Utility of multi-parametric quantitative magnetic resonance imaging of the lacrimal gland for diagnosing and staging Graves' ophthalmopathy. Issue 141 (August 2021) - Wu, Dide; Zhu, Hongzhang; Hong, Shubin; Li, Bin; Zou, Mengsha; Ma, Xiaoyi; Zhao, Xiaojuan; Wan, Pengxia; Yang, Zhiyun; Li, Yanbing; Xiao, Haipeng
Highlights: Multi-parametric MRI features of the lacrimal gland (LG) are significantly altered in Graves ophthalmopathy (GO). T2 and ΔT1 values of lacrimal gland are valuable parameters for diagnosis and activity evaluation of GO. T2 of LG showed ideal practical utility for staging GO. Abstract: Purpose: To explore radiological changes of the lacrimal gland (LG) in Graves' ophthalmopathy (GO) based on multi-parametric quantitative MRI and its clinical utility in LG diagnosis and activity in GO. Methods: We enrolled 99 consecutive patients with GO (198 eyes) and 12 Graves' Disease (GD) patients (24 eyes) from July 2018 to June 2020. Clinical, laboratory, and MRI data were collected at the first visit. Based on clinical activity scores, eyes with GO were subdivided into active and inactive groups. T2-relaxation time (T2) and the absolute reduction in T1-relaxation time (ΔT1) were determined. After MRI and processing, we performed descriptive data analysis and group comparisons. Novel logistic regression predictive models were developed for diagnosing and staging GO. Diagnostic performance of MRI parameters and models was assessed by receiver operating characteristic curve analysis. Results: LG in GO group had significantly higher T2 and ΔT1 values than the GD group [106.25(95.30, 120.21) vs. 83.35(78.15, 91.45), P< 0.001, and 662.62(539.33, 810.95) vs. 547.35(458.62, 585.57), P = 0.002, respectively]. The GO group had higher T2 of LG indicating higher disease activity [110.93(102.54, 127.67) vs. 93.29(87.06, 101.96), P < 0.001]. Combining T2 and ΔT1 values of LG, Model I had higher diagnostic value for distinguishing GO from GD (AUC=0.94, 95 %CI: 0.89, 0.99, P< 0.001). Meanwhile, T2 of LG had higher diagnostic value for grading GO activity (AUC = 0.84, 95 %CI: 0.76, 0.92, P< 0.001). Conclusions: Multi-parametric quantitative MRI parameters of the LG in GO were significantly altered. Novel models combining LG T2 and ΔT1 values showed excellent predictive performances in diagnosing GO. Furthermore, T2 of LG showed practical utility for staging GO.