Development and Validation of the Periodontal Map Derived From IOS and CBCT Registration for Diagnosis and Treatment Planning in Moderate-to-severe Periodontitis

Overview

This prospective diagnostic study aims to validate the clinical utility of a "Periodontal Panoramic Map" generated by the PerioAI V2.0 system, an artificial intelligence-based platform that integrates intraoral scans and cone-beam CT data, for preoperative diagnosis and surgical planning in patients with moderate to severe periodontitis (Stage II-IV). Current clinical standards-manual probing and two-dimensional radiography-have inherent limitations in accurately visualizing complex three-dimensional bone defect morphology, leading to potential underestimation of disease severity and suboptimal surgical outcomes. Building upon our team's previously published high-precision PerioAI V1.0 system, this study will enroll 80 patients requiring periodontal surgery. Preoperative intraoral scans and cone-beam CT images will be acquired as part of routine care, and the PerioAI V2.0 system will automatically generate a "Periodontal Panoramic Map" with intelligent outputs including probing depth, clinical attachment loss, bone defect morphology classification, furcation involvement grading, and automated measurements of key parameters such as intra-bony defect depth and width. These automated diagnostic results will be compared against the gold standard of full mouth clinical examination and intra-operative direct measurements and observations obtained during periodontal surgery under strict blinded conditions. The primary outcome measures are the accuracy of bone defect morphology classification and the agreement between automated and intra-operative linear measurements assessed by intraclass correlation coefficients and Bland-Altman analysis. Secondary outcomes include accuracy of probing depth, clinical attachment loss, periodontitis staging and grading, furcation involvement grading and treatment planning. This study will provide critical evidence supporting the paradigm shift in periodontal surgery from experience-dependent assessment to data-driven precision medicine, ultimately offering clinicians an intuitive, quantitative, and three-dimensional visualization tool for optimized surgical decision-making.

Interventions

• Diagnostic test Perio AI V2.0 System
  This is a single-arm, prospective diagnostic accuracy study. The intervention is the application of an artificial intelligence-based software (PerioAI V2.0) to routinely acquired preoperative intra-oral scan and cone-beam CT data. The software generates a "Periodontal Panoramic Map" with automated measurements and classifications. All participants then undergo routine full clinical examination and clinically indicated periodontal surgery, which are obtained as the gold standard to validate the a

Primary outcome measures

• Accuracy of Bone Defect Morphology Classification by PerioAI System Compared to Intraoperative Findings [Time frame: Preoperative (PerioAI system analysis) and intraoperative (direct surgical observation)]

Secondary outcome measures (6)

• Agreement Between PerioAI-Automated Probing Depth Measurements and Clinical Probing Depth [Time frame: Preoperative (PerioAI system analysis and clinical examination)]
• Agreement Between PerioAI-Automated Clinical Attachment Loss Measurements and Clinical Attachment Loss [Time frame: Preoperative (PerioAI system analysis and clinical examination)]
• Agreement Between PerioAI-Automated Periodontitis Staging and Grading and Clinical Staging and Grading [Time frame: Preoperative (PerioAI system analysis and clinical examination)]
• Accuracy of Furcation Involvement Grading by PerioAI System Compared to Intraoperative Findings [Time frame: Preoperative (PerioAI system analysis) and intraoperative (direct surgical exploration)]
• Agreement Between PerioAI-Automated Intrabony Defect Depth Measurements and Intraoperative Direct Measurements [Time frame: Preoperative (PerioAI system analysis) and intraoperative (direct surgical measurement)]
• Agreement Between PerioAI-Automated Intrabony Defect Width Measurements and Intraoperative Direct Measurements [Time frame: Preoperative (PerioAI system analysis) and intraoperative (direct surgical measurement)]

Eligibility criteria

Inclusion criteria

• Aged ≥ 18 years.
• Diagnosed with Stage II-IV periodontitis according to the 2018 Classification of Periodontal Diseases.
• Presence of at least one tooth requiring periodontal surgery (including open flap debridement or regenerative surgery) due to periodontitis, where the intra-bony defect can be exposed intra-operatively for measurement.
• Voluntary participation and provision of written informed consent.

Exclusion criteria

• Pregnant or lactating women.
• Presence of uncontrolled systemic diseases that significantly affect surgery or tissue healing, such as uncontrolled diabetes mellitus or immunodeficiency.
• History of head and neck radiotherapy.
• Inability to cooperate with the required study examinations.

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model

Cohort

Study locations

Center list to be confirmed — check the primary protocol.

Publications

• Tan M, Cui Z, Li Y, Fang Y, Mei L, Zhao Y, Wu X, Lai H, Tonetti MS, Shen D. PerioAI: A digital system for periodontal disease diagnosis from an intra-oral scan and cone-beam CT image. Cell Rep Med. 2025 Jun 17;6(6):102186. doi: 10.1016/j.xcrm.2025.102186. PMID 40532658

Identifiers

NCT: NCT07505251 · SH9H-2026-T98-1 · JYLJ2025015

Primary sources (government registries)

• ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