Related Experiment Video
Updated: May 1, 2026
Magnetic Resonance Imaging of Multiple Sclerosis at 7.0 Tesla
Published on: February 19, 2021
Diagnostic Performance of Quantitative T1rho MRI for the Assessment of Disease Activity in Relapsing-Remitting
Tiffany Y So1, Lei Wang1, Weitian Chen1
1Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong Special Administrative Region of China (T.Y.S., L.W., W.C., Q.H.A., D.K.W.Y., Y.X.J.W., J.A., A.D.K.).
Rationale And Objectives:
Accurate identification of active multiple sclerosis (MS) lesions is essential for guiding treatment decisions and monitoring disease response.
Materials And Methods:
To evaluate the performance of T1rho in differentiating active from inactive MS lesions. A total of 275 (27 active, 248 inactive) lesions from patients with relapsing-remitting MS were included. T1rho and quantitative magnetic resonance imaging (MRI) parameters, including T2 relaxation, and diffusion metrics (apparent diffusion coefficient [ADC], fractional anisotropy [FA], mean diffusivity [MD], radial diffusivity [RD], axial diffusivity [AD], were measured for each lesion. Differences between lesion types were assessed using linear mixed-effects models. Discriminative performance was evaluated using receiver operating characteristic (ROC) analysis, and univariate, multivariate, and stepwise logistic regression were applied to identify the optimal MRI combination for lesion differentiation.
Results:
Active lesions demonstrated significantly lower T1rho values than inactive lesions (91.70 ± 10.19 ms vs. 114.04 ± 28.49 ms, P < 0.01). T1rho showed the highest discriminative performance (area under the curve [AUC] 0.83, 95% confidence interval [CI] 0.78-0.87), outperforming T2 and all diffusion metrics. Both T1rho and ADC were independent predictors of lesion activity, with their combined model achieving excellent discriminatory performance (AUC 0.85, 95% CI 0.81-0.89).
Conclusion:
T1rho imaging is a highly promising non-contrast technique for differentiating active MS lesions, demonstrating superior performance compared with conventional T2 mapping and diffusion metrics. Combining T1rho with ADC provides an approach that may further improve lesion discrimination.
