AI-driven morphometric comparison of fibula vs. iliac flap in mandibular reconstruction.

OBJECTIVE

To compare the clinical outcomes of vascularized free fibula flap (FFF) and deep circumflex iliac artery (DCIA) flap for mandibular reconstruction, using a novel AI-driven dual-modality system for quantitative 3D morphological fidelity and facial symmetry analysis.

METHODS

We evaluated 56 patients with tumors (34 undergoing FFF and 22 undergoing DCIA) using a 3D U-Net deep learning model and Face Mesh. The U-Net model predicted mandibular shapes to generate patient-specific, anatomically plausible reference mandibles, and surface deviations were compared with the actual reconstructions. Facial symmetry was quantified using MediaPipe Face Mesh.

RESULTS

No significant differences in facial symmetry (S = 0.084 ± 0.013 vs. 0.083 ± 0.012, p = 0.781), functional recovery, or complications. DCIA showed lower morphological deviations for body defects: mean difference (1.42 ± 0.83 mm vs. 2.58 ± 0.62 mm, p = 0.001), maximum deviation (19.8 ± 2.7 mm vs. 21.4 ± 4.1 mm, p < 0.05).

CONCLUSION

FFF and DCIA flaps achieve comparable facial symmetry, functional recovery and complication rates in mandibular reconstruction. DCIA flap offers significantly improved 3D geometric accuracy only for isolated mandibular body defects, while the clinical relevance of this statistical difference remains uncertain. The AI-based quantitative assessment system established in this study provides an objective tool for defect-specific flap selection in mandibular reconstruction.