Growth Evaluation After Costochondral Graft Combined With Functional Appliance in Children With Temporomandibular Joint Ankylosis.

The treatment of temporomandibular joint (TMJ) ankylosis in children is a great challenge for surgeons. Costochondral graft (CCG) is a common method of reconstructing the TMJ in children. However, the growth pattern of CCG is unpredictable. In this study, we introduced a surgical-orthodontic approach and evaluated the growth results of the mandible and maxilla in children with TMJ ankylosis through 3-dimensional computed tomography measurements. A prospective cohort study was conducted on child patients diagnosed as having TMJ ankylosis between September 1, 2018 and June 1, 2020. Computer-aided virtual mandibular position guided the CCG, and removable functional appliance was used after surgery. The maximal incisal opening (MIO), the maxilla height, and the length of mandibular ramus were determined. Paired t test was performed to analyze the differences among various stages. Six patients (3 females, 3 males; aged 6-9 y) were included in this study. MIO was 12.4 mm before surgery and improved to 36.8 mm after 42.8 months' follow-up. Mandible length increased by 5.1 mm in the affected side and by 5.3 mm in the unaffected side, without significant difference. The affected maxilla height increased by 6.7 mm, which was more than 5.0 mm in the unaffected side. In conclusion, continued growth of mandible and maxilla can be achieved through CCG combined with functional appliance treatment for children TMJ ankylosis.

Craniomaxillofacial Bone Segmentation and Landmark Detection Using Semantic Segmentation Networks and an Unbiased Heatmap.

Craniomaxillofacial (CMF) surgery always relies on accurate preoperative planning to assist surgeons, and automatically generating bone structures and digitizing landmarks for CMF preoperative planning is crucial. Since the soft and hard tissues of the CMF regions possess complicated attachment, segmenting the CMF bones and detecting the CMF landmarks are challenging problems. In this study, we proposed a semantic segmentation network to segment the maxilla, mandible, zygoma, zygomatic arch, and frontal bones. Then, we obtained the minimum bounding box around the CMF bones. After cropping, we used the top-down heatmap landmark detection network, similar to the segmentation module, to identify 18 CMF landmarks from the cropping patch. In addition, an unbiased heatmap encoding method was proposed to generate actual landmark coordinates in the heatmap. To overcome quantization effects in the heatmap-based landmark detection networks, the distribution-prior coordinate representation of medical landmarks (DCRML) was proposed to utilize the prior distribution of the encoding heatmap, approximating the accurate landmark coordinates in heatmap decoding by Taylor's theorem. The encoding and decoding method can easily contribute to other existing landmark detection frameworks based on heatmaps; consequently, these approaches can readily benefit without changing model structure. We used prior segmentation knowledge to enhance the semantic information around the landmarks, increasing landmark detection accuracy. The proposed framework was evaluated by 100 healthy persons and 86 patients from multicenter cooperation. The mean Dice score of our proposed segmentation network achieved over 88 %; in particular, the mandible accuracy was approximately 95%. The mean error of landmarks was 1.84 ±1.32 mm.

Reconstruction of the temporomandibular joint using a vascularized medial femoral condyle osteocartilaginous flap: an experimental investigation in miniature pigs.

BACKGROUND: Reconstruction of the temporomandibular joint (TMJ) is a significant challenge in maxillofacial surgery. A vascularized medial femoral condyle (MFC) osteocartilaginous flap is a good choice for TMJ reconstruction. In this study, we evaluated the radiographic and histological changes of MFC after TMJ reconstruction. METHODS: A ramus-condyle unit (RCU) defect was created unilaterally in five adult male Bama miniature pigs. The ipsilateral vascularized MFC osteocartilaginous flap was used to reconstruct the TMJ, and the non-operative sides served as controls. Multislice spiral computed tomography (CT) was performed preoperatively, immediately postoperatively, and at two weeks, three months, and six months postoperatively. Three animals were euthanized at 6 months postoperatively. Their reconstructed condyles, natural condyles and the MFCs on the opposite side were collected and subjected to µCT and histological evaluation. RESULTS: In the miniature pigs, the vascularized MFC osteocartilaginous flap was fused to the mandible, thus restoring the structure and function of the RCU. The postoperative radiographic changes and histological results showed that the reconstructed condyle was remodeled toward the natural condyle, forming a similar structure, which was significantly different from the MFC. CONCLUSIONS: In miniature pigs, the RCU can be successfully reconstructed by vascularized osteocartilaginous MFC flap. The reconstructed condyle had almost the same appearance and histological characteristics as the natural condyle.

