Lauterbur, P. C. Image formation by induced local interactions: examples employing nuclear magnetic resonance. Nature 242, 190–191 (1973).
Mansfield, P. Multi-planar image formation using NMR spin echoes. J. Phys. C Solid State Phys. 10, L55–L58 (1977).
Wattjes, M. P. et al. Evidence-based guidelines: MAGNIMS consensus guidelines on the use of MRI in multiple sclerosis—establishing disease prognosis and monitoring patients. Nat. Rev. Neurol. 11, 597–606 (2015).
Wen, P. Y. et al. Updated response assessment criteria for high-grade gliomas: response assessment in neuro-oncology working group. J. Clin. Oncol. 28, 1963–1972 (2010).
Seiler, A. et al. Multiparametric quantitative MRI in neurological diseases. Front. Neurol. 12, 640239 (2021).
Filippi, M. et al. MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines. Lancet Neurol. 15, 292–303 (2016).
Villanueva-Meyer, J. E., Mabray, M. C. & Cha, S. Current clinical brain tumor imaging. Neurosurgery 81, 397–415 (2017).
Frisoni, G. B., Fox, N. C., Jack, C. R., Scheltens, P. & Thompson, P. M. The clinical use of structural MRI in Alzheimer disease. Nat. Rev. Neurol. 6, 67–77 (2010).
Ma, D. et al. Magnetic resonance fingerprinting. Nature 495, 187–192 (2013).
Zhang, Z. et al. Blip up-down acquisition for spin- and gradient-echo imaging (BUDA-SAGE) with self-supervised denoising enables efficient T2, T2*, para- and dia-magnetic susceptibility mapping. Magn. Reson. Med. 88, 633–650 (2022).
Skare, S. et al. A 1-minute full brain MR exam using a multicontrast EPI sequence. Magn. Reson. Med. 79, 3045–3054 (2018).
Christodoulou, A. G. et al. Magnetic resonance multitasking for motion-resolved quantitative cardiovascular imaging. Nat. Biomed. Eng. 2, 215–226 (2018).
Ma, S. et al. Three dimensional simultaneous brain T1, T2, and ADC mapping with MR multitasking. Magn. Reson. Med. 84, 72–88 (2020).
Wang, F. et al. 3D Echo Planar Time-resolved Imaging (3D-EPTI) for ultrafast multi-parametric quantitative MRI. Neuroimage 250, 118963 (2022).
Dupuis, A. et al. Quantifying 3D MR fingerprinting (3D-MRF) reproducibility across subjects, sessions, and scanners automatically using MNI atlases. Magn. Reson. Med. 91, 2074–2088 (2024).
Haacke, E. M. et al. STrategically Acquired Gradient Echo (STAGE) imaging, part III: technical advances and clinical applications of a rapid multi-contrast multi-parametric brain imaging method. Magn. Reson. Imaging 65, 15–26 (2020).
Posse, S., Otazo, R., Dager, S. R. & Alger, J. MR spectroscopic imaging: principles and recent advances. J. Magn. Reson. Imaging 37, 1301–1325 (2013).
de Graaf, R. A. In Vivo NMR Spectroscopy: Principles and Techniques (Wiley, 2007).
Liang, Z.-P. Spatiotemporal imaging with partially separable functions. In Proc. 2007 4th IEEE International Symposium on Biomedical Imaging: From Nano to Macro 988–991 (IEEE, 2007).
Qian, E., Poojar, P., Vaughan, J. T., Jin, Z. & Geethanath, S. Tailored magnetic resonance fingerprinting for simultaneous non-synthetic and quantitative imaging: a repeatability study. Med. Phys. 49, 1673–1685 (2022).
Eftekhari, Z. et al. Reliability and reproducibility of metabolite quantification using 1H MRS in the human brain at 3 T and 7 T. NMR Biomed. 38, e70087 (2025).
van de Bank, B. L. et al. Multi-center reproducibility of neurochemical profiles in the human brain at 7 T. NMR Biomed. 28, 306–316 (2015).
Naji, N. et al. Multisite reproducibility of quantitative susceptibility mapping and effective transverse relaxation rate in deep gray matter at 3 T using locally optimized sequences in 24 traveling heads. NMR Biomed. 35, e4788 (2022).
