Philipp Ehses

Purpose: To evaluate the repeatability of an extended multiparametric 7 T MRI protocol for voxel‐wise tissue characterization combining morphological, CEST, QSM, QTI, and Sodium contrasts. Methods: A repeatability study was performed in 12 volunteers without diagnosed neurological disease on a 7 T MRI system, using a comprehensive acquisition protocol with a combined acquisition time of 45:24 min, from which 45 contrast maps were derived. Quantitative repeatability was assessed using region‐based and voxel‐wise analyses. Precision and reliability were evaluated using the coefficient of variation (CV), repeatability coefficient (%RC), and intraclass correlation coefficient (ICC). Voxel‐wise agreement between scan–rescan images was assessed using Pearson correlation coefficients. Results: Across contrasts spanning morphological, CEST, QSM, QTI, and ²³ Na imaging, %RC was below 20% for 20 contrasts, with mean CV below 5% for most. Repeatability was highest for MP2RAGE T ₁ maps and QTI MD (CV ≈ 1%–2%; ICC up to 0.86) and lowest for ²³ Na imaging (ICC < 0.6). CEST contrasts were highly repeatable at low saturation power but more variable at higher power (CV up to ≈8%). QSM contrasts showed moderate ICC (0.46–0.82). Voxel‐wise correlations exceeded r = 0.8 for most contrasts, confirming preserved spatial patterns across repeated scans. Conclusion: Multiparametric 7 T MRI enables reproducible voxel‐wise characterization of brain tissue across a wide range of contrasts. Despite variability in specific contrasts, the overall high repeatability and strong voxel‐wise agreement support the feasibility of voxel‐wise imaging approaches for quantitative brain imaging and provide a foundation for future applications in clinical research and neuroscience.

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 integrate MR‐based servo navigation in MPRAGE and 3D‐TSE sequences and demonstrate its potential for prospective head motion correction in structural imaging. Methods: Repeated modules of servo navigators were inserted before each preparation pulse of MPRAGE and 3D‐TSE sequences (before‐prep) for rapid convergence of motion parameter estimation. Additionally, reference navigators were distributed along the imaging echo train to test a within‐echo train correction (within‐ET) with contrast‐matched models, enabling more frequent geometry updates. The methods were evaluated in instructed motion experiments and in high‐resolution scans at 7T. Results: Artifacts caused by instructed abrupt motion were clearly reduced in scans with servo navigation for both sequences using the before‐prep correction. Residual artifacts of rapid in‐train motion were further mitigated by the within‐ET correction in MPRAGE. In high‐resolution scans with minimal motion, servo navigation preserved fine anatomical details, while it improved image quality under involuntary motion in long acquisitions. Conclusion: Servo navigation provides accurate real‐time head motion correction for structural brain imaging.

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.

Background: 7T MRI received FDA/CE clearance almost 7 years ago. However, until today, it has not yet been widely adopted in clinical routine. This is mainly due to field inhomogeneities that impede whole-brain coverage. Moreover, the long scan times often associated with high-resolution imaging are an additional limiting factor. Purpose: To combine calibration-free parallel transmit technology (pTx) using universal pulses (UP) with advanced imaging acceleration strategies to achieve homogenous multicontrast 7T MRI with whole-brain coverage and high spatial resolution in short scan time. Materials and Methods: Ten healthy volunteers were scanned both with conventional vendor-provided sequences and with custom sequences for anatomical whole-brain imaging [ -weighted, -weighted, FLAIR, and susceptibility-weighted]. The scan times for the 2 anatomical protocols were matched (25 minutes). In addition, a quantitative MRI protocol [multi-parametric mapping (MPM) and chemical exchange saturation transfer (CEST)] was scanned twice using custom sequences with conventional (circular polarized) and UPs, respectively, in a scan time of 2×25 minutes. Moreover, 4 patients with different neurological diseases were scanned, namely temporal lobe epilepsy, spinocerebellar ataxia, cerebral amyloid angiopathy, and glioblastoma. For the patients, only optimized custom sequences with UPs were acquired. Results: Compared with conventional implementations, the custom sequences provide strongly improved image homogeneity and quality with significantly higher SNR and CNR across the whole brain, including cerebellum and brain stem. Moreover, UPs improve the repeatability of derived quantitative parameters. The suggested protocol has additionally been successfully demonstrated in 4 patients with different neurological pathologies. Conclusions: Homogeneous whole-brain 7T MRI with high spatial resolution and high image quality is possible in clinically feasible scan times. The developed protocol can be applied without any expert knowledge and is ready for clinical use. The approach could largely extend applicability of UHF MRI in neuroradiology paving the way for increased routine use of 7T MRI.

