Dental implant quality registries and databases: A systematic review

Development of a Minimum Data Set for Dental Implants Registry

Objectives: Registries are powerful tools for the collection and distribution of valid and reliable data. The initial step in health information management is to design a minimum data set that can improve the collection of high-quality data from the registry. The present pilot study aimed to determine the optimal minimum data set for dental implants to effectively utilize at Tehran University of Medical Sciences, Tehran, Iran. Materials and Methods: This descriptive cross-sectional study was conducted in 2019 at Tehran University of Medical Sciences. A minimum data set checklist was developed based on our previous systematic review. The content validity of the minimum data set was approved by the recruited experts and the final minimum data set was established using the Delphi technique. Results: The minimum data set for dental implants consists of two separate sections - administrative and clinical data. The administrative portion includes two main segments: patient demographic data and clinic data, consisting of 12 data elements. The clinical part includes five main segments (patient clinical data, implant data, implant complications, implant loss, and implant follow-up), and contains 96 data elements. Conclusion: This study suggests a minimum set of data for dental implants that can aid in efficient management of information, facilitate evidence-based decision-making, and enable high-quality clinical research, evaluation of treatment results, monitoring, and benchmarking of care.

A diagnostic accuracy study on an innovative auto-edge detection technique for identifying simulated implant fractures on radiographic images

Implant fracture is a rare but devastating complication of treatment in partially or fully edentulous patients which requires prompt diagnosis. Nevertheless, studies on defining the most accurate technique for the detection of implant fractures are lacking. In the present study, the Canny edge detection algorithm was applied on multiple radiographic modalities including parallel periapical (PPA), oblique periapical (OPA), and cone beam CT (CBCT) with and without metal artifact reduction (MAR) to examine its accuracy for diagnosis of simulated implant fractures. Radiographs were taken from 24 intact implants and 24 implants with artificially created fractures. Images were evaluated in their original and Canny formats. The accuracy of each radiograph was assessed by comparison with a reference standard of direct observation of the implant. The greatest area under the receiver operating characteristic curve belonged to Canny CBCT with MAR (0.958), followed by original CBCT with MAR (0.917), original CBCT without MAR = Canny CBCT without MAR = Canny OPA (0.875), Canny PPA (0.833), original PPA = original OPA (0.792), respectively. The Canny edge detection algorithm is suggested as an innovative method for accurate diagnosis of clinically suspected implant fractures on CBCT and periapical radiographies.