AI- Powered Multiphasic 3D Printed Scaffold for Periodontal Defect Regeneration
试验速览
- 阶段
- 1 期
- 状态
- Enrolling By Invitation
- 入组人数
- 1
- 试验地点
- 1
- 主要终点
- Probing Depth
研究概览
简要总结
The periodontal ligament is vital for tooth support, and its loss, frequently resulting from periodontitis, trauma, or endodontic lesions, presents a significant clinical challenge; global cases of severe periodontitis increased by 91.54% from 1990 to 2021. Conventional monophasic scaffolds offer a uniform environment, limiting their efficacy in regenerating complex, multi-tissue structures like the periodontium. This study introduces an AI-enhanced, 3D multi-phasic scaffold to precisely restore the periodontal apparatus and overcome the limitations of non-uniform tissue growth seen in some multiphasic designs. The methodology involved sequential steps: high-resolution CBCT and intraoral scans to capture defect geometry; precise defect mapping to define the Target Regeneration Volume; and AI Mesh mixer implementation to generate three distinct, seamlessly graded lattice zones. This AI-driven design ensures Optimal Biomechanics (Precision) by perfectly matching the scaffold's stiffness to native tissue, thereby eliminating stress-shielding.
详细描述
Background: The global prevalence of severe periodontitis increased by 91.54% between 1990 and 2021, driven primarily by population growth and population ageing, and now affects more than one billion people worldwide . Left untreated, periodontitis progressively destroys the attachment apparatus and is a leading cause of tooth loss. Conventional regenerative therapies rely largely on monophasic scaffolds, which impose a single, uniform biological and structural environment and therefore struggle to reproduce the layered, multi-tissue architecture of the periodontium. Study Problem: The periodontium is a composite of three histologically and mechanically distinct tissues - alveolar bone, the periodontal ligament (PDL), and cementum - each of which requires a different stiffness, porosity, and biochemical microenvironment for optimal regeneration. Monophasic scaffolds cannot satisfy this requirement simultaneously, which frequently results in fibrous encapsulation, incomplete integration, or stress-shielding. Objectives: This thesis examines the design, fabrication rationale, and clinical evaluation of an Artificial-Intelligence (AI)-boosted three-dimensional (3D) multiphasic scaffold intended to achieve simultaneous, tailored regeneration of alveolar bone, PDL, and cementum through a graded lattice architecture matched to native tissue stiffness. Methodology: The target regeneration volume was defined using high-resolution Cone-Beam Computed Tomography (CBCT) and intraoral optical scanning, processed through AI-assisted defect-segmentation software. A tri-zonal multiphasic scaffold - an outer bone-directed zone, a middle PDL-directed zone, and an inner cementum-directed zone - was generated and produced by 3D 2 Smart Scaffolds, Stronger Smiles bioprinting using biocompatible polymer and bio-ceramic bio-inks, then surgically placed in patients with severe infrabony defects. Clinical and radiographic outcomes were assessed at 2, 6, and 12 months post-operatively.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Treatment
- 盲法
- None
入排标准
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Normal Lab investigation
排除标准
- •Bone diseases , Bleeding disorders
研究组 & 干预措施
1 patient
干预措施: AI algorithms generated a 3D multiphasic, graded lattice structure (Procedure)
结局指标
主要结局
Probing Depth
时间窗: 12 months
the measured distance from the edge of the gum (gingival margin) to the bottom of the gum pocket or sulcus.
Bone quality , PDL formation
时间窗: 2,6,12 month
refers to the density and architectural composition of the jawbone, which determines its strength and ability to stabilize a dental implant
次要结局
未报告次要终点
研究者
Sana Ahmed Sakr
Dr
Misr University for Science and Technology
