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Kang B, Lee W, Seo H, Heo HY, Park H. Self-supervised learning for denoising of multidimensional MRI data. Magn Reson Med 2024; 92:1980-1994. [PMID: 38934408 PMCID: PMC11341249 DOI: 10.1002/mrm.30197] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 05/27/2024] [Accepted: 05/28/2024] [Indexed: 06/28/2024]
Abstract
PURPOSE To develop a fast denoising framework for high-dimensional MRI data based on a self-supervised learning scheme, which does not require ground truth clean image. THEORY AND METHODS Quantitative MRI faces limitations in SNR, because the variation of signal amplitude in a large set of images is the key mechanism for quantification. In addition, the complex non-linear signal models make the fitting process vulnerable to noise. To address these issues, we propose a fast deep-learning framework for denoising, which efficiently exploits the redundancy in multidimensional MRI data. A self-supervised model was designed to use only noisy images for training, bypassing the challenge of clean data paucity in clinical practice. For validation, we used two different datasets of simulated magnetization transfer contrast MR fingerprinting (MTC-MRF) dataset and in vivo DWI image dataset to show the generalizability. RESULTS The proposed method drastically improved denoising performance in the presence of mild-to-severe noise regardless of noise distributions compared to previous methods of the BM3D, tMPPCA, and Patch2self. The improvements were even pronounced in the following quantification results from the denoised images. CONCLUSION The proposed MD-S2S (Multidimensional-Self2Self) denoising technique could be further applied to various multi-dimensional MRI data and improve the quantification accuracy of tissue parameter maps.
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Affiliation(s)
- Beomgu Kang
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Guseong-dong, Yuseong-gu, Daejeon, Republic of Korea
- Bionics Research Center, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - Wonil Lee
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, USA
| | - Hyunseok Seo
- Bionics Research Center, Biomedical Research Division, Korea Institute of Science and Technology (KIST), Seoul, Republic of Korea
| | - Hye-Young Heo
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - HyunWook Park
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Guseong-dong, Yuseong-gu, Daejeon, Republic of Korea
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2
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Mahmud SZ, Singh M, van Zijl P, Heo HY. Fast and motion-robust saturation transfer MRI with inherent B 0 correction using rosette trajectories and compressed sensing. Magn Reson Med 2024. [PMID: 39129199 DOI: 10.1002/mrm.30249] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Revised: 07/25/2024] [Accepted: 07/26/2024] [Indexed: 08/13/2024]
Abstract
PURPOSE To implement rosette readout trajectories with compressed sensing reconstruction for fast and motion-robust CEST and magnetization transfer contrast imaging with inherent correction of B0 inhomogeneity. METHODS A pulse sequence was developed for fast saturation transfer imaging using a stack of rosette trajectories with a higher sampling density near the k-space center. Each rosette lobe was segmented into two halves to generate dual-echo images. B0 inhomogeneities were estimated using the phase difference between the images and corrected subsequently. The rosette-based imaging was evaluated in comparison to a fully sampled Cartesian trajectory and demonstrated on CEST phantoms (creatine solutions and egg white) and healthy volunteers at 3 T. RESULTS Compared with the conventional Cartesian acquisition, compressed sensing reconstructed rosette images provided image quality with overall higher contrast-to-noise ratio and significantly faster readout time. Accurate B0 map estimation was achieved from the rosette acquisition with a negligible bias of 0.01 Hz between the rosette and dual-echo Cartesian gradient echo B0 maps, using the latter as ground truth. The water-saturation spectra (Z-spectra) and amide proton transfer weighted signals obtained from the rosette-based sequence were well preserved compared with the fully sampled data, both in the phantom and human studies. CONCLUSIONS Fast, motion-robust, and inherent B0-corrected CEST and magnetization transfer contrast imaging using rosette trajectories could improve subject comfort and compliance, contrast-to-noise ratio, and provide inherent B0 homogeneity information. This work is expected to significantly accelerate the translation of CEST-MRI into a robust, clinically viable approach.
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Affiliation(s)
- Sultan Z Mahmud
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Munendra Singh
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Peter van Zijl
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Hye-Young Heo
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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3
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Wu Q, Gong P, Liu S, Li Y, Liang D, Zheng H, Wu Y. B 1 inhomogeneity corrected CEST MRI based on direct saturation removed omega plot model at 5T. Magn Reson Med 2024; 92:532-542. [PMID: 38650080 DOI: 10.1002/mrm.30112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 02/23/2024] [Accepted: 03/25/2024] [Indexed: 04/25/2024]
Abstract
PURPOSE CEST can image macromolecules/compounds via detecting chemical exchange between labile protons and bulk water. B1 field inhomogeneity impairs CEST quantification. Conventional B1 inhomogeneity correction methods depend on interpolation algorithms, B1 choices, acquisition number or calibration curves, making reliable correction challenging. This study proposed a novel B1 inhomogeneity correction method based on a direct saturation (DS) removed omega plot model. METHODS Four healthy volunteers underwent B1 field mapping and CEST imaging under four nominal B1 levels of 0.75, 1.0, 1.5, and 2.0 μT at 5T. DS was resolved using a multi-pool Lorentzian model and removed from respective Z spectrum. Residual spectral signals were used to construct the omega plot as a linear function of 1/B 1 2 $$ {B}_1^2 $$ , from which corrected signals at nominal B1 levels were calculated. Routine asymmetry analysis was conducted to quantify amide proton transfer (APT) effect. Its distribution across white matter was compared before and after B1 inhomogeneity correction and also with the conventional interpolation approach. RESULTS B1 inhomogeneity yielded conspicuous artifact on APT images. Such artifact was mitigated by the proposed method. Homogeneous APT maps were shown with SD consistently smaller than that before B1 inhomogeneity correction and the interpolation method. Moreover, B1 inhomogeneity correction from two and four CEST acquisitions yielded similar results, superior over the interpolation method that derived inconsistent APT contrasts among different B1 choices. CONCLUSION The proposed method enables reliable B1 inhomogeneity correction from at least two CEST acquisitions, providing an effective way to improve quantitative CEST MRI.
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Affiliation(s)
- Qiting Wu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Pengcheng Gong
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
- Department of Biomedical Engineering, Chongqing University of Technology, Chongqing, China
| | - Shengping Liu
- Department of Biomedical Engineering, Chongqing University of Technology, Chongqing, China
| | - Ye Li
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Dong Liang
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Hairong Zheng
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Yin Wu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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Heo HY, Singh M, Mahmud SZ, Blair L, Kamson DO, Zhou J. Unraveling contributions to the Z-spectrum signal at 3.5 ppm of human brain tumors. Magn Reson Med 2024. [PMID: 39086185 DOI: 10.1002/mrm.30241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 06/26/2024] [Accepted: 07/17/2024] [Indexed: 08/02/2024]
Abstract
PURPOSE To evaluate the influence of the confounding factors, direct water saturation (DWS), and magnetization transfer contrast (MTC) effects on measured Z-spectra and amide proton transfer (APT) contrast in brain tumors. METHODS High-grade glioma patients were scanned using an RF saturation-encoded 3D MR fingerprinting (MRF) sequence at 3 T. For MRF reconstruction, a recurrent neural network was designed to learn free water and semisolid macromolecule parameter mappings of the underlying multiple tissue properties from saturation-transfer MRF signals. The DWS spectra and MTC spectra were synthesized by solving Bloch-McConnell equations and evaluated in brain tumors. RESULTS The dominant contribution to the saturation effect at 3.5 ppm was from DWS and MTC effects, but 25%-33% of the saturated signal in the gadolinium-enhancing tumor (13%-20% for normal tissue) was due to the APT effect. The APT# signal of the gadolinium-enhancing tumor was significantly higher than that of the normal-appearing white matter (10.1% vs. 8.3% at 1 μT and 11.2% vs. 7.8% at 1.5 μT). CONCLUSION The RF saturation-encoded MRF allowed us to separate contributions to the saturation signal at 3.5 ppm in the Z-spectrum. Although free water and semisolid MTC are the main contributors, significant APT contrast between tumor and normal tissues was observed.
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Affiliation(s)
- Hye-Young Heo
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Munendra Singh
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Sultan Z Mahmud
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Lindsay Blair
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, USA
| | - David Olayinka Kamson
- Department of Neurology, Johns Hopkins University, Baltimore, Maryland, USA
- Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jinyuan Zhou
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
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Peng Y, Dai Y, Zhang S, Deng J, Jia X. Joint k- ω Space Image Reconstruction and Data Fitting for Chemical Exchange Saturation Transfer Magnetic Resonance Imaging. Tomography 2024; 10:1123-1138. [PMID: 39058057 PMCID: PMC11280605 DOI: 10.3390/tomography10070085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2024] [Revised: 07/05/2024] [Accepted: 07/08/2024] [Indexed: 07/28/2024] Open
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is a novel MRI technology to image certain compounds at extremely low concentrations. Long acquisition time to measure signals at a set of offset frequencies of the Z-spectra and to repeat measurements to reduce noise pose significant challenges to its applications. This study explores correlations of CEST MR images along the spatial and Z-spectral dimensions to improve MR image quality and robustness of magnetization transfer ratio (MTR) asymmetry estimation via a joint k-ω reconstruction model. The model was formulated as an optimization problem with respect to MR images at all frequencies ω, while incorporating regularizations along the spatial and spectral dimensions. The solution was subject to a self-consistency condition that the Z-spectrum of each pixel follows a multi-peak data fitting model corresponding to different CEST pools. The optimization problem was solved using the alternating direction method of multipliers. The proposed joint reconstruction method was evaluated on a simulated CEST MRI phantom and semi-experimentally on choline and iopamidol phantoms with added Gaussian noise of various levels. Results demonstrated that the joint reconstruction method was more tolerable to noise and reduction in number of offset frequencies by improving signal-to-noise ratio (SNR) of the reconstructed images and reducing uncertainty in MTR asymmetry estimation. In the choline and iopamidol phantom cases with 10.5% noise in the measurement data, our method achieved an averaged SNR of 31.0 dB and 32.2 dB compared to the SNR of 24.7 dB and 24.4 dB in the conventional reconstruction approach. It reduced uncertainty of the MTR asymmetry estimation over all regions of interest by 54.4% and 43.7%, from 1.71 and 2.38 to 0.78 and 1.71, respectively.
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Affiliation(s)
- Yuting Peng
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD 21287, USA
| | - Yan Dai
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Shu Zhang
- Department of Radiology, Houston Methodist Research Institute, Houston, TX 77030, USA
| | - Jie Deng
- Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX 75390, USA
| | - Xun Jia
- Department of Radiation Oncology and Molecular Radiation Sciences, Johns Hopkins University, Baltimore, MD 21287, USA
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Heo HY, Singh M, Yedavalli V, Jiang S, Zhou J. CEST and nuclear Overhauser enhancement imaging with deep learning-extrapolated semisolid magnetization transfer reference: Scan-rescan reproducibility and reliability studies. Magn Reson Med 2024; 91:1002-1015. [PMID: 38009996 PMCID: PMC10842109 DOI: 10.1002/mrm.29937] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 10/18/2023] [Accepted: 11/04/2023] [Indexed: 11/29/2023]
Abstract
PURPOSE To develop a novel MR physics-driven, deep-learning, extrapolated semisolid magnetization transfer reference (DeepEMR) framework to provide fast, reliable magnetization transfer contrast (MTC) and CEST signal estimations, and to determine the reproducibility and reliability of the estimates from the DeepEMR. METHODS A neural network was designed to predict a direct water saturation and MTC-dominated signal at a certain CEST frequency offset using a few high-frequency offset features in the Z-spectrum. The accuracy, scan-rescan reproducibility, and reliability of MTC, CEST, and relayed nuclear Overhauser enhancement (rNOE) signals estimated from the DeepEMR were evaluated on numerical phantoms and in heathy volunteers at 3 T. In addition, we applied the DeepEMR method to brain tumor patients and compared tissue contrast with other CEST calculation metrics. RESULTS The DeepEMR method demonstrated a high degree of accuracy in the estimation of reference MTC signals at ±3.5 ppm for APT and rNOE imaging, and computational efficiency (˜190-fold) compared with a conventional fitting approach. In addition, the DeepEMR method achieved high reproducibility and reliability (intraclass correlation coefficient = 0.97, intersubject coefficient of variation = 3.5%, and intrasubject coefficient of variation = 1.3%) of the estimation of MTC signals at ±3.5 ppm. In tumor patients, DeepEMR-based amide proton transfer images provided higher tumor contrast than a conventional MT ratio asymmetry image, particularly at higher B1 strengths (>1.5 μT), with a distinct delineation of the tumor core from normal tissue or peritumoral edema. CONCLUSION The DeepEMR approach is feasible for measuring clean APT and rNOE effects in longitudinal and cross-sectional studies with low scan-rescan variability.
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Affiliation(s)
- Hye-Young Heo
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Munendra Singh
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Vivek Yedavalli
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Shanshan Jiang
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
| | - Jinyuan Zhou
- The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
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Kim H, Park S, Hu R, Hoang KB, Sun PZ. 3D CEST MRI with an unevenly segmented RF irradiation scheme: A feasibility study in brain tumor imaging. Magn Reson Med 2023; 90:2400-2410. [PMID: 37526017 PMCID: PMC10586718 DOI: 10.1002/mrm.29810] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 06/17/2023] [Accepted: 07/08/2023] [Indexed: 08/02/2023]
Abstract
PURPOSE To integrate 3D CEST EPI with an unevenly segmented RF irradiation module and preliminarily demonstrate it in the clinical setting. METHODS A CEST MRI with unevenly segmented RF saturation was implemented, including a long primary RF saturation to induce the steady-state CEST effect, maintained with repetitive short secondary RF irradiation between readouts. This configuration reduces relaxation-induced blur artifacts during acquisition, allowing fast 3D spatial coverage. Numerical simulations were performed to select parameters such as flip angle (FA), short RF saturation duration (Ts2), and the number of readout segments. The sequence was validated experimentally with data from a phantom, healthy volunteers, and a brain tumor patient. RESULTS Based on the numerical simulation and l-carnosine gel phantom experiment, FA, Ts2, and the number of segments were set to 20°, 0.3 s, and the range from 4 to 8, respectively. The proposed method minimized signal modulation in the human brain images in the kz direction during the acquisition and provided the blur artifacts-free CEST contrast over the whole volume. Additionally, the CEST contrast in the tumor tissue region is higher than in the contralateral normal tissue region. CONCLUSIONS It is feasible to implement a highly accelerated 3D EPI CEST imaging with unevenly segmented RF irradiation.
