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Simegn GL, Sun PZ, Zhou J, Kim M, Reddy R, Zu Z, Zaiss M, Yadav NN, Edden RA, van Zijl PC, Knutsson L. Motion and magnetic field inhomogeneity correction techniques for chemical exchange saturation transfer (CEST) MRI: A contemporary review. NMR IN BIOMEDICINE 2025; 38:e5294. [PMID: 39532518 PMCID: PMC11606773 DOI: 10.1002/nbm.5294] [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: 09/05/2024] [Revised: 10/14/2024] [Accepted: 10/31/2024] [Indexed: 11/16/2024]
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has emerged as a powerful imaging technique sensitive to tissue molecular composition, pH, and metabolic processes in situ. CEST MRI uniquely probes the physical exchange of protons between water and specific molecules within tissues, providing a window into physiological phenomena that remain invisible to standard MRI. However, given the very low concentration (millimolar range) of CEST compounds, the effects measured are generally only on the order of a few percent of the water signal. Consequently, a few critical challenges, including correction of motion artifacts and magnetic field (B0 and B1 +) inhomogeneities, have to be addressed in order to unlock the full potential of CEST MRI. Motion, whether from patient movement or inherent physiological pulsations, can distort the CEST signal, hindering accurate quantification. B0 and B1 + inhomogeneities, arising from scanner hardware imperfections, further complicate data interpretation by introducing spurious variations in the signal intensity. Without proper correction of these confounding factors, reliable analysis and clinical translation of CEST MRI remain challenging. Motion correction methods aim to compensate for patient movement during (prospective) or after (retrospective) image acquisition, reducing artifacts and preserving data quality. Similarly, B0 and B1 + inhomogeneity correction techniques enhance the spatial and spectral accuracy of CEST MRI. This paper aims to provide a comprehensive review of the current landscape of motion and magnetic field inhomogeneity correction methods in CEST MRI. The methods discussed apply to saturation transfer (ST) MRI in general, including semisolid magnetization transfer contrast (MTC) and relayed nuclear Overhauser enhancement (rNOE) studies.
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Affiliation(s)
- Gizeaddis Lamesgin Simegn
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Phillip Zhe Sun
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30329, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30329, USA
- Emory National Primate Research Center, Emory University, Atlanta, GA 30329, USA
| | - Jinyuan Zhou
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Mina Kim
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Ravinder Reddy
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zhongliang Zu
- Vanderbilt University Institute of Imaging Science, Vanderbilt University Medical Center, Nashville, TN 37232, USA
| | - Moritz Zaiss
- Institute of Neuroradiology, University Clinic Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Nirbhay Narayan Yadav
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Richard A.E. Edden
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Peter C.M. van Zijl
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
| | - Linda Knutsson
- Russell H. Morgan Department of Radiology and Radiological Sciences, Division of MR Research, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F. M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21205, USA
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Yang Q, Wang M, Dou W, Ren Y, Zhang T, Qian L, Xu Y, Li K, Wang M, Sun Y, Liu Z, Tan T. Parameter map guided explainable segmentation framework for breast cancer using amide proton transfer weighted imaging. Med Phys 2024. [PMID: 39699234 DOI: 10.1002/mp.17574] [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: 07/04/2024] [Revised: 11/27/2024] [Accepted: 11/28/2024] [Indexed: 12/20/2024] Open
Abstract
BACKGROUND Amide proton transfer weighted (APTw) imaging has demonstrated extensive clinical applications in diagnosing, treating evaluating, and prognosis prediction of breast cancer. There is a pressing need to automatically segment breast lesions on APTw original images to facilitate downstream quantification, which is however challenging. PURPOSE To build a segmentation model on the original images of APTw imaging sequence by leveraging the varying contrasts between breast lesions and their surrounding glandular and fat tissues displayed on the original images of APTw imaging at different frequency offsets. METHODS This paper proposes a network with multiple tasks, including a breast lesion segmentation model (task I) incorporating multiple images at different frequencies with different contrasts between tumor and surrounding tissues, an automatic classification of pathological task (task II), and an APTw parameter map fitting (task III). RESULTS Compared with these advanced segmentation methods such as U-Net, segment anything model (SAM), segment anything in medical images (Med-SAM), and transfomer for MRI brain tumor segmentation (TransBTS), our method achieves higher accuracy (ACC). Furthermore, the model's interpretability facilitates the evaluation of how maps with varying gray contrasts contribute to the segmentation. Moreover, improving the ACC of segmentation can be accomplished through tasks such as pathological classification and parametric map fitting. CONCLUSIONS The pathological classification task and parameter fitting task could improve the ACC of segmentation.
