1
|
Zhou L, Pan W, Huang R, Wang T, Wei Z, Wang H, Zhang Y, Li Y. Amide Proton Transfer-Weighted MRI, Associations with Clinical Severity and Prognosis in Ischemic Strokes. J Magn Reson Imaging 2024. [PMID: 38426606 DOI: 10.1002/jmri.29333] [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: 01/11/2024] [Revised: 02/21/2024] [Accepted: 02/21/2024] [Indexed: 03/02/2024] Open
Abstract
BACKGROUND The National Institutes of Health Stroke Scale (NIHSS) and the modified Rankin scale (mRS) scores have important shortcomings. Amide proton transfer-weighted (APTw) imaging might offer more valuable information in ischemic strokes assessment. PURPOSE To utilize APTw, apparent diffusion coefficient (ADC), and computed tomography perfusion (CTP) for the assessment of clinical symptom severity and 90-day prognosis in patients diagnosed with ischemic stroke. STUDY TYPE Prospective. SUBJECTS 61 patients (mean age 63.2 ± 9.7 years; 46 males, 15 females) with ischemic strokes were included in the study. FIELD STRENGTH/SEQUENCE 3T/turbo spin echo (TSE) T1 -weighted imaging, T2 -weighted imaging, T2 -fluid attenuated inversion recovery (T2 -FLAIR), diffusion-weighted imaging (DWI), and single-shot TSE APTw imaging. ASSESSMENT APTw, ADC, and CTP were used to compare patient subgroups and construct a prognostic nomogram model. STATISTICAL TESTS Kolmogorov-Smirnov test, t-test, Mann-Whitney U test, chi-square test, Pearson correlation analysis, multivariate logistic regression analysis, decision curve analysis (DCA), receiver operating characteristic curves (ROCs). The significance threshold was set at P < 0.05. RESULTS Correlation analysis revealed that APTw and NIHSS exhibit the highest correlation (r = -0.634, 95% confidence interval [CI] -0.418 to -0.782), surpassing that of ADC and lesion size. Multivariable analysis revealed APTw (odds ratio [OR] 0.905, 95% CI 0.845-0.970), ADC (OR 0.745, 95% CI 0.609-0.911), and infarct core-cerebral blood volume (IC-CBV) (OR 0.547, 95% CI 0.310-0.964) as potential risk factors associated with a poor prognosis. The nomogram model demonstrated the highest predictive efficacy, with an area under the curve (AUC) of 0.960 (95% CI 0.911-0.988), exceeding that of APTw, ADC, and IC-CBV individually. DATA CONCLUSION The APTw technique holds potential value in categorizing and managing patients with ischemic stroke, offering guidance for the implementation of clinical treatment strategies. LEVEL OF EVIDENCE 1 TECHNICAL EFFICACY: Stage 2.
Collapse
Affiliation(s)
- Le Zhou
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou city, Jiangsu Province, China
| | - Wanqian Pan
- Department of Cardiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China
| | - Renjun Huang
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou city, Jiangsu Province, China
| | - Tianye Wang
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, China
| | - Zifan Wei
- Suzhou Medical College of Soochow University, Suzhou, China
| | - Hui Wang
- Department of Neurology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu Province, 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
| | - Yonggang Li
- Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou city, Jiangsu Province, China
- Institute of Medical Imaging, Soochow University, Suzhou city, Jiangsu Province, China
| |
Collapse
|
2
|
Xu J, Zu T, Hsu YC, Wang X, Chan KWY, Zhang Y. Accelerating CEST imaging using a model-based deep neural network with synthetic training data. Magn Reson Med 2024; 91:583-599. [PMID: 37867413 DOI: 10.1002/mrm.29889] [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: 05/24/2023] [Revised: 08/31/2023] [Accepted: 09/25/2023] [Indexed: 10/24/2023]
Abstract
PURPOSE To develop a model-based deep neural network for high-quality image reconstruction of undersampled multi-coil CEST data. THEORY AND METHODS Inspired by the variational network (VN), the CEST image reconstruction equation is unrolled into a deep neural network (CEST-VN) with a k-space data-sharing block that takes advantage of the inherent redundancy in adjacent CEST frames and 3D spatial-frequential convolution kernels that exploit correlations in the x-ω domain. Additionally, a new pipeline based on multiple-pool Bloch-McConnell simulations is devised to synthesize multi-coil CEST data from publicly available anatomical MRI data. The proposed network is trained on simulated data with a CEST-specific loss function that jointly measures the structural and CEST contrast. The performance of CEST-VN was evaluated on four healthy volunteers and five brain tumor patients using retrospectively or prospectively undersampled data with various acceleration factors, and then compared with other conventional and state-of-the-art reconstruction methods. RESULTS The proposed CEST-VN method generated high-quality CEST source images and amide proton transfer-weighted maps in healthy and brain tumor subjects, consistently outperforming GRAPPA, blind compressed sensing, and the original VN. With the acceleration factors increasing from 3 to 6, CEST-VN with the same hyperparameters yielded similar and accurate reconstruction without apparent loss of details or increase of artifacts. The ablation studies confirmed the effectiveness of the CEST-specific loss function and data-sharing block used. CONCLUSIONS The proposed CEST-VN method can offer high-quality CEST source images and amide proton transfer-weighted maps from highly undersampled multi-coil data by integrating the deep learning prior and multi-coil sensitivity encoding model.
