ArticleNature biomedical engineering2025
Ultrafast J-resolved magnetic resonance spectroscopic imaging for high-resolution metabolic brain imaging.
Article in Nature biomedical engineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- High-spatiotemporal resolution deuterium metabolic imaging enables in vivo phenotyping of intra- and intertumoral heterogeneity.Science advances · 2026Article
- Single-breath-hold 3D abdominal metabolic MRI enables label-free diagnosis of liver cancer.Nature communications · 2026Article
- Motion Correction in High-Resolution 3D Brain MRSI Without Water and Lipid Suppression.Magnetic resonance in medicine · 2026Article
- Dual association patterns between microglial activation and neuronal health in Alzheimer's disease: a whole-brain MRSI/PET study.Alzheimer's & dementia : the journal of the Alzheimer's Association · 2026Article
- The rise and deceleration of neuronal excitability in aging and Alzheimer's disease: Mechanisms, implications, and therapeutic targets.Ageing research reviews · 2026Review
- Mitochondrial dysfunction in Alzheimer's disease: connecting pathophysiology with neuroimaging.Frontiers in aging neuroscience · 2026Review
- Creatine-weighted imaging in patients with Parkinson's disease.NPJ Parkinson's disease · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Magnetic resonance spectroscopic imaging has potential for non-invasive metabolic imaging of the human brain. Here we report a method that overcomes several long-standing technical barriers associated with clinical magnetic resonance spectroscopic imaging, including long data acquisition times, limited spatial coverage and poor spatial resolution. Our method achieves ultrafast data acquisition using an efficient approach to encode spatial, spectral and J-coupling information of multiple molecules. Physics-informed machine learning is synergistically integrated in data processing to enable reconstruction of high-quality molecular maps. We validated the proposed method through phantom experiments. We obtained high-resolution molecular maps from healthy participants, revealing metabolic heterogeneities in different brain regions. We also obtained high-resolution whole-brain molecular maps in regular clinical settings, revealing metabolic alterations in tumours and multiple sclerosis. This method has the potential to transform clinical metabolic imaging and provide a long-desired capability for non-invasive label-free metabolic imaging of brain function and diseases for both research and clinical applications.
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Registered trials
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