Dental Versus Zygomatic Implants in the Treatment of Maxillectomy: A Finite Element Analysis.

This study analyzed the stress distributions on zygomatic and dental implants placed in the zygomatic bone, supporting bones, and superstructures under occlusal loads after maxillary reconstruction with obturator prostheses. A total of 12 scenarios of 3-dimensional finite element models were constructed based on computerized tomography scans of a hemimaxillectomy patient. Two obturator prostheses were analyzed for each model.

A Comparative Analysis of Deep Learning-Based Approaches for Classifying Dental Implants Decision Support System.

This study aims to provide an effective solution for the autonomous identification of dental implant brands through a deep learning-based computer diagnostic system. It also seeks to ascertain the system's potential in clinical practices and to offer a strategic framework for improving diagnosis and treatment processes in implantology. This study employed a total of 28 different deep learning models, including 18 convolutional neural network (CNN) models (VGG, ResNet, DenseNet, EfficientNet, RegNet, ConvNeXt) and 10 vision transformer models (Swin and Vision Transformer).

Dental versus zygomatic implants in the treatment of maxillectomy: a finite element analysis.

Purpose: This study analyzed the stress distributions on zygomatic and dental implants placed in the zygomatic bone, supporting bones, and superstructures under occlusal loads after maxillary reconstruction with obturator prostheses.

Materials And Methods: 12 scenarios of three-dimensional finite element models were constructed based on computed tomography scans of a patient who had hemimaxillectomy. Two obturator prostheses were analyzed for each model.

A robust deep learning model for the classification of dental implant brands.

Objective: In cases where the brands of implants are not known, treatment options can be significantly limited in potential complications arising from implant procedures. This research aims to explore the application of deep learning techniques for the classification of dental implant systems using panoramic radiographs. The primary objective is to assess the superiority of the proposed model in achieving accurate and efficient dental implant classification.

Finite Element Analysis of the Stress Distribution Associated With Different Implant Designs for Different Bone Densities.

Purpose: The main objective of this study was to investigate the influence of implant design, bone type, and abutment angulation on stress distribution around dental implants.

Materials And Methods: Two implant designs with different thread designs, but with the same length and brand were used. The three-dimensional geometry of the bone was simulated with four different bone types, for two different abutment angulations.

Dental Implant-Supported Prosthetic Rehabilitation With Custom Attachment in a Patient With Partial Maxillectomy Defect Because of Osteosarcoma: A Case Report.

Prosthetic rehabilitation in maxillectomy patients aims to separate the oral and nasal cavities to provide adequate articulation, restore the contour of the midface, and provide acceptable aesthetic results. This clinical case report describes prosthetic rehabilitation via placement of dental implants in the zygomatic bone in a patient who underwent partial maxillectomy because of osteosarcoma. The success of obturator placement after maxillectomy requires retention by the surrounding dental tissue or dental implants.

A 5-Year Retrospective Study Evaluating Periodontal Health and Oral Health-Related Quality of Life of Implant-Supported Overdentures With Locator and Magnetic Attachments.

This study compared peri-implant vertical bone loss, the periodontal index, prosthodontic maintenance requirements and oral health-related quality of life (OHQoL) of patients using mandibular implant-supported overdentures with 2 different attachment systems after an average of 5 years of use. Sixteen mandibular overdenture patients with magnet attachments (group 3), 24 with implant-supported mandibular overdentures with Locator attachments (group 2), and 25 conventional complete denture patients (group 1) were included in the study. The existing at least 5 years old dentures of all patients were evaluated for prosthodontic maintenance by the same prosthodontist and the patients were administered the oral health impact profile-14-Turkish version (OHIP-TR-14) questionnaire.

Evaluation of Oral Stereognosis in Relation to Tactile Ability and Patient Satisfaction.

We investigated the oral stereognostic ability (OSA) of dentate individuals, conventional complete denture patients, and maxillary implant-supported denture patients with bar attachments. Stereognosis tests were carried out, and the relationship between OSA and patient satisfaction was assessed with a satisfaction survey: the Turkish version of the oral health impact profile-14 (OHIP-TR-14). To compare differences in oral sensory function among individuals with natural dentition, complete denture wearers, and maxillary implant-supported denture wearers, tactile awareness (thickness perception threshold) and pressure awareness (threshold of lateral loading) were assessed.