Collapse
Affiliation(s)
- Jianping Xu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, People's Republic of China
| | - Tao Zu
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, People's Republic of China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, People's Republic of China
| | - Xiaoli Wang
- School of Medical Imaging, Weifang Medical University, Weifang, People's Republic of China
| | - Kannie W Y Chan
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, People's Republic of 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, People's Republic of China
| |
Collapse
|
3
|
Han M, Li Q, Yang T, Li J. Amide proton transfer imaging in rats after heatstroke. Neuroreport 2024; 35:37-41. [PMID: 37983618 DOI: 10.1097/wnr.0000000000001974] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
Metabolic acidosis is the most common acid-base change following heatstroke. This study aimed to evaluate the internal environment changes caused by heatstroke using amide proton transfer (APT) imaging. Nineteen male Sprague-Dawley rats were randomly divided into the control group (CTRL, n = 7) and the heatstroke group (HS, n = 12). All the rats underwent a 7.0-T MRI, which included T2-weighted imaging (T2WI) and APT imaging. Subsequently, the surviving HS group rats repeated the same magnetic resonance scanning after 25 days and were designated as the follow-up group (FU, n = 7). APT values were measured in the hippocampus, thalamus, and corpus callosum. The APT values of the three groups were statistically analyzed and found in the hippocampus (CTRL vs. HS, P = 0.011; CTRL vs. FU, P = 0.078; HS vs. FU, P = 0.484; η ² = 0.276), left thalamus (CTRL vs. HS, P = 0.004; CTRL vs. FU, P = 0.014; HS vs. FU, P = 0.822; η ² = 0.331), right thalamus (CTRL vs. HS, P = 0.003; CTRL vs. FU, P = 0.015; HS vs. FU P = 0.769; η ² = 0.336), and corpus callosum (CTRL vs. HS, P < 0.001; CTRL vs. FU, P = 0.005; HS vs. FU, P = 0.523; η ² = 0.437). APT imaging can be a viable and practical tool for diagnosing heatstroke and monitoring its progression.
