Affiliation:
1. School of Electrical Engineering Chongqing University Chongqing China
2. Shenzhen Academy of Aerospace Technology Shenzhen China
3. Harbin Institute of Technology Harbin China
4. Chongqing University Central Hospital Chongqing China
Abstract
AbstractUltralow‐field (ULF) magnetic resonance imaging (MRI) can suffer from inferior image quality because of low signal‐to‐noise ratio (SNR). As an efficient way to cover the k‐space, the spiral acquisition technique has shown great potential in improving imaging SNR efficiency at ULF. The current study aimed to address the problems of noise and blurring cancelation in the ULF case with spiral trajectory, and we proposed a spiral‐out sequence for brain imaging using a portable 50‐mT MRI system. The proposed sequence consisted of three modules: noise calibration, field map acquisition, and imaging. In the calibration step, transfer coefficients were obtained between signals from primary and noise‐pick‐up coils to perform electromagnetic interference (EMI) cancelation. Embedded field map acquisition was performed to correct accumulated phase error due to main field inhomogeneity. Considering imaging SNR, a lower bandwidth for data sampling was adopted in the sequence design because the 50‐mT scanner is in a low SNR regime. Image reconstruction proceeded with sampled data by leveraging system imperfections, such as gradient delays and concomitant fields. The proposed method can provide images with higher SNR efficiency compared with its Cartesian counterparts. An improvement in temporal SNR of approximately 23%–44% was measured via phantom and in vivo experiments. Distortion‐free images with a noise suppression rate of nearly 80% were obtained by the proposed technique. A comparison was also made with a state‐of‐the‐art EMI cancelation algorithm used in the ULF‐MRI system. SNR efficiency‐enhanced spiral acquisitions were investigated for ULF‐MR scanners and future studies could focus on various image contrasts based on our proposed approach to widen ULF applications.
Funder
Science, Technology and Innovation Commission of Shenzhen Municipality
National Natural Science Foundation of China
Subject
Spectroscopy,Radiology, Nuclear Medicine and imaging,Molecular Medicine