Biology subjects

Henning, A.

Publications and source records attributed to Henning, A..

12 recordsLinked to original sources

bioRxiv2026

Deep Learning-Based Reconstruction: Model Comparison for Variable-Density GRAPPA 1H MRSI

Proton magnetic resonance spectroscopic imaging (1H MRSI) enables quantitative mapping of brain metabolites, but its clinical use remains limited by long acquisition time. The goal of this work to improve the applicability of high-resolution 1H FID-MRSI at 7T by enhancing GRAPPA-based acceleration through deep learning-driven k-space reconstruction. In particular, compared with conventional GRAPPA, MultiNet PyGRAPPA enables substantially higher in-plane acceleration while suppressing residual lipid aliasing and preserving metabolite map fidelity in non-lipid-suppressed MRSI. Building on the MultiNet PyGRAPPA framework, we introduce a comprehensive comparison of advanced machine-learning models for predicting missing k-space points. Multiple architectures--including multilayer perceptrons, convolutional neural networks, and several U-Net variants--were trained within a variable-density k-space undersampling scheme to support acceleration factors of R = 4, 6, and 7. The proposed U-Net model extends the MultiNet concept by leveraging nonlinear hierarchical feature extraction, thereby improving reconstruction fidelity while maintaining robustness to noise.The methods were evaluated in vivo using retrospectively undersampled 7T 1H FID-MRSI datasets from healthy volunteers and patients. Quantitative analyses demonstrate that the U-Net outperforms the original MultiNet approach, offering improved SNR retention rate, reduced lipid RMSE, and higher structural similarity of major metabolites. Metabolite maps reconstructed with the U-Net showed reduced lipid artifacts and improved anatomical consistency. In conclusion, integrating deep convolutional networks into GRAPPA-based k-space prediction provides a more reliable and higher-fidelity reconstruction pipeline. When combined with variable-density undersampling, this approach enables faster acquisition of high-resolution 1H MRSI without compromising spectral quality or metabolite quantification.

bioengineering↗

bioRxiv2025

OmniShim - a vendor-independent B0 Shimming software toolbox

PurposeTo introduce the OmniShim Toolbox, a software package designed to calibrate and perform B0 shimming in user-defined regions of interest across systems from different vendors, supporting various shim orders. MethodsIn this study, we systematically compared the performance of vendor-implemented B0 shim routines with our custom developed OmniShim toolbox, designed to improve static magnetic field homogeneity. Single-voxel magnetic resonance spectroscopy (MRS) data were acquired from the prefrontal cortex and occipital lobe, while magnetic resonance spectroscopic imaging (MRSI) data were collected from regions above and below the corpus callosum in healthy volunteers. Measurements were conducted on both 3T and 7T MR systems to evaluate the robustness and scalability of each B0 shimming strategy across different field strengths. Additionally, functional MRI (fMRI) data were acquired at 7T to assess the impact of improved shimming on EPI data quality and BOLD contrast. ResultsThe OmniShim Toolbox demonstrated superior B0 homogeneity across all applications and field strength, leading to reduced signal dropout in fMRI and MRSI data, significantly improved spectral linewidths in SV MRS and MRSI data as well improved detection of neural networks by resting state fMRI. ConclusionThe proposed OmniShim Toolbox offers a robust and flexible approach to control B0 inhomogeneity, resulting in substantial improvements in image quality and spectral resolution. These enhancements benefit a broad range of MR applications.

bioengineering↗

bioRxiv2025

Characterization of real B0 shim fields generated by higher order B0 shim systems of whole body human 3T and 7T MRI systems