Collapse
Affiliation(s)
- Mingxing Han
- Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai
| | - Qinglong Li
- Department of Radiology, Henan Provincial Hospital of Traditional Chinese Medicine (The Second Affiliated Hospital of Henan University of Traditional Chinese Medicine), Zhengzhou, People's Republic of China
| | - Ting Yang
- Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai
| | - Jun Li
- Department of Radiology, Yantai Affiliated Hospital of Binzhou Medical University, Yantai
| |
Collapse
|
4
|
Zeng Z, Dong Y, Zou L, Xu D, Luo X, Chu T, Wang J, Ren Q, Liu Q, Li X. GluCEST Imaging and Structural Alterations of the Bilateral Hippocampus in First-Episode and Early-Onset Major Depression Disorder. J Magn Reson Imaging 2023; 58:1431-1440. [PMID: 36808678 DOI: 10.1002/jmri.28651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 02/05/2023] [Accepted: 02/06/2023] [Indexed: 02/22/2023] Open
Abstract
BACKGROUND Glutamate dysregulation is one of the key pathogenic mechanisms of major depressive disorder (MDD), and glutamate chemical exchange saturation transfer (GluCEST) has been used for glutamate measurement in some brain diseases but rarely in depression. PURPOSE To investigate the GluCEST changes in hippocampus in MDD and the relationship between glutamate and hippocampal subregional volumes. STUDY TYPE Cross-sectional. SUBJECTS Thirty-two MDD patients (34% males; 22.03 ± 7.21 years) and 47 healthy controls (HCs) (43% males; 22.00 ± 3.28 years). FIELD STRENGTH/SEQUENCE 3.0 T; magnetization prepared rapid gradient echo (MPRAGE) for three-dimensional T1-weighted images, two-dimensional turbo spin echo GluCEST, and multivoxel chemical shift imaging (CSI) for proton magnetic resonance spectroscopy (1 H MRS). ASSESSMENT GluCEST data were quantified by magnetization transfer ratio asymmetry (MTRasym ) analysis and assessed by the relative concentration of 1 H MRS-measured glutamate. FreeSurfer was used for hippocampus segmentation. STATISTICAL TESTS The independent sample t test, Mann-Whitney U test, Spearman's correlation, and partial correlation analysis were used. P < 0.05 was considered statistically significant. RESULTS In the left hippocampus, GluCEST values were significantly decreased in MDD (2.00 ± 1.08 [MDD] vs. 2.62 ± 1.41 [HCs]) and showed a significantly positive correlation with Glx/Cr (r = 0.37). GluCEST values were significantly positively correlated with the volumes of CA1 (r = 0.40), subiculum (r = 0.40) in the left hippocampus and CA1 (r = 0.51), molecular_layer_HP (r = 0.50), GC-ML-DG (r = 0.42), CA3 (r = 0.44), CA4 (r = 0.44), hippocampus-amygdala-transition-area (r = 0.46), and the whole hippocampus (r = 0.47) in the right hippocampus. Hamilton Depression Rating Scale scores showed significantly negative correlations with the volumes of the left presubiculum (r = -0.40), left parasubiculum (r = -0.47), and right presubiculum (r = -0.41). DATA CONCLUSION GluCEST can be used to measure glutamate changes and help to understand the mechanism of hippocampal volume loss in MDD. Hippocampal volume changes are associated with disease severity. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 1.
Collapse
Affiliation(s)
- Zhen Zeng
- School of Medical Imaging, Binzhou Medical University, Yantai, China
| | - Yingying Dong
- Department of Psychology, Binzhou Medical University Hospital, Binzhou, China
| | - Linxuan Zou
- School of Medical Imaging, Binzhou Medical University, Yantai, China
| | - Donghao Xu
- School of Medical Imaging, Binzhou Medical University, Yantai, China
| | - Xunrong Luo
- Department of Radiology, Cancer Hospital of Chongqing University, Chongqing, China
| | - Tongpeng Chu
- Department of Radiology, Yantai Yuhuangding Hospital, Affiliated Hospital of Qingdao University, Yantai, China
| | - Jing Wang
- Department of Radiology, Binzhou Medical University Hospital, Binzhou, China
| | - Qingfa Ren
- School of Medical Imaging, Binzhou Medical University, Yantai, China
| | - Quanyuan Liu
- Department of Radiology, Binzhou Medical University Hospital, Binzhou, China
| | - Xianglin Li
- School of Medical Imaging, Binzhou Medical University, Yantai, China
| |
Collapse
|
5
|
Zhang Y, Zu T, Liu R, Zhou J. Acquisition sequences and reconstruction methods for fast chemical exchange saturation transfer imaging. NMR IN BIOMEDICINE 2023; 36:e4699. [PMID: 35067987 DOI: 10.1002/nbm.4699] [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: 11/09/2021] [Revised: 01/02/2022] [Accepted: 01/17/2022] [Indexed: 05/23/2023]
Abstract
Chemical exchange saturation transfer (CEST) imaging is an emerging molecular magnetic resonance imaging (MRI) technique that has been developed and employed in numerous diseases. Based on the unique saturation transfer principle, a family of CEST-detectable biomolecules in vivo have been found capable of providing valuable diagnostic information. However, CEST MRI needs a relatively long scan time due to the common long saturation labeling module and typical acquisition of multiple frequency offsets and signal averages, limiting its widespread clinical applications. So far, a plethora of imaging schemes and techniques has been developed to accelerate CEST MRI. In this review, the key acquisition and reconstruction methods for fast CEST imaging are summarized from a practical and systematic point of view. The first acquisition sequence section describes the major development of saturation schemes, readout patterns, ultrafast z-spectroscopy, and saturation-editing techniques for rapid CEST imaging. The second reconstruction method section lists the important advances of parallel imaging, compressed sensing, sparsity in the z-spectrum, and algorithms beyond the Fourier transform for speeding up CEST MRI.