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Affiliation(s)
- Hahnsung Kim
- Emory National Primate Research Center, Emory University, Atlanta GA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta GA
| | - Suhyung Park
- Department of Computer Engineering, Chonnam National University, South Korea
- Department of ICT Convergence System Engineering, Chonnam National University, South Korea
| | - Ranliang Hu
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta GA
| | - Kimberly B Hoang
- Department of Neurosurgery, Emory University School of Medicine, Atlanta GA
| | - Phillip Zhe Sun
- Emory National Primate Research Center, Emory University, Atlanta GA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta GA
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Singh M, Jiang S, Li Y, van Zijl P, Zhou J, Heo HY. Bloch simulator-driven deep recurrent neural network for magnetization transfer contrast MR fingerprinting and CEST imaging. Magn Reson Med 2023; 90:1518-1536. [PMID: 37317675 PMCID: PMC10524222 DOI: 10.1002/mrm.29748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Revised: 04/17/2023] [Accepted: 05/18/2023] [Indexed: 06/16/2023]
Abstract
PURPOSE To develop a unified deep-learning framework by combining an ultrafast Bloch simulator and a semisolid macromolecular magnetization transfer contrast (MTC) MR fingerprinting (MRF) reconstruction for estimation of MTC effects. METHODS The Bloch simulator and MRF reconstruction architectures were designed with recurrent neural networks and convolutional neural networks, evaluated with numerical phantoms with known ground truths and cross-linked bovine serum albumin phantoms, and demonstrated in the brain of healthy volunteers at 3 T. In addition, the inherent magnetization-transfer ratio asymmetry effect was evaluated in MTC-MRF, CEST, and relayed nuclear Overhauser enhancement imaging. A test-retest study was performed to evaluate the repeatability of MTC parameters, CEST, and relayed nuclear Overhauser enhancement signals estimated by the unified deep-learning framework. RESULTS Compared with a conventional Bloch simulation, the deep Bloch simulator for generation of the MTC-MRF dictionary or a training data set reduced the computation time by 181-fold, without compromising MRF profile accuracy. The recurrent neural network-based MRF reconstruction outperformed existing methods in terms of reconstruction accuracy and noise robustness. Using the proposed MTC-MRF framework for tissue-parameter quantification, the test-retest study showed a high degree of repeatability in which the coefficients of variance were less than 7% for all tissue parameters. CONCLUSION Bloch simulator-driven, deep-learning MTC-MRF can provide robust and repeatable multiple-tissue parameter quantification in a clinically feasible scan time on a 3T scanner.
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Affiliation(s)
- Munendra Singh
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Yuguo Li
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Peter van Zijl
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Song G, Chen Y, Luo X, Gong T, Yang H, Zhou J, Li C, Chen M. Amide proton transfer-weighted MRI features of acute ischemic stroke subtypes. NMR IN BIOMEDICINE 2023; 36:e4983. [PMID: 37259224 DOI: 10.1002/nbm.4983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 02/14/2023] [Accepted: 05/13/2023] [Indexed: 06/02/2023]
Abstract
Stroke is a highly heterogeneous disorder with distinct subtypes, and the stroke subtype influences the outcome. Amide proton transfer-weighted (APTW) MRI has been demonstrated to be promising in stroke patients, but the image characteristics of stroke subtypes have not been sufficiently investigated. The purpose of this study was to investigate the APTW MRI features of different subtypes of acute ischemic stroke (AIS). Ninety-two AIS patients presenting within 96 h of symptom onset were enrolled and examined with a 3.0-T MRI system. Patients were grouped into four subtypes: lacunar circulation infarcts (LACI, n = 33); total anterior circulation infarcts (TACI, n = 9); partial anterior circulation infarcts (PACI, n = 28); and posterior circulation infarcts (POCI, n = 22). APTW values in the lesion (APTWlesion ) and the contralateral normal-appearing region (APTWcontral ) were measured. The change in APTW values between the acute ischemic lesion and the contralateral normal-appearing region (APTWles-con ) was calculated. A two-sample t-test, one-way ANOVA, and the Chi-square method were used. There were significant differences between APTWlesion and APTWcontral in the three categories of nonlacunar strokes (TACI, PACI, and POCI, all p < 0.01), but not for lacunar strokes (LACI, p = 0.080). TACI patients had the lowest APTWlesion and APTWles-con in all groups (p < 0.05). In the POCI group, patients with supratentorial infarcts showed significant differences between APTWlesion and APTWcontral (p = 0.001), while the differences were not significant for infratentorial infarcts (p = 0.135). Our results suggest that the APT effect was heterogeneous in different stroke subtypes, and that APTW MRI gave an excellent performence in depicting nonlacunar AIS in supratentorial locations.
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Affiliation(s)
- Guodong Song
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Yuhui Chen
- Department of Neurology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Xiaojie Luo
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Tao Gong
- Department of Neurology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Huan Yang
- Department of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Chunmei Li
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
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Sun C, Zhao Y, Zu Z. Validation of the presence of fast exchanging amine CEST effect at low saturation powers and its influence on the quantification of APT. Magn Reson Med 2023; 90:1502-1517. [PMID: 37317709 PMCID: PMC10614282 DOI: 10.1002/mrm.29742] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 05/16/2023] [Accepted: 05/17/2023] [Indexed: 06/16/2023]
Abstract
PURPOSE Accurately quantifying the amide proton transfer (APT) effect and the underlying exchange parameters is crucial for its applications, but previous studies have reported conflicting results. In these quantifications, the CEST effect from the fast exchange amine was always ignored because it was considered weak with low saturation powers. This paper aims to evaluate the influence of the fast exchange amine CEST on the quantification of APT at low saturation powers. METHODS A quantification method with low and high saturation powers was used to distinguish APT from the fast exchange amine CEST effect. Simulations were conducted to assess the method's capability to separate APT from the fast exchange amine CEST effect. Animal experiments were performed to assess the relative contributions from the fast exchange amine and amide to CEST signals at 3.5 ppm. Three APT quantification methods, each with varying degrees of contamination from the fast exchange amine, were employed to process the animal data to assess the influence of the amine on the quantification of APT effect and the exchange parameters. RESULTS The relative size of the fast exchange amine CEST effect to APT effect gradually increases with increasing saturation power. At 9.4 T, it increases from approximately 20% to 40% of APT effect with a saturation power increase from 0.25 to 1 μT. CONCLUSION The fast exchange amine CEST effect leads overestimation of APT effect, fitted amide concentration, and amide-water exchange rate, potentially contributing to the conflicting results reported in previous studies.
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Affiliation(s)
- Casey Sun
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, US
- Department of Chemistry, University of Florida, Gainesville, US
| | - Yu Zhao
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
- Department of Biomedical Engineering, Vanderbilt University, Nashville, US
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11
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Zhao Y, Sun C, Zu Z. Isolation of amide proton transfer effect and relayed nuclear Overhauser enhancement effect at -3.5ppm using CEST with double saturation powers. Magn Reson Med 2023; 90:1025-1040. [PMID: 37154382 PMCID: PMC10646838 DOI: 10.1002/mrm.29691] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2022] [Revised: 03/18/2023] [Accepted: 04/16/2023] [Indexed: 05/10/2023]
Abstract
PURPOSE Quantifications of amide proton transfer (APT) and nuclear Overhauser enhancement (rNOE(-3.5)) mediated saturation transfer with high specificity are challenging because their signals measured in a Z-spectrum are overlapped with confounding signals from direct water saturation (DS), semi-solid magnetization transfer (MT), and CEST of fast-exchange pools. In this study, based on two canonical CEST acquisitions with double saturation powers (DSP), a new data-postprocessing method is proposed to specifically quantify the effects of APT and rNOE. METHODS For CEST imaging with relatively low saturation powers (ω 1 2 $$ {\upomega}_1^2 $$ ), both the fast-exchange CEST effect and the semi-solid MT effect roughly depend onω 1 2 $$ {\upomega}_1^2 $$ , whereas the slow-exchange APT/rNOE(-3.5) effect do not, which is exploited to isolate a part of the APT and rNOE effects from the confounding signals in this study. After a mathematical derivation for the establishment of the proposed method, numerical simulations based on Bloch equations are then performed to demonstrate its specificity to detections of the APT and rNOE effects. Finally, an in vivo validation of the proposed method is conducted using an animal tumor model at a 4.7 T MRI scanner. RESULTS The simulations show that DSP-CEST can quantify the effects of APT and rNOE and substantially eliminate the confounding signals. The in vivo experiments demonstrate that the proposed DSP-CEST method is feasible for the imaging of tumors. CONCLUSION The data-postprocessing method proposed in this study can quantify the APT and rNOE effects with considerably increased specificities and a reduced cost of imaging time.
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Affiliation(s)
- Yu Zhao
- Vanderbilt University Institute of Imaging Science, Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
- Department of Radiology, West China Hospital of Sichuan University, Chengdu, China
| | - Casey Sun
- Vanderbilt University Institute of Imaging Science, Nashville, US
- Department of Chemistry, University of Florida, Gainesville, US
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Nashville, US
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, US
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12
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Kang B, Singh M, Park H, Heo HY. Only-train-once MR fingerprinting for B 0 and B 1 inhomogeneity correction in quantitative magnetization-transfer contrast. Magn Reson Med 2023; 90:90-102. [PMID: 36883726 PMCID: PMC10149616 DOI: 10.1002/mrm.29629] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 02/15/2023] [Accepted: 02/16/2023] [Indexed: 03/09/2023]
Abstract
PURPOSE To develop a fast, deep-learning approach for quantitative magnetization-transfer contrast (MTC)-MR fingerprinting (MRF) that simultaneously estimates multiple tissue parameters and corrects the effects of B0 and B1 variations. METHODS An only-train-once recurrent neural network was designed to perform the fast tissue-parameter quantification for a large range of different MRF acquisition schedules. It enabled a dynamic scan-wise linear calibration of the scan parameters using the measured B0 and B1 maps, which allowed accurate, multiple-tissue parameter mapping. MRF images were acquired from 8 healthy volunteers at 3 T. Estimated parameter maps from the MRF images were used to synthesize the MTC reference signal (Zref ) through Bloch equations at multiple saturation power levels. RESULTS The B0 and B1 errors in MR fingerprints, if not corrected, would impair the tissue quantification and subsequently corrupt the synthesized MTC reference images. Bloch equation-based numerical phantom studies and synthetic MRI analysis demonstrated that the proposed approach could correctly estimate water and semisolid macromolecule parameters, even with severe B0 and B1 inhomogeneities. CONCLUSION The only-train-once deep-learning framework can improve the reconstruction accuracy of brain-tissue parameter maps and be further combined with any conventional MRF or CEST-MRF method.
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Affiliation(s)
- Beomgu Kang
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Guseong-dong, Yuseong-gu, Daejeon, Republic of Korea
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Munendra Singh
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - HyunWook Park
- School of Electrical Engineering, Korea Advanced Institute of Science and Technology, Guseong-dong, Yuseong-gu, Daejeon, Republic of Korea
| | - Hye-Young Heo
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
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13
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Kim H, Kim J, Sun PZ. CEST2022 - mapping multi-pool CEST signal changes in an animal model of brain tumor with quasi-steady-state reconstruction-empowered CEST quantification. Magn Reson Imaging 2023:S0730-725X(23)00100-5. [PMID: 37321379 DOI: 10.1016/j.mri.2023.06.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2023] [Accepted: 06/12/2023] [Indexed: 06/17/2023]
Abstract
Chemical exchange saturated transfer (CEST) MRI has biomarker potential to assess tissue microenvironment in brain tumors. Multi-pool Lorentzian or spinlock models provides useful insights into the CEST contrast mechanism. However, T1 contribution to the complex overlapping effects of brain tumors is difficult under the non-equilibrium state. Therefore, this study evaluated T1 contributions on multi-pool parameters with quasi-steady-state (QUASS) algorithm reconstructed equilibrium data. MRI scans were performed in rat brain tumor models, including relaxation, diffusion, and CEST imaging. A pixel-wise seven-pool spinlock-model was employed to fit QUASS reconstructed CEST Z-spectra and evaluated the magnetization transfer (MT), amide, amine, guanidyl, and nuclear-overhauled effect (NOE) signals in tumor and normal tissues. In addition, T1 was estimated from the spinlock-model fitting and compared with measured T1. We observed tumor had a statistically significant increase in the amide signal (p < 0.001) and decreases in the MT and NOE signals (p < 0.001). On the other hand, the differences in amine and guanidyl between the tumor and contralateral normal regions were not statistically significant. The differences between measured and estimated T1 values were 8% in the normal tissue and 4% in the tumor. Furthermore, the isolated MT signal strongly correlated with R1 (r = 0.96, P < 0.001). In summary, we successfully unraveled multi-factorial effects in the CEST signal using spinlock-model fitting and QUASS method and demonstrated the effect of T1 relaxation on MT and NOE.
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Affiliation(s)
- Hahnsung Kim
- Emory National Primate Research Center, Emory University, Atlanta, GA, United States of America; Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States of America.
| | - Jinsuh Kim
- Emory National Primate Research Center, Emory University, Atlanta, GA, United States of America; Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States of America
| | - Phillip Zhe Sun
- Emory National Primate Research Center, Emory University, Atlanta, GA, United States of America; Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, United States of America.
