Predictive Performance of Raman Spectroscopy in Osteoarthritis: A Systematic Review.

Area of Science:

• Biomedical Engineering
• Molecular Spectroscopy
• Orthopedics

Background:

• Early diagnosis of osteoarthritis (OA) is crucial for effective intervention but lacks reliable methods.
• Raman spectroscopy (RS) offers potential for molecular-level detection and monitoring of OA.
• Current diagnostic tools have limitations in predicting OA progression and severity.

Purpose of the Study:

• To systematically evaluate the predictive performance of Raman spectroscopy (RS) for osteoarthritis (OA) assessment in human samples.
• To highlight advancements and identify limitations of RS in OA detection.
• To assess the potential of RS for early OA diagnosis and disease monitoring.

Main Methods:

• Systematic literature search of major databases (PubMed, Scopus, Web of Science, IEEE) up to July 31, 2024.
• Screening and data extraction by two independent reviewers using Covidence software.
• Risk of bias and applicability assessment using the Prediction Model Risk of Bias Assessment Tool.

Main Results:

• Ten studies met the inclusion criteria, primarily using near-infrared excited RS.
• Reported predictive accuracy for OA assessment ranged from 73% to 100% in preclinical settings.
• All studies had internal validation, but most exhibited high risk of bias; none reported external validation.

Conclusions:

• Raman spectroscopy demonstrates significant potential for early OA detection and assessment at the molecular level.
• High reported accuracy is limited by methodological biases and lack of external validation.
• Future research requires larger cohorts, external validation, and standardized protocols for clinical translation.