Collapse
Affiliation(s)
- 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
| | - 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
| | - 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
| | - Jinyuan Zhou
- Department of Radiology, Johns Hopkins University, Baltimore, Maryland, USA
| |
Collapse
|
6
|
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.
Collapse
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
| |
Collapse
|
7
|
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.
Collapse
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
| |
Collapse
|
8
|
Amide Proton Transfer-Weighted Imaging Combined with ZOOMit Diffusion Kurtosis Imaging in Predicting Lymph Node Metastasis of Cervical Cancer. Bioengineering (Basel) 2023; 10:bioengineering10030331. [PMID: 36978722 PMCID: PMC10045132 DOI: 10.3390/bioengineering10030331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 02/23/2023] [Accepted: 03/02/2023] [Indexed: 03/08/2023] Open
Abstract
Background: The aim of this study is to investigate the feasibility of amide proton transfer-weighted (APTw) imaging combined with ZOOMit diffusion kurtosis imaging (DKI) in predicting lymph node metastasis (LNM) in cervical cancer (CC). Materials and Methods: Sixty-one participants with pathologically confirmed CC were included in this retrospective study. The APTw MRI and ZOOMit diffusion-weighted imaging (DWI) were acquired. The mean values of APTw and DKI parameters including mean kurtosis (MK) and mean diffusivity (MD) of the primary tumors were calculated. The parameters were compared between the LNM and non-LNM groups using the Student’s t-test or Mann–Whitney U test. Binary logistic regression analysis was performed to determine the association between the LNM status and the risk factors. The diagnostic performance of these quantitative parameters and their combinations for predicting the LNM was assessed with receiver operating characteristic (ROC) curve analysis. Results: Patients were divided into the LNM group (n = 17) and the non-LNM group (n = 44). The LNM group presented significantly higher APTw (3.7 ± 1.1% vs. 2.4 ± 1.0%, p < 0.001), MK (1.065 ± 0.185 vs. 0.909 ± 0.189, p = 0.005) and lower MD (0.989 ± 0.195 × 10−3 mm2/s vs. 1.193 ± 0.337 ×10−3 mm2/s, p = 0.035) than the non-LNM group. APTw was an independent predictor (OR = 3.115, p = 0.039) for evaluating the lymph node status through multivariate analysis. The area under the curve (AUC) of APTw (0.807) was higher than those of MK (AUC, 0.715) and MD (AUC, 0.675) for discriminating LNM from non-LNM, but the differences were not significant (all p > 0.05). Moreover, the combination of APTw, MK, and MD yielded the highest AUC (0.864), with the corresponding sensitivity of 76.5% and specificity of 88.6%. Conclusion: APTw and ZOOMit DKI parameters may serve as potential noninvasive biomarkers in predicting LNM of CC.
Collapse
|
9
|
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.
