TL;DR
Both MGRP and SSVR improved voxel placement and metabolite measurement reproducibility compared with conventional anatomy-based placement and improved within-subject reproducibility across repeated sessions, providing a robust approach for longitudinal single-voxel MRS studies.
While small-voxel SVS is technically feasible and reduces scan time, these findings represent protocol-specific descriptive data in a small sample of healthy dogs and do not establish clinical reference values or diagnostic accuracy.
Qualitative similarities between volume measurements in adults and the questions of reproducibility through test-retest reliability and external validity using recent software updates to the Hyperfine Swoop system constitute a crucial foundation for the clinical utility of 64 mT MRI in monitoring brain volume loss over time.
Transparent assessment of diffusion magnetic resonance imaging (dMRI) techniques with empirical verification of confounding factors requires adequately designed protocols and collected datasets. Publicly available diffusion-weighted MR datasets often provide limited sampling across b-values, making it difficult to study optimal acquisition protocols or the relationships between different processes occurring in brain tissue. In this work, we introduce a new densely sampled longitudinal test-retest diffusion-weighted MR dataset of the brain. Our dataset was collected from eleven healthy volunteers, each scanned four times: two sessions on consecutive days, which form the test data, followed by two additional sessions completed one week later (retest data). The data were acquired using twenty-two b-values ranging from 10 to 3000 s/mm2, along with structural T1-weighted scans. Potential applications of the dataset include, but are not limited to, assessing longitudinal reproducibility and reliability of quantitative metrics, evaluating robust and outlier-resistant estimation techniques, investigating experimental factors affecting estimation procedures, and verifying optimal acquisition protocols for different signal models. The dataset is publicly available in raw and fully preprocessed variants.
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.
Background/Objectives: Automated brain volumetry is increasingly integrated into the work-up of several neurological disorders, yet between-software variability may limit the interchangeability of absolute measures. This study aimed to assess inter-software variability, agreement, and interchangeability among four clinically available AI-based brain volumetry tools. Methods: We conducted a single-center, retrospective comparison of four clinically available tools (Neurophet AQUA®, icobrain dm®, mdbrain®, Pixyl®) applied to identical 3D T1-weighted MRI examinations (IR-FSPGR, 1 mm isotropic) acquired at 3 T in 47 adults referred for tremor evaluation. Absolute volumes (mL) were extracted for hippocampus, temporal, parietal, and frontal lobes, lateral ventricles, and total brain volume; the occipital lobe was analyzed where reported (three tools). Region-wise complete-case analyses were performed. Repeated-measures ANOVA with Bonferroni post hoc tests assessed systematic differences, and intraclass correlation coefficients (two-way mixed, consistency) were reported as single- and average-measure with 95% CIs to quantify agreement. Results: Across regions, all tests were significant (p < 0.001), indicating method-dependent scale offsets typically on the order of ~20–40%. A consistent pattern emerged: icobrain dm® yielded the largest absolute volumes, Neurophet AQUA® the lowest, mdbrain® tended to be lower for parietal measurements, and Pixyl® was generally intermediate. Agreement was structure-dependent: excellent for lateral ventricles (single-measure ICC ≈ 0.92 [0.85–0.96]; average-measure ICC ≈ 0.98 [0.96–0.99]); good-to-excellent for temporal and parietal lobes (average-measure ICC ≈ 0.83–0.84); moderate-to-good for hippocampus and total brain volume (TBV) (average-measure ICC ≈ 0.79–0.81), with only moderate single-measure agreement for TBV (ICC ≈ 0.51); and lowest for the frontal lobe (single-measure ICC ≈ 0.43 [0.23–0.65]; average-measure ICC ≈ 0.75 [0.54–0.88]). In the occipital lobe (three tools), Neurophet AQUA® yielded substantially smaller values than icobrain dm® and mdbrain® (p < 0.0001). Conclusions: Overall, absolute volumetric outputs are not directly interchangeable across platforms, but relative subject ranking is largely preserved; platform-consistent analysis is advisable for longitudinal monitoring, and cross-site studies should implement calibration/harmonization before pooling data.
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