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Affiliation(s)
- Qiuhui Yang
- Faculty of Applied Sciences, Macao Polytechnic University, Macao, China
- Guangxi Key Laboratory of Machine Vision and Intelligent Control, Wuzhou University, Wuzhou, China
| | - Meng Wang
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Shenzhen, China
- Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China
| | | | - Ya Ren
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Shenzhen, China
| | - Tianyu Zhang
- Department of Medical Imaging, Radboud University Medical Center, Nijmegen, Netherlands
- Department of Radiology, Netherlands Cancer Institute (NKI), Amsterdam, Netherlands
| | - Long Qian
- GE MR Research China, Shanghai, China
| | - Yi Xu
- Shanghai Key Lab of Digital Media Processing and Transmission, Shanghai Jiao Tong University, Shanghai, China
| | - Kefeng Li
- Faculty of Applied Sciences, Macao Polytechnic University, Macao, China
| | - Mingwei Wang
- Affiliated Hospital of Hangzhou Normal University, Hangzhou, China
| | - Yue Sun
- Faculty of Applied Sciences, Macao Polytechnic University, Macao, China
| | - Zhou Liu
- National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Shenzhen, China
| | - Tao Tan
- Faculty of Applied Sciences, Macao Polytechnic University, Macao, China
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Ding D, Chang L, Men C, Yang B, Pylypenko D, Zhang T, Yu D, Wang F. Does amide proton transfer-weighted MRI have diagnostic and differential value in ovarian cystic and predominantly cystic lesion? Abdom Radiol (NY) 2024:10.1007/s00261-024-04768-w. [PMID: 39694947 DOI: 10.1007/s00261-024-04768-w] [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: 09/18/2024] [Revised: 12/10/2024] [Accepted: 12/13/2024] [Indexed: 12/20/2024]
Abstract
OBJECTIVES This study aims to evaluate the diagnostic value of amide proton transfer-weighted (APTw) imaging in distinguishing cystic or predominantly cystic ovarian lesions. MATERIALS AND METHODS 49 patients underwent APTw imaging at 3T-MR before surgery, with 20 volunteers serving as the control group. Participants were divided into the following groups: solid components of normal ovaries (Group A, n = 29), solid components of malignant lesions (Group B, n = 7), cystic fluid of follicles (Group C, n = 31), cystic fluid of benign lesions (Group D, n = 46), functional cysts (Group d1, n = 8), endometriomas (Group d2, n = 28), cystadenomas (Group d3, n = 10), and cystic fluid of malignant lesions (Group E, n = 12). Independent t-tests or Mann-Whitney U tests and one-way ANOVA were used to compare group differences. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic efficacy in distinguishing between different lesions. RESULTS For solid components, significant differences in MTRasym values were observed between Groups A and B (P < 0.001). For cystic components, significant differences were found between Groups C and D, C and E, d1 and d2, d2 and d3, d1 and d3, C and d2, C and d3, E and d1, and E and d2 (all P < 0.01). ROC analysis of these results showed high AUC values (ranging from 0.813 to 1.0), all P < 0.05. CONCLUSIONS APTw can reveal differences in MTRasym values between normal and diseased ovarian tissues, demonstrating high clinical value in differentiating functional cysts, endometriomas, and cystadenomas, as well as distinguishing benign lesions (functional cysts or endometriomas) from malignant tumors.
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Affiliation(s)
- Dawei Ding
- Qilu Hospital of Shandong University, Jinan, China
- Qingzhou People's Hospital, Qingzhou, China
| | - Lingyu Chang
- Qilu Hospital of Shandong University, Jinan, China
| | | | - Bo Yang
- Qilu Hospital of Shandong University, Jinan, China
- Qingzhou People's Hospital, Qingzhou, China
| | | | - Tao Zhang
- Weifang People's Hospital, Weifang, China
| | - Dexin Yu
- Qilu Hospital of Shandong University, Jinan, China
| | - Fang Wang
- Qilu Hospital of Shandong University, Jinan, China.