PurposeEnsuring optimal homogeneity of the static magnetic field (B0) is critically important for significantly enhancing the image quality, spectral resolution, and overall diagnostic accuracy of magnetic resonance imaging (MRI) and magnetic resonance spectroscopy/spectroscopic imaging (MRS/MRSI), especially at high and ultra-high field strengths. Achieving this goal relies on the deployment of advanced, higher-order shim hardware, which is indispensable for effective and precise B0 shimming. MethodsIn this study, we acquired B0 field maps to characterize the performance of each shim channel of vendor-provided B0 shim hardware integrated into whole body human 7T MRI system. To rigorously evaluate and compare the B0 field homogeneity achievable using these devices, we utilized spherical harmonic expansions to fit the measured B0 distributions for each shim channel in each of the investigated built-in B0 shim systems. This methodology enabled a systematic assessment of shim field "purity" and the effectiveness of different B0 shim configurations. ResultsWhile our analysis confirmed that the linear-order shim terms provided by the gradient coils maintained high purity, certain second-order shim terms and all third-order B0 shim coils of all vendors 7T whole body human MRI systems exhibit a high level of impurity and more specifically introduce substantial linear field components. These unintended linear contributions interfere with the linear shim fields provided by the gradient coils negating their corrective influence. As a result, the 3rd order B0 shim coils and some 2nd order B0 shim coil elements compromised the overall effectiveness of the B0 shimming process rather than improving it. Although pure higher order B0 shim fields were previously shown to substantially improve B0 field inhomogeneity, the vendor implemented versions of higher order B0 shim systems in current 7T whole-body human MRI scanners cannot achieve the desired level of uniformity and partly perform worse than first order B0 shimming. Substantial deviations between 2nd order and especially 3rd order real shim fields versus ideal shim fields demonstrate the necessity of real shim field calibration and call for improvement of future 2nd and 3rd order B0 shim coil design for human whole-body MRI scanners. Our findings offer valuable guidance for optimizing B0 shimming strategies at high and ultra-high field strengths, ultimately enhancing image quality. ConclusionRecent evaluations have demonstrated that certain second- and third-order shim coils, as implemented in current commercial 7T human whole-body MRI systems, introduce unintended lower-order (linear) field components. These field "impurities" substantially deviate from the desired higher-order spatial harmonics, thereby diminishing the orthogonality of the higher order B0 shim system. This in turn largely compromises the effectiveness of higher-order B0 shimming at whole-body 7T MRI scanners. These findings emphasize the necessity of conducting accurate shim field calibration to best utilize the current 7T B0 shim system configurations on one hand. On the other hand, improving the purity of these commercial B0 shim systems in the design phase to ensure that the higher-order terms accurately match their intended spherical harmonic profiles, particularly for the third-order shim terms--would largely enhance the achievable B0 field homogeneity at 7T. This improvement has directly clinically significant outcomes.

bioengineering↗

bioRxiv2025

Human Fcγ-receptors selectively respond to C-reactive protein (CRP) isoforms

The pentameric C-reactive protein (pCRP), an acute-phase protein, binds to lysophosphatidylcholine (LPC) displayed on the surface of dying cells and microorganisms to activate the complement system and to opsonize immune cells via Fc{gamma}-receptors (Fc{gamma}Rs). Members of the Fc{gamma}R family are characterized by the recognition of the Fc part of IgG antibodies. We utilized a mouse thymoma BW5147 reporter cell panel stably expressing chimeric human Fc{gamma}R-CD3{zeta}-chain receptors to define the molecular requirements for Fc{gamma}R crosslinking by C-reactive protein (CRP). Applying this approach, we show a robust activation of CD64/Fc{gamma}RI and CD32a/Fc{gamma}RIIa by immobilized CRP isoforms as well as triggering of inhibitory CD32b/Fc{gamma}RIIb. Of note, activation of Fc{gamma}RIIa was restricted to the 131R allelic variant but not observed with 131H. In contrast, Fc{gamma}RIII isoforms CD16aF, CD16aV and CD16b were not activated by pCRP, although binding of CRP isoforms to Fc{gamma}RIII was detectable. Activation of Fc{gamma}Rs by free pCRP in solution phase was considerably lower than with immobilized pCRP on hydrophilic plastic surfaces and readily abolished by IgG at serum level concentrations, whereas it was enhanced by the addition of streptococci. The types of Fc{gamma}Rs mainly responding to pCRP in solution phase (CD64/Fc{gamma}RI and CD32aR/Fc{gamma}RIIaR) clearly differed from Fc{gamma}Rs responding to soluble multimeric IgG complexes (i.e., CD16aV/Fc{gamma}RIIIaV and CD32aH/Fc{gamma}RIIaH). Compared to pCRP, monomeric CRP (mCRP) showed lower levels of activation in those selective Fc{gamma}Rs. Fc{gamma}R activation was linked to recognition by conformation-dependent CRP antibodies. Unmasking of the mAb 9C9-defined neoepitope in pCRP* correlated with the triggering of Fc{gamma}Rs, indicating that pCRP* is the major Fc{gamma}R-activating CRP conformation. The assay provides a novel, scalable approach to determine the molecular properties of CRP as a physiological ligand of Fc{gamma}R-mediated bioactivities. Scope statementFc{gamma} receptors (Fc{gamma}Rs) are important immune regulators that come in different variants and combinations, making it difficult to predict which components will ultimately lead to immunological effector functions. Classical Fc{gamma}Rs are defined by their recognition of IgG-Fc, while other ligands, such as C-reactive protein (CRP), are often neglected. Circulating concentrations of CRP, an acute phase protein, are elevated during inflammatory responses. As a pattern recognition receptor, CRP binds to lysophosphatidylcholine expressed on the surface of dying cells and microbes in order to activate the complement system via C1q. We have established a reporter cell assay platform that goes beyond ligand binding and takes a deeper look at the activation outcome(s) by CRP compared with IgG-Fc. This is the first comprehensive study defining CRP-responsive vs non-responsive Fc{gamma}Rs and investigating the interaction of Fc{gamma}Rs with CRP isoforms (pCRP/pCRP*/mCRP). We distinguish binding from receptor triggering using reporter cells stably expressing a chimeric Fc{gamma}R-CD3{zeta} chain, thereby defining the molecular requirements for Fc{gamma}R cross-linking by CRP. The assay provides a novel, sensitive and scalable approach to the properties of CRP as a ligand inducing Fc{gamma}R-mediated bioactivities.

