Single-shot multi-parametric mapping based on multiple overlapping-echo detachment (MOLED) imaging
Lingceng Ma,
Jian Wu,
Qinqin Yang,
Zihan Zhou,
Hongjian He,
Jianfeng Bao,
Lijun Bao,
Xiaoyin Wang,
Pujie Zhang,
Jianhui Zhong,
Congbo Cai,
Shuhui Cai,
Zhong Chen
Affiliations
Lingceng Ma
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
Jian Wu
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
Qinqin Yang
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
Zihan Zhou
The Center for Brain Imaging Science and Technology, The Collaborative Innovation Center for Diagnosis and The Treatment of Infectious Diseases, Zhejiang University, Hangzhou 310027, China
Hongjian He
The Center for Brain Imaging Science and Technology, The Collaborative Innovation Center for Diagnosis and The Treatment of Infectious Diseases, Zhejiang University, Hangzhou 310027, China
Jianfeng Bao
Department of MRI, Henan Key Laboratory of Magnetic Resonance Function and Molecular Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450000, China
Lijun Bao
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
Xiaoyin Wang
The Center for Brain Imaging Science and Technology, The Collaborative Innovation Center for Diagnosis and The Treatment of Infectious Diseases, Zhejiang University, Hangzhou 310027, China
Pujie Zhang
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China
Jianhui Zhong
The Center for Brain Imaging Science and Technology, The Collaborative Innovation Center for Diagnosis and The Treatment of Infectious Diseases, Zhejiang University, Hangzhou 310027, China; Department of Imaging Sciences, University of Rochester, Rochester, NY 14642, USA
Congbo Cai
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China; Corresponding authors.
Shuhui Cai
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China; Corresponding authors.
Zhong Chen
Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen 361005, China; Corresponding authors.
Multi-parametric quantitative magnetic resonance imaging (mqMRI) allows the characterization of multiple tissue properties non-invasively and has shown great potential to enhance the sensitivity of MRI measurements. However, real-time mqMRI during dynamic physiological processes or general motions remains challenging. To overcome this bottleneck, we propose a novel mqMRI technique based on multiple overlapping-echo detachment (MOLED) imaging, termed MQMOLED, to enable mqMRI in a single shot. In the data acquisition of MQMOLED, multiple MR echo signals with different multi-parametric weightings and phase modulations are generated and acquired in the same k-space. The k-space data is Fourier transformed and fed into a well-trained neural network for the reconstruction of multi-parametric maps. We demonstrated the accuracy and repeatability of MQMOLED in simultaneous mapping apparent proton density (APD) and any two parameters among T2, T2*, and apparent diffusion coefficient (ADC) in 130–170 ms. The abundant information delivered by the multiple overlapping-echo signals in MQMOLED makes the technique potentially robust to system imperfections, such as inhomogeneity of static magnetic field or radiofrequency field. Benefitting from the single-shot feature, MQMOLED exhibits a strong motion tolerance to the continuous movements of subjects. For the first time, it captured the synchronous changes of ADC, T2, and T1-weighted APD in contrast-enhanced perfusion imaging on patients with brain tumors, providing additional information about vascular density to the hemodynamic parametric maps. We expect that MQMOLED would promote the development of mqMRI technology and greatly benefit the applications of mqMRI, including therapeutics and analysis of metabolic/functional processes.
