ReviewNMR in biomedicine2013
Nuts and bolts of chemical exchange saturation transfer MRI.
Review in NMR in biomedicine, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 182 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
182 citing papers in PubMed.
- Enhanced Quantitative Phosphocreatine MR Imaging of Skeletal Muscle Using a Global-Local Two-Branch Deep Learning Model.Magnetic resonance in medicine · 2026Article
- Chemical exchange saturation transfer NMR: An analytical tool and its applications.Magnetic resonance letters · 2026Review
- Peptide-Based pH-Responsive MRI-CEST Agents: In Vivo Comparison between a Selected Pentapeptide and the Established Iopamidol Reference in Tumor pH Mapping Ability.Chemical & biomedical imaging · 2026Article
- Accelerating Proton Exchange in 1,8-Bis(dialkylamino)naphthalene Proton Sponges through Intramolecular Catalysis for CEST MRI.Journal of the American Chemical Society · 2026Article
- CEST MRI: Translational prospects for intervertebral disc degeneration - from basic research to clinical applications.Journal of orthopaedic translation · 2026Review
- Brain Tumor Imaging with Iopamidol CEST MRI: In Vivo Detection and Validation.Chemical & biomedical imaging · 2026Article
- Optimization of Pulsed Saturation Transfer MR Fingerprinting (ST MRF) Acquisition Using the Cramér-Rao Bound and Sequential Quadratic Programming.Magnetic resonance in medicine · 2026Article
- Denoising Low-Power CEST Imaging Using a Deep Learning Approach With a Dual-Power Feature Preparation Strategy.Magnetic resonance in medicine · 2026Article
- A rapid and accurate guanidine CEST imaging in ischemic stroke using a machine learning approach.Physics in medicine and biology · 2026Article
- Chemical exchange saturation transfer MRI for neurodegenerative diseases: An update on clinical and preclinical studies.Neural regeneration research · 2026Article
- Radiofrequency bandwidth effects in direct saturation dynamic glucose enhanced MRI at 3T.Frontiers in neuroscience · 2026Article
- CEST MRI assessment of HIV-1-associated neurometabolic impairments in a humanized mouse model.NeuroImmune pharmacology and therapeutics · 2025Article
- Quantitative multi-metabolite imaging of Parkinson's disease using AI boosted molecular MRI.Npj imaging · 2025Article
- Multi-contrast generation and quantitative MRI using a transformer-based framework with RF excitation embeddings.Communications biology · 2025Article
- Chemical Exchange Saturation Transfer Imaging in Neuroinflammation: Methods, Challenges, and Recommendations.International journal of molecular sciences · 2025Review
- Quantitative molecular imaging using deep magnetic resonance fingerprinting.Nature protocols · 2025Review
- Machine learning-based multi-pool Voigt fitting of CEST, rNOE, and MTC in Z-spectra.Magnetic resonance in medicine · 2025Article
- Article
- In Vivo Brain BNMR in biomedicine · 2025Article
- Ungated, plug-and-play preclinical cardiac CEST-MRI using radial FLASH with segmented saturation.Magnetic resonance in medicine · 2025Article
122 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Chemical exchange saturation transfer (CEST) has emerged as a novel MRI contrast mechanism that is well suited for molecular imaging studies. This new mechanism can be used to detect small amounts of contrast agent through the saturation of rapidly exchanging protons on these agents, allowing a wide range of applications. CEST technology has a number of indispensable features, such as the possibility of simultaneous detection of multiple 'colors' of agents and of changes in their environment (e.g. pH, metabolites, etc.) through MR contrast. Currently, a large number of new imaging schemes and techniques are being developed to improve the temporal resolution and specificity and to correct for the influence of B0 and B1 inhomogeneities. In this review, the techniques developed over the last decade are summarized with the different imaging strategies and post-processing methods discussed from a practical point of view, including the description of their relative merits for the detection of CEST agents. The goal of the present work is to provide the reader with a fundamental understanding of the techniques developed, and to provide guidance to help refine future applications of this technology. This review is organized into three main sections ('Basics of CEST contrast', 'Implementation' and 'Post-processing'), and also includes a brief Introduction and Summary. The 'Basics of CEST contrast' section contains a description of the relevant background theory for saturation transfer and frequency-labeled transfer, and a brief discussion of methods to determine exchange rates. The 'Implementation' section contains a description of the practical considerations in conducting CEST MRI studies, including the choice of magnetic field, pulse sequence, saturation pulse, imaging scheme, and strategies to separate magnetization transfer and CEST. The 'Post-processing' section contains a description of the typical image processing employed for B0 /B1 correction, Z-spectral interpolation, frequency-selective detection and improvement of CEST contrast maps.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.