Cheng Jingyi, Zhang Xiuying, Lian Jianxiu, Piao Zhenyu, Zhou Lingli, Gou Xinyi, Chen Chuhan, Chen Lei, Jiang Ke, Cheng Jin, Ji Linong, Hong Nan
Department of Radiology, Peking University People's Hospital, Beijing, China.
Department of Endocrinology, Peking University People's Hospital, Beijing, China.
Quant Imaging Med Surg. 2023 May 1;13(5):3040-3049. doi: 10.21037/qims-22-814. Epub 2023 Feb 6.
When quantitative magnetic resonance imaging (MRI) is used to assess the activity of Graves' orbitopathy (GO), the examination is generally focused on a specific orbital tissue, especially the extraocular muscles (EOMs). However, GO usually involves the entire intraorbital soft tissue. The aim of this study was to use multiparameter MRI on multiple orbital tissues to distinguish the active and inactive GO.
From May 2021 to March 2022, consecutive patients with GO were prospectively enrolled at Peking University People's Hospital (Beijing, China) and divided into those with active disease and those with inactive disease based on a clinical activity score. Patients then underwent MRI, including sequences of conventional imaging, T1 mapping, T2 mapping, and mDIXON Quant. Width, T2 signal intensity ratio (SIR), T1 values, T2 values, and fat fraction of EOMs, as well as water fraction (WF) of orbital fat (OF), were measured. Parameters were compared between the 2 groups, and a combined diagnostic model was constructed using logistic regression analysis. Receiver operating characteristic analysis was used to test the diagnostic performance of the model.
Sixty-eight patients with GO (27 with active GO, 41 with inactive GO) were included in the study. The active GO group had higher values of EOM thickness, T2 SIR, and T2 values, as well as higher WF of OF. The diagnostic model, which included EOM T2 value and WF of OF, demonstrated a good ability to distinguish between active and inactive GO (area under the curve, 0.878; 95% CI: 0.776-0.945; sensitivity, 88.89%; specificity, 75.61%).
A combined model incorporating the T2 value of EOMs and the WF of OF was able to identify cases of active GO, potentially offering an effective and noninvasive method to assess pathological changes in this disease.
当使用定量磁共振成像（MRI）评估格雷夫斯眼眶病（GO）的活动情况时，检查通常聚焦于特定的眼眶组织，尤其是眼外肌（EOMs）。然而，GO通常累及整个眶内软组织。本研究的目的是利用多参数MRI对多个眼眶组织进行检查，以区分活动期和非活动期GO。
2021年5月至2022年3月，北京大学人民医院（中国北京）前瞻性纳入连续的GO患者，并根据临床活动评分将其分为活动期疾病组和非活动期疾病组。患者随后接受MRI检查，包括传统成像序列、T1 mapping、T2 mapping和mDIXON Quant。测量EOMs的宽度、T2信号强度比（SIR）、T1值、T2值和脂肪分数，以及眶脂肪（OF）的水分数（WF）。比较两组之间的参数，并使用逻辑回归分析构建联合诊断模型。采用受试者工作特征分析来检验模型的诊断性能。
本研究纳入了68例GO患者（27例活动期GO，41例非活动期GO）。活动期GO组的EOM厚度、T2 SIR和T2值以及OF的WF值较高。包含EOM T2值和OF的WF的诊断模型显示出良好的区分活动期和非活动期GO的能力（曲线下面积，0.878；95%CI：0.776-0.945；敏感性，88.89%；特异性，75.61%）。
结合EOMs的T2值和OF的WF值的联合模型能够识别活动期GO病例，可能提供一种有效且无创的方法来评估该疾病的病理变化。