Collapse
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
| |
Collapse
|
10
|
Xu L, Lai L, Wen Y, Lin J, Chen B, Zhong Y, Cheng Y, Zhang X, Guan J, Mikulis DJ, Lin Y, Yan G, Wu R. Angiopep-2, an MRI Biomarker, Dynamically Monitors Amyloid Deposition in Early Alzheimer's Disease. ACS Chem Neurosci 2023; 14:226-234. [PMID: 36599050 PMCID: PMC9854622 DOI: 10.1021/acschemneuro.2c00513] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 12/27/2022] [Indexed: 01/06/2023] Open
Abstract
The reliable and dynamic detection of amyloid β-protein (Aβ) deposition using imaging technology is necessary for preclinical Alzheimer's disease (AD), which may significantly improve prognosis. The present study aimed to evaluate the feasibility of applying angiopep-2 (ANG), a chemical exchange saturation transfer-magnetic resonance imaging (CEST-MRI) biomarker, for monitoring Aβ deposition in vivo. ANG exerted a good chemical exchange saturation transfer (CEST) effect and displayed a moderate binding affinity to Aβ1-42 in vitro. Six-month-old mice with AD injected with ANG exhibited a significantly enhanced CEST effect than controls in vivo; this effect gradually became more apparent at 8, 10, and 12 months. Spatial learning impairment caused by abundant Aβ deposition (representing mild cognitive impairment in AD patients) develops at 12 months in APPswe/PSEN1dE9 (line 85) AD mice. To conclude, the CEST of ANG could display very earlier age-related Aβ pathological progress in mice with AD, consistent with immunohistochemistry. ANG has extraordinary potential for clinical transformation as an imaging biomarker to diagnose early AD and track its progress dynamically and nonradiationally.
Collapse
Affiliation(s)
- Liang Xu
- Department
of Medical Imaging, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
- Department
of Medical Imaging, Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, Guangdong 518000, P. R. China
| | - Lingfeng Lai
- Department
of Medical Imaging, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
| | - Yaqi Wen
- Department
of Medical Imaging, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
| | - Jia Lin
- Department
of Ultrasound, First Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
| | - Beibei Chen
- Department
of Medical Imaging, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
| | - Yazhi Zhong
- Department
of Medical Imaging, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
| | - Yan Cheng
- Department
of Medical Imaging, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
| | - XiaoLei Zhang
- Department
of Medical Imaging, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
- Provincial
Key Laboratory for Breast Cancer Diagnosis and Treatment, Guangdong
Province, Shantou, Guangdong 515041, P. R. China
| | - Jitian Guan
- Department
of Medical Imaging, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
- Provincial
Key Laboratory for Breast Cancer Diagnosis and Treatment, Guangdong
Province, Shantou, Guangdong 515041, P. R. China
| | - David J Mikulis
- Joint
Department of Medical Imaging and the Functional Neuroimaging Laboratory
(D.J.M.), University Health Network, Toronto M2J4A6, Canada
| | - Yan Lin
- Department
of Medical Imaging, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
- Provincial
Key Laboratory for Breast Cancer Diagnosis and Treatment, Guangdong
Province, Shantou, Guangdong 515041, P. R. China
| | - Gen Yan
- Department
of Radiology, The Second Affiliated Hospital
of Xiamen Medical College, Xiamen, Fujian 361023, P. R. China
| | - Renhua Wu
- Department
of Medical Imaging, Second Affiliated Hospital, Shantou University Medical College, Shantou, Guangdong 515000, P. R. China
- Provincial
Key Laboratory for Breast Cancer Diagnosis and Treatment, Guangdong
Province, Shantou, Guangdong 515041, P. R. China
| |
Collapse
|
11
|
Ren Q, Wan B, Luo X, Liu Q, Gong H, Li H, Luo M, Xu D, Liu P, Wang J, Yin Z, Li X. Glutamate alterations in the premature infant brain during different gestational ages with glutamate chemical exchange saturation transfer imaging: a pilot study. Eur Radiol 2023; 33:4214-4222. [PMID: 36600123 DOI: 10.1007/s00330-022-09374-2] [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: 08/05/2022] [Revised: 11/02/2022] [Accepted: 12/08/2022] [Indexed: 01/05/2023]
Abstract
OBJECTIVES To elucidate the change in glutamate levels in preterm infants at different gestational ages by glutamate chemical exchange saturated transfer (GluCEST) magnetic resonance imaging and to compare the difference in glutamate levels among different brain regions between very early preterm infants and middle and late preterm infants. METHODS Fifty-three preterm infants (59% males; median gestational age = 33.6 weeks) underwent MRI, including conventional MRI and GluCEST. The original data were postprocessed in MATLAB. Correlation analysis was used to determine the relationship between the MTRasym and gestational age. The differences in MTRasym signals among different ROIs were statistically analysed by one-way analysis of variance (ANOVA). The MTRasym difference of the bilateral hemispherical ROI was compared by a paired T test. RESULTS In all ROIs, glutamate concentration was positively correlated with gestational age. The glutamate concentration in the thalamus was higher than that in the frontal lobe in very early, middle and late preterm infants. A difference in glutamate concentration was not found in the bilateral ROIs. CONCLUSIONS The concentration of glutamate in the brains of preterm infants of different gestational ages increased with gestational age, which may be one of the factors contributing to the higher incidence of neurodevelopmental dysfunction in very early preterm infants compared to that in middle and late preterm infants. Meanwhile, the glutamate concentrations among different brain regions were also diverse. KEY POINTS • The glutamate concentration was positively correlated with gestational age in preterm infants of the brain. • Glutamate concentrations were dissimilar in different brain regions of preterm infants. • Glutamate concentration during the process of brain development in premature infants was not found to be asymmetric.
