In vivo sensitivity estimation and imaging acceleration with rotating RF coil arrays at 7 Tesla

• Published in: Journal of magnetic resonance (1997) Vol. 252; pp. 29 - 40
• Main Authors: Li, Mingyan, Jin, Jin, Zuo, Zhentao, Liu, Feng, Trakic, Adnan, Weber, Ewald, Zhuo, Yan, Xue, Rong, Crozier, Stuart
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.03.2015
• Subjects: 7 Tesla; Algorithms; Brain - anatomy & histology; Equipment Design; Equipment Failure Analysis; Feasibility Studies; Human brain imaging; Humans; Image Enhancement - instrumentation; Image Enhancement - methods; Image Interpretation, Computer-Assisted - instrumentation; Image Interpretation, Computer-Assisted - methods; In vivo sensitivity estimation; Magnetic Resonance Imaging - instrumentation; Magnetics - instrumentation; Parallel imaging; Patient Positioning - methods; Phased array coils; Reproducibility of Results; Rotating RF coil array (RRFCA); Rotating SENSitivity Encoding (rotating-SENSE); Rotation; Sensitivity and Specificity; Signal-to-noise ratio (SNR); Subtraction Technique - instrumentation; Transducers; Rotating SENSitivity Encoding (rotating-SENSE); Human brain imaging; Phased array coils; Rotating RF coil array (RRFCA); Signal-to-noise ratio (SNR); Parallel imaging; In vivo sensitivity estimation; 7 Tesla
• ISSN: 1090-7807; 1096-0856
• DOI: 10.1016/j.jmr.2014.12.004

[Display omitted] •The in vivo imaging feasibility of rotating RF coil array (RRFCA) was investigated.•A registration based sensitivity estimation algorithm was developed.•The in vivo sensitivity maps at other angular positions can be well estimated.•The RRFCA had better imaging acceleration performance compared to stationary coils.•The RRFCA exhibited a higher SNR and fewer artifacts than that of stationary coils. Using a new rotating SENSitivity Encoding (rotating-SENSE) algorithm, we have successfully demonstrated that the rotating radiofrequency coil array (RRFCA) was capable of achieving a significant reduction in scan time and a uniform image reconstruction for a homogeneous phantom at 7 Tesla. However, at 7 Tesla the in vivo sensitivity profiles (B1-) become distinct at various angular positions. Therefore, sensitivity maps at other angular positions cannot be obtained by numerically rotating the acquired ones. In this work, a novel sensitivity estimation method for the RRFCA was developed and validated with human brain imaging. This method employed a library database and registration techniques to estimate coil sensitivity at an arbitrary angular position. The estimated sensitivity maps were then compared to the acquired sensitivity maps. The results indicate that the proposed method is capable of accurately estimating both magnitude and phase of sensitivity at an arbitrary angular position, which enables us to employ the rotating-SENSE algorithm to accelerate acquisition and reconstruct image. Compared to a stationary coil array with the same number of coil elements, the RRFCA was able to reconstruct images with better quality at a high reduction factor. It is hoped that the proposed rotation-dependent sensitivity estimation algorithm and the acceleration ability of the RRFCA will be particularly useful for ultra high field MRI.