Chan L-L, Tan H-E, Fook-Chong S, Teo T-H, Lim L-H, Seah L-L
Department of Diagnostic Radiology, Singapore General Hospital, Singapore.
AJNR Am J Neuroradiol. 2009 Mar;30(3):597-602. doi: 10.3174/ajnr.A1413. Epub 2009 Jan 15.
Optic neuropathy (ON), a serious complication of Graves ophthalmopathy, is often subclinical and masked by symptoms of orbitopathy. We examined herein bony and soft-tissue CT features associated with ON, including an angular assessment of orbital apex capacity, and their usefulness in the risk prediction of ON.
The CT scans of 41 patients with Graves ophthalmopathy (17 men, 24 women; mean age, 49.1 years) clinically diagnosed with (19 patients, 32 orbits) or without ON were evaluated by 2 independent raters. Quantitative linear and angular measurements of the orbital structures and bony walls and categoric scores of apical crowding and intracranial fat prolapse were assessed on a clinical workstation. Inter- and intrarater variability of these features was determined. The CT features of the 2 patient groups were compared, and multivariate logistic regression analysis was performed to evaluate the predictive features of ON.
Bony orbital angles (P < .005), length of the lateral orbital wall (P < .05), muscular diameters (P < .0005), muscular bulk of the medial rectus muscle relative to the bony orbit (P < .05), and apical crowding (P < .0005) were associated with clinical ON. Stepwise multivariate logistic regression analysis revealed the muscle diameter index and medial and lateral wall angles to be independent predictors. Combining these in a single multivariate equation yielded sensitivity, specificity, and positive and negative predictive values of 73%, 90%, 82%, and 85%, respectively.
Orbital wall angles, especially the medial wall, and muscular enlargement are independent risk predictors.
视神经病变(ON)是格雷夫斯眼病的一种严重并发症,通常为亚临床状态,并被眼眶病症状所掩盖。我们在此研究了与ON相关的骨和软组织CT特征,包括眶尖容量的角度评估,以及它们在ON风险预测中的作用。
由2名独立评估者对41例临床诊断为有(19例患者,32个眼眶)或无ON的格雷夫斯眼病患者(17例男性,24例女性;平均年龄49.1岁)的CT扫描进行评估。在临床工作站上评估眼眶结构和骨壁的定量线性和角度测量,以及尖部拥挤和颅内脂肪脱垂的分类评分。确定这些特征在评估者间和评估者内的变异性。比较两组患者的CT特征,并进行多因素逻辑回归分析以评估ON的预测特征。
眼眶骨角(P <.005)、眶外侧壁长度(P <.05)、肌肉直径(P <.0005)、相对于眼眶骨的内直肌肌肉体积(P <.05)和尖部拥挤(P <.0005)与临床ON相关。逐步多因素逻辑回归分析显示肌肉直径指数以及内侧和外侧壁角度是独立的预测因素。将这些因素组合在一个多变量方程中,得出的敏感度、特异度、阳性预测值和阴性预测值分别为73%、90%、82%和85%。
眼眶壁角度,尤其是内侧壁角度和肌肉增大是独立的风险预测因素。