Collapse
Affiliation(s)
- Qingfa Ren
- School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Laishan District, Yantai, 264003, China
| | - Bin Wan
- Neonatal Intensive Care Unit, Binzhou Medical University Hospital, No. 661 Huanghe 2nd Road, Bincheng District, Binzhou, 256600, China
| | - Xunrong Luo
- Department of Radiology, Affiliated Cancer Hospital of Chongqing University, No. 181 Hanyu Road, Shapingba District, Chongqing, 400016, China
| | - Quanyuan Liu
- Department of Radiology, Binzhou Medical University Hospital, No. 661 Huanghe 2nd Road, Bincheng District, Binzhou, 256600, China
| | - He Gong
- School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Laishan District, Yantai, 264003, China
| | - Hao Li
- School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Laishan District, Yantai, 264003, China
| | - Mingfang Luo
- Department of Radiology, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, No. 32, West Second Section, First Ring Road, Qingyang District, Chengdu, 610072, China
| | - Donghao Xu
- School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Laishan District, Yantai, 264003, China
| | - Pan Liu
- School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Laishan District, Yantai, 264003, China
| | - Jing Wang
- Department of Radiology, Binzhou Medical University Hospital, No. 661 Huanghe 2nd Road, Bincheng District, Binzhou, 256600, China.
| | - Zhijie Yin
- Department of Radiology, Binzhou Medical University Hospital, No. 661 Huanghe 2nd Road, Bincheng District, Binzhou, 256600, China.
| | - Xianglin Li
- School of Medical Imaging, Binzhou Medical University, No. 346 Guanhai Road, Laishan District, Yantai, 264003, China.
| |
Collapse
|
12
|
Li S, He K, Yuan G, Yong X, Meng X, Feng C, Zhang Y, Kamel IR, Li Z. WHO/ISUP grade and pathological T stage of clear cell renal cell carcinoma: value of ZOOMit diffusion kurtosis imaging and chemical exchange saturation transfer imaging. Eur Radiol 2022; 33:4429-4439. [PMID: 36472697 DOI: 10.1007/s00330-022-09312-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 10/07/2022] [Accepted: 11/21/2022] [Indexed: 12/12/2022]
Abstract
OBJECTIVES To evaluate the value of ZOOMit diffusion kurtosis imaging (DKI) and chemical exchange saturation transfer (CEST) imaging in predicting WHO/ISUP grade and pathological T stage in clear cell renal cell carcinoma (ccRCC). METHODS Forty-six patients with ccRCC were included in this retrospective study. All participants underwent MRI including ZOOMit DKI and CEST. The non-Gaussian mean kurtosis (MK), mean diffusivity (MD), magnetization transfer ratio asymmetry (MTRasym (3.5 ppm)), and Ssat (3.5 ppm)/S0 were analyzed based on different WHO/ISUP grades and pT stages. Binary logistic regression was used to identify the best combination of the parameters. Pearson's correlation coefficients were calculated between CEST and diffusion-related parameters. RESULTS The ADC, MD, and Ssat (3.5 ppm)/S0 values were significantly lower for higher WHO/ISUP grade tumors, whereas the MK and MTRasym (3.5 ppm) were higher in higher WHO/ISUP grade and higher pT stage tumors. MTRasym (3.5 ppm) combined with MD (AUC, 0.930; 95% CI, 0.858-1.000) showed the best diagnostic efficacy in evaluating the WHO/ISUP grade. MTRasym (3.5 ppm) and MK were mildly positively correlated (r = 0.324, p = 0.028). Ssat (3.5 ppm)/S0 was moderately positively correlated with ADC (r = 0.580, p < 0.001), mildly positively correlated with MD (r = 0.412, p = 0.005), and moderately negatively correlated with MK (r = -0.575, p < .001). CONCLUSION The microstructural and biochemical assessment of ZOOMit DKI and CEST allowed for the characterization of different WHO/ISUP grades and pT stages in ccRCC. MTRasym (3.5 ppm) combined with MD showed the best diagnostic performance for WHO/ISUP grading. KEY POINTS • Both diffusion kurtosis imaging (DKI) and chemical exchange saturation transfer (CEST) can be used to predict the WHO/ISUP grade and pathological T stage. • MTRasym (3.5 ppm) combined with MD showed the highest AUC (0.930; 95% CI, 0.858-1.000) in WHO/ISUP grading. • MTRasym at 3.5 ppm showed a positive correlation with mean kurtosis.
