Radiographic volumetric risk factors for late enophthalmos prediction in orbital blow-out fractures: A retrospective study

Bouet, Benjamin; Schlund, Matthias; Sentucq, Camille; Gryseleyn, Remi; Ferri, Joël; Nicot, Romain

doi:10.1016/j.jcms.2022.05.005

Cited by 3 publications

(1 citation statement)

References 31 publications

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“…All studies used CT scans for imaging, and the measurement methods varied across studies, including manual, semiautomatic, and automatic techniques. Supplemental Table (Supplemental Digital Content, Table 1, http://links.lww.com/SCS/F126) 9–26 provides a summary of the key characteristics of the included studies.…”

Section: Resultsmentioning

confidence: 99%

Evaluating the Accuracy and Reliability of Blowout Fracture Area Measurement Methods: A Review and the Potential Role of Artificial Intelligence

Kang

2023

Journal of Craniofacial Surgery

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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.

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Section: Resultsmentioning

confidence: 99%