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Pflüger I, Rastogi A, Casagranda S, Papageorgakis C, Behnisch R, Liebig P, Prager M, Ippen FM, Paech D, Wick W, Bendszus M, Brugnara G, Vollmuth P. Amide proton transfer weighted MRI measurements yield consistent and repeatable results in patients with gliomas: a prospective test-retest study. Eur Radiol 2024:10.1007/s00330-024-11197-2. [PMID: 39694884 DOI: 10.1007/s00330-024-11197-2] [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: 02/02/2024] [Revised: 08/12/2024] [Accepted: 10/28/2024] [Indexed: 12/20/2024]
Abstract
OBJECTIVES Chemical exchange saturation transfer (CEST) imaging has emerged as a promising imaging biomarker, but its reliability for clinical practice remains uncertain. This study aimed to investigate the robustness of CEST parameters in healthy volunteers and patients with brain tumours. METHODS A total of n = 52 healthy volunteers and n = 52 patients with histologically confirmed glioma underwent two consecutive 3-T MRI scans separated by a 1-min break. The CEST measurements were reconstructed using two models: with and without fluid suppression and included the evaluation of both amide (amidePTw) and amine (aminePTw) offsets. Mean intensity values in healthy volunteers were compared from volumetric segmentations (VOI) of grey matter, white matter, and the whole brain. Mean intensity values in brain tumour patients were assessed from VOI of the contrast-enhancing, non-enhancing and whole tumour, as well as from the normal-appearing white matter. Test-retest reliability was assessed using ICC and Bland-Altman plots. RESULTS The amidePTw/aminePTw signal intensity distribution was significantly affected by fluid suppression (p < 0.001 for each VOI). Test-retest reliability in healthy volunteers showed fair to excellent agreement (ICC = 0.53-0.74), with the highest signal intensity values observed by amidePTw (ICC = 0.73-0.74). In patients, an excellent agreement of both amidePTw and aminePTw measurements was observed across different tumour regions (ICC = 0.76-0.89), with the highest ICC for contrast-enhancing tumour measurements. Bland-Altman analysis indicated negligible systematic bias and no proportional bias in measurement errors. CONCLUSION Measurements from amide/aminePTw imaging obtained from an adequately powered test-retest study yield consistent and reproducible results in glioma patients, as a prerequisite for robust imaging biomarker discovery in neuro-oncology. KEY POINTS Question The clinical reliability of chemical exchange saturation transfer imaging remains uncertain, necessitating further investigation to establish its robustness as a biomarker in neuro-oncology. Findings This study demonstrates that amide/amine proton transfer imaging provides repeatable, high-agreement measurements in glioma patients, particularly in contrast-enhancing tumour regions. Clinical relevance This test-retest study demonstrates that chemical exchange saturation transfer imaging using two models and assessing amide and amine offsets yield consistent and repeatable results in glioma patients, as a prerequisite for robust imaging biomarker discovery for neuro-oncology studies and clinical practice.
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Affiliation(s)
- Irada Pflüger
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Division for Computational Neuroimaging, Heidelberg University Hospital, Heidelberg, Germany
| | - Aditya Rastogi
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Division for Computational Neuroimaging, Heidelberg University Hospital, Heidelberg, Germany
- Division for Computational Radiology & Clinical AI (CCIBonn.ai), Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Stefano Casagranda
- Department of R&D Advanced Applications, Olea Medical, La Ciotat, France
| | | | - Rouven Behnisch
- Institute of Medical Biometry, University of Heidelberg, Heidelberg, Germany
| | | | - Marcel Prager
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - Daniel Paech
- Department of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Department of Neuroradiology, Bonn University Hospital, Bonn, Germany
| | - Wolfgang Wick
- Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany
- Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Division for Computational Neuroimaging, Heidelberg University Hospital, Heidelberg, Germany
- Division for Medical Image Computing (MIC), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.
- Division for Computational Neuroimaging, Heidelberg University Hospital, Heidelberg, Germany.
- Division for Computational Radiology & Clinical AI (CCIBonn.ai), Department of Neuroradiology, University Hospital Bonn, Bonn, Germany.
- Division for Medical Image Computing (MIC), German Cancer Research Center (DKFZ), Heidelberg, Germany.
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Zhu D, Fu X, Liu J, Liu X, Cheng L, Zhang X, Lu J, Qin Q, Sun P, Zhou Z, Feng Y, Wang J. Multiparametric Chemical Exchange Saturation Transfer MRI Detects Metabolic Changes in Mild Cognitive Impairment Cases at 3.0 Tesla. Neurochem Res 2024; 50:51. [PMID: 39648256 DOI: 10.1007/s11064-024-04307-5] [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: 08/07/2024] [Revised: 11/08/2024] [Accepted: 12/02/2024] [Indexed: 12/10/2024]
Abstract
This study aimed to assess the potential of multiparametric chemical exchange saturation transfer magnetic resonance imaging (CEST MRI) for MCI detection. Twenty-eight patients with MCI and 31 age- and gender-matched normal controls (NCs) were enrolled. CEST MRI was performed with a gradient and spin-echo sequence on a 3T scanner. Multi-parametric CEST parameters were analyzed, such as amide CEST, amine CEST, amine and amide concentration independent assay (AACID), magnetization transfer ratio yielding rex (MTRrex-amide), and downfield rNOE suppressed apparent exchange-dependent relaxation amide proton (DNS-AREX-amide). Statistical analyses of CEST parameters were performed to evaluate group differences, their correlations with Montreal cognitive assessment (MoCA) score, and diagnostic performance for MCI. Compared with NC group, amide CEST as well as MTRrex-amide decreased in the left hippocampus and amine CEST as well as AACID increased in the right hippocampus in the MCI group; In both hippocampi, the DNS-AREX-amide were significantly lower in the MCI group versus the NC group (all P < 0.05). Amine CEST in the right hippocampus was negatively correlated with MoCA score (r = - 0.457, p = 0.017); DNS-AREX-amide in the bilateral hippocampus was positively correlated with MoCA score (left: r = 0.449, P = 0.019; right: AUC = 0.529, P = 0.05). DNS-AREX-amide in the bilateral hippocampus have a good ability to identify MCI (left: AUC = 0.756, P < 0.01; right: AUC = 0.762, P < 0.01). CEST MRI provides a potential imaging diagnostic strategy for MCI, which may promote early detection of MCI and provide novel insights into the pathological progress toward AD.
