L.S. Gensler, MD, Department of Medicine, Division of Rheumatology, University of California, San Francisco, California, USA;
L. Jans, MD, PhD, Department of Radiology and Medical Imaging, Ghent University Hospital, Ghent, Belgium.
J Rheumatol. 2024 Dec 1;51(12):1241-1246. doi: 10.3899/jrheum.2024-0937.
Imaging biomarkers in axial spondyloarthritis (axSpA) are currently the most specific biomarkers for the diagnosis of this condition. Despite advances in imaging, from plain radiographs-which detect only damage-to magnetic resonance imaging (MRI)-which identifies disease activity and structural change-there are still many challenges that remain. Imaging in sacroiliitis is characterized by active and structural changes. Current classification criteria stress the importance of bone marrow edema (BME); however, BME can occur in various diseases, mechanical conditions, and healthy individuals. Thus, the identification of structural lesions such as erosion, subchondral fat, backfill, and ankylosis is important to distinguish from mimics on differential diagnosis. Various imaging modalities are available to examine structural lesions, but computed tomography (CT) is considered the current reference standard. Nonetheless, recent advances in MRI allow for direct bone imaging and the reconstruction of CT-like images that can provide similar information. Therefore, the ability of MRI to detect and measure structural lesions is strengthened. Here, we present an overview of the spectrum of current and cutting-edge techniques for SpA imaging in clinical practice; namely, we discuss the advantages, disadvantages, and usefulness of imaging in SpA through radiography, low-dose and dual-energy CT, and MRI. Cutting-edge MRI sequences including volumetric interpolated breath-hold examination, ultrashort echo time, zero echo time, and deep learning-based synthetic CT that creates CT-like images without ionizing radiation, are discussed. Imaging techniques allow for quantification of inflammatory and structural lesions, which is important in the assessment of treatment response and disease progression. Radiographic damage is poorly sensitive to change. Artificial intelligence has already revolutionized radiology practice, including protocolization, image quality, and image interpretation.
影像学生物标志物在中轴型脊柱关节炎（axSpA）中是目前最特异的诊断此类疾病的生物标志物。尽管影像学技术不断进步，从仅能检测到损伤的普通 X 线摄影到能够识别疾病活动和结构改变的磁共振成像（MRI），但仍存在许多挑战。在骶髂关节炎的影像学表现为既有活动性改变也有结构性改变。目前的分类标准强调骨髓水肿（BME）的重要性；然而，BME 可发生于各种疾病、机械状况和健康个体中。因此，识别侵蚀、软骨下脂肪、填充和强直等结构性病变对于鉴别诊断中的类似物很重要。有多种影像学方法可用于检查结构性病变，但计算机断层扫描（CT）被认为是目前的参考标准。尽管如此，MRI 的最新进展允许直接进行骨成像和 CT 样图像的重建，这些可以提供类似的信息。因此，MRI 检测和测量结构性病变的能力得到了增强。在这里，我们对当前和前沿的 SpA 影像学技术在临床实践中的应用进行了概述；即，我们讨论了 X 线摄影、低剂量和双能 CT 以及 MRI 在 SpA 中的优缺点和实用性。讨论了包括容积内插呼吸门控检查、超短回波时间、零回波时间和基于深度学习的合成 CT 等前沿 MRI 序列，这些序列可以在不产生电离辐射的情况下创建 CT 样图像。影像学技术可用于量化炎症和结构性病变，这在评估治疗反应和疾病进展方面很重要。放射学损害对变化的敏感性较差。人工智能已经彻底改变了放射科的实践，包括方案制定、图像质量和图像解释。
