Imaging of sodium in the brain: a brief review

Shah, N. Jon; Worthoff, Wieland Alexander; Langen, Karl‐Josef

doi:10.1002/nbm.3389

Cited by 52 publications

(54 citation statements)

References 101 publications

(142 reference statements)

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“…Rapidly growing malignant cells have increased Na + concentrations that can be measured with 23 Na MRI . TSC was shown to increase in edema and necrotic tissue …”

Section: Physiologymentioning

confidence: 99%

X‐nuclei imaging: Current state, technical challenges, and future directions

Kleimaier

Malzacher

et al. 2019

Magnetic Resonance Imaging

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1H imaging is concerned with contrast generation among anatomically distinct soft tissues. X‐nuclei imaging, on the other hand, aims to reveal the underlying changes in the physiological processes on a cellular level. Advanced clinical MR hardware systems improved 1H image quality and simultaneously enabled X‐nuclei imaging. Adaptation of 1H methods and optimization of both sequence design and postprocessing protocols launched X‐nuclei imaging past feasibility studies and into clinical studies. This review outlines the current state of X‐nuclei MRI, with the focus on 23Na, 35Cl, 39K, and 17O. Currently, various aspects of technical challenges limit the possibilities of clinical X‐nuclei MRI applications. To address these challenges, quintessential physical and technical concepts behind different applications are presented, and the advantages and drawbacks are delineated. The working process for methods such as quantification and multiquantum imaging is shown step‐by‐step. Clinical examples are provided to underline the potential value of X‐nuclei imaging in multifaceted areas of application. In conclusion, the scope of the latest technical advance is outlined, and suggestions to overcome the most fundamental hurdles on the way into clinical routine by leveraging the full potential of X‐nuclei imaging are presented. Level of Evidence: 1 Technical Efficacy Stage: 3 J. Magn. Reson. Imaging 2020;51:355–376.

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“…Rapidly growing malignant cells have increased Na + concentrations that can be measured with 23 Na MRI . TSC was shown to increase in edema and necrotic tissue …”

Section: Physiologymentioning

confidence: 99%

X‐nuclei imaging: Current state, technical challenges, and future directions

Kleimaier

Malzacher

et al. 2019

Magnetic Resonance Imaging

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“…Any irregularity in tissue metabolism leads to remarkable 23 Na signal intensity changes, and in tumours the sodium concentration level is usually elevated [3, 13,14]. 31…”

Section: Mr-detectablementioning

confidence: 99%

An in vivo multimodal feasibility study in a rat brain tumour model using flexible multinuclear MR and PET systems

Choi

Stegmayr

Shymanskaya

et al. 2020

Preprint

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Background : In addition to the structural information afforded by 1 H MRI, the use of X-nuclei, such as sodium-23 ( 23 Na) or phosphorus-31 ( 31 P), offers important complementary information concerning physiological and biochemical parameters. By then combining this technique with PET, which provides valuable insight into a wide range of metabolic and molecular processes by using of a variety of radioactive tracers, the scope of medical imaging and diagnostics can be significantly increased. While the use of multimodal imaging is undoubtedly advantageous, identifying the optimal combination of these parameters to diagnose a specific dysfunction is very important and is advanced by the use of sophisticated imaging techniques in specific animal models.Methods : In this pilot study, rats with intracerebral 9L gliosarcomas were used to explore a combination of sequential multinuclear MRI using a sophisticated switchable coil set in a small animal 9.4 T MRI scanner and, subsequently, a small animal PET with the tumour tracer O-(2-[ 18 F]-fluoroethyl)-L-tyrosine ( 18 F-FET). This enabled in vivo multinuclear MR-PET experiments to be conducted without compromising the performance of either multinuclear MR or PET.Results : High-quality in vivo images and spectra including high-resolution 1 H imaging, 23 Na-weighted imaging, detection of 31 P metabolites and 18 F-FET uptake were obtained, allowing the characterisation of tumour tissues in comparison to a normal brain. These parameters have been shown to be useful in the identification of the genetic profile of gliomas, particularly concerning the mutation of the isocitrate hydrogenase gene, which is highly relevant for treatment strategy.Conclusions : The combination of multinuclear MR and PET in, for example, brain tumour models with specific genetic mutations will enable the physiological background of signal alterations to be explored and the identification of the optimal combination of imaging parameters for the non-invasive characterisation of the molecular profile of tumours.

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“…Diffusion weighted imaging (DWI) and dynamic susceptibility contrast imaging (DSC) are two advanced magnetic resonance imaging (MRI) techniques available to understand tissue microstructure and perfusion on a cellular and tissue level (Goo and Ra, 2017;Shah et al, 2016;Zhou et al, 2011). These techniques have been used extensively to understand the role of cellularity and microvascular perfusion, in both paediatric and adult brain tumours (Hales et al, 2019;Poussaint et al, 2016), with strong correlations with histology for the aforementioned.…”

Section: Introductionmentioning

confidence: 99%

Distinguishing between paediatric brain tumour types using multi-parametric magnetic resonance imaging and machine learning: A multi-site study

Grist

Withey

MacPherson

et al. 2020

NeuroImage: Clinical

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The imaging and subsequent accurate diagnosis of paediatric brain tumours presents a radiological challenge, with magnetic resonance imaging playing a key role in providing tumour specific imaging information. Diffusion weighted and perfusion imaging are commonly used to aid the non-invasive diagnosis of children's brain tumours, but are usually evaluated by expert qualitative review. Quantitative studies are mainly single centre and single modality.The aim of this work was to combine multi-centre diffusion and perfusion imaging, with machine learning, to develop machine learning based classifiers to discriminate between three common paediatric tumour types.The results show that diffusion and perfusion weighted imaging of both the tumour and whole brain provide significant features which differ between tumour types, and that combining these features gives the optimal machine learning classifier with >80% predictive precision. This work represents a step forward to aid in the non-invasive diagnosis of paediatric brain tumours, using advanced clinical imaging.

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Imaging of sodium in the brain: a brief review

Cited by 52 publications

References 101 publications

X‐nuclei imaging: Current state, technical challenges, and future directions

X‐nuclei imaging: Current state, technical challenges, and future directions

An in vivo multimodal feasibility study in a rat brain tumour model using flexible multinuclear MR and PET systems

Distinguishing between paediatric brain tumour types using multi-parametric magnetic resonance imaging and machine learning: A multi-site study

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