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Affiliation(s)
- Dongyong Zhu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China
| | - Xiaona Fu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China
| | - Jia Liu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China
| | - Xiaoming Liu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China
| | - Lan Cheng
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China
| | - Xinli Zhang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China
| | - Jue Lu
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China
| | - Qian Qin
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China
| | - Peng Sun
- Clinical & Technical Support, Philips Healthcare, Beijing, China
| | - Zhenyu Zhou
- Clinical & Technical Support, Philips Healthcare, Beijing, China
| | - Yiming Feng
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China.
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China.
| | - Jing Wang
- Department of Radiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, No.1277 Jiefang Avenue, Wuhan, 430022, China.
- Hubei Province Key Laboratory of Molecular Imaging, Wuhan, 430022, China.
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Yan M, Bie C, Jia W, Liu C, He X, Song X. Synthesis of higher-B 0 CEST Z-spectra from lower-B 0 data via deep learning and singular value decomposition. NMR IN BIOMEDICINE 2024; 37:e5221. [PMID: 39113170 DOI: 10.1002/nbm.5221] [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: 12/30/2023] [Revised: 06/28/2024] [Accepted: 07/03/2024] [Indexed: 11/15/2024]
Abstract
Chemical exchange saturation transfer (CEST) MRI at 3 T suffers from low specificity due to overlapping CEST effects from multiple metabolites, while higher field strengths (B0) allow for better separation of Z-spectral "peaks," aiding signal interpretation and quantification. However, data acquisition at higher B0 is restricted by equipment access, field inhomogeneity and safety issues. Herein, we aim to synthesize higher-B0 Z-spectra from readily available data acquired with 3 T clinical scanners using a deep learning framework. Trained with simulation data using models based on Bloch-McConnell equations, this framework comprised two deep neural networks (DNNs) and a singular value decomposition (SVD) module. The first DNN identified B0 shifts in Z-spectra and aligned them to correct frequencies. After B0 correction, the lower-B0 Z-spectra were streamlined to the second DNN, casting into the key feature representations of higher-B0 Z-spectra, obtained through SVD truncation. Finally, the complete higher-B0 Z-spectra were recovered from inverse SVD, given the low-rank property of Z-spectra. This study constructed and validated two models, a phosphocreatine (PCr) model and a pseudo-in-vivo one. Each experimental dataset, including PCr phantoms, egg white phantoms, and in vivo rat brains, was sequentially acquired on a 3 T human and a 9.4 T animal scanner. Results demonstrated that the synthetic 9.4 T Z-spectra were almost identical to the experimental ground truth, showing low RMSE (0.11% ± 0.0013% for seven PCr tubes, 1.8% ± 0.2% for three egg white tubes, and 0.79% ± 0.54% for three rat slices) and high R2 (>0.99). The synthesized amide and NOE contrast maps, calculated using the Lorentzian difference, were also well matched with the experiments. Additionally, the synthesis model exhibited robustness to B0 inhomogeneities, noise, and other acquisition imperfections. In conclusion, the proposed framework enables synthesis of higher-B0 Z-spectra from lower-B0 ones, which may facilitate CEST MRI quantification and applications.
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Affiliation(s)
- Mengdi Yan
- School of Information Sciences and Technology, Northwest University, Xi'an, China
- Center for Biomedical Imaging Research, Tsinghua University, Beijing, China
| | - Chongxue Bie
- School of Information Sciences and Technology, Northwest University, Xi'an, China
- Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Wentao Jia
- School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Chuyu Liu
- Center for Biomedical Imaging Research, Tsinghua University, Beijing, China
| | - Xiaowei He
- School of Information Sciences and Technology, Northwest University, Xi'an, China
| | - Xiaolei Song
- Center for Biomedical Imaging Research, Tsinghua University, Beijing, China
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Margolis DJA, Chatterjee A, deSouza NM, Fedorov A, Fennessy FM, Maier SE, Obuchowski N, Punwani S, Purysko A, Rakow-Penner R, Shukla-Dave A, Tempany CM, Boss M, Malyarenko D. Quantitative Prostate MRI, From the AJR Special Series on Quantitative Imaging. AJR Am J Roentgenol 2024. [PMID: 39356481 DOI: 10.2214/ajr.24.31715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/03/2024]
Abstract
Prostate MRI has traditionally relied on qualitative interpretation. However, quantitative components hold the potential to markedly improve performance. The ADC from DWI is probably the most widely recognized quantitative MRI biomarker and has shown strong discriminatory value for clinically significant prostate cancer (csPCa) as well as for recurrent cancer after treatment. Advanced diffusion techniques, including intravoxel incoherent motion, diffusion kurtosis, diffusion tensor imaging, and specific implementations such as restriction spectrum imaging, purport even better discrimination, but are more technically challenging. The inherent T1 and T2 of tissue also provide diagnostic value, with more advanced techniques deriving luminal water imaging and hybrid-multidimensional MRI. Dynamic contrast-enhanced imaging, primarily using a modified Tofts model, also shows independent discriminatory value. Finally, quantitative size and shape features can be combined with the aforementioned techniques and be further refined using radiomics, texture analysis, and artificial intelligence. Which technique will ultimately find widespread clinical use will depend on validation across a myriad of platforms use-cases.
