ArticleNMR in biomedicine2017
Accuracy in the quantification of chemical exchange saturation transfer (CEST) and relayed nuclear Overhauser enhancement (rNOE) saturation transfer effects.
Article in NMR in biomedicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 72 papers.
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72 citing papers in PubMed, 114 citations in OpenAlex.
- Effective Modeling of Continuous WaveMagnetic resonance in medicine · 2026Article
- Detection of Lipid-Mediated Diffused Pathological Changes in Multiple Sclerosis.Research square · 2026Article
- FlexCENT: A frequency-flexible CEST imaging network combining frequency offset encoding and three-dimensional U-Net.Magnetic resonance letters · 2026Article
- Multimodal MRI Reveals Cerebral and Vascular Amyloid-Driven Myeloarchitectural Disorganization in a Mouse Model of Alzheimer's Disease.NMR in biomedicine · 2026Article
- Robust Extrapolated Semi-Solid Magnetization Transfer Reference Fitting for Quantitative Amide Proton Transfer Imaging at 3 T: Application to Patients With Mild Cognitive Impairment and Mild Dementia.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
- Chemical exchange saturation transfer MRI for neurodegenerative diseases: An update on clinical and preclinical studies.Neural regeneration research · 2026Article
- Chemical exchange saturation transfer magnetic resonance imaging of the kidney: applications and challenges.Abdominal radiology (New York) · 2025Review
- Chemical exchange saturation transfer magnetic resonance imaging of the kidney: applications and challenges.Abdominal radiology (New York) · 2025Review
- CEST MRI data analysis using Kolmogorov-Arnold network (KAN) and Lorentzian-KAN (LKAN) models.Magnetic resonance in medicine · 2025Article
- Double-Step R1rho-Based Lorentzian Fitting (DROF): A New CEST Analysis Approach and Its Comparison With Existing Methods.NMR in biomedicine · 2025Article
- Machine learning-based multi-pool Voigt fitting of CEST, rNOE, and MTC in Z-spectra.Magnetic resonance in medicine · 2025Article
- Improving quantification accuracy of a nuclear Overhauser enhancement signal at -1.6 ppm at 4.7 T using a machine learning approach.Physics in medicine and biology · 2025Article
- Enhancing amide proton transfer imaging in ischemic stroke using a machine learning approach with partially synthetic data.NMR in biomedicine · 2025Article
- Unraveling contributions to the Z-spectrum signal at 3.5 ppm of human brain tumors.Magnetic resonance in medicine · 2024Article
- Reproducibility of 3D chemical exchange saturation transfer (CEST) contrasts in the healthy brain at 3T.Scientific reports · 2024Article
- Quantitative separation of CEST effect by RScientific reports · 2024Article
- Development and Validation of Four Different Methods to Improve MRI-CEST Tumor pH Mapping in Presence of Fat.Journal of imaging · 2024Article
- A Denoising Convolutional Autoencoder for SNR Enhancement in Chemical Exchange Saturation Transfer imaging: (DCAE-CEST).bioRxiv : the preprint server for biology · 2024Article
- A rapid method for phosphocreatine-weighted imaging in muscle using double saturation power-chemical exchange saturation transfer.NMR in biomedicine · 2024Article
12 more citing papers are in PubMed but not listed here.
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7 authors at 1 institution in 1 country.
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Abstract
Accurate quantification of chemical exchange saturation transfer (CEST) effects, including dipole-dipole mediated relayed nuclear Overhauser enhancement (rNOE) saturation transfer, is important for applications and studies of molecular concentration and transfer rate (and thereby pH or temperature). Although several quantification methods, such as Lorentzian difference (LD) analysis, multiple-pool Lorentzian fits, and the three-point method, have been extensively used in several preclinical and clinical applications, the accuracy of these methods has not been evaluated. Here we simulated multiple-pool Z spectra containing the pools that contribute to the main CEST and rNOE saturation transfer signals in the brain, numerically fit them using the different methods, and then compared their derived CEST metrics with the known solute concentrations and exchange rates. Our results show that the LD analysis overestimates contributions from amide proton transfer (APT) and intermediate exchanging amine protons; the three-point method significantly underestimates both APT and rNOE saturation transfer at -3.5 ppm (NOE(-3.5)). The multiple-pool Lorentzian fit is more accurate than the other two methods, but only at lower irradiation powers (≤1 μT at 9.4 T) within the range of our simulations. At higher irradiation powers, this method is also inaccurate because of the presence of a fast exchanging CEST signal that has a non-Lorentzian lineshape. Quantitative parameters derived from in vivo images of rodent brain tumor obtained using an irradiation power of 1 μT were also compared. Our results demonstrate that all three quantification methods show similar contrasts between tumor and contralateral normal tissue for both APT and the NOE(-3.5). However, the quantified values of the three methods are significantly different. Our work provides insight into the fitting accuracy obtainable in a complex tissue model and provides guidelines for evaluating other newly developed quantification methods.
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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.