骨盆倾斜
投影(关系代数)
医学
放射科
计算机科学
骨盆
计算机视觉
人工智能
算法
作者
Yuan Chai,A. Mounir Boudali,Sam Khadra,Amrita Dasgupta,Vincent Maes,William L. Walter
标识
DOI:10.1016/j.arth.2023.10.035
摘要
BackgroundPelvic tilt (PT) is a routinely evaluated parameter in hip and spine surgeries, and is usually measured on a sagittal pelvic radiograph. This may not always be feasible due to limitations such as landmark visibility, pelvic anomaly, and hardware presence. Tremendous efforts have been dedicated to using pelvic antero-posterior (AP) radiographs for assessing sagittal PT. Thus, this systematic review aimed to collect these methods and evaluate their performances.MethodsTwo independent reviewers searched the PubMed, Ovid, Cochrane, and Web of Science databases in June 2023 with backward reference trailing (Google Scholar archive). There were 30 studies recruited. Risk of bias was assessed using the prediction model risk of bias assessment tool. The relevant data were tabulated in a standardized form for evaluating either the absolute PT or relative PT. Disagreement was resolved by discussing with the senior author.ResultsThere were 19 parameters from pelvic AP projection images involved, with 4 studies which used artificial intelligence, eyeball, or statistical shape method not involving a specific parameter. In comparing the PT values from pelvic sagittal images with those extrapolated from antero-posterior projection images, the highest correlation coefficient was found to be 0.91. The mean absolute difference (error) was 2.6°, with a maximum error reaching 10.9°. Most studies supported the feasibility of using AP parameters to calculate changes in PT.ConclusionsNo individual AP parameter was found to precisely estimate absolute PT. However, relative PT can be derived by evaluating serial AP radiographs of a patient in varying postures, employing any AP parameters.
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