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Affiliation(s)
| | | | - Nandita M deSouza
- The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust, London, UK
| | - Andriy Fedorov
- Department of Radiology, Brigham and Women's Hospital, Boston, MA
| | - Fiona M Fennessy
- Department of Radiology, Brigham and Women's Hospital, Boston, MA
| | - Stephan E Maier
- Department of Radiology, Brigham and Women's Hospital, Boston, MA
| | | | - Shonit Punwani
- Centre for Medical Imaging, University College London, London, UK
| | - Andrei Purysko
- Department of Radiology, Cleveland Clinic, Cleveland, OH
| | | | - Amita Shukla-Dave
- Departments of Medical Physics and Radiology, Memorial Sloan Kettering Cancer Center, New York, NY
| | - Clare M Tempany
- Department of Radiology, Brigham and Women's Hospital, Boston, MA
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8
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Hooijmans MT, Schlaffke L, Bolsterlee B, Schlaeger S, Marty B, Mazzoli V. Compositional and Functional MRI of Skeletal Muscle: A Review. J Magn Reson Imaging 2024; 60:860-877. [PMID: 37929681 PMCID: PMC11070452 DOI: 10.1002/jmri.29091] [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: 08/18/2023] [Revised: 10/09/2023] [Accepted: 10/09/2023] [Indexed: 11/07/2023] Open
Abstract
Due to its exceptional sensitivity to soft tissues, MRI has been extensively utilized to assess anatomical muscle parameters such as muscle volume and cross-sectional area. Quantitative Magnetic Resonance Imaging (qMRI) adds to the capabilities of MRI, by providing information on muscle composition such as fat content, water content, microstructure, hypertrophy, atrophy, as well as muscle architecture. In addition to compositional changes, qMRI can also be used to assess function for example by measuring muscle quality or through characterization of muscle deformation during passive lengthening/shortening and active contractions. The overall aim of this review is to provide an updated overview of qMRI techniques that can quantitatively evaluate muscle structure and composition, provide insights into the underlying biological basis of the qMRI signal, and illustrate how qMRI biomarkers of muscle health relate to function in healthy and diseased/injured muscles. While some applications still require systematic clinical validation, qMRI is now established as a comprehensive technique, that can be used to characterize a wide variety of structural and compositional changes in healthy and diseased skeletal muscle. Taken together, multiparametric muscle MRI holds great potential in the diagnosis and monitoring of muscle conditions in research and clinical applications. EVIDENCE LEVEL: 5 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Melissa T Hooijmans
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam Movement Sciences, Amsterdam, The Netherlands
| | - Lara Schlaffke
- Department of Neurology BG-University Hospital Bergmannsheil, Ruhr-University Bochum, Bochum, Germany
| | - Bart Bolsterlee
- Neuroscience Research Australia (NeuRA), Sydney, New South Wales, Australia
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, New South Wales, Australia
- School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Sarah Schlaeger
- Department of Diagnostic and Interventional Neuroradiology, School of Medicine, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Department of Radiology, LMU University Hospital, LMU Munich, Munich, Germany
| | - Benjamin Marty
- Institute of Myology, Neuromuscular Investigation Center, NMR Laboratory, Paris, France
| | - Valentina Mazzoli
- Department of Radiology, Stanford University, Stanford, California, USA
- Bernard and Irene Schwartz Center for Biomedical Imaging, Department of Radiology, NYU Langone Medical Center, New York, New York, USA
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Gammaraccio F, Villano D, Irrera P, Anemone AA, Carella A, Corrado A, Longo DL. Development and Validation of Four Different Methods to Improve MRI-CEST Tumor pH Mapping in Presence of Fat. J Imaging 2024; 10:166. [PMID: 39057737 PMCID: PMC11277679 DOI: 10.3390/jimaging10070166] [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: 05/08/2024] [Revised: 06/28/2024] [Accepted: 07/09/2024] [Indexed: 07/28/2024] Open
Abstract
CEST-MRI is an emerging imaging technique suitable for various in vivo applications, including the quantification of tumor acidosis. Traditionally, CEST contrast is calculated by asymmetry analysis, but the presence of fat signals leads to wrong contrast quantification and hence to inaccurate pH measurements. In this study, we investigated four post-processing approaches to overcome fat signal influences and enable correct CEST contrast calculations and tumor pH measurements using iopamidol. The proposed methods involve replacing the Z-spectrum region affected by fat peaks by (i) using a linear interpolation of the fat frequencies, (ii) applying water pool Lorentzian fitting, (iii) considering only the positive part of the Z-spectrum, or (iv) calculating a correction factor for the ratiometric value. In vitro and in vivo studies demonstrated the possibility of using these approaches to calculate CEST contrast and then to measure tumor pH, even in the presence of moderate to high fat fraction values. However, only the method based on the water pool Lorentzian fitting produced highly accurate results in terms of pH measurement in tumor-bearing mice with low and high fat contents.