Is Convolutional Neural Network Accurate for Automatic Detection of Zygomatic Fractures on Computed Tomography?

PURPOSE: Zygomatic fractures involve complex anatomical structures of the mid-face and the diagnosis can be challenging and labor-consuming. This research aimed to evaluate the performance of an automatic algorithm for the detection of zygomatic fractures based on convolutional neural network (CNN) on spiral computed tomography (CT). MATERIALS AND METHODS: We designed a cross-sectional retrospective diagnostic trial study. Clinical records and CT scans of patients with zygomatic fractures were reviewed. The sample consisted of two types of patients with different zygomatic fractures statuses (positive or negative) in Peking University School of Stomatology from 2013 to 2019. All CT samples were randomly divided into three groups at a ratio of 6:2:2 as training set, validation set, and test set, respectively. All CT scans were viewed and annotated by three experienced maxillofacial surgeons, serving as the gold standard. The algorithm consisted of two modules as follows: (1) segmentation of the zygomatic region of CT based on U-Net, a type of CNN model; (2) detection of fractures based on Deep Residual Network 34(ResNet34). The region segmentation model was used first to detect and extract the zygomatic region, then the detection model was used to detect the fracture status. The Dice coefficient was used to evaluate the performance of the segmentation algorithm. The sensitivity and specificity were used to assess the performance of the detection model. The covariates included age, gender, duration of injury, and the etiology of fractures. RESULTS: A total of 379 patients with an average age of 35.43 ± 12.74 years were included in the study. There were 203 nonfracture patients and 176 fracture patients with 220 sites of zygomatic fractures (44 patients underwent bilateral fractures). The Dice coefficient of zygomatic region detection model and gold standard verified by manual labeling were 0.9337 (coronal plane) and 0.9269 (sagittal plane), respectively. The sensitivity and specificity of the fracture detection model were 100% (p＞.05). CONCLUSION: The performance of the algorithm based on CNNs was not statistically different from the gold standard (manual diagnosis) for zygomatic fracture detection in order for the algorithm to be applied clinically.

Accurate Reconstruction of Mandibular Defects With Vascularized Bone Flaps Through Utilization of Mandible Space-Retention Guides.

PURPOSE: Comprehensive evaluation of the effects of using computer-aided design and space retention guide technology to reconstruct mandibular defects using vascularized autogenous bone flaps. METHOD: This study included 8 patients who received autogenous bone flaps (2 cases of vascularized fibula flaps and 6 cases of vascularized iliac flaps) for mandibular defect reconstruction at Peking University School and Hospital of Stomatology, from July 2018 to May 2021. All patients received digital surgery planning, computer aided design/computer aided manufacture, surgical guide technique for the removal of diseased bone segments, as well as vascularized fibular flap/iliac flap reconstruction. Three-dimensional deviations were analyzed after the operation. RESULT: The mandibular defects of all 8 patients were successfully reconstructed using the vascularized fibular flap/iliac bone flap. There were no serious complications at either the donor site or recipient site during our follow-up. The average three-dimensional deviation of all 8 patients was 1.92 mm, based on comparisons of preoperative design and actual postoperative computed tomography. CONCLUSION: Utilizing computer aided design/computer aided manufacture, we designed a new mandibular space-retention guide, which can accurately translate the preoperative digital design plan to real-time surgery with satisfactory accuracy and efficacy.

Statistical and individual characteristics-based reconstruction for craniomaxillofacial surgery.