Ellingson, B. M. et al. Consensus recommendations for a standardized brain tumor imaging protocol in clinical trials. Neuro Oncol. 17, 1188–1198 (2015).
Barker, P. B. & Phil, D. Imaging of brain tumors: MR spectroscopy and metabolic imaging. Neuroimaging Clin. N. Am. 20, 293–310 (2011).
Ekici, S. et al. Glutamine imaging: a new avenue for glioma management. Am. J. Neuroradiol. 43, 11–18 (2022).
Li, T.-J., Jiang, J., Tang, Y.-L. & Liang, X.-H. Insights into the leveraging of GABAergic signaling in cancer therapy. Cancer Med. 12, 14498–14510 (2023).
Schaffer, S., Takahashi, K. & Azuma, J. Role of osmoregulation in the actions of taurine. Amino Acids 19, 527–546 (2000).
Thomas, D. C. et al. A fast protocol for multicenter and multiparametric quantitative MRI studies in brain tumor patients using vendor sequences. Neurooncol. Adv. 6, vdae117 (2024).
Oughourlian, T. C. et al. Relative oxygen extraction fraction (rOEF) MR imaging reveals higher hypoxia in human epidermal growth factor receptor (EGFR) amplified compared with non-amplified gliomas. Neuroradiology 63, 857–868 (2021).
Chang, E. L. et al. Evaluation of peritumoral edema in the delineation of radiotherapy clinical target volumes for glioblastoma. Int. J. Radiat. Oncol. Biol. Phys. 68, 144–150 (2007).
De Feyter, H. M. et al. Deuterium metabolic imaging (DMI) for MRI-based 3D mapping of metabolism in vivo. Sci. Adv. 4, eaat7314 (2018).
Meyerand, M. E., Pipas, J. M., Mamourian, A., Tosteson, T. D. & Dunn, J. F. Classification of biopsy-confirmed brain tumors using single-voxel MR spectroscopy. Am. J. Neuroradiol. 20, 117–123 (1999).
Le, Q.-T. et al. In vivo 1H magnetic resonance spectroscopy of lactate in patients with stage IV head and neck squamous cell carcinoma. Int. J. Radiat. Oncol. Biol. Phys. 71, 1151–1157 (2008).
Jonkman, L. E. et al. Can MS lesion stages be distinguished with MRI? A postmortem MRI and histopathology study. J. Neurol. 262, 1074–1080 (2015).
Granziera, C. et al. Quantitative magnetic resonance imaging towards clinical application in multiple sclerosis. Brain 144, 1296–1311 (2021).
Simone, I. L. et al. High resolution proton MR spectroscopy of cerebrospinal fluid in MS patients. Comparison with biochemical changes in demyelinating plaques. J. Neurol. Sci. 144, 182–190 (1996).
Heckova, E. et al. Extensive brain pathologic alterations detected with 7.0-T MR spectroscopic imaging associated with disability in multiple sclerosis. Radiology 303, 141–150 (2022).
Xiong, H. et al. The digital twin brain: a bridge between biological and artificial intelligence. Intell. Comput. 2, 0055 (2023).
Hashemi, M. et al. Principles and operation of virtual brain twins. IEEE Rev. Biomed. Eng. 19, 111–139 (2025).
Guo, R. et al. Simultaneous mapping of water diffusion coefficients and metabolite distributions of the brain using MR spectroscopic imaging without water suppression. IEEE Trans. Biomed. Eng. 70, 962–969 (2023).
Detre, J. A., Leigh, J. S., Williams, D. S. & Koretsky, A. P. Perfusion imaging. Magn. Reson. Med. 23, 37–45 (1992).
Wolff, S. D. & Balaban, R. S. Magnetization transfer imaging: practical aspects and clinical applications. Radiology 192, 593–599 (1994).
Mariappan, Y. K., Glaser, K. J. & Ehman, R. L. Magnetic resonance elastography: a review. Clin. Anat. 23, 497–511 (2010).
Lopez Kolkovsky, A. L., Carlier, P. G., Marty, B. & Meyerspeer, M. Interleaved and simultaneous multi-nuclear magnetic resonance in vivo. Review of principles, applications and potential. NMR Biomed. 35, e4735 (2022).
Østergaard, L. & Sakoh, M. Tissue viability assessed by MRI. Int. Congr. Ser. 1270, 91–96 (2004).