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14
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Igarashi T, Kim H, Sun PZ. Detection of tissue pH with quantitative chemical exchange saturation transfer magnetic resonance imaging. NMR IN BIOMEDICINE 2023; 36:e4711. [PMID: 35141979 PMCID: PMC10249910 DOI: 10.1002/nbm.4711] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 02/03/2022] [Accepted: 02/05/2022] [Indexed: 05/12/2023]
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a novel means for sensitive detection of dilute labile protons and chemical exchange rates. By sensitizing to pH-dependent chemical exchange, CEST MRI has shown promising results in monitoring tissue statuses such as pH changes in disorders like acute stroke, tumor, and acute kidney injury. This article briefly reviews the basic principles for CEST imaging and quantitative measures, from the simplistic asymmetry analysis to multipool Lorentzian decoupling and quasi-steady-state reconstruction. In particular, the advantages and limitations of commonly used quantitative approaches for CEST applications are discussed.
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Affiliation(s)
- Takahiro Igarashi
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA
| | - Hahnsung Kim
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA
| | - Phillip Zhe Sun
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA
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15
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Qian Z, Liu R, Wu Z, Hsu YC, Fu C, Sun Y, Wu D, Zhang Y. Saturation-prolongated and inhomogeneity-mitigated chemical exchange saturation transfer imaging with parallel transmission. NMR IN BIOMEDICINE 2023; 36:e4689. [PMID: 34994025 DOI: 10.1002/nbm.4689] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 12/20/2021] [Accepted: 01/04/2022] [Indexed: 05/23/2023]
Abstract
Chemical exchange saturation transfer (CEST) imaging benefits from a longer saturation duration and a higher saturation duty cycle. Dielectric shading effects occur when the radiofrequency (RF) wavelength approaches the object size. Here, we proposed a simultaneous parallel transmission-based CEST (pTx-CEST) sequence to prolongate the saturation duration at a 100% duty cycle and improve the RF saturation homogeneity in CEST imaging. The simultaneous pTx-CEST sequence was implemented by switching the CEST saturation module from the non-pTx to pTx mode, using the pTx functionality with both transmit channels being driven simultaneously (instead of time-interleaved). The optimization of amplitude ratio and phase difference settings between RF channels for best B1 homogeneity was performed in phantoms of two different sizes mimicking the human brain and abdomen. The optimal amplitude and phase settings generating the best B1 homogeneity in the phantoms were used in pTx-CEST scans of the human study. The comparison of the maximum achievable saturation duration between the non-pTx-CEST and pTx-CEST sequences was performed in a protein phantom, healthy volunteers, and a metastatic brain tumor patient. The optimal amplitude ratio and phase difference setting between transmit channels manifested circular and elliptical polarization in the head-sized and abdomen-sized phantoms. In the brain, the maximum saturation durations achieved at a 100% duty cycle using the simultaneous pTx-CEST sequence were prolonged to 2240, 3220, and 4200 ms compared with 980 ms using the non-pTx-CEST sequence at repetition times of 3, 4, and 5 s, respectively. The longer saturation duration helped improve the image contrast between the tumor and the normal tissue in the patient. The optimized elliptical polarization mode saturation pulses yielded improved uniformity of CEST signals acquired from the human abdomen. The proposed simultaneous pTx-CEST sequence enabled essentially arbitrarily long saturation duration at a 100% duty cycle and helped reduce the dielectric shading effects with the optimized RF setting.
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Affiliation(s)
- Zihua Qian
- Department of Radiology, The Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Ruibin Liu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Zhe Wu
- Techna Institute, University Health Network, Toronto, Ontario, Canada
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Caixia Fu
- MR Application Development, Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
- Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China
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16
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Chen Y, Dang X, Zhao B, Chen Z, Zhao Y, Zhao F, Zheng Z, He X, Peng J, Song X. Frequency importance analysis for chemical exchange saturation transfer magnetic resonance imaging using permuted random forest. NMR IN BIOMEDICINE 2023; 36:e4744. [PMID: 35434864 DOI: 10.1002/nbm.4744] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Revised: 04/07/2022] [Accepted: 04/14/2022] [Indexed: 05/23/2023]
Abstract
Chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) is a promising molecular imaging tool that allows sensitive detection of endogenous metabolic changes. However, because the CEST spectrum does not display a clear peak like MR spectroscopy, its signal interpretation is challenging, especially under 3-T field strength or with a large saturation B1 . Herein, as an alternative to conventional Z-spectral fitting approaches, a permuted random forest (PRF) method is developed to determine featured saturation frequencies for lesion identification, so-called CEST frequency importance analysis. Briefly, voxels in the CEST dataset were labeled as lesion and control according to multicontrast MR images. Then, by considering each voxel's saturation signal series as a sample, a permutation importance algorithm was employed to rank the contribution of saturation frequency offsets in the differentiation of lesion and normal tissue. Simulations demonstrated that PRF could correctly determine the frequency offsets (3.5 or -3.5 ppm) for classifying two groups of Z-spectra, under a range of B0 , B1 conditions and sample sizes. For ischemic rat brains, PRF only displayed high feature importance around amide frequency at 2 h postischemia, reflecting that the pH changes occurred at an early stage. By contrast, the data acquired at 24 h postischemia exhibited high feature importance at multiple frequencies (amide, water, and lipids), which suggested the complex tissue changes that occur during the later stages. Finally, PRF was assessed using 3-T CEST data from four brain tumor patients. By defining the tumor region on amide proton transfer-weighted images, PRF analysis identified different CEST frequency importance for two types of tumors (glioblastoma and metastatic tumor) (p < 0.05, with each image slice as a subject). In conclusion, the PRF method was able to rank and interpret the contribution of all acquired saturation offsets to lesion identification; this may facilitate CEST analysis in clinical applications, and open up new doors for comprehensive CEST analysis tools other than model-based approaches.
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Affiliation(s)
- Yibing Chen
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Xujian Dang
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Benqi Zhao
- Department of Radiology, Beijing Tsinghua Changgung Hospital, Beijing, China
| | - Zhensen Chen
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Yingcheng Zhao
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Fengjun Zhao
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Zhuozhao Zheng
- Department of Radiology, Beijing Tsinghua Changgung Hospital, Beijing, China
| | - Xiaowei He
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Jinye Peng
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Xiaolei Song
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Beijing, China
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17
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Jiang S, Wen Z, Ahn SS, Cai K, Paech D, Eberhart CG, Zhou J. Applications of chemical exchange saturation transfer magnetic resonance imaging in identifying genetic markers in gliomas. NMR IN BIOMEDICINE 2023; 36:e4731. [PMID: 35297117 PMCID: PMC10557022 DOI: 10.1002/nbm.4731] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Revised: 03/07/2022] [Accepted: 03/14/2022] [Indexed: 05/23/2023]
Abstract
Chemical exchange saturation transfer (CEST) imaging is an important molecular magnetic resonance imaging technique that can image numerous low-concentration biomolecules with water-exchangeable protons (such as cellular proteins) and tissue pH. CEST, or more specially amide proton transfer-weighted imaging, has been widely used for the detection, diagnosis, and response assessment of brain tumors, and its feasibility in identifying molecular markers in gliomas has also been explored in recent years. In this paper, after briefing on the basic principles and quantification methods of CEST imaging, we review its early applications in identifying isocitrate dehydrogenase mutation status, MGMT methylation status, 1p/19q deletion status, and H3K27M mutation status in gliomas. Finally, we discuss the limitations or weaknesses in these studies.
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Affiliation(s)
- Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
| | - Zhibo Wen
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Daniel Paech
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany
- Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | | | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, MD, USA
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18
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Glang F, Fabian MS, German A, Khakzar KM, Mennecke A, Liebert A, Herz K, Liebig P, Kasper BS, Schmidt M, Zuazua E, Nagel AM, Laun FB, Dörfler A, Scheffler K, Zaiss M. Linear projection-based chemical exchange saturation transfer parameter estimation. NMR IN BIOMEDICINE 2023; 36:e4697. [PMID: 35067998 DOI: 10.1002/nbm.4697] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 12/14/2021] [Accepted: 01/15/2022] [Indexed: 05/23/2023]
Abstract
Isolated evaluation of multiparametric in vivo chemical exchange saturation transfer (CEST) MRI often requires complex computational processing for both correction of B0 and B1 inhomogeneity and contrast generation. For that, sufficiently densely sampled Z-spectra need to be acquired. The list of acquired frequency offsets largely determines the total CEST acquisition time, while potentially representing redundant information. In this work, a linear projection-based multiparametric CEST evaluation method is introduced that offers fast B0 and B1 inhomogeneity correction, contrast generation and feature selection for CEST data, enabling reduction of the overall measurement time. To that end, CEST data acquired at 7 T in six healthy subjects and in one brain tumor patient were conventionally evaluated by interpolation-based inhomogeneity correction and Lorentzian curve fitting. Linear regression was used to obtain coefficient vectors that directly map uncorrected data to corrected Lorentzian target parameters. L1-regularization was applied to find subsets of the originally acquired CEST measurements that still allow for such a linear projection mapping. The linear projection method allows fast and interpretable mapping from acquired raw data to contrast parameters of interest, generalizing from healthy subject training data to unseen healthy test data and to the tumor patient dataset. The L1-regularization method shows that a fraction of the acquired CEST measurements is sufficient to preserve tissue contrasts, offering up to a 2.8-fold reduction of scan time. Similar observations as for the 7-T data can be made for data from a clinical 3-T scanner. Being a fast and interpretable computation step, the proposed method is complementary to neural networks that have recently been employed for similar purposes. The scan time acceleration offered by the L1-regularization ("CEST-LASSO") constitutes a step towards better applicability of multiparametric CEST protocols in a clinical context.
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Affiliation(s)
- Felix Glang
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Moritz S Fabian
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Alexander German
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Katrin M Khakzar
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Angelika Mennecke
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Andrzej Liebert
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany
| | - Kai Herz
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Biomedical Magnetic Resonance, Eberhard Karls University Tübingen, Tübingen, Germany
| | | | - Burkhard S Kasper
- Department of Neurology, University Clinic of Friedrich Alexander University Erlangen-Nürnberg, Erlangen, Germany
| | - Manuel Schmidt
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Enrique Zuazua
- Department of Data Science, Friedrich-Alexander-Universität Erlangen, Erlangen, Germany
| | - Armin M Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany
| | - Frederik B Laun
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Germany
| | - Arnd Dörfler
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Klaus Scheffler
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Biomedical Magnetic Resonance, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Moritz Zaiss
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
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19
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Heo HY, Tee YK, Harston G, Leigh R, Chappell M. Amide proton transfer imaging in stroke. NMR IN BIOMEDICINE 2023; 36:e4734. [PMID: 35322482 PMCID: PMC9761584 DOI: 10.1002/nbm.4734] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2021] [Revised: 03/04/2022] [Accepted: 03/21/2022] [Indexed: 05/23/2023]
Abstract
Amide proton transfer (APT) imaging, a variant of chemical exchange saturation transfer MRI, has shown promise in detecting ischemic tissue acidosis following impaired aerobic metabolism in animal models and in human stroke patients due to the sensitivity of the amide proton exchange rate to changes in pH within the physiological range. Recent studies have demonstrated the possibility of using APT-MRI to detect acidosis of the ischemic penumbra, enabling the assessment of stroke severity and risk of progression, monitoring of treatment progress, and prognostication of clinical outcome. This paper reviews current APT imaging methods actively used in ischemic stroke research and explores the clinical aspects of ischemic stroke and future applications for these methods.
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Affiliation(s)
- Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
| | - Yee Kai Tee
- Lee Kong Chian Faculty of Engineering and Science, University Tunku Abdul Rahman, Malaysia
| | - George Harston
- Acute Stroke Programme, Oxford University Hospitals NHS Foundation Trust, Oxford, UK
| | - Richard Leigh
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Michael Chappell
- Radiological Sciences, Mental Health and Clinical Neurosciences, School of Medicine, University of Nottingham, Nottingham, UK
- Nottingham Biomedical Research Centre, Queen’s Medical Centre, University of Nottingham, Nottingham, United Kingdom, UK
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20
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Sun PZ. Generalization of quasi-steady-state reconstruction to CEST MRI with two-tiered RF saturation and gradient-echo readout-Synergistic nuclear Overhauser enhancement contribution to brain tumor amide proton transfer-weighted MRI. Magn Reson Med 2023; 89:2014-2023. [PMID: 36579767 DOI: 10.1002/mrm.29570] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 12/13/2022] [Accepted: 12/14/2022] [Indexed: 12/30/2022]
Abstract
PURPOSE While amide proton transfer-weighted (APTw) MRI has been adopted in tumor imaging, there are concurrent APT, magnetization transfer, and nuclear Overhauser enhancement changes. Also, the APTw image is confounded by relaxation changes, particularly when the relaxation delay and saturation time are not sufficiently long. Our study aimed to extend a quasi-steady-state (QUASS) solution to determine the contribution of the multipool CEST signals to the observed tumor APTw contrast. METHODS Our study derived the QUASS solution for a multislice CEST-MRI sequence with an interleaved RF saturation and gradient-echo readout between signal averaging. Multiparametric MRI scans were obtained in rat brain tumor models, including T1 , T2 , diffusion, and CEST scans. Finally, we performed spinlock model-based multipool fitting to determine multiple concurrent CEST signal changes in the tumor. RESULTS The QUASS APTw MRI showed small but significant differences in normal and tumor tissues and their contrast from the acquired asymmetry calculation. The spinlock model-based fitting showed significant differences in semisolid magnetization transfer, amide, and nuclear Overhauser enhancement effects between the apparent and QUASS CEST MRI. In addition, we determined that the tumor APTw contrast is due to synergistic APT increase (+3.5 ppm) and NOE decrease (-3.5 ppm), with their relative contribution being about one third and two thirds under a moderate B1 of 0.75 μT at 4.7 T. CONCLUSION Our study generalized QUASS analysis to gradient-echo image readout and quantified the underlying tumor CEST signal changes, providing an improved elucidation of the commonly used APTw MRI.