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Affiliation(s)
- Francesco Gammaraccio
- Department of Molecular Biotechnology and Health Sciences, University of Turin, 10126 Torino, Italy
| | - Daisy Villano
- Department of Molecular Biotechnology and Health Sciences, University of Turin, 10126 Torino, Italy
| | - Pietro Irrera
- Institute of Biostructures and Bioimaging (IBB), National Research Council of Italy (CNR), 10126 Torino, Italy
| | - Annasofia A. Anemone
- Department of Molecular Biotechnology and Health Sciences, University of Turin, 10126 Torino, Italy
| | - Antonella Carella
- Institute of Biostructures and Bioimaging (IBB), National Research Council of Italy (CNR), 10126 Torino, Italy
| | - Alessia Corrado
- Institute of Biostructures and Bioimaging (IBB), National Research Council of Italy (CNR), 10126 Torino, Italy
| | - Dario Livio Longo
- Institute of Biostructures and Bioimaging (IBB), National Research Council of Italy (CNR), 10126 Torino, Italy
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10
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Yu T, Li L, Shi J, Gong X, Cheng Y, Wang W, Cao Y, Cao M, Jiang F, Wang L, Wang X, Zhang J. Predicting histopathological types and molecular subtype of breast tumors: A comparative study using amide proton transfer-weighted imaging, intravoxel incoherent motion and diffusion kurtosis imaging. Magn Reson Imaging 2024; 105:37-45. [PMID: 37890802 DOI: 10.1016/j.mri.2023.10.010] [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: 10/12/2022] [Revised: 10/07/2023] [Accepted: 10/24/2023] [Indexed: 10/29/2023]
Abstract
PURPOSE To evaluate the predictive performance of multiparameter and histogram features derived from amide proton transfer-weighted imaging (APTWI), intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) for histopathological types of breast tumors. METHODS Region of interest (ROI) was delineated by outlining the largest slice of the tumor on the false-color images of the DKI, IVIM and APTWI parameters, and extracted the histogram features. Receiver operating characteristic (ROC) curve was used to evaluate the performance of parameters in predicting benign and malignant breast lesions, molecular prognostic biomarkers, lymph node status, and subtypes of breast lesions. The Spearman correlation coefficient was used to determine the correlations between each parameter and clinical-pathological factors. RESULTS All 52 breast lesions were enrolled in this prospective study, including 8 benign lesions and 44 breast cancers. To diagnose malignant and benign breast lesions, the value of APT (min) performed best, with the AUC reaching 0.983. According to the different imaging methods, the APTWI performed best. To predict the positive status of ER, PR, Ki67, the value of Dapp (uniformity), Dapp (uniformity), f (entropy) performed best, with the AUC values reaching 0.743, 0.770, 0.848, respectively. For the identification of Luminal B, HER2-enriched, and TNBC breast cancers, Kapp (max), f (kurtosis), and Dapp (uniformity) performed best, with AUC values reaching 0.679, 0.826, 0.771, respectively. CONCLUSION This study found the APTWI, IVIM and DKI parameters could diagnose breast cancer. The histogram features of DKI and IVIM, based on tumor heterogeneity, may help to predict breast cancer subtypes.
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Affiliation(s)
- Tao Yu
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Lan Li
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Jinfang Shi
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Xueqin Gong
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Yue Cheng
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Wei Wang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Ying Cao
- School of Medicine, Chongqing University, Chongqing 400030, China
| | - Meimei Cao
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Fujie Jiang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Lu Wang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Xiaoxia Wang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China
| | - Jiuquan Zhang
- Department of Radiology, Chongqing University Cancer Hospital, Chongqing Key Laboratory for Intelligent Oncology in Breast Cancer (iCQBC), Chongqing 400030, China.
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11
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Swain A, Soni ND, Wilson N, Juul H, Benyard B, Haris M, Kumar D, Nanga RPR, Detre J, Lee VM, Reddy R. Early-stage mapping of macromolecular content in APP NL-F mouse model of Alzheimer's disease using nuclear Overhauser effect MRI. Front Aging Neurosci 2023; 15:1266859. [PMID: 37876875 PMCID: PMC10590923 DOI: 10.3389/fnagi.2023.1266859] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 09/15/2023] [Indexed: 10/26/2023] Open
Abstract
Non-invasive methods of detecting early-stage Alzheimer's disease (AD) can provide valuable insight into disease pathology, improving the diagnosis and treatment of AD. Nuclear Overhauser enhancement (NOE) MRI is a technique that provides image contrast sensitive to lipid and protein content in the brain. These macromolecules have been shown to be altered in Alzheimer's pathology, with early disruptions in cell membrane integrity and signaling pathways leading to the buildup of amyloid-beta plaques and neurofibrillary tangles. We used template-based analyzes of NOE MRI data and the characteristic Z-spectrum, with parameters optimized for increase specificity to NOE, to detect changes in lipids and proteins in an AD mouse model that recapitulates features of human AD. We find changes in NOE contrast in the hippocampus, hypothalamus, entorhinal cortex, and fimbria, with these changes likely attributed to disruptions in the phospholipid bilayer of cell membranes in both gray and white matter regions. This study suggests that NOE MRI may be a useful tool for monitoring early-stage changes in lipid-mediated metabolism in AD and other disorders with high spatial resolution.