PURPOSE: In craniomaxillofacial (CMF) surgery planning, a preoperative reconstruction of the CMF reference model is crucial for surgical restoration, especially the reconstruction of bilateral defects. Current reconstruction algorithms mainly generate reference models from the image analysis aspect, however, clinical indicators of the CMF reference model mostly consider the distribution of anatomical landmarks. Generating a reference model with optimal clinical evaluation helps promote the feasibility of an algorithm. METHODS: We first build a dataset with 100 normal skull models and then calculate a statistical shape model (SSM) and the distribution of normal cephalometric values, which indicate the statistical features of a population. To further generate personalized reference models, we apply non-rigid registration to align the SSM with the defect skull model. An evaluation standard to select the optimal reference model considers both global performance and anatomical evaluation. Moreover, we develop a landmark detection network to improve the automatic level of the algorithm. RESULTS: The proposed method performs better than methods including Iterative Closest Point and SSM. From a global evaluation aspect, the results show that the RMSE between the reference model and the ground truth is [Formula: see text] mm, the percentage of vertices with error below 2 mm is [Formula: see text]% and the average faces distance is [Formula: see text] mm (better than the state-of-the-art method). From the anatomical evaluation aspect, the target registration error between the landmark pairs is [Formula: see text] mm. In addition, the clinical application confirms that the reference model can meet clinical requirements. CONCLUSION: To the best of our knowledge, we propose the first CMF reconstruction method considering the global performance of reconstruction and anatomically local evaluation from clinical experience. Simulated experiments and clinical cases prove the general applicability and strength of the method.

Detection and classification of mandibular fracture on CT scan using deep convolutional neural network.

OBJECTIVES: This study aimed to evaluate the accuracy and reliability of convolutional neural networks (CNNs) for the detection and classification of mandibular fracture on spiral computed tomography (CT). MATERIALS AND METHODS: Between January 2013 and July 2020, 686 patients with mandibular fractures who underwent CT scan were classified and annotated by three experienced maxillofacial surgeons serving as the ground truth. An algorithm including two convolutional neural networks (U-Net and ResNet) was trained, validated, and tested using 222, 56, and 408 CT scans, respectively. The diagnostic performance of the algorithm was compared with the ground truth and evaluated by DICE, accuracy, sensitivity, specificity, and area under the ROC curve (AUC). RESULTS: One thousand five hundred six mandibular fractures in nine subregions of 686 patients were diagnosed. The DICE of mandible segmentation using U-Net was 0.943. The accuracies of nine subregions were all above 90%, with a mean AUC of 0.956. CONCLUSIONS: CNNs showed comparable reliability and accuracy in detecting and classifying mandibular fractures on CT. CLINICAL RELEVANCE: The algorithm for automatic detection and classification of mandibular fractures will help improve diagnostic efficiency and provide expertise to areas with lower medical levels.

Automatic virtual reconstruction of maxillofacial bone defects assisted by ICP (iterative closest point) algorithm and normal people database.

OBJECTIVES: The aim of this study was to propose and validate an automatic approach based on iterative closest point algorithm for virtual complement and reconstruction for maxillofacial bone defects. MATERIALS AND METHODS: A 3D craniomaxillofacial database of normal Chinese people including 500 skull models was established. Modified iterative closest point (ICP) algorithm was developed to complete bone defects automatically. The performances were evaluated by two approaches: (1) model experiment, virtual bony defects were created on 30 intact normal skull models not included in the database. For each defect model, the algorithm was applied to select the reference skull model from the database. 3-Dimensional and 2-dimensional comparison were conducted to evaluate the error between reference skull model with original intact model. Root mean square error (RMSE) and processing time were calculated. (2) Clinical application, the algorithm was utilized to assist reconstruction of 5 patients with maxillofacial bone defects. The symmetry of post-operative skull model was evaluated by comparing with its mirrored model. RESULTS: The algorithm was tested on an CPU with 1.80 GHz and average processing time was 493.5 s. (1) Model experiment, the average root-mean-square deviation of defect area was less than 2 mm. (2) Clinical application, the RMSE of post-operative skull and its mirrored model was 1.72 mm. CONCLUSION: It is feasible using iterative closest point algorithm based on normal people database to automatically predict the reference data of missing maxillofacial bone. CLINICAL RELEVANCE: An automated approach based on ICP algorithm and normal people database for maxillofacial bone defect reconstruction has been proposed and validated.

New series of surgical design for anterior maxillary reconstruction with deep circumflex iliac artery flap.