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Affiliation(s)
- Phillip Zhe Sun
- Emory Primate Imaging Center, Emory National Primate Research Center, Emory University, Atlanta, Georgia, USA.,Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
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21
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Yong X, Lu S, Hsu YC, Fu C, Sun Y, Zhang Y. Numerical fitting of Extrapolated semisolid Magnetization transfer Reference signals: Improved detection of ischemic stroke. Magn Reson Med 2023; 90:722-736. [PMID: 37052377 DOI: 10.1002/mrm.29660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 03/09/2023] [Accepted: 03/18/2023] [Indexed: 04/14/2023]
Abstract
PURPOSE To propose a novel Numerical fitting method of the Extrapolated semisolid Magnetization transfer Reference (NEMR) signal for quantifying the CEST effect. THEORY AND METHODS Modified two-pool Bloch-McConnell equations were used to numerically fit the magnetization transfer (MT) and direct water saturation (DS) signals at far off-resonance frequencies, which was subsequently extrapolated into the frequency range of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) pools. Then the subtraction of the fitted two-pool z-spectrum and the experimentally acquired z-spectrum yielded APT# and NOE# signals mostly free of MT and DS contamination. Several strategies were used to accelerate the NEMR fitting. Furthermore, the proposed NEMR method was compared with the conventional extrapolated semisolid magnetization transfer reference (EMR) and magnetization transfer ratio asymmetry (MTRasym ) methods in simulations and stroke patients. RESULTS The combination of RF downsampling, MT lineshape look-up table, and conversion of MATLAB code to C code accelerated the NEMR fitting by over 2700-fold. Monte-Carlo simulations showed that NEMR had higher accuracy than EMR and eliminated the requirement of the steady-state condition. In ischemic stroke patients, the NEMR maps at 1 μT removed hypointense artifacts seen on EMR and MTRasym images, and better depicted stroke lesions than EMR. For NEMR, NOE# yielded significantly (p < 0.05) stronger signal contrast between stroke and normal tissues than APT# at 1 μT. CONCLUSION The proposed NEMR method is suitable for arbitrary saturation settings and can remove MT and DS contamination from the CEST signal for improved detection of ischemic stroke.
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Affiliation(s)
- Xingwang Yong
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Shanshan Lu
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Caixia Fu
- Siemens Shenzhen Magnetic Resonance Ltd., Shenzhen, Guangdong, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
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22
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Zhang L, Xu C, Li Z, Sun J, Wang X, Hou B, Zhao Y. Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) quantification of transient ischemia using a combination method of 5-pool Lorentzian fitting and inverse Z-spectrum analysis. Quant Imaging Med Surg 2023; 13:1860-1873. [PMID: 36915363 PMCID: PMC10006163 DOI: 10.21037/qims-22-420] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 10/30/2022] [Indexed: 12/12/2022]
Abstract
Background Chemical exchange saturation transfer (CEST) is a promising method for the detection of biochemical alterations in cancers and neurological diseases. However, the sensitivity of the currently existing quantitative method for detecting ischemia needs further improvement. Methods To further improve the quantification of the CEST signal and enhance the CEST detection for ischemia, we used a quantitative analysis method that combines an inverse Z-spectrum analysis and a 5-pool Lorentzian fitting. Specifically, a 5-pool Lorentzian simulation was conducted with the following brain tissue parameters: water, amide (3.5 ppm), amine (2.2 ppm), magnetization transfer (MT), and nuclear Overhauser enhancement (NOE; -3.5 ppm). The parameters were first calculated offline and stored as the initial value of the Z-spectrum fitting. Then, the measured Z-spectrum with the peak value set to 0 was fitted via the stored initial value, which yielded the reference Z-spectrum. Finally, the difference between the inverse of the Z-spectrum and the inverse of the reference Z-spectrum was used as the CEST definite spectrum. Results The simulation results demonstrated that the Z-spectra of the rat brain were well simulated by a 5-pool Lorentzian fitting. Further, the proposed method detected a larger difference than did either the saturation transfer difference or the 5-pool Lorentzian fitting, as demonstrated by simulations. According to the results of the cerebral ischemia rat model, the proposed method provided the highest contrast-to-noise ratio (CNR) between the contralateral and the ipsilateral striatum under various acquisition conditions. The results indicated that the difference of fitted amplitudes generated with a 5-pool Lorentzian fitting in amide at 3.5 ppm (6.04%±0.39%; 6.86%±0.39%) was decreased in a stroke lesion compared to the contralateral normal tissue. Moreover, the difference of the residual of inversed Z-spectra in which 5-pool Lorentzian fitting was used to calculate the reference Z-spectra ( M T R R e x 5 L ) amplitudes in amide at 3.5 ppm (13.83%±2.20%, 15.69%±1.99%) was reduced in a stroke lesion compared to the contralateral normal tissue. Conclusions M T R R e x 5 L is predominantly pH-sensitive and is suitable for detecting tissue acidosis following an acute stroke.
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Affiliation(s)
- Lihong Zhang
- College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China
| | - Chongxin Xu
- College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China
| | - Zhen Li
- Department of Medical Imaging, Weifang Medical University, Weifang, China
| | - Junding Sun
- College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China
| | - Xiaoli Wang
- Department of Medical Imaging, Weifang Medical University, Weifang, China
| | - Beibei Hou
- College of Computer Science and Technology, Henan Polytechnic University, Jiaozuo, China
| | - Yingcheng Zhao
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, China
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23
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Zu T, Sun Y, Wu D, Zhang Y. Joint K-space and Image-space Parallel Imaging (KIPI) for accelerated chemical exchange saturation transfer acquisition. Magn Reson Med 2023; 89:922-936. [PMID: 36336741 DOI: 10.1002/mrm.29480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Revised: 08/25/2022] [Accepted: 09/16/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE To develop an auto-calibrated technique by joint K-space and Image-space Parallel Imaging (KIPI) for accelerated CEST acquisition. THEORY AND METHODS The KIPI method selects a calibration frame with a low acceleration factor (AF) and auto-calibration signals (ACS) acquired, from which the coil sensitivity profiles and artifact correction maps are calculated after restoring the k-space by GRAPPA. Then the other frames with high AF and without ACS can be reconstructed by SENSE and artifact suppression. The signal leakage due to the T2 -decay filtering in k-space compromises the SENSE reconstruction, which can be corrected by the artifact suppression algorithm of KIPI. The 2D and 3D imaging experiments were done on the phantom, healthy volunteer, and brain tumor patient with a 3T scanner. RESULTS The proposed KIPI method was evaluated by retrospectively undersampled data with variable AFs and compared against existing parallel imaging methods (SENSE/auto, GRAPPA, and ESPIRiT). KIPI enabled CEST frames with random AFs to achieve similar image quality, eliminated the strong aliasing artifacts, and generated significantly smaller errors than the other methods (p < 0.01). The KIPI method permitted an AF up to 12-fold in both phase-encoding and slice-encoding directions for 3D CEST source images, achieving an overall 8.2-fold speedup in scan time. CONCLUSION KIPI is a novel auto-calibrated parallel imaging method that enables variable AFs for different CEST frames, achieves a significant reduction in scan time, and does not compromise the accuracy of CEST maps.
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Affiliation(s)
- Tao Zu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi Sun
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
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24
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Chung J, Jin T. Average saturation efficiency filter ASEF-CEST MRI of stroke rodents. Magn Reson Med 2023; 89:565-576. [PMID: 36300851 PMCID: PMC9757140 DOI: 10.1002/mrm.29463] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Revised: 07/29/2022] [Accepted: 08/29/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE The average saturation efficiency filter (ASEF) is a novel method of improving the specificity of CEST; however, there is a mismatch between the magnetization transfer (MT) effect under high-duty cycle and low-duty cycle pulse trains. We explore measures of mitigation and the sensitivity and potential of ASEF imaging in phantoms and stroke rats. METHODS Simulation and nicotinamide phantoms in denatured protein were used to investigate the effect of different average saturation powers and MT pool parameters on matching coefficients used for correction as well as the ASEF ratio signal and baseline. Then, in vivo studies were performed in stroke rodents to further investigate the sensitivity and fidelity of ASEF ratio spectra. RESULTS Simulation and studies of nicotinamide phantoms show that the matching coefficient needed to correct the baseline MT mismatch is strongly dependent on the average saturation power. In vivo studies in stroke rodents show that the matching coefficient required to correct the baseline MT mismatch is different for normal versus ischemic tissue. Thus, a baseline correction was performed to further suppress the residue MT mismatch. After correction of the mismatch, ASEF ratio achieved comparable contrast at 3.6 ppm between normal and ischemic tissue when compared to the apparent amide proton transfer (APT*) approach. Moreover, contrasts for 2.0 and 2.6 ppm were also ascertainable from the same spectra. CONCLUSION ASEF can improve the CEST signal specificity of slow exchange labile protons such as amide and guanidyl, with small loss to sensitivity. It has strong potential in the CEST imaging of various diseases.
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Affiliation(s)
- Julius Chung
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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25
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Wang K, Park S, Kamson DO, Li Y, Liu G, Xu J. Guanidinium and amide CEST mapping of human brain by high spectral resolution CEST at 3 T. Magn Reson Med 2023; 89:177-191. [PMID: 36063502 PMCID: PMC9617768 DOI: 10.1002/mrm.29440] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2022] [Revised: 08/01/2022] [Accepted: 08/11/2022] [Indexed: 11/09/2022]
Abstract
PURPOSE To extract guanidinium (Guan) and amide CEST on the human brain at 3 T MRI with the high spectral resolution (HSR) CEST combined with the polynomial Lorentzian line-shape fitting (PLOF). METHODS Continuous wave (cw) turbo spin-echo (TSE) CEST was implemented to obtain the optimum saturation parameters. Both Guan and amide CEST peaks were extracted and quantified using the PLOF method. The NMR spectra on the egg white phantoms were acquired to reveal the fitting range and the contributions to the amide and GuanCEST. Two types of CEST approaches, including cw gradient- and spin-echo (cwGRASE) and steady state EPI (ssEPI), were implemented to acquire multi-slice HSR-CEST. RESULTS GuanCEST can be extracted with the PLOF method at 3 T, and the optimumB 1 = 0.6 μ T $$ {\mathrm{B}}_1=0.6\kern0.2em \upmu \mathrm{T} $$ was determined for GuanCEST in white matter (WM) and 1.0 μT in gray matter (GM). The optimum B1 = 0.8-1 μT was found for amideCEST. AmideCEST is lower in both WM and GM collected with ssEPI compared to those by cwGRASE (ssEPI = [1.27-1.63]%; cwGRASE = [2.19-2.25]%). The coefficients of variation (COV) of the amide and Guan CEST in both WM and GM for ssEPI (COV: 28.6-33.4%) are significantly higher than those of cwGRASE (COV: 8.6-18.8%). Completely different WM/GM contrasts for Guan and amide CEST were observed between ssEPI and cwGRASE. The amideCEST was found to have originated from the unstructured amide protons as suggested by the NMR spectrum of the unfolded proteins in egg white. CONCLUSION Guan and amide CEST mapping can be achieved by the HSR-CEST at 3 T combing with the PLOF method.
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Affiliation(s)
- Kexin Wang
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Sooyeon Park
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
| | - David Olayinka Kamson
- The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University, Baltimore, Maryland, USA
| | - Yuguo Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Guanshu Liu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
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26
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Mehrabian H, Chan RW, Sahgal A, Chen H, Theriault A, Lam WW, Myrehaug S, Tseng CL, Husain Z, Detsky J, Soliman H, Stanisz GJ. Chemical Exchange Saturation Transfer MRI for Differentiating Radiation Necrosis From Tumor Progression in Brain Metastasis-Application in a Clinical Setting. J Magn Reson Imaging 2022; 57:1713-1725. [PMID: 36219521 DOI: 10.1002/jmri.28440] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 09/07/2022] [Accepted: 09/08/2022] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND High radiation doses of stereotactic radiosurgery (SRS) for brain metastases (BM) can increase the likelihood of radiation necrosis (RN). Advanced MRI sequences can improve the differentiation between RN and tumor progression (TP). PURPOSE To use saturation transfer MRI methods including chemical exchange saturation transfer (CEST) and magnetization transfer (MT) to distinguish RN from TP. STUDY TYPE Prospective cohort study. SUBJECTS Seventy patients (median age 60; 73% females) with BM (75 lesions) post-SRS. FIELD STRENGTH/SEQUENCE 3-T, CEST imaging using low/high-power (saturation B1 = 0.52 and 2.0 μT), quantitative MT imaging using B1 = 1.5, 3.0, and 5.0 μT, WAter Saturation Shift Referencing (WASSR), WAter Shift And B1 (WASABI), T1 , and T2 mapping. All used gradient echoes except T2 mapping (gradient and spin echo). ASSESSMENT Voxel-wise metrics included: magnetization transfer ratio (MTR); apparent exchange-dependent relaxation (AREX); MTR asymmetry; normalized MT exchange rate and pool size product; direct water saturation peak width; and the observed T1 and T2 . Regions of interests (ROIs) were manually contoured on the post-Gd T1 w. The mean (of median ROI values) was compared between groups. Clinical outcomes were determined by clinical and radiologic follow-up or histopathology. STATISTICAL TESTS t-Test, univariable and multivariable logistic regression, receiver operating characteristic, and area under the curve (AUC) with sensitivity/specificity values with the optimal cut point using the Youden index, Akaike information criterion (AIC), Cohen's d. P < 0.05 with Bonferroni correction was considered significant. RESULTS Seven metrics showed significant differences between RN and TP. The high-power MTR showed the highest AUC of 0.88, followed by low-power MTR (AUC = 0.87). The combination of low-power CEST scans improved the separation compared to individual parameters (with an AIC of 70.3 for low-power MTR/AREX). Cohen's d effect size showed that the MTR provided the largest effect sizes among all metrics. DATA CONCLUSION Significant differences between RN and TP were observed based on saturation transfer MRI. EVIDENCE LEVEL 3 Technical Efficacy: Stage 2.
