Hao Hu1, Lu Chen1, Jiang Zhou1, Wen Chen1, Huan-Huan Chen2, Jiu-Lou Zhang1, Yi-Cheng Hsu3, Xiao-Quan Xu4, Fei-Yun Wu5. 1. Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. 2. Department of Endocrinology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. 3. MR Collaboration, Siemens Healthcare Ltd., Shanghai, China. 4. Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. Electronic address: xiaoquanxu_1987@163.com. 5. Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China. Electronic address: wfydd_njmu@163.com.
Abstract
PURPOSE: To investigate the feasibility of using magnetization transfer (MT) magnetic resonance imaging for evaluating patients with thyroid-associated ophthalmopathy (TAO), and determine its added value for differentiating active from inactive TAO and predicting clinical activity score (CAS), compared with conventional fat-saturated T2-weighted and diffusion-weighted imaging. METHODS: Orbital MT, fat-saturated T2-weighted, and diffusion-weighted imaging of 60 prospectively enrolled consecutive patients with TAO was analyzed. Simplified histogram parameters (mean, max, min) of magnetization transfer ratio (MTR), signal intensity ratio (SIR), and apparent diffusion coefficient (ADC) at extraocular muscles were calculated for each orbit and compared between the active and inactive groups. RESULTS: Intraclass correlation coefficients of MTRs and SIRs were similar (0.802-0.963 vs 0.812-0.974, respectively), followed by those of ADCs (0.714-0.855). Patients with active TAO showed significantly lower MTRs and higher SIRs and ADCs than those with inactive TAO (P < 0.05). MTRmean achieved the highest area under the curve (AUC) of 0.868 for differentiating active from inactive group, followed by SIRmax (AUC, 0.836). MTRmean also demonstrated a higher and negative correlation with CAS (r = -0.614, P < 0.001) than MTRmax and MTRmin (r = -0.495, P < 0.001; r = -0.243, P = 0.007; respectively). Support vector machine-based analysis revealed that uniting MTRs could prosper concurrently added performance for disease activity differentiation and CAS prediction, compared with merely combining SIRs and ADCs (AUC, 0.933 vs 0.901; r = 0.703 vs. 0.673). CONCLUSIONS: MT imaging could potentially be used as a noninvasive method for differentiating the activity of TAO and predicting CAS, thereby offering added value to conventional SIR and ADC.
PURPOSE: To investigate the feasibility of using magnetization transfer (MT) magnetic resonance imaging for evaluating patients with thyroid-associated ophthalmopathy (TAO), and determine its added value for differentiating active from inactive TAO and predicting clinical activity score (CAS), compared with conventional fat-saturated T2-weighted and diffusion-weighted imaging. METHODS: Orbital MT, fat-saturated T2-weighted, and diffusion-weighted imaging of 60 prospectively enrolled consecutive patients with TAO was analyzed. Simplified histogram parameters (mean, max, min) of magnetization transfer ratio (MTR), signal intensity ratio (SIR), and apparent diffusion coefficient (ADC) at extraocular muscles were calculated for each orbit and compared between the active and inactive groups. RESULTS: Intraclass correlation coefficients of MTRs and SIRs were similar (0.802-0.963 vs 0.812-0.974, respectively), followed by those of ADCs (0.714-0.855). Patients with active TAO showed significantly lower MTRs and higher SIRs and ADCs than those with inactive TAO (P < 0.05). MTRmean achieved the highest area under the curve (AUC) of 0.868 for differentiating active from inactive group, followed by SIRmax (AUC, 0.836). MTRmean also demonstrated a higher and negative correlation with CAS (r = -0.614, P < 0.001) than MTRmax and MTRmin (r = -0.495, P < 0.001; r = -0.243, P = 0.007; respectively). Support vector machine-based analysis revealed that uniting MTRs could prosper concurrently added performance for disease activity differentiation and CAS prediction, compared with merely combining SIRs and ADCs (AUC, 0.933 vs 0.901; r = 0.703 vs. 0.673). CONCLUSIONS: MT imaging could potentially be used as a noninvasive method for differentiating the activity of TAO and predicting CAS, thereby offering added value to conventional SIR and ADC.