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Affiliation(s)
- Anshuman Swain
- School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Narayan D. Soni
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Neil Wilson
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Halvor Juul
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Blake Benyard
- School of Engineering and Applied Science, University of Pennsylvania, Philadelphia, PA, United States
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Mohammad Haris
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Dushyant Kumar
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Ravi Prakash Reddy Nanga
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - John Detre
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Center for Functional Neuroimaging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Virginia M. Lee
- Center for Neurodegenerative Disease Research, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Alzheimer’s Disease Research Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Ravinder Reddy
- Center for Advanced Metabolic Imaging in Precision Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Kuribayashi S, Saito S, Sawaya R, Takahashi Y, Kioka H, Takezawa K, Kiuchi H, Fukuhara S, Nonomura N. Creatine Chemical Exchange Saturation Transfer (Cr-CEST) Imaging Can Evaluate Cisplatin-induced Testicular Damage. Magn Reson Med Sci 2023; 22:345-351. [PMID: 35545506 PMCID: PMC10449556 DOI: 10.2463/mrms.mp.2021-0125] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Accepted: 03/26/2022] [Indexed: 11/09/2022] Open
Abstract
PURPOSE This study aimed to investigate the ability of creatine-chemical exchange saturation transfer (Cr-CEST) technique assessed through 7-T MRI to evaluate cisplatin-induced testicular damage. METHODS We used 8-10 weeks C57BL/6 mice (n = 10) that were divided into a control group (n = 5) and a cisplatin-treated group (n = 5). The cisplatin group received cisplatin at a dose of 15 mg/kg, via intraperitoneal injection, while the control group received saline. MR images of mouse testes were acquired under anesthesia 18 days after the injection using a horizontal 7-T scanner. The pulse sequence consisted of rapid acquisition with a relaxation enhancement (RARE) with magnetization transfer. The Z-spectra were collected using a 2000-ms saturation pulse at a B1 amplitude of 1.2 μT, with frequencies varying from -4.8 to +4.8 parts per million (ppm). Maps of magnetization transfer ratio with asymmetric analysis (MTRasym) were reconstructed at a Cr metabolite concentration of 1.8 ppm. RESULTS The Cr-CEST effect was significantly reduced in the cisplatin-treated group compared to the control group (MTRasym of control mice vs. cisplatin-treated mice: 6.9 [6-7.5] vs. 5.2 [4-5.5], P = 0.008). Correlation analysis revealed a strong correlation between the Cr-CEST effect and the pathological score (ρ = 0.93, P < 0.001). CONCLUSION Cr-CEST MRI can be useful for the evaluation of cisplatin-induced testicular damage in mice.
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Affiliation(s)
- Sohei Kuribayashi
- Department of Urology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Shigeyoshi Saito
- Department of Medical Physics and Engineering, Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
- Department of Advanced Medical Technologies, National Cardiovascular and Cerebral Research Center, Suita, Osaka, Japan
| | - Reika Sawaya
- Department of Medical Physics and Engineering, Division of Health Sciences, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Yusuke Takahashi
- Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
- Department of Molecular Pharmacology, National Cerebral and Cardiovascular Center Research Institute, Suita, Osaka, Japan
| | - Hidetaka Kioka
- Department of Cardiovascular Medicine, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Kentaro Takezawa
- Department of Urology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Hiroshi Kiuchi
- Department of Urology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Shinichiro Fukuhara
- Department of Urology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
| | - Norio Nonomura
- Department of Urology, Osaka University Graduate School of Medicine, Suita, Osaka, Japan
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13
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Tian Y, Li X, Wang X, Su W, Li S, Wang W, Zhang Y, Li C, Chen M. CEST 2022-three-dimensional amide proton transfer (APT) imaging can identify the changes of cerebral cortex in Parkinson's disease. Magn Reson Imaging 2023:S0730-725X(23)00099-1. [PMID: 37356600 DOI: 10.1016/j.mri.2023.06.006] [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: 02/01/2023] [Accepted: 06/12/2023] [Indexed: 06/27/2023]
Abstract
PURPOSE Amide proton transfer (APT) imaging has shown its diagnostic and predictive superiority in PD in our previous studies using 2D APT imaging based on deep nuclei. We hypothesized that the pathophysiological abnormality of PD will change the APT-related parameters in the cerebral cortex, and the signal changes can contribute to accurate diagnosis of Parkinson's disease. METHODS 34 patients with sporadic Parkinson's disease (IPD) and 29 age- and sex-matched normal controls (NC) were enrolled in this prospective study. 3D-APT imaging and 3D-T1WI was performed in our participants. A volume-based morphometry algorithm was used and get automated cortical segmentations. Quantitative parameter maps of APT-related metrics were calculated by using SPM and MATLAB. The unpaired Student's t-test or Mann-Whitney U test was used for comparison of these values between IPD and NC groups. The associations between APT-related metrics and clinical assessments were investigated by Spearman correlation analysis. The receiver-operating characteristic (ROC) analysis was used to assess the diagnostic performances. The binary logistic regression model was used to combine the imaging parameters. RESULTS There wasn't any correlations between cortical APT-related signals and clinical assessment, including the H&Y scale, the disease duration, the UPDRS III scores and the MMSE scores. The MTRasym, CESTRnr and MTRRex had significantly higher values (p <0.001, corrected by Bonferroni methods) in the IPD group than NC groups in the region of bilateral and total temporal grey matter. The single parameters achieved the best diagnostic performance among all APT-related metrics was MTRRex on the right temporal grey matter, with an area under the ROC curve (AUC) of 0.865. The combined parameters achieved the highest diagnostic performance (AUC: 0.932). CONCLUSIONS 3D-APT imaging could identify the changes of the cerebral cortex in Parkinson's disease. The cortical changes of APT-related parameters could potentially serve as imaging biomarkers to aid in the non-invasive diagnosis of PD.
