cross-validation was used to validate the method's capacity to discriminate different implant conditions. The integrated approach showcased high sensitivity and specificity and an overall balanced accuracy of 92%, demonstrating its potential to serve as a non-invasive diagnostic tool for real-time implant monitoring and early detection of inflammatory conditions.