Purpose: The study aims at investigating field inhomogeneity artifacts arising from remote locations in the FOV and encountered in accelerated 3D gradient‐recalled echo (GRE) sequences at ultra‐high field, and at providing mitigation strategies. Methods: Measurements were conducted at 11.7T using a head‐shaped phantom and an accelerated 3D GRE sequence with either integrated or external auto‐calibration signal (ACS) lines. Simulations were performed to reproduce the artifacts. The effects of varying GRAPPA reconstruction parameters (kernel size and regularization) were also examined. Results: field inhomogeneities located outside the shimmed region of interest (i.e., the brain) were observed to return ripple‐like artifacts within this region, particularly at long echo times. The simulation results support these findings, and the idea that the observed artifact originates from a mismatch between ACS and accelerated data due to intra‐voxel dephasing at different resolutions (ACS lines having an intrinsically lower resolution). The short echo time enabled by external (i.e., preacquired) ACS lines reduced artifacts compared to integrated ones. Varying GRAPPA kernel sizes and increasing the number of ACS lines can improve image quality, yet without full compensation. Conclusion: This study highlights ripple‐like artifacts amplified with field strength and arising from a lack of coherence between the ACS and imaging (3D GRE) signal caused by intra‐voxel dephasing. To minimize these artifacts, care should be taken in order to preserve the relevant information in the ACS data to properly compute the GRAPPA kernels.

Purpose: High‐resolution fMRI is a rapidly growing research field focused on capturing functional signal changes across cortical layers. However, the data acquisition is limited by low spatial frequency EPI artifacts; termed here as Fuzzy Ripples. These artifacts limit the practical applicability of acquisition protocols with higher spatial resolution, faster acquisition speed, and they challenge imaging in inferior regions of the brain. Methods: We characterize Fuzzy Ripple artifacts across commonly used sequences and distinguish them from conventional EPI Nyquist ghosts and off‐resonance effects. To investigate their origin, we employ dual‐polarity readouts. Results: Our findings indicate that Fuzzy Ripples are primarily caused by readout‐specific imperfections in k‐space trajectories, which can be exacerbated by short‐term eddy current, and by inductive coupling between third‐order shims and readout gradients. We also find that these artifacts can be mitigated through complex‐valued averaging of dual‐polarity EPI or by disconnecting the third‐order shim coils. Conclusion: The proposed mitigation strategies allow overcoming current limitations in layer‐fMRI protocols: Achieving resolutions beyond 0.8 mm is feasible, and even at 3T, we achieved 0.53 mm voxel functional connectivity mapping. Sub‐millimeter sampling acceleration can be increased to allow sub‐second TRs and laminar whole brain protocols with up to GRAPPA 8. Sub‐millimeter fMRI is achievable in lower brain areas, including the cerebellum.

Purpose: MR‐based FID navigators (FIDnavs) do not require gradient pulses and are attractive for prospective motion correction (PMC) due to short acquisition times and high sampling rates. However, accuracy and precision are limited and depend on a separate calibration measurement. Besides FIDnavs, stationary NMR field probes are also capable of measuring local, motion‐induced field changes. In this work, a linear model is calibrated between field probe data and motion parameters analog to FIDnav calibration and both tracking methods are compared and combined for PMC. Methods: FIDnavs and field probe navigators were implemented in a fast 3D‐EPI sequence and calibrated by a linear model to realignment motion parameters of the 3D‐EPI time series. A workflow was established to correct head motion prospectively by FIDnavs, field probe navigators or a combination of both. Large motions were instructed to test the accuracy and the impact on image quality in EPI data. Results: In a group of five subjects, FIDnavs demonstrated approximately doubled accuracy and precision in comparison with field probe navigators for large motions, especially nodding motions were tracked less accurately by field probes. A combination of both methods could not improve the accuracy consistently. Motion artifacts in high‐resolution data were reduced similarly by both PMC methods, although artifacts remained due to susceptibility‐induced B0 changes. Conclusion: Stationary field probe navigators can be calibrated equivalently as FIDnavs and enable rapid PMC of large and fast motions. Although they reveal decreased accuracy, their contrast‐independence facilitates the potential insertion into many sequences.

Neuroimaging has an essential role in studies of brain health and of cerebrovascular and neurodegenerative diseases, requiring the availability of versatile magnetic resonance imaging (MRI) acquisition and processing protocols. We designed and developed a multipurpose high-resolution MRI protocol for large-scale and long-term population neuroimaging studies that includes structural, diffusion-weighted and functional MRI modalities. This modular protocol takes almost 1 h of scan time and is, apart from a concluding abdominal scan, entirely dedicated to the brain. The protocol links the acquisition of an extensive set of MRI contrasts directly to the corresponding fully automated data processing pipelines and to the required quality assurance of the MRI data and of the image-derived phenotypes. Since its successful implementation in the population-based Rhineland Study (ongoing, currently more than 11,000 participants, target participant number of 20,000), the proposed MRI protocol has proved suitable for epidemiological and clinical cross-sectional and longitudinal studies, including multisite studies. The approach requires expertise in magnetic resonance image acquisition, in computer science for the data management and the execution of processing pipelines, and in brain anatomy for the quality assessment of the MRI data. The protocol takes ~1 h of MRI acquisition and ~20 h of data processing to complete for a single dataset, but parallelization over multiple datasets using high-performance computing resources reduces the processing time. By making the protocol, MRI sequences and pipelines available, we aim to contribute to better comparability, interoperability and reusability of large-scale neuroimaging data.