immunology↗

bioRxiv2024

ProFit-1D for quantifying J-difference edited data at 3T

Reproducible and accurate fitting of the magnetic resonance spectrum is critical for estimating metabolite concentrations. We have previously developed a fitting software called ProFit-1D which was shown to fit 9.4T semi-LASER data from the human brain with high accuracy and precision. In this study, we adapted ProFit-1D to fit J-difference edited spectra acquired at a clinical field strength of 3T and to assessed its performance in simulated and in vivo data. ProFit-1D was adapted to fit J-difference edited data with alterations to the fitting range to exclude the 1.3 ppm lipid resonance, starting T2 relaxation constants, initial fit parameters, and adaptive spectral baseline determination. The accuracy of ProFit-1D was systematically evaluated on simulated GABA-edited and 2-hydroxyglutarate-edited (2HG-edited) data with different types of in vivo parameter variations and compared to that of LCModel and Gannet, two software commonly used to fit J-difference edited data. The precision of ProFit-1D was also evaluated in GABA-edited spectra acquired in vivo in the occipital cortex (OCC) and medial prefrontal cortex (mPFC) of healthy participants at 3T using subsets of averages and compared to that of LCModel and Gannet. The 2HG fit error was also evaluated for ProFit-1D in 2HG-edited spectra acquired in glioma patients and compared to that of LCModel. Overall, it was found that ProFit-1D generally produced fits with low parameter fit errors across a variety of parameter variations. GABA, glutamate plus glutamine (Glx), and 2HG levels were also more accurately estimated with ProFit-1D than with LCModel and Gannet across different spectral disturbances and simulated concentrations. ProFit-1D was found to be as precise as LCModel and more precise than Gannet in estimating GABA and Glx. 2HG fit errors were 45% lower with ProFit-1D than with LCModel. Thus, ProFit-1D was found to produce high-quality fits to J- difference edited data with high accuracy and precision.

bioengineering↗

bioRxiv2024

Quantitative 2D J-resolved metabolite-cycled semiLASER spectroscopy of metabolites and macromolecules in the human brain at 9.4 T

PurposeWhile two-dimensional (2D) in vivo spectroscopy yields rich information and has been successfully used in clinical trials, it requires a localization scheme that minimizes the impact of chemical shift displacement on J-coupling evolution, a robust frequency drift correction and dedicated processing and quantification methods. Considering these needs this study demonstrates a novel data acquisition and an analysis pipeline to quantify 16 metabolites in mmol/kg in the human brain using a 2D J-resolved metabolite-cycled (MC) semiLASER localization sequence at 9.4 T in the human brain. MethodsMetabolite spectra were acquired in vivo using the newly developed J-resolved MC semiLASER localization sequence with maximum echo sampling (MES) at 9.4 T. In order to account for the underlying macromolecular (MM) spectra in the acquired metabolite spectra, J-resolved MM spectra were acquired using a double inversion recovery (DIR) J-resolved MC semiLASER. Spectral fitting was performed with ProFit 2.0 using a simulated basis set from VesPA tailored to 2D J-resolved semiLASER with MES. Finally, metabolite concentrations were calculated using internal water referencing. ResultsTissue concentrations for 16 metabolites in mmol/kg are reported after correcting for number of protons, tissue content, and relaxation effects of both water and metabolites at 9.4T. Quantification results of spectra considering 8 and 2 averages per TE did not show any significant differences. Conclusion2D spectra of metabolites acquired at 9.4T and 2D MMs acquired at any field strength are presented for the first time. Basis set simulation and quantification of metabolites for metabolite spectra acquired using maximum-echo-sampled 2D J-resolved semiLASER was performed for the first time. The sensitivity in the detection of J-coupled metabolites such as glutamine, glucose or lactate. At ultra-high field, the acquisition duration of 2D MRS can be also substantially reduced since only a very low number of averages per TE are needed.

