Metabolic magnetic resonance imaging (MRI) enables visualization of metabolic processes within tissues throughout the body in a noninvasive way, without the use of targeting agents like radionuclides or the need for ex vivo tissue assessment. Although not a new imaging technique – nuclear MR spectroscopy (MRS) predates MR imaging by several decades – translation to the clinic has proven difficult because the relevant target molecules are of low concentration in the human body, requiring a detection sensitivity that is difficult to achieve on standard clinical MRI platforms (1.5-3.0 tesla (T)).
Ultrahigh field (UHF) MRI – 7 T and beyond – has the potential to improve clinical applicability of metabolic MRI. UHF with its increased signal-to-noise ratio enables higher spatial and spectral resolution, which translates to increased sensitivity for low-concentration molecules like neurotransmitters and other metabolites associated with tissue function and metabolism. UHF MRI has already tentatively shown its value for metabolic MR modalities like MRS, chemical exchange saturation transfer (CEST) and X-nuclei (other than 1H) imaging in recent years. Nevertheless, both metabolic MRI and UHF imaging are still regarded primarily as research tools, available at a few dedicated clinical centers.
With the advent of the first clinically approved 7 T MRI platforms in October 2017, UHF MRI – and therefore metabolic MRI – should become more accessible for clinical use. This calls for an active approach towards clinical translatability of UHF metabolic MRI, not only from a research perspective (e.g., improving techniques for clinical use, showing the added diagnostic value for the individual patient) but also from a clinical perspective (e.g., what diagnostic challenges need to be solved, clinical relevance of current approaches). Now more than ever, collaborations between the clinic and the research world will be essential if we want to take full advantage of UHF metabolic MRI for clinical care.
This Research Topic aims to stimulate translation of UHF metabolic MRI from bench to bedside. The topics we would like to cover in this article collection include but are not limited to:
• Metabolic pathways relevant for cancer / metabolic disease / degenerative disease / etc. (also from a pathology perspective)
• Technical considerations regarding currently available metabolic MRI sequences
• Technical requirements of research metabolic MRI techniques and adaptations needed for clinical systems
• Emerging (pre)clinical metabolic MRI techniques
• Clinical challenges for which no or limited diagnostic measures are available
• Consensus guidelines for specific metabolic MRI techniques at UHF / their use in the clinic
• Methods to facilitate clinical translation of UHF metabolic MRI from a research / clinical perspective
• Metabolic modeling using metabolic MR data with specific tools as slow-fast systems;
• AI issues concerning spectroscopic data and other problems as super resolution 3T-7T.
Topic Editor Armin Nagel (University Hospital Erlangen) received research support from Siemens Healthineers. The other Topic Editors declare no competing interests with regard to the Research Topic subject.
Metabolic magnetic resonance imaging (MRI) enables visualization of metabolic processes within tissues throughout the body in a noninvasive way, without the use of targeting agents like radionuclides or the need for ex vivo tissue assessment. Although not a new imaging technique – nuclear MR spectroscopy (MRS) predates MR imaging by several decades – translation to the clinic has proven difficult because the relevant target molecules are of low concentration in the human body, requiring a detection sensitivity that is difficult to achieve on standard clinical MRI platforms (1.5-3.0 tesla (T)).
Ultrahigh field (UHF) MRI – 7 T and beyond – has the potential to improve clinical applicability of metabolic MRI. UHF with its increased signal-to-noise ratio enables higher spatial and spectral resolution, which translates to increased sensitivity for low-concentration molecules like neurotransmitters and other metabolites associated with tissue function and metabolism. UHF MRI has already tentatively shown its value for metabolic MR modalities like MRS, chemical exchange saturation transfer (CEST) and X-nuclei (other than 1H) imaging in recent years. Nevertheless, both metabolic MRI and UHF imaging are still regarded primarily as research tools, available at a few dedicated clinical centers.
With the advent of the first clinically approved 7 T MRI platforms in October 2017, UHF MRI – and therefore metabolic MRI – should become more accessible for clinical use. This calls for an active approach towards clinical translatability of UHF metabolic MRI, not only from a research perspective (e.g., improving techniques for clinical use, showing the added diagnostic value for the individual patient) but also from a clinical perspective (e.g., what diagnostic challenges need to be solved, clinical relevance of current approaches). Now more than ever, collaborations between the clinic and the research world will be essential if we want to take full advantage of UHF metabolic MRI for clinical care.
This Research Topic aims to stimulate translation of UHF metabolic MRI from bench to bedside. The topics we would like to cover in this article collection include but are not limited to:
• Metabolic pathways relevant for cancer / metabolic disease / degenerative disease / etc. (also from a pathology perspective)
• Technical considerations regarding currently available metabolic MRI sequences
• Technical requirements of research metabolic MRI techniques and adaptations needed for clinical systems
• Emerging (pre)clinical metabolic MRI techniques
• Clinical challenges for which no or limited diagnostic measures are available
• Consensus guidelines for specific metabolic MRI techniques at UHF / their use in the clinic
• Methods to facilitate clinical translation of UHF metabolic MRI from a research / clinical perspective
• Metabolic modeling using metabolic MR data with specific tools as slow-fast systems;
• AI issues concerning spectroscopic data and other problems as super resolution 3T-7T.
Topic Editor Armin Nagel (University Hospital Erlangen) received research support from Siemens Healthineers. The other Topic Editors declare no competing interests with regard to the Research Topic subject.
