Impact: This work proposed a fast, high-resolution, quantitative MRSI technology for non-invasive mapping of brain metabolites and neurotransmitters, which is expected to provide a powerful metabolic imaging tool to study brain function and diseases.

Impact: A means to quantify uncertainty in SPICE-reconstructed MRSI is proposed, improving the interpretability of SPICE reconstructions by providing informative uncertainty measures on metabolite concentrations derived from SPICE reconstructed MRSI. Spatial priors and undersampling factor affecting SPICE uncertainty are explored.

Impact: This weakly supervised artifact-removal DL network for ¹H-MRSI, trained exclusively on in-vivo data, robustly suppresses residual water, ghosting, lipid contamination, and gradient modulation sidebands across different artifact severities. The results showed significantly improved spectral fidelity and metabolite-quantification accuracy.

Impact: PhoENIx outperformed competing models in the 2024 MRSI Quantitation Challenge, leveraging semi-supervised training. Despite the success of PhoENIx, critical evaluation of the winning model sharpens the understanding of strengths, limitations, and possible fields of application for deep learning-based fitting methods.

Impact: Multiverse MRS analyses improve the accuracy of modeling results compared to a single-model approach and better characterize the real uncertainty. This approach reduces inter-operator bias and will reduce the analytic variability of the findings of MRS studies.

Impact: Macromolecular fitting strategies substantially influence the detection of metabolic age-related effects. Careful evaluation and selection of appropriate macromolecular models are crucial for accurate interpretation of neurometabolic changes across the lifespan.

Impact: This first real-time assessment of prefrontal HD-tDCS revealed a specific decrease in Glx, while GABA⁺ exhibited only non-specific, time-dependent changes. These findings provide key insight into the mechanisms of HD-tDCS, supporting its optimization as a targeted intervention for psychiatric disorders.

Impact: The spatial overlap of neuronal dysfunction and glucose hypometabolism from the PCC/PCu to association cortices highlights their vulnerability during AD progression. Preserving neuronal integrity in these regions may confer cognitive resilience and guide targeted interventions to slow disease progression.

Impact: If mouse models of cerebrospinal fluid (CSF) stagnation exhibit abnormal in vivo proton magnetic resonance spectroscopy (¹H-MRS)-visible brain lactate dynamics during CSF flow manipulations, then ¹H-MRS may be used to noninvasively investigate CSF-mediated brain solute clearance.