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Affiliation(s)
- Hatef Mehrabian
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Rachel W Chan
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Hanbo Chen
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Aimee Theriault
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Wilfred W Lam
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Sten Myrehaug
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Zain Husain
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Jay Detsky
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Hany Soliman
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - Greg J Stanisz
- Physical Sciences Platform, Sunnybrook Research Institute, Toronto, Ontario, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada.,Department of Neurosurgery and Pediatric Neurosurgery, Medical University of Lublin, Lublin, Poland
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27
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Wu QX, Liu HQ, Wang YJ, Chen TC, Wei ZY, Chang JH, Chen TH, Seema J, Lin EC. Chemical Exchange Saturation Transfer (CEST) Signal at −1.6 ppm and Its Application for Imaging a C6 Glioma Model. Biomedicines 2022; 10:biomedicines10061220. [PMID: 35740241 PMCID: PMC9219881 DOI: 10.3390/biomedicines10061220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2022] [Revised: 05/17/2022] [Accepted: 05/21/2022] [Indexed: 02/01/2023] Open
Abstract
The chemical exchange saturation transfer (CEST) signal at −1.6 ppm is attributed to the choline methyl on phosphatidylcholines and results from the relayed nuclear Overhauser effect (rNOE), that is, rNOE(−1.6). The formation of rNOE(−1.6) involving the cholesterol hydroxyl is shown in liposome models. We aimed to confirm the correlation between cholesterol content and rNOE(−1.6) in cell cultures, tissues, and animals. C57BL/6 mice (N = 9) bearing the C6 glioma tumor were imaged in a 7 T MRI scanner, and their rNOE(−1.6) images were cross-validated through cholesterol staining with filipin. Cholesterol quantification was obtained using an 18.8-T NMR spectrometer from the lipid extracts of the brain tissues from another group of mice (N = 3). The cholesterol content in the cultured cells was manipulated using methyl-β-cyclodextrin and a complex of cholesterol and methyl-β-cyclodextrin. The rNOE(−1.6) of the cell homogenates and their cholesterol levels were measured using a 9.4-T NMR spectrometer. The rNOE(−1.6) signal is hypointense in the C6 tumors of mice, which matches the filipin staining results, suggesting that their tumor region is cholesterol deficient. The tissue extracts also indicate less cholesterol and phosphatidylcholine contents in tumors than in normal brain tissues. The amplitude of rNOE(−1.6) is positively correlated with the cholesterol concentration in the cholesterol-manipulated cell cultures. Our results indicate that the cholesterol dependence of rNOE(−1.6) occurs in cell cultures and solid tumors of C6 glioma. Furthermore, when the concentration of phosphatidylcholine is carefully considered, rNOE(−1.6) can be developed as a cholesterol-weighted imaging technique.
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Affiliation(s)
- Qi-Xuan Wu
- Department of Chemistry and Biochemistry, National Chung Cheng University, Chiayi 62102, Taiwan; (Q.-X.W.); (H.-Q.L.); (Y.-J.W.); (Z.-Y.W.); (J.-H.C.); (T.-H.C.)
- Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan; (T.-C.C.); (J.S.)
| | - Hong-Qing Liu
- Department of Chemistry and Biochemistry, National Chung Cheng University, Chiayi 62102, Taiwan; (Q.-X.W.); (H.-Q.L.); (Y.-J.W.); (Z.-Y.W.); (J.-H.C.); (T.-H.C.)
- Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan; (T.-C.C.); (J.S.)
| | - Yi-Jiun Wang
- Department of Chemistry and Biochemistry, National Chung Cheng University, Chiayi 62102, Taiwan; (Q.-X.W.); (H.-Q.L.); (Y.-J.W.); (Z.-Y.W.); (J.-H.C.); (T.-H.C.)
| | - Tsai-Chen Chen
- Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan; (T.-C.C.); (J.S.)
| | - Zi-Ying Wei
- Department of Chemistry and Biochemistry, National Chung Cheng University, Chiayi 62102, Taiwan; (Q.-X.W.); (H.-Q.L.); (Y.-J.W.); (Z.-Y.W.); (J.-H.C.); (T.-H.C.)
- Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan; (T.-C.C.); (J.S.)
| | - Jung-Hsuan Chang
- Department of Chemistry and Biochemistry, National Chung Cheng University, Chiayi 62102, Taiwan; (Q.-X.W.); (H.-Q.L.); (Y.-J.W.); (Z.-Y.W.); (J.-H.C.); (T.-H.C.)
| | - Ting-Hao Chen
- Department of Chemistry and Biochemistry, National Chung Cheng University, Chiayi 62102, Taiwan; (Q.-X.W.); (H.-Q.L.); (Y.-J.W.); (Z.-Y.W.); (J.-H.C.); (T.-H.C.)
| | - Jaya Seema
- Institute of Biomedical Sciences, Academia Sinica, Taipei 11529, Taiwan; (T.-C.C.); (J.S.)
| | - Eugene C. Lin
- Department of Chemistry and Biochemistry, National Chung Cheng University, Chiayi 62102, Taiwan; (Q.-X.W.); (H.-Q.L.); (Y.-J.W.); (Z.-Y.W.); (J.-H.C.); (T.-H.C.)
- Center for Nano Bio-Detection, National Chung Cheng University, Chiayi 62102, Taiwan
- Correspondence: ; Tel.: +886-5-272-0411 (ext. 66418); Fax: +886-5-272-1040
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28
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Kang B, Kim B, Park H, Heo HY. Learning-based optimization of acquisition schedule for magnetization transfer contrast MR fingerprinting. NMR IN BIOMEDICINE 2022; 35:e4662. [PMID: 34939236 PMCID: PMC9761585 DOI: 10.1002/nbm.4662] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 11/12/2021] [Accepted: 11/16/2021] [Indexed: 05/03/2023]
Abstract
Magnetization transfer contrast MR fingerprinting (MTC-MRF) is a novel quantitative imaging method that simultaneously quantifies free bulk water and semisolid macromolecule parameters using pseudo-randomized scan parameters. To improve acquisition efficiency and reconstruction accuracy, the optimization of MRF sequence design has been of recent interest in the MRF field, but has been challenging due to the large number of degrees of freedom to be optimized in the sequence. Herein, we propose a framework for learning-based optimization of the acquisition schedule (LOAS), which optimizes RF saturation-encoded MRF acquisitions with a minimal number of scan parameters for tissue parameter determination. In a supervised learning framework, scan parameters were subsequently updated to minimize a predefined loss function that can directly represent tissue quantification errors. We evaluated the performance of the proposed approach with a numerical phantom and in in vivo experiments. For validation, MRF images were synthesized using the tissue parameters estimated from a fully connected neural network framework and compared with references. Our results showed that LOAS outperformed existing indirect optimization methods with regard to quantification accuracy and acquisition efficiency. The proposed LOAS method could be a powerful optimization tool in the design of MRF pulse sequences.
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Affiliation(s)
- Beomgu Kang
- Department of Electrical Engineering, Korea Advanced
Institute of Science and Technology, Guseong-dong, Yuseong-gu, Daejeon, Republic of
Korea
| | - Byungjai Kim
- Department of Electrical Engineering, Korea Advanced
Institute of Science and Technology, Guseong-dong, Yuseong-gu, Daejeon, Republic of
Korea
- Divison of MR Research, Department of Radiology, Johns
Hopkins University, Baltimore, Maryland, USA
| | - HyunWook Park
- Department of Electrical Engineering, Korea Advanced
Institute of Science and Technology, Guseong-dong, Yuseong-gu, Daejeon, Republic of
Korea
| | - Hye-Young Heo
- Divison of MR Research, Department of Radiology, Johns
Hopkins University, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging,
Kennedy Krieger Institute, Baltimore, Maryland, USA
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29
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Zhou J, Zaiss M, Knutsson L, Sun PZ, Ahn SS, Aime S, Bachert P, Blakeley JO, Cai K, Chappell MA, Chen M, Gochberg DF, Goerke S, Heo HY, Jiang S, Jin T, Kim SG, Laterra J, Paech D, Pagel MD, Park JE, Reddy R, Sakata A, Sartoretti-Schefer S, Sherry AD, Smith SA, Stanisz GJ, Sundgren PC, Togao O, Vandsburger M, Wen Z, Wu Y, Zhang Y, Zhu W, Zu Z, van Zijl PCM. Review and consensus recommendations on clinical APT-weighted imaging approaches at 3T: Application to brain tumors. Magn Reson Med 2022; 88:546-574. [PMID: 35452155 PMCID: PMC9321891 DOI: 10.1002/mrm.29241] [Citation(s) in RCA: 81] [Impact Index Per Article: 40.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2021] [Revised: 02/26/2022] [Accepted: 03/02/2022] [Indexed: 12/16/2022]
Abstract
Amide proton transfer-weighted (APTw) MR imaging shows promise as a biomarker of brain tumor status. Currently used APTw MRI pulse sequences and protocols vary substantially among different institutes, and there are no agreed-on standards in the imaging community. Therefore, the results acquired from different research centers are difficult to compare, which hampers uniform clinical application and interpretation. This paper reviews current clinical APTw imaging approaches and provides a rationale for optimized APTw brain tumor imaging at 3 T, including specific recommendations for pulse sequences, acquisition protocols, and data processing methods. We expect that these consensus recommendations will become the first broadly accepted guidelines for APTw imaging of brain tumors on 3 T MRI systems from different vendors. This will allow more medical centers to use the same or comparable APTw MRI techniques for the detection, characterization, and monitoring of brain tumors, enabling multi-center trials in larger patient cohorts and, ultimately, routine clinical use.
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Affiliation(s)
- Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Moritz Zaiss
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Linda Knutsson
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Medical Radiation Physics, Lund University, Lund, Sweden.,F.M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | - Phillip Zhe Sun
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, Georgia, USA
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science, Yonsei University College of Medicine, Seoul, South Korea
| | - Silvio Aime
- Molecular Imaging Center, Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Peter Bachert
- Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany.,Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Jaishri O Blakeley
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kejia Cai
- Department of Radiology, University of Illinois at Chicago, Chicago, Illinois, USA
| | - Michael A Chappell
- Mental Health and Clinical Neurosciences and Sir Peter Mansfield Imaging Centre, School of Medicine, University of Nottingham, Nottingham, UK.,Nottingham Biomedical Research Centre, Queen's Medical Centre, University of Nottingham, Nottingham, UK
| | - Min Chen
- Department of Radiology, Beijing Hospital, National Center of Gerontology, Beijing, China
| | - Daniel F Gochberg
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Physics, Vanderbilt University, Nashville, Tennessee, USA
| | - Steffen Goerke
- Department of Medical Physics in Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Seong-Gi Kim
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Suwon, South Korea
| | - John Laterra
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
| | - Daniel Paech
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany.,Clinic for Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Mark D Pagel
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, South Korea
| | - Ravinder Reddy
- Center for Advance Metabolic Imaging in Precision Medicine, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Akihiko Sakata
- Department of Diagnostic Imaging and Nuclear Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | | | - A Dean Sherry
- Advanced Imaging Research Center and Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas, USA.,Department of Chemistry and Biochemistry, University of Texas at Dallas, Richardson, Texas, USA
| | - Seth A Smith
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, USA
| | - Greg J Stanisz
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Pia C Sundgren
- Department of Diagnostic Radiology/Clinical Sciences Lund, Lund University, Lund, Sweden.,Lund University Bioimaging Center, Lund University, Lund, Sweden.,Department of Medical Imaging and Physiology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Osamu Togao
- Department of Molecular Imaging and Diagnosis, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan
| | | | - Zhibo Wen
- Department of Radiology, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Yin Wu
- Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science (VUIIS), Vanderbilt University Medical Center, Nashville, Tennessee, USA.,Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Peter C M van Zijl
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Hugo W. Moser Research Institute at Kennedy Krieger, Baltimore, Maryland, USA
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Huang J, Chen Z, Park SW, Lai JHC, Chan KWY. Molecular Imaging of Brain Tumors and Drug Delivery Using CEST MRI: Promises and Challenges. Pharmaceutics 2022; 14:451. [PMID: 35214183 PMCID: PMC8880023 DOI: 10.3390/pharmaceutics14020451] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2022] [Revised: 02/16/2022] [Accepted: 02/17/2022] [Indexed: 12/10/2022] Open
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) detects molecules in their natural forms in a sensitive and non-invasive manner. This makes it a robust approach to assess brain tumors and related molecular alterations using endogenous molecules, such as proteins/peptides, and drugs approved for clinical use. In this review, we will discuss the promises of CEST MRI in the identification of tumors, tumor grading, detecting molecular alterations related to isocitrate dehydrogenase (IDH) and O-6-methylguanine-DNA methyltransferase (MGMT), assessment of treatment effects, and using multiple contrasts of CEST to develop theranostic approaches for cancer treatments. Promising applications include (i) using the CEST contrast of amide protons of proteins/peptides to detect brain tumors, such as glioblastoma multiforme (GBM) and low-grade gliomas; (ii) using multiple CEST contrasts for tumor stratification, and (iii) evaluation of the efficacy of drug delivery without the need of metallic or radioactive labels. These promising applications have raised enthusiasm, however, the use of CEST MRI is not trivial. CEST contrast depends on the pulse sequences, saturation parameters, methods used to analyze the CEST spectrum (i.e., Z-spectrum), and, importantly, how to interpret changes in CEST contrast and related molecular alterations in the brain. Emerging pulse sequence designs and data analysis approaches, including those assisted with deep learning, have enhanced the capability of CEST MRI in detecting molecules in brain tumors. CEST has become a specific marker for tumor grading and has the potential for prognosis and theranostics in brain tumors. With increasing understanding of the technical aspects and associated molecular alterations detected by CEST MRI, this young field is expected to have wide clinical applications in the near future.
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Affiliation(s)
- Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
| | - Zilin Chen
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
| | - Se-Weon Park
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
| | - Joseph H. C. Lai
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
| | - Kannie W. Y. Chan
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China; (J.H.); (Z.C.); (S.-W.P.); (J.H.C.L.)
- Hong Kong Centre for Cerebro-Cardiovascular Health Engineering (COCHE), Hong Kong, China
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- Shenzhen Research Institute, City University of Hong Kong, Shenzhen 518057, China
- Tung Biomedical Science Centre, City University of Hong Kong, Hong Kong, China
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31
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Perlman O, Farrar CT, Heo HY. MR fingerprinting for semisolid magnetization transfer and chemical exchange saturation transfer quantification. NMR IN BIOMEDICINE 2022; 36:e4710. [PMID: 35141967 PMCID: PMC9808671 DOI: 10.1002/nbm.4710] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 01/18/2022] [Accepted: 02/04/2022] [Indexed: 05/11/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI has positioned itself as a promising contrast mechanism, capable of providing molecular information at sufficient resolution and amplified sensitivity. However, it has not yet become a routinely employed clinical technique, due to a variety of confounding factors affecting its contrast-weighted image interpretation and the inherently long scan time. CEST MR fingerprinting (MRF) is a novel approach for addressing these challenges, allowing simultaneous quantitation of several proton exchange parameters using rapid acquisition schemes. Recently, a number of deep-learning algorithms have been developed to further boost the performance and speed of CEST and semi-solid macromolecule magnetization transfer (MT) MRF. This review article describes the fundamental theory behind semisolid MT/CEST-MRF and its main applications. It then details supervised and unsupervised learning approaches for MRF image reconstruction and describes artificial intelligence (AI)-based pipelines for protocol optimization. Finally, practical considerations are discussed, and future perspectives are given, accompanied by basic demonstration code and data.
