Universal nonselective excitation and refocusing pulses with improved robustness to off‐resonance for Magnetic Resonance Imaging at 7 Tesla with parallel transmission

激发 磁共振成像 旋转 翻转角度 核磁共振 波形 物理 光学 计算机科学 电信 医学 量子力学 放射科 雷达 凝聚态物理
作者
L. Van Damme,Franck Mauconduit,Thomas Chambrion,Nicolas Boulant,Vincent Gras
出处
期刊:Magnetic Resonance in Medicine [Wiley]
卷期号:85 (2): 678-693 被引量:34
标识
DOI:10.1002/mrm.28441
摘要

Purpose In MRI at ultra‐high field, the ‐point and spiral nonselective (SPINS) pulse design techniques can be advantageously combined with the parallel transmission (pTX) and universal pulse techniques to create uniform excitation in a calibration‐free manner. However, in these approaches, pulse duration is typically increased as compared to standard hard pulses, and excitation quality in regions exhibiting large resonance frequency offsets often suffer. This limitation is inherent to structure of ‐point or SPINS pulse, and likely can be mitigated using parameterization‐free pulse design approaches. Methods The Gradient Ascent Pulse Engineering (GRAPE) algorithm was used to design parameterization‐free RF and magnetic field gradient (MFG) waveforms for creating excitation, up to scalable refocusing and inversion, nonselectively across the brain. Simulations were performed to provide flip angle normalized root‐mean‐squares error (FA‐NRMSE) estimations for the and the ‐point, SPINS, and GRAPE pulses. GRAPE pulses were tested experimentally with anatomical head scans at 7T. Results As compared to ‐points and SPINS, GRAPE provided substantial improvement of excitation, refocusing, and inversion quality at off‐resonance while at least preserving the same global FA‐NRMSE performance. As compared to ‐points, GRAPE allowed for a substantial reduction of the pulse duration for the excitation and the refocusing. Conclusions Parameterization‐free universal nonselective pTX‐pulses were successfully computed using GRAPE. Performance gains as compared to ‐points were validated numerically and experimentally for three imaging protocols. In its current implementation, the computational burden of GRAPE limits its use to applications where pulse computations are not subject to time constraints.
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