Malte Riedel

Purpose: To enhance time‐resolved segmented imaging by synergy of run‐time stabilization and retrospective data‐driven phase correction. Methods: A segmented 3D EPI sequence for fMRI time series is equipped with servo navigation based on short orbital navigators and a linear perturbation model, enabling run‐time correction for rigid‐body motion, bulk phase, and frequency fluctuations. Complementary retrospective phase correction is based on the repetitive structure of the time series and serves to address residual phase and frequency offsets. The combined approach is termed phase equalization enhanced by run‐time stabilization (PEERS). Results: The proposed methods are assessed in terms of resulting alignment and tSNR of 3D EPI time series in a phantom and in vivo. Servo navigation is found to diminish motion confound in raw data and maintain k‐space consistency over time series. Coarse frequency tracking based on short navigators is supplemented by precise shot‐wise frequency and phase correction using retrospective phase equalization of EPI data. Relative to conventional volume realignment, PEERS achieved tSNR improvements of up to for small motion and on the order of when volunteers tried to hold still. Conclusion: Servo navigation achieves high‐precision run‐time motion correction for 3D EPI and is synergistic with retrospective phase equalization. Fully automatic and self‐calibrated, PEERS offers effective plug‐and‐play motion and phase correction for stabilized 3D EPI time series. The translation of stability gains into metrics of functional sensitivity is complex and must be studied with suitable statistical power. The data obtained in this work does not support any conclusions in this regard.

Ultra-high-field MRI promises major gains in BOLD sensitivity but introduces severe challenges such as RF field inhomogeneity, B0 field inhomogeneity, motion and vibration-induced field variations. We report the first whole-brain resting-state and task-based fMRI experiments at 11.7T. A 3D-EPI sequence was optimized using tailored parallel-transmit RF pulses, gradient reshaping to suppress vibration-induced B0 fluctuations, and prospective motion correction using servo navigation combined with retrospective phase equalization (PEERS). Four participants were scanned at 11.7T with whole-brain 1.2 mm isotropic resolution with servo navigation and PEERS that considerably reduced residual motion and increased temporal SNR. The Default Mode Network in resting state could be detected and a physiological-noise-dominated regime was identified. Four additional but different participants were scanned at 7T for tSNR comparison and validation of the protocol, data quality and processing pipeline. Task-based fMRI likewise was conducted at 11.7T and yielded robust, spatially specific activations across motor, visual, mathematical, and language networks, again with improved sensitivity and cleaner BOLD responses when using servo navigation and PEERS. These results demonstrate the feasibility and reliability of whole-brain human fMRI at 11.7T and constitute a first quality control milestone to further increase resolution at that field strength.

Purpose: To mitigate artifacts related to motion and field changes in high‐resolution ‐weighted human brain imaging using servo navigation at ultra‐high fields up to 11.7 T. Methods: MR‐based servo navigators were integrated into a segmented 3D‐EPI sequence to allow for prospective correction of involuntary head motion and first‐order shim changes. Seven subjects were scanned with whole‐brain protocols at 0.3 mm isotropic resolution with and without correction at 7 and 11.7 T. Validation was performed on detailed brain vasculature in scans with involuntary motion. Results: Blurring of small veins was reduced by servo navigation for all subjects and across field strengths. In case of involuntary large motion, the method preserved image quality, while uncorrected motion led to severe artifacts. In case of microscopic motion, reduced blurring and shading in the frontal lobe demonstrate the additional benefit of prospective field drift correction. Conclusion: Servo‐navigated segmented 3D‐EPI improves 0.3 mm isotropic whole‐brain ‐weighted imaging under realistic motion and field changes within 5.5 to 11 min scan time at 11.7 and 7 T.

Purpose: Navigator‐based correction of rigid‐body motion reconciling high precision with minimal acquisition, minimal calibration and simple, fast processing.Methods: A short orbital navigator (2.3 ms) is inserted in a three‐dimensional (3D) gradient echo sequence for human head imaging. Head rotation and translation are determined by linear regression based on a complex‐valued model built either from three reference navigators or in a reference‐less fashion, from the first actual navigator. Optionally, the model is expanded by global phase and field offset. Run‐time scan correction on this basis establishes servo control that maintains validity of the linear picture by keeping its expansion point stable in the head frame of reference. The technique is assessed in a phantom and demonstrated by motion‐corrected imaging in vivo.Results: The proposed approach is found to establish stable motion control both with and without reference acquisition. In a phantom, it is shown to accurately detect motion mimicked by rotation of scan geometry as well as change in global B₀. It is demonstrated to converge to accurate motion estimates after perturbation well beyond the linear signal range. In vivo, servo navigation achieved motion detection with precision in the single‐digit range of micrometers and millidegrees. Involuntary and intentional motion in the range of several millimeters were successfully corrected, achieving excellent image quality.Conclusion: The combination of linear regression and feedback control enables prospective motion correction for head imaging with high precision and accuracy, short navigator readouts, fast run‐time computation, and minimal demand for reference data.

