Toward Precision Radiologic Assessment in Alveolar Cleft Reconstruction: From 2-Dimensional Scoring to Artificial...

Area of Science:

• Oral and Maxillofacial Surgery
• Radiology
• Biomedical Engineering

Background:

• Radiological evaluation is crucial for assessing alveolar bone grafting success in cleft reconstruction.
• Traditional methods rely on subjective two-dimensional (2D) scoring, which has limitations in accuracy and volumetric assessment.
• Advancements include objective three-dimensional (3D) quantitative imaging and emerging artificial intelligence (AI) tools.

Purpose of the Study:

• To review the evolution of radiological assessment techniques for alveolar bone grafting.
• To compare the efficacy of 2D, 3D imaging (CBCT), and AI in evaluating graft success.
• To identify future directions for enhanced radiologic assessment in alveolar cleft reconstruction.

Main Methods:

• Literature review of radiological assessment methods in alveolar cleft reconstruction.
• Comparison of traditional 2D scoring with advanced 3D imaging techniques like cone-beam computed tomography (CBCT).
• Exploration of the potential role and current limitations of artificial intelligence (AI) in radiologic analysis.

Main Results:

• Two-dimensional (2D) scoring methods are widely used but suffer from distortion and inadequate volumetric assessment.
• Three-dimensional (3D) imaging, particularly CBCT, offers more objective evaluation of graft morphology and healing.
• AI-assisted approaches show potential for image analysis and prognosis but have limited clinical application currently.

Conclusions:

• Radiologic assessment for alveolar cleft reconstruction has progressed from subjective 2D to objective 3D imaging.
• Cone-beam computed tomography (CBCT) is currently the most informative imaging modality.
• Artificial intelligence (AI) is an emerging adjunct with potential for future precision in radiologic evaluation.