neuroscience↗

bioRxiv2024

Quantitative metabolic reference for healthy human cerebrum derived from group averaged 9.4T 1H MRSI data

Drawing inspiration from previous works using 1H FID MRSI, this study quantifies metabolite concentrations at 9.4 T in the human cerebrum of a volunteer cohort and performs a respective group analysis to derive region specific metabolite concentrations. Voxel-specific corrections were performed for both water and individual metabolites, as well as used tissue specific T1-relaxation times. Anatomical and magnetic resonance spectroscopic imaging data were collected using MP2RAGE and FID MRSI sequences, and subsequent data underwent a series of preprocessing techniques. Results showed consistent metabolite maps for key metabolites (NAA, tCr, Glu, tCho and mI), while instability in data quality was noted for lower slices. This study not only showcases the potential of metabolite quantification and mapping at 9.4 T but also underscores the necessity for meticulous data processing to ensure accurate metabolite representations. Comparisons with earlier works and single voxel results validate the methodologies adopted. HighlightsO_LIQuantitative whole cerebrum metabolite maps in the human brain acquired at 9.4 T. C_LIO_LIGroup averaged regional metabolite concentrations. C_LIO_LIGroup summed regional metabolite spectra. C_LI

neuroscience↗

bioRxiv2022

Mapping of Glutamate Metabolism using 1H FID-MRSI after oral Administration of Glc at 9.4 T

Glutamate is the major excitatory transmitter in the brain and malfunction of the related metabolism is associated with various neurological diseases and disorders. The observation of labeling changes in the spectra after the administration of a 13C labelled tracer is a common tool to gain better insights into the function of the metabolic system. But so far, only a very few studies presenting the labelling effects in more than two voxels to show the spatial dependence of metabolism. In the present work, the labeling effects were measured in a transversal plane in the human brain using ultra-short TE and TR 1H FID-MRSI. The measurement set-up was most simple: The [1-13C]Glc was administered orally instead of intravenous and the spectra were measured with a pure 1H technique without the need of a 13C channel (as Boumezbeur et al. demonstrated in 2004). Thus, metabolic maps and enrichment curves could be obtained for more metabolites and in more voxels than ever before in human brain. Labeling changes could be observed in [4-13C]glutamate, [3-13C]glutamate+glutamine, [2-13C]glutamate+glutamine, [4-13C]glutamine, [2,3-13C]aspartate and [6-13C]N-acetyl aspartate with a high temporal (3.6 min) and spatial resolution (32x32 grid with nominal voxel size of 0.33 L) in five volunteers.

neuroscience↗

bioRxiv2022

Test-retest reproducibility of human brain multi-slice 1H FID-MRSI data at 9.4 T after optimization of lipid regularization, macromolecular model and spline baseline stiffness

* PurposeThis study analyzes the effects of retrospective lipid suppression, a simulated macromolecular prior knowledge and different spline baseline stiffness values on 9.4 T multi-slice proton FID-MRSI data spanning the whole cerebrum of human brain and its reproducibility of metabolite ratio (/tCr) maps for 10 brain metabolites. * MethodsMeasurements were performed twice on five volunteers using a non-accelerated FID MRSI 2D sequence at 9.4 T. The effects of retrospective lipid L2-regularization, macromolecular spectrum and different LCModel baseline flexibilities on SNR, FWHM, fitting residual, CRLB and the concentration ratio maps were investigated. Intra-subject, inter-session coefficient of variation of the mean metabolite ratios (/tCr) of each slice was calculated. * ResultsL2-regularization provided effective suppression of lipid-artifacts, but should be avoided if no artifacts are detected. Transversal, sagittal and coronal of many metabolite ratio maps correspond to anatomically expected concentration relations in gray and white matter for the majority of the cerebrum when using a flexible baseline in LCModel fit. Additionally, results from the second measurements of the same subjects show that slice positioning and data quality correlate significantly to the first measurement. * ConclusionConcentration ratio maps (/tCr) for 4 metabolites (tCho, NAA, Glu, mI) spanning the majority and six metabolites (NAAG, GABA, GSH, Tau, Gln, Asp) covering 32 mm in the upper part of the brain were acquired at 9.4 T using multi-slice FID MRSI with retrospective lipid suppression, a macromolecular spectrum and a flexible LCModel baseline.

