Does an In-House Computer-Aided Design/Computer-Aided Manufacturing Approach Contribute to Accuracy and Time Shortening in Mandibular Reconstruction?

Realizing in-house algorithm-driven free fibula flap set up within 24 hours: a pilot study evaluating accuracy with open-source tools

Objective

This study aims to critically evaluate the effectiveness and accuracy of a time safing and cost-efficient open-source algorithm for in-house planning of mandibular reconstructions using the free osteocutaneous fibula graft. The evaluation focuses on quantifying anatomical accuracy and assessing the impact on ischemia time.

Methods

A pilot study was conducted, including patients who underwent in-house planned computer-aided design and manufacturing (CAD/CAM) of free fibula flaps between 2021 and 2023. Out of all patient cases, we included all with postoperative 3D imaging in the study. The study utilized open-source software tools for the planning step, and three-dimensional (3D) printing techniques. The Hausdorff distance and Dice coefficient metrics were used to evaluate the accuracy of the planning procedure.

Results

The study assessed eight patients (five males and three females, mean age 61.75 ± 3.69 years) with different diagnoses such as osteoradionecrosis and oral squamous cell carcinoma. The average ischemia time was 68.38 ± 27.95 min. For the evaluation of preoperative planning vs. the postoperative outcome, the mean Hausdorff Distance was 1.22 ± 0.40. The Dice Coefficients yielded a mean of 0.77 ± 0.07, suggesting a satisfactory concordance between the planned and postoperative states. Dice Coefficient and Hausdorff Distance revealed significant correlations with ischemia time (Spearman's rho = -0.810, p = 0.015 and Spearman's rho = 0.762, p = 0.028, respectively). Linear regression models adjusting for disease type further substantiated these findings.

Conclusions

The in-house planning algorithm not only achieved high anatomical accuracy, as reflected by the Dice Coefficients and Hausdorff Distance metrics, but this accuracy also exhibited a significant correlation with reduced ischemia time. This underlines the critical role of meticulous planning in surgical outcomes. Additionally, the algorithm's open-source nature renders it cost-efficient, easy to learn, and broadly applicable, offering promising avenues for enhancing both healthcare affordability and accessibility.

From bench to bedside - current clinical and translational challenges in fibula free flap reconstruction

Fibula free flaps (FFF) represent a working horse for different reconstructive scenarios in facial surgery. While FFF were initially established for mandible reconstruction, advancements in planning for microsurgical techniques have paved the way toward a broader spectrum of indications, including maxillary defects. Essential factors to improve patient outcomes following FFF include minimal donor site morbidity, adequate bone length, and dual blood supply. Yet, persisting clinical and translational challenges hamper the effectiveness of FFF. In the preoperative phase, virtual surgical planning and artificial intelligence tools carry untapped potential, while the intraoperative role of individualized surgical templates and bioprinted prostheses remains to be summarized. Further, the integration of novel flap monitoring technologies into postoperative patient management has been subject to translational and clinical research efforts. Overall, there is a paucity of studies condensing the body of knowledge on emerging technologies and techniques in FFF surgery. Herein, we aim to review current challenges and solution possibilities in FFF. This line of research may serve as a pocket guide on cutting-edge developments and facilitate future targeted research in FFF.

Automatic orbital segmentation using deep learning-based 2D U-net and accuracy evaluation: A retrospective study

The purpose of this study was to verify whether the accuracy of automatic segmentation (AS) of computed tomography (CT) images of fractured orbits using deep learning (DL) is sufficient for clinical application. In the surgery of orbital fractures, many methods have been reported to create a 3D anatomical model for use as a reference. However, because the orbit bone is thin and complex, creating a segmentation model for 3D printing is complicated and time-consuming. Here, the training of DL was performed using U-Net as the DL model, and the AS output was validated with Dice coefficients and average symmetry surface distance (ASSD). In addition, the AS output was 3D printed and evaluated for accuracy by four surgeons, each with over 15 years of clinical experience. One hundred twenty-five CT images were prepared, and manual orbital segmentation was performed in all cases. Ten orbital fracture cases were randomly selected as validation data, and the remaining 115 were set as training data. AS was successful in all cases, with good accuracy: Dice, 0.860 ± 0.033 (mean ± SD); ASSD, 0.713 ± 0.212 mm. In evaluating AS accuracy, the expert surgeons generally considered that it could be used for surgical support without further modification. The orbital AS algorithm developed using DL in this study is extremely accurate and can create 3D models rapidly at low cost, potentially enabling safer and more accurate surgeries.

Deep-learning-based automatic facial bone segmentation using a two-dimensional U-Net

The use of deep learning (DL) in medical imaging is becoming increasingly widespread. Although DL has been used previously for the segmentation of facial bones in computed tomography (CT) images, there are few reports of segmentation involving multiple areas. In this study, a U-Net was used to investigate the automatic segmentation of facial bones into eight areas, with the aim of facilitating virtual surgical planning (VSP) and computer-aided design and manufacturing (CAD/CAM) in maxillofacial surgery. CT data from 50 patients were prepared and used for training, and five-fold cross-validation was performed. The output results generated by the DL model were validated by Dice coefficient and average symmetric surface distance (ASSD). The automatic segmentation was successful in all cases, with a mean± standard deviation Dice coefficient of 0.897 ± 0.077 and ASSD of 1.168 ± 1.962 mm. The accuracy was very high for the mandible (Dice coefficient 0.984, ASSD 0.324 mm) and zygomatic bones (Dice coefficient 0.931, ASSD 0.487 mm), and these could be introduced for VSP and CAD/CAM without any modification. The results for other areas, particularly the teeth, were slightly inferior, with possible reasons being the effects of defects, bonded maxillary and mandibular teeth, and metal artefacts. A limitation of this study is that the data were from a single institution. Hence further research is required to improve the accuracy for some facial areas and to validate the results in larger and more diverse populations.

