Quantitative magnetic resonance imaging (qMRI), independent from specific choice of sequence parameters or hardware setups, supplements quantitative parametric maps with robustness, reliability, and abundant contrasts. However, its lengthy scan time hinders its application in dynamic or real-time scenarios. Recently, we proposed a single-shot multiple overlapping-echo detachment (MOLED) qMRI method which can implement synchronous T2, proton density (M0), and B1 mapping in a single-shot acquisition with the help of a trained convolutional neural network (CNN) who learnt the nonlinear relationship between MOLED images and quantitative maps through synthesized data [1]. The method MOLED with short echo time (TE) is suited for musculoskeletal system due to higher signal-to-noise ratio. In this work, an ischemia and post-occlusive reactive hyperemia experiment was performed. The results reveal that MOLED can capture delicate T2 variations of different muscles. Inter-day repeatability measurements demonstrate that the method is accurate and repeatable. Compared to other qMRI methods, there are three main advantages of our method: high temporal resolution, immunity to B1 inhomogeneity, and synchronous multiparametric mapping, which facilitates complementary tissue information and comprehensive tissue characterization. Expectantly, MOLED may provide new insights into the metabolic responses of musculatures to human activities.
This work was supported by the NNSF of China under Grants 22161142024 and 11775184.