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Affiliation(s)
- Or Perlman
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Christian T. Farrar
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Hye-Young Heo
- Division of MR Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Wu Y, Wood TC, Arzanforoosh F, Hernandez-Tamames JA, Barker GJ, Smits M, Warnert EAH. 3D APT and NOE CEST-MRI of healthy volunteers and patients with non-enhancing glioma at 3 T. MAGMA (NEW YORK, N.Y.) 2022; 35:63-73. [PMID: 34994858 PMCID: PMC8901510 DOI: 10.1007/s10334-021-00996-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 12/17/2021] [Accepted: 12/23/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVE Clinical application of chemical exchange saturation transfer (CEST) can be performed with investigation of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects. Here, we investigated APT- and NOE-weighted imaging based on advanced CEST metrics to map tumor heterogeneity of non-enhancing glioma at 3 T. MATERIALS AND METHODS APT- and NOE-weighted maps based on Lorentzian difference (LD) and inverse magnetization transfer ratio (MTRREX) were acquired with a 3D snapshot CEST acquisition at 3 T. Saturation power was investigated first by varying B1 (0.5-2 µT) in 5 healthy volunteers then by applying B1 of 0.5 and 1.5 µT in 10 patients with non-enhancing glioma. Tissue contrast (TC) and contrast-to-noise ratios (CNR) were calculated between glioma and normal appearing white matter (NAWM) and grey matter, in APT- and NOE-weighted images. Volume percentages of the tumor showing hypo/hyperintensity (VPhypo/hyper,CEST) in APT/NOE-weighted images were calculated for each patient. RESULTS LD APT resulting from using a B1 of 1.5 µT was found to provide significant positive TCtumor,NAWM and MTRREX NOE (B1 of 1.5 µT) provided significant negative TCtumor,NAWM in tissue differentiation. MTRREX-based NOE imaging under 1.5 µT provided significantly larger VPhypo,CEST than MTRREX APT under 1.5 µT. CONCLUSION This work showed that with a rapid CEST acquisition using a B1 saturation power of 1.5 µT and covering the whole tumor, analysis of both LD APT and MTRREX NOE allows for observing tumor heterogeneity, which will be beneficial in future studies using CEST-MRI to improve imaging diagnostics for non-enhancing glioma.
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Affiliation(s)
- Yulun Wu
- Department of Radiology and Nuclear Medicine, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
| | - Tobias C Wood
- Centre for Neuroimaging Science, King's College London, London, UK
| | - Fatemeh Arzanforoosh
- Department of Radiology and Nuclear Medicine, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Juan A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Gareth J Barker
- Centre for Neuroimaging Science, King's College London, London, UK
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Esther A H Warnert
- Department of Radiology and Nuclear Medicine, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
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Zhao Y, Chen Y, Chen Y, Zhang L, Wang X, He X. A Fully Convolutional Network (FCN) based Automated Ischemic Stroke Segment Method using Chemical Exchange Saturation Transfer Imaging. Med Phys 2022; 49:1635-1647. [PMID: 35083756 DOI: 10.1002/mp.15483] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 12/26/2021] [Accepted: 01/02/2022] [Indexed: 11/11/2022] Open
Abstract
BACKGROUND Chemical exchange saturation transfer (CEST) MRI is a promising imaging modality in ischemic stroke detection for its sensitivity in sensing post-ischemic pH alteration. However, the accurate segmentation of pH-altered regions remains difficult due to the complicated sources in water signal changes of CEST MRI. Meanwhile, manual localization and quantification of stroke lesions are laborious and time-consuming, which cannot meet the urgent need for timely therapeutic interventions. PURPOSE The goal of this study was to develop an automatic lesion segmentation approach of ischemic region based on CEST MR images. A novel segmentation framework based on fully convolutional neural network was investigated for our task. METHODS Z-spectra from 10 rats were manually labeled as ground truth and split into two datasets, where the training dataset including 3 rats was used to generate a segmentation model, and the remaining rats were used as test datasets to evaluate the model's performance. Then a 1-D fully convolutional neural network equipped with bottleneck structures was set up, and a Grad-CAM approach was used to produce a coarse localization map, which can reflect the relevancy to the 'ischemia' class of each pixel. RESULTS As compared with the ground truth, the proposed network model achieved satisfying segmentation results with high values of evaluation metrics including specificity (SPE), sensitivity (SEN), accuracy (ACC), and Dice similarity coefficient (DSC), especially in some intractable situations where conventional MRI modalities and CEST quantitative method failed to distinguish between ischemic and normal tissues, and the model with augmentation was robust to input perturbations. The Grad-CAM maps performed clear tissue change distributions and interpreted the segmentations, and showed a strong correlation with the quantitative method, gave extended thinking to the function of networks. CONCLUSIONS The proposed method can segment ischemia region from CEST images, with the Grad-CAM maps give access to interpretative information about the segmentations, which demonstrates great potential in clinical routines. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Yingcheng Zhao
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, Shaanxi, 710069, China
| | - Yibing Chen
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, Shaanxi, 710069, China
| | - Yanrong Chen
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, Shaanxi, 710069, China
| | - Lihong Zhang
- College of Computer Science and Technology (Software College), Henan Polytechnic University, Jiaozuo, Henan, 454003, China
| | - Xiaoli Wang
- Department of Medical Imaging, Weifang Medical University, Weifang, 261053, China
| | - Xiaowei He
- Xi'an Key Lab of Radiomics and Intelligent Perception, School of Information Sciences and Technology, Northwest University, Xi'an, Shaanxi, 710069, China
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Jia X, Wang W, Liang J, Ma X, Chen W, Wu D, Lai C, Zhang Y. Risk stratification of abdominal tumors in children with amide proton transfer imaging. Eur Radiol 2022; 32:2158-2167. [PMID: 35031842 DOI: 10.1007/s00330-021-08376-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 09/01/2021] [Accepted: 09/30/2021] [Indexed: 11/25/2022]
Abstract
OBJECTIVES To evaluate the potential of molecular amide proton transfer (APT) MRI for predicting the risk group of abdominal tumors in children, and compare it with quantitative T1 and T2 mapping. METHODS This prospective study enrolled 133 untreated pediatric patients with suspected abdominal tumors from February 2019 to September 2020. APT-weighted (APTw) imaging and quantitative relaxation time mapping sequences were executed for each subject. The region of interest (ROI) was generated with automatic artifact detection and ROI-shrinking algorithms, within which the APTw, T1, and T2 indices were calculated and compared between different risk groups. The prediction performance of different imaging parameters was assessed with the receiver operating characteristics (ROC) analysis and Student's t-test. RESULTS Fifty-seven patients were included in the final analysis, including 24 neuroblastomas (NB), 18 Wilms' tumors (WT), and 15 hepatoblastomas (HB). The APTw signal was significantly (p < .001) higher in patients with high-risk NB than those with low-risk NB, while the difference between patients with low-risk and high-risk WT (p = .69) or HB (p = .35) was not statistically significant. The associated areas under the curve (AUC) for APT to differentiate low-risk and high-risk NB, WT, and HB were 0.93, 0.58, and 0.71, respectively. The quantitative T1 and T2 values generated AUCs of 0.61-0.70 for the risk stratification of abdominal tumors. CONCLUSIONS APT MRI is a potential imaging biomarker for stratifying the risk group of pediatric neuroblastoma in the abdomen preoperatively and provides added value to structural MRI. KEY POINTS • Amide proton transfer (APT) imaging showed significantly (p < .001) higher values in pediatric patients with high-risk neuroblastoma than those with low-risk neuroblastoma, but did not demonstrate a significant difference in patients with Wilms' tumor (p = .69) or hepatoblastoma (p = .35). • The associated areas under the curve (AUC) for APT to differentiate low-risk and high-risk neuroblastoma, Wilms' tumor, and hepatoblastoma were 0.93, 0.58, and 0.71, respectively. • The quantitative T1 and T2 indices generated AUCs of 0.61-0.70 for dichotomizing the risk group of abdominal tumors.
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Affiliation(s)
- Xuan Jia
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Wenqi Wang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Jiawei Liang
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xiaohui Ma
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | | | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Can Lai
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China.
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Han P, Cheema K, Lee HL, Zhou Z, Cao T, Ma S, Wang N, Han H, Christodoulou AG, Li D. Whole-brain steady-state CEST at 3 T using MR Multitasking. Magn Reson Med 2021; 87:2363-2371. [PMID: 34843114 DOI: 10.1002/mrm.29109] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 11/11/2021] [Accepted: 11/12/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE To perform fast 3D steady-state CEST (ss-CEST) imaging using MR Multitasking. METHODS A continuous acquisition sequence with repetitive ss-CEST modules was developed. Each ss-CEST module contains a single-lobe Gaussian saturation pulse, followed by a spoiler gradient and eight FLASH readouts (one "training line" + seven "imaging lines"). Three-dimensional Cartesian encoding was used for k-space acquisition. Reconstructed CEST images were quantified with four-pool Lorentzian fitting. RESULTS Steady-state CEST with whole-brain coverage was performed in 5.6 s per saturation frequency offset at the spatial resolution of 1.7 × 1.7 × 3.0 mm3 . The total scan time was 5.5 min for 55 different frequency offsets. Quantitative CEST maps from multipool fitting showed consistent image quality across the volume. CONCLUSION Three-dimensional ss-CEST with whole-brain coverage can be done at 3 T within 5.5 min using MR Multitasking.
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Affiliation(s)
- Pei Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Karandeep Cheema
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Hsu-Lei Lee
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Zhengwei Zhou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Tianle Cao
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Sen Ma
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Nan Wang
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA
| | - Anthony G Christodoulou
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
| | - Debiao Li
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, California, USA.,Department of Bioengineering, University of California, Los Angeles, California, USA
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Gao T, Zou C, Li Y, Jiang Z, Tang X, Song X. A Brief History and Future Prospects of CEST MRI in Clinical Non-Brain Tumor Imaging. Int J Mol Sci 2021; 22:11559. [PMID: 34768990 PMCID: PMC8584005 DOI: 10.3390/ijms222111559] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2021] [Revised: 10/12/2021] [Accepted: 10/23/2021] [Indexed: 02/08/2023] Open
Abstract
Chemical exchange saturation transfer (CEST) MRI is a promising molecular imaging tool which allows the specific detection of metabolites that contain exchangeable amide, amine, and hydroxyl protons. Decades of development have progressed CEST imaging from an initial concept to a clinical imaging tool that is used to assess tumor metabolism. The first translation efforts involved brain imaging, but this has now progressed to imaging other body tissues. In this review, we summarize studies using CEST MRI to image a range of tumor types, including breast cancer, pelvic tumors, digestive tumors, and lung cancer. Approximately two thirds of the published studies involved breast or pelvic tumors which are sites that are less affected by body motion. Most studies conclude that CEST shows good potential for the differentiation of malignant from benign lesions with a number of reports now extending to compare different histological classifications along with the effects of anti-cancer treatments. Despite CEST being a unique 'label-free' approach with a higher sensitivity than MR spectroscopy, there are still some obstacles for implementing its clinical use. Future research is now focused on overcoming these challenges. Vigorous ongoing development and further clinical trials are expected to see CEST technology become more widely implemented as a mainstream imaging technology.
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Affiliation(s)
- Tianxin Gao
- School of Life Science, Institute of Engineering Medicine, Beijing Institute of Technology, Beijing 100081, China; (T.G.); (C.Z.); (Z.J.)
| | - Chuyue Zou
- School of Life Science, Institute of Engineering Medicine, Beijing Institute of Technology, Beijing 100081, China; (T.G.); (C.Z.); (Z.J.)
| | - Yifan Li
- Center for Biomedical Imaging Research, School of Medicine, Tsinghua University, Beijing 100084, China;
| | - Zhenqi Jiang
- School of Life Science, Institute of Engineering Medicine, Beijing Institute of Technology, Beijing 100081, China; (T.G.); (C.Z.); (Z.J.)
| | - Xiaoying Tang
- School of Life Science, Institute of Engineering Medicine, Beijing Institute of Technology, Beijing 100081, China; (T.G.); (C.Z.); (Z.J.)
| | - Xiaolei Song
- Center for Biomedical Imaging Research, School of Medicine, Tsinghua University, Beijing 100084, China;
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Kim H, Krishnamurthy LC, Sun PZ. Demonstration of fast multi-slice quasi-steady-state chemical exchange saturation transfer (QUASS CEST) human brain imaging at 3T. Magn Reson Med 2021; 87:810-819. [PMID: 34590726 DOI: 10.1002/mrm.29028] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2021] [Revised: 08/01/2021] [Accepted: 09/09/2021] [Indexed: 12/21/2022]
Abstract
PURPOSE To combine multi-slice chemical exchange saturation transfer (CEST) imaging with quasi-steady-state (QUASS) processing and demonstrate the feasibility of fast QUASS CEST MRI at 3T. METHODS Fast multi-slice echo planar imaging (EPI) CEST imaging was developed with concatenated slice acquisition after single radiofrequency irradiation. The multi-slice CEST signal evolution was described by the spin-lock relaxation during saturation duration (Ts ) and longitudinal relaxation during the relaxation delay time (Td ) and post-label delay (PLD), from which the QUASS CEST was generalized to fast multi-slice acquisition. In addition, numerical simulations, phantom, and normal human subjects scans were performed to compare the conventional apparent and QUASS CEST measurements with different Ts , Td, and PLD. RESULTS The numerical simulation showed that the apparent CEST effect strongly depends on Ts , Td , and PLD, while the QUASS CEST algorithm minimizes such dependences. In the L-carnosine gel phantom, the proposed QUASS CEST effects (2.68 ± 0.12% [mean ± SD]) were higher than the apparent CEST effects (1.85 ± 0.26%, p < 5e-4). In the human brain imaging, Bland-Altman analysis bias of the proposed QUASS CEST effects was much smaller than the PLD-corrected apparent CEST effects (0.03% vs. -0.54%), indicating the proposed fast multi-slice CEST imaging is robust and accurate. CONCLUSIONS The QUASS processing enables fast multi-slice CEST imaging with minimal loss in the measurement of the CEST effect.
