Evaluating the Accuracy and Reliability of Blowout Fracture Area Measurement Methods: A Review and the Potential Role of Artificial Intelligence
Authors:
Kang, D.
Abstract:
Blowout fractures are a common type of facial injury that requires accurate measurement of the fracture area for proper treatment planning. This systematic review aimed to summarize and evaluate the current methods for measuring blowout fracture areas and explore the potential role of artificial intelligence (AI) in enhancing accuracy and reliability. A comprehensive search of the PubMed database was conducted, focusing on studies published since 2000 that investigated methods for measuring blowout fracture area using computed tomography scans. The review included 20 studies, and the results showed that automatic methods, such as computer-aided measurements and computed tomography-based volumetric analysis, provide higher accuracy and reliability compared with manual and semiautomatic techniques. Standardizing the method for measuring blowout fracture areas can improve clinical decision-making and facilitate outcome comparison across studies. Future research should focus on developing AI models that can account for multiple factors, including fracture area and herniated tissue volume, to enhance their accuracy and reliability. Integration of AI models has the potential to improve clinical decision-making and patient outcomes in the assessment and management of blowout fractures.
Diseases of and symptoms related to the musculoskeletal system and connective tissue Injury, poisoning and certain other consequences of external causes