Development and Validation of the Periodontal Map Derived From IOS and CBCT Registration for Diagnosis and Treatment Planning in Moderate-to-severe Periodontitis
试验速览
- 阶段
- 不适用
- 状态
- 尚未招募
- 发起方
- 入组人数
- 80
- 主要终点
- Accuracy of Bone Defect Morphology Classification by PerioAI System Compared to Intraoperative Findings
研究概览
简要总结
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.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •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.
排除标准
- •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.
结局指标
主要结局
Accuracy of Bone Defect Morphology Classification by PerioAI System Compared to Intraoperative Findings
时间窗: Preoperative (PerioAI system analysis) and intraoperative (direct surgical observation)
The PerioAI 2.0 system automatically classifies bone defect morphology (1-wall, 2-wall, 3-wall intrabony defects, dehiscence, or fenestration) based on preoperative intraoral scan and cone-beam CT data. The classification accuracy is assessed by comparing the PerioAI-generated classification against the gold standard of intraoperative direct visual observation by an experienced surgeon during periodontal surgery. Results are reported as the percentage of correctly classified defects (accuracy rate), with sensitivity and specificity for each defect type.
次要结局
- Agreement Between PerioAI-Automated Probing Depth Measurements and Clinical Probing Depth(Preoperative (PerioAI system analysis and clinical examination))
- Agreement Between PerioAI-Automated Clinical Attachment Loss Measurements and Clinical Attachment Loss(Preoperative (PerioAI system analysis and clinical examination))
- Agreement Between PerioAI-Automated Periodontitis Staging and Grading and Clinical Staging and Grading(Preoperative (PerioAI system analysis and clinical examination))
- Accuracy of Furcation Involvement Grading by PerioAI System Compared to Intraoperative Findings(Preoperative (PerioAI system analysis) and intraoperative (direct surgical exploration))
- Agreement Between PerioAI-Automated Intrabony Defect Depth Measurements and Intraoperative Direct Measurements(Preoperative (PerioAI system analysis) and intraoperative (direct surgical measurement))
- Agreement Between PerioAI-Automated Intrabony Defect Width Measurements and Intraoperative Direct Measurements(Preoperative (PerioAI system analysis) and intraoperative (direct surgical measurement))