骶髂关节炎
医学
骶髂关节
临床实习
医学物理学
强直性脊柱炎
人工智能
可解释性
医学影像学
物理医学与康复
接头(建筑物)
梅德林
放射科
协议(科学)
计算机科学
磁共振成像
物理疗法
作者
Robert George William Lambert,Matthew Li,Anne Grethe Jurik
标识
DOI:10.1097/bor.0000000000001163
摘要
PURPOSE OF REVIEW: Recently reported criteria are more stringent for classification of axial spondyloarthritis (axSpA) in the absence of positive imaging. This places increased reliance on the accuracy of sacroiliac joint (SIJ) imaging. This review highlights some of the key challenges to bringing advances in SIJ imaging to clinical practice. RECENT FINDINGS: The first international consensus for an MRI acquisition protocol for sacroiliitis, published in 2024, defines how the sequences should be orientated, and which sequences are required to identify various lesions that may be seen in inflammatory sacroiliitis and degeneration. However, as anatomical and physiological variation and degeneration are very common in the SIJ, new techniques are not necessarily specific for sacroiliitis and may be more sensitive to changes in the SIJ regardless of cause. Artificial intelligence techniques are currently in use for improvement in image acquisition, but models used for enhancement of diagnostic ascertainment still need development and validation. SUMMARY: New techniques, especially adherence to a recommended MRI protocol, are essential for accurate assessment of sacroiliitis. However, the introduction of new techniques to clinical practice must be accompanied by the appropriate education to assist less experienced observers with appropriate interpretation of novel images.
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