Double‐Step R1rho‐Based Lorentzian Fitting (DROF): A New CEST Analysis Approach and Its Comparison With Existing Methods

At 3-T MRI, reliable quantification of CEST contrast is challenged by peak overlap and broad background contamination. Because of this limitation, some previous studies employ four-pool Lorentzian fitting (i.e., amide, direct water saturation, magnetization transfer, and relayed nuclear Overhauser enhancement) for CEST analysis at 3 T, where the multiple CEST contrasts at positive frequency offsets are treated as a single pool. In addition, for fitting-based methods, the fitting accuracy can be readily affected by initial values and boundary conditions. To address these problems, a new CEST analysis approach, named double-step R1rho-based Lorentzian fitting (DROF), with initial value randomization, was developed in this study for extracting five-pool (additional CEST@2 ppm pool) Lorentzian fitting parameters at 3 T. Moreover, a comprehensive evaluation framework including three metrics was proposed to assess the performance of CEST analysis methods. The accuracy and robustness of DROF were evaluated using both simulation and in vivo human data at 3 T, and its performance was compared with existing methods. Results demonstrate that DROF offers improved specificity and stability, suggesting its potential to enhance CEST applicability at 3 T.

Authors

Institutions

Publication Details

Journal
NMR in Biomedicine
Published
2025-06-22
DOI
https://doi.org/10.1002/nbm.70082
Citations
3
Primary Topic
Advanced MRI Techniques and Applications
Type
article
Field-Weighted Citation Impact
4.08

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Double‐Step R1rho‐Based Lorentzian Fitting (DROF): A New CEST Analysis Approach and Its Comparison With Existing Methods

Bensheng Qiu, Jianpan Huang, Lin Chen, Ziyan Wang et al.
3 citations
NMR in Biomedicine
Advanced MRI Techniques and Applications
4.08
article

Double‐Step R1rho‐Based Lorentzian Fitting (DROF): A New CEST Analysis Approach and Its Comparison With Existing Methods

Bensheng Qiu, Jianpan Huang, Lin Chen, Ziyan Wang, Jiawen Wang, Shihao Zeng, Pei Cai, Huabin Zhang
article en
3 citations

Abstract

At 3-T MRI, reliable quantification of CEST contrast is challenged by peak overlap and broad background contamination. Because of this limitation, some previous studies employ four-pool Lorentzian fitting (i.e., amide, direct water saturation, magnetization transfer, and relayed nuclear Overhauser enhancement) for CEST analysis at 3 T, where the multiple CEST contrasts at positive frequency offsets are treated as a single pool. In addition, for fitting-based methods, the fitting accuracy can be readily affected by initial values and boundary conditions. To address these problems, a new CEST analysis approach, named double-step R1rho-based Lorentzian fitting (DROF), with initial value randomization, was developed in this study for extracting five-pool (additional CEST@2 ppm pool) Lorentzian fitting parameters at 3 T. Moreover, a comprehensive evaluation framework including three metrics was proposed to assess the performance of CEST analysis methods. The accuracy and robustness of DROF were evaluated using both simulation and in vivo human data at 3 T, and its performance was compared with existing methods. Results demonstrate that DROF offers improved specificity and stability, suggesting its potential to enhance CEST applicability at 3 T.

NMR in BiomedicineVol. 38(8)
University of Science and Technology of China (CN), Chinese University of Hong Kong (HK), Xiamen University (CN), NanoBioImaging (China) (CN), University of Hong Kong (HK)
National Natural Science Foundation of China, University of Hong Kong
Clean water and sanitation
Openalex Percentile: Top 6%
Advanced MRI Techniques and Applications
4.08
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.