Affiliations: [a] School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan, China | [b] Key Laboratory for NeuroInformation of Ministry of Education, Chengdu, Sichuan, China | [c] High Field Magnetic Resonance Brain Imaging Laboratory of Sichuan, Chengdu, Sichuan, China | [d] College of Computer Science, Neijiang Normal University, Neijiang, Sichuan, China
Correspondence:
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Corresponding author: Tao Zhang, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China. E-mail: [email protected].
Note: [1] These authors contributed equally to this work.
Abstract: BACKGROUND: Over the past 20 years, magnetic resonance receiving coil technology has developed rapidly. The traditional, commercial knee joint coil has a fixed mechanical structure. To meet the imaging needs of most patients, it is necessary to ensure that the mechanical geometry of the coil is as large as possible. Therefore, different quality images can be obtained by filling coefficients under loads of knees of different sizes. Lufkin et al. [1] have demonstrated that
the signal-to-noise ratio (SNR) of coil imaging is directly proportional to its filling coefficient, which is S/N≈QL*η. Thus, the pursuit of an optimal coil filling coefficient is an important way to improve the coil imaging quality. OBJECTIVE: This study combines wearable concepts and coil development techniques and applies flexible and elastic materials to coil designs. METHODS: We used an elastic material instead of the traditional fixed mechanical structure to develop a 1.5T 5-channel knee joint receiving coil that can be attached to knee joints of different sizes within a certain range, allowing the coil to achieve a maximum filling coefficient under the loads of knees of different sizes. RESULTS:Compared to commercial 8-channel knee coils, the phantom test and clinical knee joint imaging demonstrated that the SNR of the developed coil increased by four times in the shallow layer and two times in the deep layer, under different load conditions. CONCLUSION: This high SNR performance demonstrates potential for the realization of high resolution and fast imaging sequences in knee imaging.
Keywords: Magnetic resonance, wearable, coil, SNR, filling coefficient
