4.6 Article

In-House, Open-Source 3D-Software-Based, CAD/CAM-Planned Mandibular Reconstructions in 20 Consecutive Free Fibula Flap Cases: An Explorative Cross-Sectional Study With Three-Dimensional Performance Analysis

Journal

FRONTIERS IN ONCOLOGY
Volume 11, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2021.731336

Keywords

in-house CAD; CAM planning; 3D printing; mandibular reconstruction; free fibula flap; open-source software

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This study analyzed an in-house, open-source software-based solution for virtual planning in mandibular reconstruction. The results showed that this method is cost-effective, fast, and accurate, making it suitable for teaching purposes.
Background Mandibular reconstruction is conventionally performed freehand, CAD/CAM-assisted, or by using partially adjustable resection aids. CAD/CAM-assisted reconstructions are usually done in cooperation with osteosynthesis manufacturers, which entails additional costs and longer lead time. The purpose of this study is to analyze an in-house, open-source software-based solution for virtual planning. Methods and Materials All consecutive cases between January 2019 and April 2021 that underwent in-house, software-based (Blender) mandibular reconstruction with a free fibula flap (FFF) were included in this cross-sectional study. The pre- and postoperative Digital Imaging and Com munications in Medicine (DICOM) data were converted to standard tessellation language (STL) files. In addition to documenting general information (sex, age, indication for surgery, extent of resection, number of segments, duration of surgery, and ischemia time), conventional measurements and three-dimensional analysis methods (root mean square error [RMSE], mean surface distance [MSD], and Hausdorff distance [HD]) were used. Results Twenty consecutive cases were enrolled. Three-dimensional analysis of preoperative and virtually planned neomandibula models was associated with a median RMSE of 1.4 (0.4-7.2), MSD of 0.3 (-0.1-2.9), and HD of 0.7 (0.1-3.1). Three-dimensional comparison of preoperative and postoperative models showed a median RMSE of 2.2 (1.5-11.1), MSD of 0.5 (-0.6-6.1), and HD of 1.5 (1.1-6.5) and the differences were significantly different for RMSE (p < 0.001) and HD (p < 0.001). The difference was not significantly different for MSD (p = 0.554). Three-dimensional analysis of virtual and postoperative models had a median RMSE of 2.3 (1.3-10.7), MSD of -0.1 (-1.0-5.6), and HD of 1.7 (0.1-5.9). Conclusions Open-source software-based in-house planning is a feasible, inexpensive, and fast method that enables accurate reconstructions. Additionally, it is excellent for teaching purposes.

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