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Affiliation(s)
- Hahnsung Kim
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, Georgia, USA.,Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Lisa C Krishnamurthy
- Center for Visual and Neurocognitive Rehabilitation, Atlanta VA, Decatur, Georgia, USA.,Department of Physics & Astronomy, Georgia State University, Atlanta, Georgia, USA
| | - Phillip Zhe Sun
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, Georgia, USA.,Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA
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Sun PZ. Quasi-steady-state chemical exchange saturation transfer (QUASS CEST) MRI analysis enables T 1 normalized CEST quantification - Insight into T 1 contribution to CEST measurement. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2021; 329:107022. [PMID: 34144360 PMCID: PMC8316384 DOI: 10.1016/j.jmr.2021.107022] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 05/29/2021] [Accepted: 06/07/2021] [Indexed: 05/26/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI depends not only on the labile proton concentration and exchange rate but also on relaxation rates, particularly T1 relaxation time. However, T1 normalization has shown to be not straightforward under non-steady-state conditions and in the presence of radiofrequency spillover effect. Our study aimed to test if the combined use of the new quasi-steady-state (QUASS) analysis and inverse CEST calculation facilitates T1 normalization for improved CEST quantification. The CEST signal was simulated with Bloch-McConnell equations, and the apparent CEST, QUASS CEST, and the inverse CEST effects were calculated. T1-normalized CEST effects were tested for their specificity to the underlying CEST system (i.e., labile proton ratio and exchange rate). CEST experiments were performed from a 9-vial phantom of independently varied concentrations of creatine (20, 40, and 60 mM) and manganese chloride (20, 30, and 40 µM) under a range of RF saturation amplitudes (0.5-4 µT) and durations (1-4 s). The simulation showed that while T1 normalization of the apparent CEST effect was subject to noticeable T1 contamination, the T1-normalized inverse QUASS CEST effect had little T1 dependence. The experimental data were analyzed using a multiple linear regression model, showing that T1-normalized inverse QUASS analysis significantly depended on creatine concentration and saturation power (P < 0.05), not on manganese chloride concentration and saturation duration, advantageous over other CEST indices. The QUASS CEST algorithm reconstructs the steady-state CEST effect, enabling T1-normalized inverse CEST effect calculation for improved quantification of the underlying CEST system.
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Affiliation(s)
- Phillip Zhe Sun
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States; Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta GA, United States.
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Schüre JR, Pilatus U, Deichmann R, Hattingen E, Shrestha M. A fast and novel method for amide proton transfer-chemical exchange saturation transfer multislice imaging. NMR IN BIOMEDICINE 2021; 34:e4524. [PMID: 33942941 DOI: 10.1002/nbm.4524] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 03/23/2021] [Accepted: 03/24/2021] [Indexed: 06/12/2023]
Abstract
Amide proton transfer-chemical exchange saturation transfer (APT-CEST) imaging provides important information for the diagnosis and monitoring of tumors. For such analysis, complete coverage of the brain is advantageous, especially when registration is performed with other magnetic resonance (MR) modalities, such as MR spectroscopy (MRS). However, the acquisition of Z-spectra across several slices via multislice imaging may be time-consuming. Therefore, in this paper, we present a new approach for fast multislice imaging, allowing us to acquire 16 slices per frequency offset within 8 s. The proposed fast CEST-EPI sequence employs a presaturation module, which drives the magnetization into the steady-state equilibrium for the first frequency offset. A second module, consisting of a single CEST pulse (for maintaining the steady-state) followed by an EPI acquisition, passes through a loop to acquire multiple slices and adjacent frequency offsets. Thus, the whole Z-spectrum can be recorded much faster than the conventional saturation scheme, which employs a presaturation for each single frequency offset. The validation of the CEST sequence parameters was performed by using the conventional saturation scheme. Subsequently, the proposed and a modified version of the conventional CEST sequence were compared in vitro on a phantom with different T1 times and in vivo on a brain tumor patient. No significant differences between both sequences could be found in vitro. The in vivo data yielded almost identical MTRasym contrasts for the white and gray matter as well as for tumor tissue. Our results show that the proposed fast CEST-EPI sequence allows for rapid data acquisition and provides similar CEST contrasts as the modified conventional scheme while reducing the scanning time by approximately 50%.
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Affiliation(s)
- Jan-Rüdiger Schüre
- Department of Neuroradiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Ulrich Pilatus
- Department of Neuroradiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Ralf Deichmann
- Brain Imaging Center (BIC), Goethe University Frankfurt, Frankfurt am Main, Germany
| | - Elke Hattingen
- Department of Neuroradiology, University Hospital Frankfurt, Frankfurt am Main, Germany
| | - Manoj Shrestha
- Brain Imaging Center (BIC), Goethe University Frankfurt, Frankfurt am Main, Germany
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Zhang H, Yong X, Ma X, Zhao J, Shen Z, Chen X, Tian F, Chen W, Wu D, Zhang Y. Differentiation of low- and high-grade pediatric gliomas with amide proton transfer imaging: added value beyond quantitative relaxation times. Eur Radiol 2021; 31:9110-9119. [PMID: 34047848 DOI: 10.1007/s00330-021-08039-w] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 04/06/2021] [Accepted: 05/03/2021] [Indexed: 01/11/2023]
Abstract
OBJECTIVES To evaluate whether amide proton transfer (APT) MRI can be used to characterize gliomas in pediatric patients and whether it provides added value beyond relaxation times. METHODS In this prospective study, APT imaging and relaxation time mapping were performed in 203 pediatric patients suspected of gliomas from February 2018 to December 2019. The region of interest (ROI) in the tumor was automatically generated with artifact detection and ROI-shrinking algorithms. Several APT-related metrics (CESTR, CESTRnr, MTRRex, AREX, and APT#) and quantitative T1 and T2 were compared between low-grade and high-grade gliomas using the student's t-test or Mann-Whitney U-test. The performance of these parameters was assessed using the receiver operating characteristic (ROC) analysis. A stepwise multivariate logistic regression model was used to combine the imaging parameters. RESULTS Forty-eight patients (mean age: 6 ± 4 years; 23 males and 25 females) were included in the final analysis. All the APT-related metrics except APT# had significantly (p < 0.05) higher values in the high-grade group than the low-grade group. Under different ROI-shrinking cutoffs, the quantitative T1 (p = 0.045-0.200) and T2 (p = 0.037-0.171) values of high-grade gliomas were typically lower than those of low-grade ones. The stepwise multivariate logistic regression revealed that CESTRnr and APT# were combined significant predictors of glioma grades (p < 0.05), with an area under the ROC curve (AUC) of 0.86 substantially larger than those of T1 (AUC = 0.69) and T2 (AUC = 0.68). CONCLUSIONS APT imaging can be used to differentiate high-grade and low-grade gliomas in pediatric patients and provide added value beyond quantitative relaxation times. KEY POINTS • Amide proton transfer (APT) MRI showed significantly (p < 0.05) higher values in pediatric patients with high-grade gliomas than those with low-grade ones. • The area under the curve was 0.86 for APT MRI to differentiate low-grade and high-grade gliomas in pediatric patients, which was substantially higher than that for quantitative T1 (0.69) and T2 (0.68). • APT MRI demonstrated added value beyond quantitative T1 and T2 mapping in characterizing pediatric gliomas.
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Affiliation(s)
- Hongxi Zhang
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xingwang Yong
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiaohui Ma
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Jianjiang Zhao
- Kangqiao Street Community Health Service Center, Gongshu District, Hangzhou, Zhejiang, China
| | - Zhipeng Shen
- Department of Neurosurgery, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Xinchun Chen
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | - Fengyu Tian
- Department of Radiology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
| | | | - Dan Wu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China. .,Cancer Center, Zhejiang University, Hangzhou, Zhejiang, China.
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Sui R, Chen L, Li Y, Huang J, Chan KWY, Xu X, van Zijl PCM, Xu J. Whole-brain amide CEST imaging at 3T with a steady-state radial MRI acquisition. Magn Reson Med 2021; 86:893-906. [PMID: 33772859 DOI: 10.1002/mrm.28770] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 02/15/2021] [Accepted: 02/18/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a steady-state saturation with radial readout chemical exchange saturation transfer (starCEST) for acquiring CEST images at 3 Tesla (T). The polynomial Lorentzian line-shape fitting approach was further developed for extracting amideCEST intensities at this field. METHOD StarCEST MRI using periodically rotated overlapping parallel lines with enhanced reconstruction-based spatial sampling was implemented to acquire Z-spectra that are robust to brain motion. Multi-linear singular value decomposition postprocessing was applied to enhance the CEST SNR. The egg white phantom studies were performed at 3T to reveal the contributions to the 3.5 ppm CEST signal. Based on the phantom validation, the amideCEST peak was quantified using the polynomial Lorentzian line-shape fitting, which exploits the inverse relationship between Z-spectral intensity and the longitudinal relaxation rate in the rotating frame. The 3D turbo spin echo CEST was also performed to compare with the starCEST method. RESULTS The amideCEST peak showed a negligible peak B1 dependence between 1.2 µT and 2.4 µT. The amideCEST images acquired with starCEST showed much improved image quality, SNR, and motion robustness compared to the conventional 3D turbo spin echo CEST method with the same scan time. The amideCEST contrast extracted by the polynomial Lorentzian line-shape fitting method trended toward a stronger gray matter signal (1.32% ± 0.30%) than white matter (0.92% ± 0.08%; P = .02, n = 5). When calculating the magnetization transfer contrast and T1 -corrected rotating frame relaxation rate maps, amideCEST again was not significantly different for white matter and gray matter. CONCLUSION Rapid multi-slice amideCEST mapping can be achieved by the starCEST method (< 5 min) at 3T by combing with the polynomial Lorentzian line-shape fitting method.
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Affiliation(s)
- Ran Sui
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Lin Chen
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, People's Republic of China
| | - Yuguo Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, People's Republic of China
| | - Kannie W Y Chan
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, People's Republic of China
| | - Xiang Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
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Kim H, Wu Y, Villano D, Longo DL, McMahon MT, Sun PZ. Analysis Protocol for the Quantification of Renal pH Using Chemical Exchange Saturation Transfer (CEST) MRI. Methods Mol Biol 2021; 2216:667-688. [PMID: 33476030 DOI: 10.1007/978-1-0716-0978-1_40] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2023]
Abstract
The kidney plays a major role in maintaining body pH homeostasis. Renal pH, in particular, changes immediately following injuries such as intoxication and ischemia, making pH an early biomarker for kidney injury before the symptom onset and complementary to well-established laboratory tests. Because of this, it is imperative to develop minimally invasive renal pH imaging exams and test pH as a new diagnostic biomarker in animal models of kidney injury before clinical translation. Briefly, iodinated contrast agents approved by the US Food and Drug Administration (FDA) for computed tomography (CT) have demonstrated promise as novel chemical exchange saturation transfer (CEST) MRI agents for pH-sensitive imaging. The generalized ratiometric iopamidol CEST MRI analysis enables concentration-independent pH measurement, which simplifies in vivo renal pH mapping. This chapter describes quantitative CEST MRI analysis for preclinical renal pH mapping, and their application in rodents, including normal conditions and acute kidney injury.This publication is based upon work from the COST Action PARENCHIMA, a community-driven network funded by the European Cooperation in Science and Technology (COST) program of the European Union, which aims to improve the reproducibility and standardization of renal MRI biomarkers. This analysis protocol chapter is complemented by two separate chapters describing the basic concepts and experimental procedure.
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Affiliation(s)
- Hahnsung Kim
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA.,Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Yin Wu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.,Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, China
| | - Daisy Villano
- Department of Molecular Biotechnology and Health Sciences, University of Torino, Torino, Italy
| | - Dario Livio Longo
- Institute of Biostructures and Bioimaging (IBB), Italian National Research Council (CNR), Torino, Italy
| | - Michael T McMahon
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD, USA.,The Russell H. Morgan Department of Radiology and Radiological Science, Division of MR Research, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Phillip Zhe Sun
- Yerkes Imaging Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, USA. .,Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA, USA. .,Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA.
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Kim B, Schär M, Park H, Heo HY. A deep learning approach for magnetization transfer contrast MR fingerprinting and chemical exchange saturation transfer imaging. Neuroimage 2020; 221:117165. [DOI: 10.1016/j.neuroimage.2020.117165] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2020] [Revised: 07/01/2020] [Accepted: 07/09/2020] [Indexed: 01/05/2023] Open
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Kang B, Kim B, Schär M, Park H, Heo HY. Unsupervised learning for magnetization transfer contrast MR fingerprinting: Application to CEST and nuclear Overhauser enhancement imaging. Magn Reson Med 2020; 85:2040-2054. [PMID: 33128483 DOI: 10.1002/mrm.28573] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 10/06/2020] [Accepted: 10/06/2020] [Indexed: 12/13/2022]
Abstract
PURPOSE To develop a fast, quantitative 3D magnetization transfer contrast (MTC) framework based on an unsupervised learning scheme, which will provide baseline reference signals for CEST and nuclear Overhauser enhancement imaging. METHODS Pseudo-randomized RF saturation parameters and relaxation delay times were applied in an MR fingerprinting framework to generate transient-state signal evolutions for different MTC parameters. Prospectively compressed sensing-accelerated (four-fold) MR fingerprinting images were acquired from 6 healthy volunteers at 3 T. A convolutional neural network framework in an unsupervised fashion was designed to solve an inverse problem of a two-pool MTC Bloch equation, and was compared with a conventional Bloch equation-based fitting approach. The MTC images synthesized by the convolutional neural network architecture were used for amide proton transfer and nuclear Overhauser enhancement imaging as a reference baseline image. RESULTS The fully unsupervised learning scheme incorporated with the two-pool exchange model learned a set of unique features that can describe the MTC-MR fingerprinting input, and allowed only small amounts of unlabeled data for training. The MTC parameter values estimated by the unsupervised learning method were in excellent agreement with values estimated by the conventional Bloch fitting approach, but dramatically reduced computation time by ~1000-fold. CONCLUSION Given the considerable time efficiency compared to conventional Bloch fitting, unsupervised learning-based MTC-MR fingerprinting could be a powerful tool for quantitative MTC and CEST/nuclear Overhauser enhancement imaging.
