About this Research Topic
This Research Topic is the second volume of the Research Topic "Brain Metabolic Imaging by Magnetic Resonance Imaging and Spectroscopy: Methods and Clinical Applications". Please see the first volume
here.
Brain metabolic imaging using Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS) is a rapidly evolving field that provides critical insights into the metabolic pathways of neuronal and glial cells. These pathways are essential for understanding how nutrients, neurotransmitters, and other neuro metabolites support cellular growth and function. In the context of neurological diseases, metabolic alterations often precede observable changes in tissue morphology and function, highlighting the importance of early detection. Despite its potential, MR metabolic imaging faces challenges such as low signal-to-noise ratio and spatial resolution due to the low concentration of brain metabolites. Recent advancements in MR metabolic imaging techniques, including 1H editing MRS and high-resolution 1H MRSI, have significantly enhanced the precision of brain metabolite quantification. Additionally, the development of multinuclear MRI/MRS and Chemical Exchange Saturation Transfer (CEST) MRI has garnered increased interest for their ability to map brain metabolites indirectly. These technological advancements, coupled with improvements in MR hardware and data reconstruction methods, underscore the translational potential of MR metabolic imaging in understanding brain disorders and guiding clinical diagnosis and treatment.
This research topic aims to explore the latest advancements in brain metabolic imaging using MRI and MRS, focusing on both methodological innovations and clinical applications. The primary objectives include addressing the challenges of low signal-to-noise ratio and spatial resolution, evaluating the efficacy of new imaging techniques, and understanding their implications for diagnosing and treating neurological disorders. Key questions include how these advancements can improve the accuracy of brain metabolite quantification and what role artificial intelligence can play in enhancing data analysis and interpretation.
To gather further insights in the field of brain metabolic imaging by MRI and MRS, we welcome articles addressing, but not limited to, the following themes:
- Advances in MR metabolic imaging methods for neuroscience, including technical innovations in MRS, MR CEST imaging, and MR multinuclear imaging.
- Clinical studies on brain metabolism using MR metabolic imaging methods, involving both healthy volunteers and patients with various nervous system disorders such as degenerative, functional, vascular, tumorous, and structural disorders.
- Integration of artificial intelligence into the workflow of brain metabolic imaging studies, focusing on data collection, post-processing, and analysis.
Liangjie Lin Ph.D. and Jiazheng Wang Ph.D. are MR research scientists in Philips Healthcare, a commercial producer of diagnosis imaging devices. This should not pose any conflict for this project, as they will maintain objectivity.
here.
Brain metabolic imaging using Magnetic Resonance Imaging (MRI) and Spectroscopy (MRS) is a rapidly evolving field that provides critical insights into the metabolic pathways of neuronal and glial cells. These pathways are essential for understanding how nutrients, neurotransmitters, and other neuro metabolites support cellular growth and function. In the context of neurological diseases, metabolic alterations often precede observable changes in tissue morphology and function, highlighting the importance of early detection. Despite its potential, MR metabolic imaging faces challenges such as low signal-to-noise ratio and spatial resolution due to the low concentration of brain metabolites. Recent advancements in MR metabolic imaging techniques, including 1H editing MRS and high-resolution 1H MRSI, have significantly enhanced the precision of brain metabolite quantification. Additionally, the development of multinuclear MRI/MRS and Chemical Exchange Saturation Transfer (CEST) MRI has garnered increased interest for their ability to map brain metabolites indirectly. These technological advancements, coupled with improvements in MR hardware and data reconstruction methods, underscore the translational potential of MR metabolic imaging in understanding brain disorders and guiding clinical diagnosis and treatment.
This research topic aims to explore the latest advancements in brain metabolic imaging using MRI and MRS, focusing on both methodological innovations and clinical applications. The primary objectives include addressing the challenges of low signal-to-noise ratio and spatial resolution, evaluating the efficacy of new imaging techniques, and understanding their implications for diagnosing and treating neurological disorders. Key questions include how these advancements can improve the accuracy of brain metabolite quantification and what role artificial intelligence can play in enhancing data analysis and interpretation.
To gather further insights in the field of brain metabolic imaging by MRI and MRS, we welcome articles addressing, but not limited to, the following themes:
- Advances in MR metabolic imaging methods for neuroscience, including technical innovations in MRS, MR CEST imaging, and MR multinuclear imaging.
- Clinical studies on brain metabolism using MR metabolic imaging methods, involving both healthy volunteers and patients with various nervous system disorders such as degenerative, functional, vascular, tumorous, and structural disorders.
- Integration of artificial intelligence into the workflow of brain metabolic imaging studies, focusing on data collection, post-processing, and analysis.
Liangjie Lin Ph.D. and Jiazheng Wang Ph.D. are MR research scientists in Philips Healthcare, a commercial producer of diagnosis imaging devices. This should not pose any conflict for this project, as they will maintain objectivity.
Keywords: brain metabolism, neurotransmitter, biomarker, MRS, multi-nuclear, spectral editing, CEST
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
