Objectives: We evaluated the accuracy of computer-assisted mandibular reconstructions.
Patients And Methods: We retrospectively reviewed data for 26 patients who had mandibular reconstruction with a microvascular free fibula flap, January 2015 to June 2018. Postoperative mandible models were obtained from computed tomography scans. After registering the models to the corresponding preoperative plan, we performed comparative measurements. Patients were grouped by condylar involvement and subdivided based on number of fibular segments used for reconstruction. For each segment, we measured length and osteotomy angles. For the final postoperative outcome, we compared intercoronoid, intergonial, and anteroposterior distances and intersegmental plane shift.
Results: Means (SD) for deviation of each osteotomy angle and fibular segment length were 1.98° (2.98) and 1.78 mm (2.69), respectively, remaining constant across subgroups. Other mean values were as follows: intercoronoid distance deviation, 3.86 mm (range, 0.20-11.21 mm); intergonial distance deviation, 3.14 mm (range, 0.05-8.28 mm); anteroposterior distance deviation, 2.92 mm (range, 0.03-8.49 mm); and intersegmental plane shift, 11.00° (range, 2.76-24.15°). Where the condyle was preserved, the intercoronoid and intergonial deviation means differed significantly (respectively 5.02 mm and 4.88 mm, both P < 0.05) for one-segmented and three-segmented fibular reconstructions. Furthermore, reconstructions involving the condylar region compared with condyle preservation showed significantly different intersegmental plane shifts (7.18°; P < 0.05).
Conclusion: Computer-assisted surgery provides cutting guides for obtaining accurate fibular segments, but current fixation methods lead to inaccuracies and reproducibility errors. In multisegmental transfer with condylar involvement, computer-assisted fixation is recommended to ensure accuracy of the preoperative plan.
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http://dx.doi.org/10.1016/j.oraloncology.2019.07.022 | DOI Listing |
Am J Orthod Dentofacial Orthop
February 2025
Department of Orthodontics, Faculty of Dentistry, Çanakkale Onsekiz Mart University, Çanakkale, Turkey.
Introduction: This study aimed to assess the precision of an open-source, clinician-trained, and user-friendly convolutional neural network-based model for automatically segmenting the mandible.
Methods: A total of 55 cone-beam computed tomography scans that met the inclusion criteria were collected and divided into test and training groups. The MONAI (Medical Open Network for Artificial Intelligence) Label active learning tool extension was used to train the automatic model.
Neural Netw
January 2025
School of Cyber Science and Engineering, Xi'an Jiaotong University, China. Electronic address:
Detecting anomalies in attributed networks has become a subject of interest in both academia and industry due to its wide spectrum of applications. Although most existing methods achieve desirable performance by the merit of various graph neural networks, the way they bundle node-affiliated multidimensional attributes into a whole for embedding calculation hinders their ability to model and analyze anomalies at the fine-grained feature level. To characterize anomalies from each feature dimension, we propose Eagle, a deep framework based on bipartitE grAph learninG for anomaLy dEtection.
View Article and Find Full Text PDFSensors (Basel)
January 2025
School of Electronic Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China.
With the advent of the 5G era, high-precision localization based on mobile communication networks has become a research hotspot, playing an important role in indoor emergency rescue in shopping malls, smart factory management and tracking, as well as precision marketing. However, in complex environments, non-line-of-sight (NLOS) propagation reduces the measurement accuracy of 5G signals, causing large deviations in position solving. In order to obtain high-precision position information, it is necessary to recognize the propagation state of the signal before distance measurement or angle measurement.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Institute of Automatic Control, Lodz University of Technology, 90-537 Lodz, Poland.
Warping is a crucial process that connects two main stages of production: yarn manufacturing and fabric creation. Two interrelated parameters affect the efficiency of this technological process: warping speed and the ability to swiftly detect the yarn breaks caused by various defects. The faster a break is detected and the warping machine stopped, the higher the machine's working speed can be.
View Article and Find Full Text PDFThe relevance of posture as a constituent of physical health varies depending on one's explanatory framework of disease. Contrasting perspectives within this discussion refer to optimal biomechanics, but often without consistent meaning. The resulting theoretical confusion presents challenges both for applied research and clinical practice.
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