Collapse
Affiliation(s)
- Shichao Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Kangwen He
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Guanjie Yuan
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 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
| | - Xiaoyan Meng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Cui Feng
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, 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.
| | - Ihab R Kamel
- Russell H. Morgan Department of Radiology and Radiological Science, the Johns Hopkins Medical Institutions, Baltimore, Maryland, USA
| | - Zhen Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
| |
Collapse
|
13
|
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: 73] [Impact Index Per Article: 36.5] [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.
Collapse
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
| |
Collapse
|
14
|
Wen Q, Wang K, Hsu YC, Xu Y, Sun Y, Wu D, Zhang Y. Chemical exchange saturation transfer imaging for epilepsy secondary to tuberous sclerosis complex at 3 T: Optimization and analysis. NMR IN BIOMEDICINE 2021; 34:e4563. [PMID: 34046976 DOI: 10.1002/nbm.4563] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/14/2020] [Revised: 03/16/2021] [Accepted: 05/01/2021] [Indexed: 06/12/2023]
Abstract
The homeostasis of various metabolites is impaired in epilepsy secondary to the tuberous sclerosis complex (TSC). Chemical exchange saturation transfer (CEST) imaging is an emerging molecular MRI technique that can detect various metabolites and proteins in vivo. However, the role of CEST imaging for TSC-associated epilepsy has not been assessed. Here, we aim to investigate the feasibility of applying CEST imaging to TSC-associated epilepsy, optimize the CEST acquisition parameters, and provide an analysis method for exploring the dominant molecular contributors to the CEST signal measured. Nine TSC epilepsy patients were scanned on a 3-T MRI system. The CEST saturation frequencies were swept from -6 to 6 ppm with 12 different combinations of saturation power (4, 3, 2 and 1 μT) and duration (1000, 700 and 400 ms). Furthermore, a two-stage simulation method based on the seven-pool Bloch-McConnell model was proposed to assess the contribution of each exchangeable pool to the CEST signal in normal-appearing white matter and cortical tubers, which avoided the complexity and uncertainty of full Bloch-McConnell fitting. The results showed that under the optimal saturation duration of 1000 ms, the greatest contrast between tubers and normal tissues occurred around 3, 2.5, 1.75 and 3.5 ppm for B1 of 4, 3, 2 and 1 μT, respectively. At the optimal frequency offsets, the CEST values of tubers were significantly higher than those in the normal brain tissues (P < 0.01). Furthermore, the two-stage analysis suggested that the amine pool played a dominant role in yielding the contrast between cortical tubers and normal tissues. These results indicate that CEST MRI may serve as a potentially useful tool for identifying tubers in TSC, and the two-stage analysis method may provide a route for investigating the molecular contributions to the CEST contrast in biological tissues.
Collapse
Affiliation(s)
- Qingqing Wen
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument Science, Zhejiang University, Hangzhou, Zhejiang, China
| | - Kang Wang
- Department of Neurology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yi-Cheng Hsu
- MR Collaboration, Siemens Healthcare Ltd., Shanghai, China
| | - Yan Xu
- Department of Neurosurgery, Zhejiang Provincial People's Hospital, 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
- Department of Neurology, First Affiliated Hospital, College of Medicine, 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
- Department of Neurology, First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| |
Collapse
|
15
|
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.
Collapse
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.
| |
Collapse
|