neuroscience↗

bioRxiv2022

Dynamic observation of 2H labeled compounds in the human brain with 1H versus 2H magnetic resonance spectroscopy at 9.4T

The metabolic pathway of [6,6-2H2]-labeled glucose was investigated with two different techniques. The first technique used direct detection of deuterium applying Deuterium Metabolic Imaging (DMI). The second technique used the indirect detection of deuterium with proton MR spectroscopy (MRS) called Quantitative Exchanged-label Turnover (QELT) MRS. For the first time, time-resolved data was acquired for both techniques in the same healthy human subjects and directly compared. The time-curves were used in a kinetic model to estimate rates of the metabolic pathway of glucose. Two different kinetic models were compared. One included only DMI data, the second one combined DMI and QELT. For the first model, a tricarboxylic acid (TCA) cycle rate of 0.69 {+/-} 0.10 mol{middle dot}min-1{middle dot}g-1 was determined. For the second model, the estimated TCA cycle rate was 0.68 {+/-} 0.12 mol{middle dot}min-1{middle dot}g-1. In addition, the rate of glutamine synthesis from glutamate could be estimated with model 2 (0.51 {+/-} 0.15 mol{middle dot}min-1{middle dot}g-1). The sensitivity of both methods was evaluated and compared to alternative techniques.

neuroscience↗

bioRxiv2021

31P Transversal Relaxation Times and Metabolite Concentrations in the Human Brain at 9.4T

A method to estimate phosphorus (31P) transversal relaxation times (T2) of coupled spin systems is demonstrated. Additionally, intracellular and extracellular pH (pHext, pHint) and relaxation corrected metabolite concentrations are reported. Echo time (TE) series of 31P metabolite spectra were acquired using STEAM localization. Spectra were fitted using LCModel with accurately modeled Vespa basis sets accounting for J-evolution of the coupled spin systems. T2s were estimated by fitting a single exponential two-parameter model across the TE series. Fitted inorganic phosphate frequencies were used to calculate pH, and relaxation times were used to determine the brain metabolite concentrations. The method was demonstrated in the healthy human brain at a field strength of 9.4T. T2 relaxation times of ATP and NAD are the shortest between 8 ms and 20 ms, followed by T2s of inorganic phosphate between 25 ms and 50 ms, and PCr with a T2 of 100 ms. Phosphomonoesters and -diesters have the longest T2s of about 130 ms. Measured T2s are comparable to literature values and fit in a decreasing trend with increasing field strengths. Calculated pHs and metabolite concentrations are also comparable to literature values.

neuroscience↗

bioRxiv2021

Quantitative T1-relaxation corrected metabolite mapping of 12 metabolites in the human brain at 9.4 T

Magnetic resonance spectroscopic imaging (MRSI) is a non-invasive imaging modality that enables observation of metabolites. Applications of MRSI for neuroimaging applications has shown promise for monitoring and detecting various diseases. This study builds off previously developed techniques of short TR, 1H FID MRSI by correcting for T1-weighting of the metabolites and utilizing an internal water reference to produce quantitative (mmol kg-1) metabolite maps. This work reports and shows quantitative metabolite maps for 12 metabolites for a single slice. Voxel-specific T1-corrections for water are common in MRSI studies; however, most studies use either averaged T1-relaxation times to correct for T1-weighting of metabolites or omit this correction step entirely. This work employs the use of voxel-specific T1-corrections for metabolites in addition to water. Utilizing averaged T1-relaxation times for metabolites can bias metabolite maps for metabolites that have strong differences between T1-relaxation for GM and WM (i.e. Glu). This work systematically compares quantitative metabolite maps to single voxel quantitative results and qualitatively compares metabolite maps to previous works. HighlightsO_LIQuantitative metabolite maps of 12 metabolites human brains acquired at 9.4 T. C_LIO_LIVoxel-specific T1-weighting corrections for water and metabolites. C_LIO_LIComparisons of T1-weighted and T1-corrected metabolite maps. C_LI

neuroscience↗