Digital analysis of the human maxilla to enable semistandardized template tool reconstructions with free fibula transplants.

Objectives: This study analyzed the human maxilla to support the development of mean-value-based cutting guide systems for maxillary reconstruction, bridging the gap between freehand techniques and virtual surgical planning (VSP).

Materials and methods: This retrospective cohort study used routine CT scans. DICOM data enabled 3D modelling and the maxilla was divided into four regions: paranasal (R1), facial maxillary sinus wall (R2), zygomatic bone (R3) and alveolar process (R4). Surface comparisons were made with a reference skull. Statistical analyses assessed anatomical variations, focusing on mean distance (Dmean), area of valid distance (AVD), integrated distance (ID) and integrated absolute distance (IAD). The study addressed hemimaxillectomy defects for two-segmental reconstructions using seven defined bilateral points to determine segmental distances and angles.

Results: Data from 50 patients showed R2 as the most homogeneous and R4 as the most heterogeneous region. Significant age and gender differences were found in R3 and R4, with younger patients and females having more outliers. Cluster analysis indicated that males had R1 and R3 positioned anterior to the reference skull. The mean angle for segmental reconstruction was 131.24° ± 1.29°, with anterior segment length of 30.71 ± 0.57 mm and posterior length of 28.15 ± 0.86 mm.

Conclusions: Anatomical analysis supported the development of semistandardized segmental resection approaches. Although gender and anatomical differences were noted, they did not significantly impact the feasibility of mean-value-based cutting-guide systems.

Clinical relevance: This study provides essential anatomical data for creating cost-effective and efficient reconstruction options for maxillary defects, potentially improving surgical outcomes and expanding reconstructive possibilities beyond current techniques.