Microsurgical reconstruction for anterior maxillary defects presents a surgical challenge. The objective of this study was to ascertain the feasibility of a new series of intraoral surgical approach using deep circumflex iliac artery (DCIA) flap to achieve functional reconstruction for anterior maxillary defects. Two male patients with anterior maxillary defects (Brown Class IC) were treated in this study. Both patients underwent computer-assisted maxillary reconstruction with a DCIA flap (with pedicle positioning laterally to the bony flap) using intraoral anastomosis techniques. The overall DCIA flap survival rate was 100% and mucosa was all healed uneventfully. One patient received dental implantation and loaded with prosthetic superstructures. Both patients were satisfied with their postoperative oral function and appearance. This study illustrated a new and feasible series of surgical design for anterior maxillary bone defect reconstruction with DCIA flaps and intraoral anastomosis assisted by digital techniques.

Correlation Between Soft and Hard Tissue Changes in the Zygomaticomaxillary Region After Bone Contouring Surgery for Fibrous Dysplasia-A Preliminary Study.

PURPOSE: The purpose of the present study was to determine the correlation between the soft and hard tissue changes in the zygomaticomaxillary region after facial bone contouring surgery for patients with craniofacial fibrous dysplasia (FD). MATERIALS AND METHODS: The present study was a retrospective case series that reviewed the cases of 13 patients with craniofacial FD in the zygomaticomaxillary region who had undergone navigation-guided facial bone contouring surgery from January 2013 to October 2017. Pre- and postoperative computed tomography (>3 months) were collected. The pre- and postoperative soft and hard tissues were placed in the same spatial coordinate system using multipoint registration to measure the distances between the corresponding pre- and postoperative points of the soft and hard tissues. The outcome variable was the corresponding soft tissue change. The correlation between the hard and soft tissue changes was obtained using correlation analysis with SPSS software (IBM Corp, Armonk, NY). The linear regression equation of the soft and hard tissue changes was used to predict the corresponding soft tissue changes. RESULTS: The Pearson correlation coefficient of the zygomatic region was 0.954 (P < .001) and the coefficient for the maxillary region was 0.758 (P < .001). The linear regression index (R2) for the zygomatic and maxillary regions was 0.910 (P < .001) and 0.575 (P < .001), respectively. The ß value of the linear regression equation for the zygomatic and maxillary regions was 0.815 (P < .001) and 0.52 (P < .001), respectively. CONCLUSIONS: The soft and hard tissue changes were highly correlated in both the zygomatic area and the maxillary area, and the variance of the maxillary area was slightly greater than that in the zygomatic area. This implied that the change of 1 mm of bone tissue along the tangent direction of the bone contour will cause a change of 0.815 mm in the soft tissue in the zygomatic region and 0.52 mm in soft tissue in the maxillary region.

Reconstruction of Bilateral Post-Traumatic Midfacial Defects Assisted by Three-Dimensional Craniomaxillofacial Data in Normal Chinese people-A Preliminary Study.

PURPOSE: To provide reference data for reconstruction of bilateral midfacial defects for which "mirror technique" cannot be applied. METHODS: The present study included 4 patients (3 males and 1 female) with post-traumatic bilateral midfacial fractures and defects. The most similar model was retrieved from a database of 552 normal Chinese people and used to guide preoperative virtual surgery planning. All patients underwent open reduction, internal fixation, and reconstruction surgery in 1 stage. A custom-made titanium prosthesis was used to repair the defects of frontal and naso-orbital-ethmoid (NOE) region in 1 patient. Two fibular flaps were used to repair the maxillary defects. A deep circumflex iliac artery flap was used to reconstruct large midfacial defects involving the right zygoma. A surgical navigation system was applied in 3 patients. RESULTS: The 4 patients were followed for 6 to 42 months. Two patients had finished all therapies and had satisfactory functional and cosmetic results. The appearance of 1 patient was obviously improved; that patient was still receiving treatment for denture prostheses. One patient had undergone first-stage reconstructive surgery and had normal occlusion at 6 months of follow-up. For 3 patients whose treatment had been assisted by navigation, the average surgical deviation was less than 3 mm (range, 1.5 to 2.2). For the patient whose treatment had not been assisted with navigation, the deviations differed in different areas: 3.47 mm in the right zygomaticomaxillary complex, 5.48 mm in the NOE area, and 5.91 mm in the maxillary area. CONCLUSIONS: For patients with bilateral post-traumatic midfacial defects across the midline, the use of a 3-dimensional craniomaxillofacial database can be considered a feasible method for providing reference data for preoperative planning.