BACKGROUND: Associations between longitudinal changes of plasma biomarkers and cerebral magnetic resonance (MR)‐derived measurements in Alzheimer's disease (AD) remain unclear.METHODS: In a study population (n = 127) of healthy older adults and patients within the AD continuum, we examined associations between longitudinal plasma amyloid beta 42/40 ratio, tau phosphorylated at threonine 181 (p‐tau181), glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and 7T structural and functional MR imaging and spectroscopy using linear mixed models.RESULTS: Increases in both p‐tau181 and GFAP showed the strongest associations to 7T MR‐derived measurements, particularly with decreasing parietal cortical thickness, decreasing connectivity of the salience network, and increasing neuroinflammation as determined by MR spectroscopy (MRS) myo‐inositol.DISCUSSION: Both plasma p‐tau181 and GFAP appear to reflect disease progression, as indicated by 7T MR‐derived brain changes which are not limited to areas known to be affected by tau pathology and neuroinflammation measured by MRS myo‐inositol, respectively.Highlights: This study leverages high‐resolution 7T magnetic resonance (MR) imaging and MR spectroscopy (MRS) for Alzheimer's disease (AD) plasma biomarker insights. Tau phosphorylated at threonine 181 (p‐tau181) and glial fibrillary acidic protein (GFAP) showed the largest changes over time, particularly in the AD group. p‐tau181 and GFAP are robust in reflecting 7T MR‐based changes in AD. The strongest associations were for frontal/parietal MR changes and MRS neuroinflammation.

Purpose: To introduce a study design and statistical analysis framework to assess the repeatability, reproducibility, and minimal detectable changes (MDCs) of metabolite concentrations determined by in vivo MRS.Methods: An unbalanced nested study design was chosen to acquire in vivo MRS data within different repeatability and reproducibility scenarios. A spin‐echo, full‐intensity acquired localized (SPECIAL) sequence was employed at 7 T utlizing three different inversion pulses: a hyperbolic secant (HS), a gradient offset independent adiabaticity (GOIA), and a wideband, uniform rate, smooth truncation (WURST) pulse. Metabolite concentrations, Cramér‐Rao lower bounds (CRLBs) and coefficients of variation (CVs) were calculated. Both Bland‐Altman analysis and a restricted maximum‐likelihood estimation (REML) analysis were performed to estimate the different variance contributions of the repeatability and reproducibility of the measured concentration. A Bland‐Altmann analysis of the spectral shape was performed to assess the variance of the spectral shape, independent of quantification model influences.Results: For the used setup, minimal detectable changes of brain metabolite concentrations were found to be between 0.40 µmol/g and 2.23 µmol/g. CRLBs account for only 16 % to 74 % of the total variance of the metabolite concentrations. The application of gradient‐modulated inversion pulses in SPECIAL led to slightly improved repeatability, but overall reproducibility appeared to be limited by differences in positioning, calibration, and other day‐to‐day variations throughout different sessions.Conclusion: A framework is introduced to estimate the precision of metabolite concentrations obtained by MRS in vivo, and the minimal detectable changes for 13 metabolite concentrations measured at 7 T using SPECIAL are obtained.

In the realm of medical research, preserving patient privacy while facilitating effective research and collaborations poses a significant challenge. Data protection impact assessments (DPIAs) and associated methodologies have emerged as a response to this dual imperative. DPIAs necessitate expertise across diverse domains, resulting in a complex procedural landscape. To address this, we present “DPIA click&go”, a user-friendly tool designed to streamline the DPIA process in a plug-and-play manner. This tool enables users to semi-automatically select risks from predefined categories, construct evaluation matrices, access risk-mitigating measures, and re-evaluate risks after the application of mitigation strategies. Tailoring risks and measures to each institute’s needs is essential, facilitated by the provided data model, considerably simplifying DPIA creation at an institutional level. The efficacy of the DPIA click&go tool was validated with a real-world project, comparing its performance with a manually created DPIA in terms of risk coverage and mitigation strategies. The promising outcomes of this tool underscore its potential within the national data protection landscape, suggesting its possible foundational role in harmonizing data protection practices at a larger, potentially, European or global, scale.

