This review highlights the benefits of new diagnostic tools in periodontal disease, indicating a shift towards more precise care.
Periodontal diseases, which are extremely common chronic inflammatory conditions, if left undiagnosed or untreated, can cause tooth loss and systemic health problems. Although clinical probing and radiography are still the gold standard for periodontal diagnostics, they have limitations in identifying early disease activity and forecasting its course. This review highlights the clinical applicability, benefits, and drawbacks of using biomarkers, chairside point-of-care (POC) diagnostic tools, digital imaging modalities, and artificial intelligence (AI)-driven technologies in periodontal diagnosis. PubMed, RSC Publishing, SpringerLink, Wiley Online Library, and other scholarly databases were used to search the literature. Microbiological test kits, lab-on-a-chip technologies, ultrasonography, optical coherence tomography (OCT), AI applications, salivary and gingival crevicular fluid (GCF) biomarkers, and 25 peer-reviewed articles published between 2000 and 2025 were included in the study. Clinical evaluation studies and narrative reviews were also included. Interleukins (ILs), matrix metalloproteinases, and host enzymes are salivary and GCF biomarkers that have high diagnostic and prognostic value in periodontics. Rapid pathogen and host-response detection is made possible by chairside kits (N-benzoyl-DL-arginine-2-naphthylamide [BANA] test, PerioSafe ® , ORALyzer). Early bone loss detection is improved by noninvasive imaging techniques such as OCT and ultrasonography, as well as AI analysis of cone-beam computed tomography and radiographs. Precision periodontal care is being advanced by new omics-based assays and standardised POC platforms that combine imaging and molecular data. Although there are still issues with clinical adoption, cost, and validation, POC diagnostics that combine AI and omics are revolutionizing periodontal care. Saliva-based multiplex assays, lab-on-a-chip biosensors, and AI-driven prognostic models for chairside use are examples of upcoming developments.
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Singh et al. (2025) studied this question.
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