Purpose: Multi‐shot diffusion‐weighted EPI allows an increase in image resolution and reduced geometric distortions and can be combined with chemical‐shift encoding (Dixon) to separate water/fat signals. However, such approaches suffer from physiological motion‐induced shot‐to‐shot phase variations. In this work, a structured low‐rank‐based navigator‐free algorithm is proposed to address the challenge of simultaneously separating water/fat signals and correcting for physiological motion‐induced shot‐to‐shot phase variations in multi‐shot EPI‐based diffusion‐weighted MRI.Theory and Methods: We propose an iterative, model‐based reconstruction pipeline that applies structured low‐rank regularization to estimate and eliminate the shot‐to‐shot phase variations in a data‐driven way, while separating water/fat images. The algorithm is tested in different anatomies, including head–neck, knee, brain, and prostate. The performance is validated in simulations and in‐vivo experiments in comparison to existing approaches.Results: In‐vivo experiments and simulations demonstrated the effectiveness of the proposed algorithm compared to extra‐navigated and an alternative self‐navigation approach. The proposed algorithm demonstrates the capability to reconstruct in the multi‐shot/Dixon hybrid space domain under‐sampled datasets, using the same number of acquired EPI shots compared to conventional fat‐suppression techniques but eliminating fat signals through chemical‐shift encoding. In addition, partial Fourier reconstruction can also be achieved by using the concept of virtual conjugate coils in conjunction with the proposed algorithm.Conclusion: The proposed algorithm effectively eliminates the shot‐to‐shot phase variations and separates water/fat images, making it a promising solution for future DWI on different anatomies.

Purpose: To develop a new water–fat separation and B₀ estimation algorithm to effectively suppress the multiple resonances of fat signal in EPI. This is especially relevant for DWI where fat is often a confounding factor.Methods: Water–fat separation based on chemical‐shift encoding enables robust fat suppression in routine MRI. However, for EPI the different chemical‐shift displacements of the multiple fat resonances along the phase‐encoding direction can be problematic for conventional separation algorithms. This work proposes a suitable model approximation for EPI under B₀ and fat off‐resonance effects, providing a feasible multi‐peak water–fat separation algorithm. Simulations were performed to validate the algorithm. In vivo validation was performed in 6 volunteers, acquiring spin‐echo EPI images in the leg (B₀ homogeneous) and head‐neck (B₀ inhomogeneous) regions, using a TE‐shifted interleaved EPI sequence with/without diffusion sensitization. The results are numerically and statistically compared with voxel‐independent water–fat separation and fat saturation techniques to demonstrate the performance of the proposed algorithm.Results: The reference separation algorithm without the proposed spatial shift correction caused water–fat ambiguities in simulations and in vivo experiments. Some spectrally selective fat saturation approaches also failed to suppress fat in regions with severe B₀ inhomogeneities. The proposed algorithm was able to achieve improved fat suppression for DWI data and ADC maps in the head–neck and leg regions.Conclusion: The proposed algorithm shows improved suppression of the multi‐peak fat components in multi‐shot interleaved EPI applications compared to the conventional fat saturation approaches and separation algorithms.

Purpose: To improve the robustness of diffusion‐weighted imaging (DWI) data acquired with segmented simultaneous multi‐slice (SMS) echo‐planar imaging (EPI) against in‐plane and through‐plane rigid motion.Theory and Methods: The proposed algorithm incorporates a 3D rigid motion correction and wavelet denoising into the image reconstruction of segmented SMS‐EPI diffusion data. Low‐resolution navigators are used to estimate shot‐specific diffusion phase corruptions and 3D rigid motion parameters through SMS‐to‐volume registration. The shot‐wise rigid motion and phase parameters are integrated into a SENSE‐based full‐volume reconstruction for each diffusion direction. The algorithm is compared to a navigated SMS reconstruction without gross motion correction in simulations and in vivo studies with four‐fold interleaved 3‐SMS diffusion tensor acquisitions.Results: Simulations demonstrate high fidelity was achieved in the SMS‐to‐volume registration, with submillimeter registration errors and improved image reconstruction quality. In vivo experiments validate successful artifact reduction in 3D motion‐compromised in vivo scans with a temporal motion resolution of approximately 0.3 s.Conclusion: This work demonstrates the feasibility of retrospective 3D rigid motion correction from shot navigators for segmented SMS DWI.