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Affiliation(s)
- Beomgu Kang
- Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Byungjai Kim
- Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea.,Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Michael Schär
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| | - HyunWook Park
- Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea
| | - Hye-Young Heo
- Divison of MR Research, Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA.,F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, Maryland, USA
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Demetriou E, Kujawa A, Golay X. Pulse sequences for measuring exchange rates between proton species: From unlocalised NMR spectroscopy to chemical exchange saturation transfer imaging. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2020; 120-121:25-71. [PMID: 33198968 DOI: 10.1016/j.pnmrs.2020.06.001] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 06/27/2020] [Accepted: 06/30/2020] [Indexed: 06/11/2023]
Abstract
Within the field of NMR spectroscopy, the study of chemical exchange processes through saturation transfer techniques has a long history. In the context of MRI, chemical exchange techniques have been adapted to increase the sensitivity of imaging to small fractions of exchangeable protons, including the labile protons of amines, amides and hydroxyls. The MR contrast is generated by frequency-selective irradiation of the labile protons, which results in a reduction of the water signal associated with transfer of the labile protons' saturated magnetization to the protons of the surrounding free water. The signal intensity depends on the rate of chemical exchange and the concentration of labile protons as well as on the properties of the irradiation field. This methodology is referred to as CEST (chemical exchange saturation transfer) imaging. Applications of CEST include imaging of molecules with short transverse relaxation times and mapping of physiological parameters such as pH, temperature, buffer concentration and chemical composition due to the dependency of this chemical exchange effect on all these parameters. This article aims to describe these effects both theoretically and experimentally. In depth analysis and mathematical modelling are provided for all pulse sequences designed to date to measure the chemical exchange rate. Importantly, it has become clear that the background signal from semi-solid protons and the presence of the Nuclear Overhauser Effect (NOE), either through direct dipole-dipole mechanisms or through exchange-relayed signals, complicates the analysis of CEST effects. Therefore, advanced methods to suppress these confounding factors have been developed, and these are also reviewed. Finally, the experimental work conducted both in vitro and in vivo is discussed and the progress of CEST imaging towards clinical practice is presented.
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Affiliation(s)
- Eleni Demetriou
- Brain Repair & Rehabilitation, Institute of Neurology, University College London, United Kingdom.
| | - Aaron Kujawa
- Brain Repair & Rehabilitation, Institute of Neurology, University College London, United Kingdom.
| | - Xavier Golay
- Brain Repair & Rehabilitation, Institute of Neurology, University College London, United Kingdom.
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Lee H, Choi SH, Sohn CH, Kim SG, Lee J, Park J. Rapid three-dimensional steady-state chemical exchange saturation transfer magnetic resonance imaging. Magn Reson Med 2020; 85:1209-1221. [PMID: 32851659 DOI: 10.1002/mrm.28487] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2020] [Revised: 07/11/2020] [Accepted: 07/30/2020] [Indexed: 02/05/2023]
Abstract
PURPOSE To make clinically feasible whole-brain chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) by enhancing imaging efficiency. METHODS A novel, whole-brain three-dimensional (3D) steady-state CEST MRI method was introduced by utilizing a time-efficient, fat-suppressed excitation followed by rapid, segmented 3D echo-planar-imaging with incoherent undersampling in k-ω space. Missing signals and CEST-specific spectral images were then jointly estimated directly from incomplete measurements using model-based reconstruction and robust spectral analysis. In vivo studies were performed at 3T both retrospectively (using a fully sampled reference) and prospectively to validate the effectiveness of the proposed method in patients with brain cancer. RESULTS In retrospective studies, the proposed method exhibits superior accuracies to existing methods in estimating images, z-spectra, and APTw relative to the reference. In prospective patient studies, compared with existing methods, the proposed method is statistically significantly different in contrast-to-noise ratio of the APTw contrast between tumor and normal appearing white matter (NAWM) and amide proton transfer weighted contrast (p < 0.05) while not being significantly different in signal-to-noise ratio in an NAWM region. CONCLUSIONS We successfully demonstrated that it is feasible to perform whole-brain CEST MRI roughly within 4 minutes for patients with brain cancer. It is expected that the proposed method widens clinical utilities of CEST MRI.
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Affiliation(s)
- Hoonjae Lee
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.,Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Seung Hong Choi
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Chul-Ho Sohn
- Department of Radiology, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Seong-Gi Kim
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.,Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Joonyeol Lee
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.,Center for Neuroscience Imaging Research, Institute for Basic Science, Suwon, Republic of Korea
| | - Jaeseok Park
- Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea.,Biomedical Institute for Convergence, Sungkyunkwan University, Suwon, Republic of Korea
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Huang J, Han X, Chen L, Xu X, Xu J, Chan KWY. Relayed nuclear Overhauser enhancement imaging with magnetization transfer contrast suppression at 3 T. Magn Reson Med 2020; 85:254-267. [PMID: 32738080 DOI: 10.1002/mrm.28433] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Revised: 06/10/2020] [Accepted: 06/24/2020] [Indexed: 12/11/2022]
Abstract
PURPOSE To develop a pulsed CEST magnetization-transfer method for rapidly acquiring relayed nuclear Overhauser enhancement (rNOE)-weighted images with magnetic transfer contrast (MTC) suppression at clinical field strength (3 T). METHODS Using a pulsed CEST magnetization-transfer method with low saturation powers (B1 ) and long mixing time (tmix ) to suppress contributions due to strong MTC from solid-like macromolecules, a low B1 also minimized direct water saturation. These MTC contributions were further reduced by subtracting the Z-spectral signals at two or three offsets by assuming that the residual MTC is a linear function between -3.5 ppm and -12.5 ppm. RESULTS Phantom studies of a lactic acid (Lac) solution mixed with cross-linked bovine serum albumin show that strong MTC interference has a significant impact on the optimum B1 for detecting rNOEs, due to lactate binding. The MTC could be effectively suppressed using a pulse train with a B1 of 0.8 μT, a pulse duration (tp ) of 40 ms, a tmix of 60 ms, and a pulse number (N) of 30, while rNOE signal was well maintained. As a proof of concept, we applied the method in mouse brain with injected hydrogel and a cell-hydrogel phantom. Results showed that rNOE-weighted images could provide good contrast between brain/cell and hydrogel. CONCLUSION The developed pulsed CEST magnetization-transfer method can achieve MTC suppression while preserving most of the rNOE signal at 3 T, which indicates the potential for translation of this technique to clinical applications related to mobile proteins/lipids change.
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Affiliation(s)
- Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Xiongqi Han
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China
| | - Lin Chen
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Xiang Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kannie W Y Chan
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, China.,Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,City University of Hong Kong Shenzhen Research Institute, Shenzhen, China
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Guo C, Wu J, Rosenberg JT, Roussel T, Cai S, Cai C. Fast chemical exchange saturation transfer imaging based on PROPELLER acquisition and deep neural network reconstruction. Magn Reson Med 2020; 84:3192-3205. [PMID: 32602965 DOI: 10.1002/mrm.28376] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Revised: 05/21/2020] [Accepted: 05/23/2020] [Indexed: 12/14/2022]
Abstract
PURPOSE To develop a method for fast chemical exchange saturation transfer (CEST) imaging. METHODS The periodically rotated overlapping parallel lines enhanced reconstruction (PROPELLER) sampling scheme was introduced to shorten the acquisition time. Deep neural network was employed to reconstruct CEST contrast images. Numerical simulation and experiments on a creatine phantom, hen egg, and in vivo tumor rat brain were performed to test the feasibility of this method. RESULTS The results from numerical simulation and experiments show that there is no significant difference between reference images and CEST-PROPELLER reconstructed images under an acceleration factor of 8. CONCLUSION Although the deep neural network is trained entirely on synthesized data, it works well on reconstructing experimental data. The proof of concept study demonstrates that the combination of the PROPELLER sampling scheme and the deep neural network enables considerable acceleration of saturated image acquisition and may find applications in CEST MRI.
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Affiliation(s)
- Chenlu Guo
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Jian Wu
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Jens T Rosenberg
- The National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA
| | - Tangi Roussel
- The National High Magnetic Field Laboratory, Florida State University, Tallahassee, FL, USA
| | - Shuhui Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Congbo Cai
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
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Amide Proton Transfer-Weighted (APTw) Imaging of Intracranial Infection in Children: Initial Experience and Comparison with Gadolinium-Enhanced T1-Weighted Imaging. BIOMED RESEARCH INTERNATIONAL 2020; 2020:6418343. [PMID: 32509865 PMCID: PMC7251435 DOI: 10.1155/2020/6418343] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2019] [Revised: 03/21/2020] [Accepted: 04/25/2020] [Indexed: 12/05/2022]
Abstract
Purpose To evaluate the performance of amide proton transfer-weighted (APTw) imaging against the reference standard of gadolinium-enhanced T1-weighted imaging (Gd-T1w) in children with intracranial infection. Materials and Methods Twenty-eight pediatric patients (15 males and 13 females; age range 1-163 months) with intracranial infection were recruited in this study. 2D APTw imaging and conventional MR sequences were conducted using a 3 T MRI scanner. Kappa (κ) statistics and the McNemar test were performed to determine whether the hyperintensity on APTw was related to the enhancement on Gd-T1w. The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of APTw imaging to predict lesion enhancement were calculated. Result In twelve patients with brain abscesses, the enhancing rim of the abscesses on the Gd-T1w images was consistently hyperintense on the APTw images. In eight patients with viral encephalitis, three showed slight spotted gadolinium enhancement, while the APTw image also showed a slight spotted high signal. Five of these patients showed no enhancement on Gd-T1w and isointensity on the APTw image. In eleven patients with meningitis, increased APTw signal intensities were clearly visible in gadolinium-enhancing meninges. Sixty infectious lesions (71%) showed enhancement on Gd-T1w images. The sensitivity and specificity of APTw were 93.3% (56/60) and 91.7% (22/24). APTw demonstrated excellent agreement (κ = 0.83) with Gd-T1w, with no significant difference (P = 0.69) in detection of infectious lesions. Conclusions These initial data show that APTw MRI is a noninvasive technique for the detection and characterization of intracranial infectious lesions. APTw MRI enabled similar detection of infectious lesions to Gd-T1w and may provide an injection-free means of evaluation of intracranial infection.
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Zhang Z, Zhang C, Yao J, Gao F, Gong T, Jiang S, Chen W, Zhou J, Wang G. Amide proton transfer-weighted magnetic resonance imaging of human brain aging at 3 Tesla. Quant Imaging Med Surg 2020; 10:727-742. [PMID: 32269932 DOI: 10.21037/qims.2020.02.22] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Background Amide proton transfer-weighted (APTw) imaging has been revealed to hold great potential in the diagnosis of several brain diseases. The purpose of this proof-of-concept study was to evaluate the feasibility and value of APTw magnetic resonance imaging (MRI) in characterizing normal brain aging. Methods A total of 106 healthy subjects were recruited and scanned at 3.0 Tesla, with APTw and conventional magnetization transfer (MT) sequences. Quantitative image analyses were performed in 12 regions of interest (ROIs) for each subject. The APTw or MT ratio (MTR) signal differences among five age groups (young, mature, middle-aged, young-old, and middle-old) were assessed using the one-way analysis of variance, with the Benjamini-Hochberg correction for multiple comparisons. The relationship between APTw and MTR signals and the age dependencies of APTw and MTR signals were assessed using the Pearson correlation and non-linear regression. Results There were no significant differences between the APTw or MTR values for males and females in any of the 12 ROIs analyzed. Among the five age groups, there were significant differences in the three white matter regions in the temporal, occipital, and frontal lobes. Overall, the mean APTw values in the older group were higher than those in the younger group. Positive correlations were observed in relation to age in most brain regions, including four with significant positive correlations (r=0.2065-0.4182) and five with increasing trends. As a comparison, the mean MTR values did not appear to be significantly different among the five age groups. In addition, the mean APTw and MTR values revealed significant positive correlations in 10 ROIs (r=0.2214-0.7269) and a significant negative correlation in one ROI (entorhinal cortex, r=-0.2141). Conclusions Our early results show that the APTw signal can be used as a promising and complementary imaging biomarker with which normal brain aging can be evaluated at the molecular level.
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Affiliation(s)
- Zewen Zhang
- Department of MR, Shandong Medical Imaging Research Institute, Shandong University, Jinan 250021, China.,Division of MR Research, Department of Radiology, Johns Hopkins University, Maryland, USA
| | - Caiqing Zhang
- Department of Respiratory Medicine, Shandong Provincial Qianfoshan Hospital, Shandong University, Jinan 250014, China
| | - Jian Yao
- Department of MR, Shandong Medical Imaging Research Institute, Shandong University, Jinan 250021, China
| | - Fei Gao
- Department of MR, Shandong Medical Imaging Research Institute, Shandong University, Jinan 250021, China
| | - Tao Gong
- Department of MR, Shandong Medical Imaging Research Institute, Shandong University, Jinan 250021, China
| | - Shanshan Jiang
- Division of MR Research, Department of Radiology, Johns Hopkins University, Maryland, USA
| | - Weibo Chen
- Philips Healthcare, Shanghai 200072, China
| | - Jinyuan Zhou
- Division of MR Research, Department of Radiology, Johns Hopkins University, Maryland, USA
| | - Guangbin Wang
- Department of MR, Shandong Medical Imaging Research Institute, Shandong University, Jinan 250021, China
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