Background: Cephalometric analysis has long been, and still is one of the most important tools in evaluating craniomaxillofacial skeletal profile. To perform this, manual tracing of x-ray film and plotting landmarks have been required. This procedure is time-consuming and demands expertise. In these days, computerized cephalometric systems have been introduced; however, tracing and plotting still have to be done on the monitor display. Artificial intelligence is developing rapidly. Deep learning is one of the most evolving areas in artificial intelligence. The authors made an automated landmark predicting system, based on a deep learning neural network. Methods: On a personal desktop computer, a convolutional network was built for regression analysis of cephalometric landmarks’ coordinate values. Lateral cephalogram images were gathered through the internet and 219 images were obtained. Ten skeletal cephalometric landmarks were manually plotted and coordinate values of them were listed. The images were randomly divided into 153 training images and 66 testing images. Training images were expanded 51 folds. The network was trained with the expanded training images. With the testing images, landmarks were predicted by the network. Prediction errors from manually plotted points were evaluated. Results: Average and median prediction errors were 17.02 and 16.22 pixels. Angles and lengths in cephalometric analysis, predicted by the neural network, were not statistically different from those calculated from manually plotted points. Conclusion: Despite the variety of image quality, using cephalogram images on the internet is a feasible approach for landmark prediction.
Arterial and venous anatomy and their relation to the anterolateral thigh flap were examined in 10 specimens of six fresh cadavers in which radiopaque materials were injected into both the arterial and venous systems. Territories and positions of individual perforating arteries were measured, and the venous drainage pathway of the flap was analyzed. All specimens were radiographed stereoscopically to observe the three-dimensional structure of the arteries and veins. The territory of each perforating artery was smaller than expected. Most of the venous blood that had perfused the dermis was considered to pool in a polygonal venous network located in the skin layer and to enter the descending branch of the lateral circumflex femoral artery through large descending veins. The venous territories were considered different from the arterial territories. The findings in this study suggest that the design of the anterolateral thigh flap should be based on the venous architecture rather than on the arterial architecture and that the flap survival rate might be improved if thinning is performed appropriately.
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