Purpose: This study investigates the feasibility of using complex‐valued neural networks (NNs) to estimate quantitative transmit magnetic RF field (B ₁ ⁺ ) maps from multi‐slice localizer scans with different slice orientations in the human head at 7T, aiming to accelerate subject‐specific B ₁ ⁺ ‐calibration using parallel transmission (pTx). Methods: Datasets containing channel‐wise B ₁ ⁺ ‐maps and corresponding multi‐slice localizers were acquired in axial, sagittal, and coronal orientation in 15 healthy subjects utilizing an eight‐channel pTx transceiver head coil. Training included five‐fold cross‐validation for four network configurations: used transversal, sagittal, coronal data, and was trained on all slice orientations. The resulting maps were compared to B ₁ ⁺ ‐reference scans using different quality metrics. The proposed network was applied in‐vivo at 7T in two unseen test subjects using dynamic kt‐point pulses. Results: Predicted B ₁ ⁺ ‐maps demonstrated a high similarity with measured B ₁ ⁺ ‐maps across multiple orientations. The estimation matched the reference with a mean relative error in the magnitude of (2.70 ± 2.86)% and mean absolute phase difference of (6.70 ± 1.99)° for transversal, (1.82 ± 0.69)% and (4.25 ± 1.62)° for sagittal (), as well as (1.33 ± 0.27)% and (2.66 ± 0.60)° for coronal slices () considering brain tissue. trained on all orientations enables a robust prediction of B ₁ ⁺ ‐maps across different orientations. Achieving a homogenous excitation over the whole brain for an in‐vivo application displayed the approach's feasibility. Conclusion: This study demonstrates the feasibility of utilizing complex‐valued NNs to estimate multi‐slice B ₁ ⁺ ‐maps in different slice orientations from localizer scans in the human brain at 7T.

Background We developed, introduced, and evaluated Molecular ONcology Optimized CLinical Evaluation (MONOCLE), a secure, open-source web application at the University Medical Center Hamburg-Eppendorf (UKE), to optimize the analysis and discussion of complex cancer cases in molecular tumor boards (MTB). Objective MONOCLE standardizes and harmonizes documentation, while its integrated Knowledge Connector accelerates literature research for personalized treatment. Patients and Methods The system was designed by merging the requirements of the German Network for Personalized Medicine (DNPM), the medical staff involved in the MTB process, and the team developing MONOCLE. The usability was evaluated using the System Usability Scale (SUS) and user tasks. Overall process optimization was measured by the number of automated tasks that can be performed. Results MONOCLE, introduced into clinical practice in June 2024, significantly reduces time for documentation, as three manual steps now run automatically, and transfer of the data to the DNPM is possible. Its usability and SUS showed positive results, ranging between 92.5 and 97.5. Conclusions As the first open-source and extendable solution for standardized MTB documentation, MONOCLE enables wider adoption by other medical centers.

Purpose To simultaneously acquire spectroscopic signals from two MRS voxels using a multi-banded 2 spin-echo, full-intensity acquired localized (2SPECIAL) sequence, and to decompose the signal to their respective regions by a novel voxel-GRAPPA (vGRAPPA) decomposition approach for in vivo brain applications at 7 T. Methods A wideband, uniform rate, smooth truncation (WURST) multi-banded pulse was incorporated into SPECIAL to implement 2SPECIAL for simultaneous multi-voxel spectroscopy (sMVS). To decompose the acquired data, the voxel-GRAPPA decomposition algorithm is introduced, and its performance is compared to the SENSE-based decomposition. Furthermore, the limitations of two-voxel excitation concerning the multi-banded adiabatic inversion pulse, as well as of the combined B-0 shim and B-1(+) adjustments, are evaluated. Results It was successfully shown that the 2SPECIAL sequence enables sMVS without a significant loss in SNR while reducing the total scan time by 21.6% compared to two consecutive acquisitions. The proposed voxel-GRAPPA algorithm properly reassigns the signal components to their respective origin region and shows no significant differences to the well-established SENSE-based algorithm in terms of leakage (both <10%) or Cramer-Rao lower bounds (CRLB) for in vivo applications, while not requiring the acquisition of additional sensitivity maps and thus decreasing motion sensitivity. Conclusion The use of 2SPECIAL in combination with the novel voxel-GRAPPA decomposition technique allows a substantial reduction of measurement time compared to the consecutive acquisition of two single voxels without a significant decrease in spectral quality or metabolite quantification accuracy and thus provides a new option for multiple-voxel applications.