In this study, we used panoramic X-ray images to classify and clarify the accuracy of different dental implant brands via deep convolutional neural networks (CNNs) with transfer-learning strategies. For objective labeling, 8859 implant images of 11 implant systems were used from digital panoramic radiographs obtained from patients who underwent dental implant treatment at Kagawa Prefectural Central Hospital, Japan, between 2005 and 2019. Five deep CNN models (specifically, a basic CNN with three convolutional layers, VGG16 and VGG19 transfer-learning models, and finely tuned VGG16 and VGG19) were evaluated for implant classification. Among the five models, the finely tuned VGG16 model exhibited the highest implant classification performance. The finely tuned VGG19 was second best, followed by the normal transfer-learning VGG16. We confirmed that the finely tuned VGG16 and VGG19 CNNs could accurately classify dental implant systems from 11 types of panoramic X-ray images.

SummaryMaxillofacial osteosynthetic surgeries require stable fixation for uneventful boney healing and optimal remodeling. Although conventional titanium plates and screws for osteofixation are considered the gold standard for rigid fixation in maxillofacial surgeries, bioresorbable implants of plates and screw systems are commonly used for various maxillofacial osteosynthetic surgeries such as orthognathic surgery, maxillofacial fractures, and reconstructive surgery. Titanium plates are limited by their palpability, mutagenic effects, and interference with imaging, which may lead to the need for subsequent removal; the use of a biologically resorbable osteofixation system could potentially address these limitations. However, several problems remain including fundamental issues involving decreased mechanical strength and stability, slow biodegradation, complex procedures, and the available bioresorbable implant materials. Major advances in bioresorbable plate systems have been made with the use of bioactive/resorbable osteoconductive materials and an accelerator of bioresorption, such as polyglycolic acid. This report presents an overview of currently available resorbable implant materials and their applications, with a focus on recent innovative advances and new developments in this field.

This study considers the use of deep learning to diagnose osteoporosis from hip radiographs, and whether adding clinical data improves diagnostic performance over the image mode alone. For objective labeling, we collected a dataset containing 1131 images from patients who underwent both skeletal bone mineral density measurement and hip radiography at a single general hospital between 2014 and 2019. Osteoporosis was assessed from the hip radiographs using five convolutional neural network (CNN) models. We also investigated ensemble models with clinical covariates added to each CNN. The accuracy, precision, recall, specificity, negative predictive value (npv), F1 score, and area under the curve (AUC) score were calculated for each network. In the evaluation of the five CNN models using only hip radiographs, GoogleNet and EfficientNet b3 exhibited the best accuracy, precision, and specificity. Among the five ensemble models, EfficientNet b3 exhibited the best accuracy, recall, npv, F1 score, and AUC score when patient variables were included. The CNN models diagnosed osteoporosis from hip radiographs with high accuracy, and their performance improved further with the addition of clinical covariates from patient records.

Introduction:OSTEOTRANS MX (Takiron Co, Ltd, Osaka, Japan) is a resorbable osteosynthetic material composed of an unsintered hydroxyapatite/poly-l-lactide composite, and its osteoconductive capacity has been documented. The authors here report their clinical experience using OSTEOTRANS MX.Methods:The authors treated 35 patients (19 men, 16 women; age, 14–88 years; mean ± standard deviation, 38.4 ± 19.9 years) with maxillofacial fractures. The authors used standard surgery to stabilize fractures in all patients, fitting resorbable plates (thickness, 1.0 or 1.4 mm) and screws (diameter, 2 mm) according to Arbeitsgemeinschaft für Osteosynthesefragen/Association (AO) for the Study of Internal Fixation guidelines.Results:All patients eventually achieved satisfactory healing with favorable restoration of form and function without foreign body reaction. Complications occurred in 3 patients—plate exposure in 2 and discomfort in 1. However, fracture sites healed in all patients. Scanning electron microscopy revealed that the devices bonded directly to the bone without interposition of nonmineralized tissue.Conclusion:OSTEOTRANS MX is a useful material with few complications. Its osteoconductive bioactivity is advantageous for the early functional improvement of maxillofacial fractures.