Mandibular reconstructions with free fibula flap using standardized partially adjustable cutting guides or CAD/CAM technique: a three- and two-dimensional comparison

Background

Mandibular reconstruction with the fibula free flap (FFF) is performed freehand, CAD/CAM-assisted, or by using partially adjustable resection/reconstruction aids. The two latter options represent the contemporary reconstructive solutions of the recent decade. The purpose of this study was to compare both auxiliary techniques with regard to feasibility, accuracy, and operative parameters.

Methods and materials

The first twenty consecutively operated patients requiring a mandibular reconstruction (within angle-to-angle) with the FFF using the partially adjustable resection aids between January 2017 and December 2019 at our department were included. Additionally, matching CAD/CAM FFF cases were used as control group in this cross-sectional study. Medical records and general information (sex, age, indication for surgery, extent of resection, number of segments, duration of surgery, and ischemia time) were analyzed. In addition, the pre- and postoperative Digital Imaging and Communications in Medicine data of the mandibles were converted to standard tessellation language (.stl) files. Conventional measurements - six horizontal distances (A-F) and temporo-mandibular joint (TMJ) spaces - and the root mean square error (RMSE) for three-dimensional analysis were measured and calculated.

Results

In total, 40 patients were enrolled (20:20). Overall operation time, ischemia time, and the interval between ischemia time start until end of operation showed no significant differences. No significant difference between the two groups were revealed in conventional measurements of distances (A-D) and TMJ spaces. The Δ differences for the distance F (between the mandibular foramina) and the right medial joint space were significantly lower in the ReconGuide group. The RMSE analysis of the two groups showed no significant difference (p=0.925), with an overall median RMSE of 3.1 mm (2.2-3.7) in the CAD/CAM and 2.9 mm (2.2-3.8) in the ReconGuide groups.

Conclusions

The reconstructive surgeon can achieve comparable postoperative results regardless of technique, which may favor the ReconGuide use in mandibular angle-to-angle reconstruction over the CAD/CAM technique because of less preoperative planning time and lower costs per case.

3D Printing and Virtual Surgical Planning in Oral and Maxillofacial Surgery

Compared to traditional manufacturing methods, additive manufacturing and 3D printing stand out in their ability to rapidly fabricate complex structures and precise geometries. The growing need for products with different designs, purposes and materials led to the development of 3D printing, serving as a driving force for the 4th industrial revolution and digitization of manufacturing. 3D printing has had a global impact on healthcare, with patient-customized implants now replacing generic implantable medical devices. This revolution has had a particularly significant impact on oral and maxillofacial surgery, where surgeons rely on precision medicine in everyday practice. Trauma, orthognathic surgery and total joint replacement therapy represent several examples of treatments improved by 3D technologies. The widespread and rapid implementation of 3D technologies in clinical settings has led to the development of point-of-care treatment facilities with in-house infrastructure, enabling surgical teams to participate in the 3D design and manufacturing of devices. 3D technologies have had a tremendous impact on clinical outcomes and on the way clinicians approach treatment planning. The current review offers our perspective on the implementation of 3D-based technologies in the field of oral and maxillofacial surgery, while indicating major clinical applications. Moreover, the current report outlines the 3D printing point-of-care concept in the field of oral and maxillofacial surgery.

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

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.

In-house 3D printing: Why, when, and how? Overview of the national French good practice guidelines for in-house 3D-printing in maxillo-facial surgery, stomatology, and oral surgery

3D-printing is part of the daily practice of maxillo-facial surgeons, stomatologists and oral surgeons. To date, no French health center is producing in-house medical devices according to the new European standards. Based on all the evidence-based data available, a group of experts from the French Society of Stomatology, Maxillo-Facial Surgery and Oral Surgery (Société Française de Chirurgie Maxillofaciale, Stomatologie et Chirurgie Orale, SFSCMFCO), provide good practice guidelines for in-house 3D-printing in maxillo-facial surgery, stomatology, and oral surgery. Briefly, technical considerations related to printers and CAD software, which were the main challenges in the last ten years, are now nearly trivial questions. The central current issues when planning the implementation of an in-house 3D-printing platform are economic and regulatory. Successful in-house 3D platforms rely on close collaborations between health professionals and engineers, backed by regulatory and logistic specialists. Several large-scale academic projects across France will soon provide definitive answers to governance and economical questions related to the use of in-house 3D printing.

Use of Dental Impression Silicone to Fabricate Simple Surgical Guides in Mandibular Reconstruction

BACKGROUND

Several recent reports have described the development and use of three-dimensional (3D) printed surgical osteotomy guides. However, these methods: are usually costly. Here, we introduce a novel method of manufacturing surgical guides built from inexpensive, easy-to-use, and sterilizable dental impression silicone.

METHODS

Mandibular and fibular models were prepared using a 3D printer for 10 patients undergoing free fibula flap transfer after mandibular resection. During preoperative simulation surgery, Protesil labor, a dental silicone, was molded to the same size as the fibular models to act as surgical guides.

RESULTS

The authors compared pre- and post-operative bone angles and bone lengths for all cases using simulation surgery models and postoperative 3D computed tomography. Mean bone angle difference was 2.6° and mean bone length difference was 1.7 mm. Cost of the dental silicone was approximately US$5/patient.

CONCLUSIONS

In our series this method allowed the surgeon to perform an accurate osteotomy, inexpensively and time-efficiently.