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

Abstract

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.

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