Proton Magnetic Resonance Spectroscopy in Brain Tumor Assessment

Proton magnetic resonance spectroscopy (1H MRS) is a non-invasive imaging technique that quantifies biochemical compounds in brain tissue, offering metabolic insights beyond conventional MRI. By measuring resonances of metabolites such as N-acetylaspartate, choline, creatine, lactate and lipids, 1H MRS can characterise tumour grade, distinguish neoplastic from non-neoplastic lesions and monitor treatment effects. Multivoxel and high-field implementations expand coverage and spectral resolution, enabling mapping of tumour heterogeneity and infiltration. Advances in hyperpolarisation dramatically enhance signal sensitivity, permitting real-time interrogation of tumour metabolism. Clinical applications include preoperative grading, prognostic stratification and early detection of recurrence or pseudoprogression. Integration with machine learning further refines classification and therapy-response prediction. Collectively, these developments position proton spectroscopy as a powerful complement to anatomical imaging, with global relevance for personalised management of brain tumours.

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Proton Magnetic Resonance Spectroscopy in Brain Tumor Assessment publication trend

The graph below shows the total number of articles in proton magnetic resonance spectroscopy in brain tumor assessment across all publications each year (not limited to Nature Index journals).

Technical terms

Proton Magnetic Resonance Spectroscopy (1H MRS): An imaging modality that measures the chemical composition of brain tissue by detecting hydrogen-proton resonances in metabolites.

Metabolite: A small molecule involved in cellular biochemical processes; in MRS, common metabolites include N-acetylaspartate, choline and creatine.

N-acetylaspartate (NAA): An amino acid derivative found predominantly in neurons, used as a marker of neuronal integrity.

Hyperpolarisation: A technique that temporarily increases signal strength in MRS by aligning a greater fraction of nuclear spins, improving sensitivity.

Spectroscopic Imaging (MRSI): A variation of MRS that acquires metabolite spectra from multiple voxels simultaneously, enabling spatial mapping of biochemical changes.

Convolutional Neural Network (CNN): A type of deep learning model well suited to pattern recognition in spectroscopic or imaging data, used for automated classification and segmentation.

References

1. Tracking Therapy Response in Glioblastoma Using 1D Convolutional Neural Networks. Cancers (2023).
2. Hyperpolarized Magnetic Resonance Imaging, Nuclear Magnetic Resonance Metabolomics, and Artificial Intelligence to Interrogate the Metabolic Evolution of Glioblastoma. Metabolites (2024).
3. Tissue-type mapping of gliomas. NeuroImage Clinical (2018).
4. Multivoxel 1H-MR Spectroscopy Biometrics for Preoprerative Differentiation Between Brain Tumors. Tomography (2018).
5. Proton MR Spectroscopy Improves Discrimination between Tumor and Pseudotumoral Lesion in Solid Brain Masses. American Journal of Neuroradiology (2008).
6. Whole-Brain N-Acetylaspartate as a Surrogate Marker of Neuronal Damage in Diffuse Neurologic Disorders. American Journal of Neuroradiology (2007).