Huang, H. et al. Simultaneous high-resolution whole-brain MR spectroscopy and [18F]FDG PET for temporal lobe epilepsy. Eur. J. Nucl. Med. Mol. Imaging 51, 721–733 (2024).
Chouliaras, L. & O’Brien, J. T. The use of neuroimaging techniques in the early and differential diagnosis of dementia. Mol. Psychiatry 28, 4084–4097 (2023).
Tiepolt, S. et al. Quantitative susceptibility mapping of amyloid-β aggregates in Alzheimer’s disease with 7T MR. J. Alzheimers Dis. 64, 393–404 (2018).
Li, Y., Lam, F., Clifford, B. & Liang, Z.-P. A subspace approach to spectral quantification for MR spectroscopic imaging. IEEE Trans. Biomed. Eng. 64, 2486–2489 (2017).
Li, Y. et al. Machine learning-enabled high-resolution dynamic deuterium MR spectroscopic imaging. IEEE Trans. Med. Imaging 40, 3879–3890 (2021).
Soher, B. J. et al. VESPA: integrated applications for RF pulse design, spectral simulation and MRS data analysis. Magn. Reson. Med. 90, 823–838 (2023).
Li, Y. et al. Improved estimation of myelin water fractions with learned parameter distributions. Magn. Reson. Med. 86, 2795–2809 (2021).
Guo, R. et al. Mapping intracellular NAD content in entire human brain using phosphorus-31 MR spectroscopic imaging at 7 Tesla. Front. Neurosci. 18, 1389111 (2024).
Song, Y. et al. Score-based generative modeling through stochastic differential equations. In Proc. The Ninth International Conference on Learning Representations (ICLR, 2021).
Peng, X., Lam, F., Li, Y., Clifford, B. & Liang, Z.-P. Simultaneous QSM and metabolic imaging of the brain using SPICE. Magn. Reson. Med. 79, 13–21 (2018).
Guo, R. et al. Simultaneous QSM and metabolic imaging of the brain using SPICE: further improvements in data acquisition and processing. Magn. Reson. Med. 85, 970–977 (2021).
Miller, K. L. et al. Multimodal population brain imaging in the UK Biobank prospective epidemiological study. Nat. Neurosci. 19, 1523–1536 (2016).
Van Essen, D. C. et al. The WU-Minn Human Connectome Project: an overview. Neuroimage 80, 62–79 (2013).
Petersen, R. C. et al. Alzheimer’s Disease Neuroimaging Initiative (ADNI). Neurology 74, 201–209 (2010).
Marcus, D. S., Fotenos, A. F., Csernansky, J. G., Morris, J. C. & Buckner, R. L. Open access series of imaging studies: longitudinal MRI data in nondemented and demented older adults. J. Cogn. Neurosci. 22, 2677–2684 (2010).
Liu, G.-H. et al. I2SB: image-to-image Schrödinger bridge. In Proc. 40th International Conference on Machine Learning 22042–22062 (Association for Computing Machinery, 2023).
Lam, F. & Liang, Z.-P. A subspace approach to high-resolution spectroscopic imaging. Magn. Reson. Med. 71, 1349–1357 (2014).
Provencher, S. W. Estimation of metabolite concentrations from localized in vivo proton NMR spectra. Magn. Reson. Med. 30, 672–679 (1993).
Ratiney, H. et al. Time-domain semi-parametric estimation based on a metabolite basis set. NMR Biomed. 18, 1–13 (2005).
Mlynárik, V., Gruber, S. & Moser, E. Proton T1 and T2 relaxation times of human brain metabolites at 3 Tesla. NMR Biomed. 14, 325–331 (2001).
Ernst, T., Kreis, R. & Ross, B. D. Absolute quantitation of water and metabolites in the human brain. I. Compartments and water. J. Magn. Reson. B 102, 1–8 (1993).
Zhang, T. et al. B1 mapping using pre-learned subspaces for quantitative brain imaging. Magn. Reson. Med. 90, 2089–2101 (2023).
Griswold, M. A. et al. Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn. Reson. Med. 47, 1202–1210 (2002).
Pruessmann, K. P., Weiger, M., Scheidegger, M. B. & Boesiger, P. SENSE: sensitivity encoding for fast MRI. Magn. Reson. Med. 42, 952–962 (1999).

