Toward Precision Radiologic Assessment in Alveolar Cleft Reconstruction: From 2-Dimensional Scoring to Artificial Intelligence-Integrated 3-Dimensional Modeling.
Authors
Affiliations (2)
Affiliations (2)
- Resident, Center for Cleft Lip and Palate Treatment, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
- Professor, Chief Physician, Doctoral Supervisor, Center for Cleft Lip and Palate Treatment, Plastic Surgery Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China. Electronic address: [email protected].
Abstract
Radiological evaluation is critical for determining alveolar bone grafting success. Assessment has evolved from subjective two-dimensional (2D) scoring to objective three-dimensional (3D) quantitative imaging using cone-beam computed tomography (CBCT). Recently, artificial intelligence (AI) has emerged as a potentially valuable tool. This review examines this evolution and identifies future directions for more precise radiologic assessment in alveolar cleft reconstruction. Traditional 2D scoring remains widely used but is limited by distortion and poor volumetric assessment. CBCT-based 3D imaging enables more objective evaluation of graft morphology and postoperative healing. AI-assisted approaches may support image analysis and prognostic assessment, but clinical application remains limited. Radiologic assessment in alveolar cleft reconstruction has evolved from subjective 2D scoring to objective 3D imaging, with CBCT currently representing the most informative approach and AI emerging as a potential adjunct for future precision evaluation.