Advancing precision dentistry: the integration of multi-omics and cutting-edge imaging technologies-a systematic review.

BACKGROUND

The convergence of multi-omics, advanced imaging technologies, and artificial intelligence (AI) is reshaping diagnostic strategies in precision dentistry. This systematic review critically assesses how the integration of multi-omics (genomics, proteomics, metabolomics), advanced imaging modalities (CBCT, MRI), and AI-based techniques synergistically enhances diagnostic accuracy, clinical decision-making, and personalized care in dentistry.

METHODS

The review follows PRISMA 2020 guidelines. A total of 50 studies published between 2015 and 2024 were selected using a PICOS framework. Analytical tools included meta-analysis (Forest and Funnel plots), risk of bias assessment, VOS viewer-based bibliometric mapping, and GRADE evidence grading.

RESULTS

Multi-omics approaches revealed key biomarkers such as TP53, IL-1, and MMPs in early diagnosis. CBCT reduced diagnostic error by 35% (CI: 30%-40%), while MRI improved soft-tissue evaluation by 25% (CI: 18%-32%). AI tools, including convolutional neural networks and radiomics, led to a 40% reduction in diagnostic time (CI: 33%-45%) and improved lesion classification.

CONCLUSION

Integrating AI with omics and imaging technologies enhances diagnostic precision in dentistry. Future efforts must address data standardization, ethical implementation, and validation through multicenter trials for clinical adoption.