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Affiliation(s)
- Yaotian Tian
- Department of Radiology, National Center of Gerontology, Beijing Hospital, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730 Beijing, China; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, 100730 Beijing, China
| | - Xinyang Li
- Department of Radiology, National Center of Gerontology, Beijing Hospital, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730 Beijing, China; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, 100730 Beijing, China
| | - Xiaonan Wang
- Department of Radiology, National Center of Gerontology, Beijing Hospital, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730 Beijing, China; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, 100730 Beijing, China
| | - Wen Su
- Department of Neurology, National Center of Gerontology, Beijing Hospital, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730 Beijing, China
| | - Shuhua Li
- Department of Neurology, National Center of Gerontology, Beijing Hospital, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730 Beijing, 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 310027, 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 310027, Zhejiang, China
| | - Chunmei Li
- Department of Radiology, National Center of Gerontology, Beijing Hospital, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730 Beijing, China; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, 100730 Beijing, China.
| | - Min Chen
- Department of Radiology, National Center of Gerontology, Beijing Hospital, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, 100730 Beijing, China; Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences, 100730 Beijing, China.
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14
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Khormi I, Al-Iedani O, Casagranda S, Papageorgakis C, Alshehri A, Lea R, Liebig P, Ramadan S, Lechner-Scott J. CEST 2022 - Differences in APT-weighted signal in T1 weighted isointense lesions, black holes and normal-appearing white matter in people with relapsing-remitting multiple sclerosis. Magn Reson Imaging 2023:S0730-725X(23)00098-X. [PMID: 37321380 DOI: 10.1016/j.mri.2023.06.002] [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: 12/17/2022] [Revised: 03/09/2023] [Accepted: 06/12/2023] [Indexed: 06/17/2023]
Abstract
PURPOSE To evaluate amide proton transfer weighted (APTw) signal differences between multiple sclerosis (MS) lesions and contralateral normal-appearing white matter (cNAWM). Cellular changes during the demyelination process were also assessed by comparing APTw signal intensity in T1weighted isointense (ISO) and hypointense (black hole -BH) MS lesions in relation to cNAWM. METHODS Twenty-four people with relapsing-remitting MS (pw-RRMS) on stable therapy were recruited. MRI/APTw acquisitions were undertaken on a 3 T MRI scanner. The pre and post-processing, analysis, co-registration with structural MRI maps, and identification of regions of interest (ROIs) were all performed with Olea Sphere 3.0 software. Generalized linear model (GLM) univariate ANOVA was undertaken to test the hypotheses that differences in mean APTw were entered as dependent variables. ROIs were entered as random effect variables, which allowed all data to be included. Regions (lesions and cNAWM) and/or structure (ISO and BH) were the main factor variables. The models also included age, sex, disease duration, EDSS, and ROI volumes as covariates. Receiver operating characteristic (ROC) curve analyses were performed to evaluate the diagnostic performance of these comparisons. RESULTS A total of 502 MS lesions manually identified on T2-FLAIR from twenty-four pw-RRMS were subcategorized as 359 ISO and 143 BH with reference to the T1-MPRAGE cerebral cortex signal. Also, 490 ROIs of cNAWM were manually delineated to match the MS lesion positions. A two-tailed t-test showed that mean APTw values were higher in females than in males (t = 3.52, p < 0.001). Additionally, the mean APTw values of MS lesions were higher than those of cNAWM after accounting for covariates (mean lesion = 0.44, mean cNAWM = 0.13, F = 44.12, p < 0.001).The mean APTw values of ISO lesions were higher than those of cNAWM after accounting for covariates (mean ISO lesions = 0.42, mean cNAWM = 0.21, F = 12.12, p < 0.001). The mean APTw values of BH were also higher than those of cNAWM (mean BH lesions = 0.47, mean cNAWM = 0.033, F = 40.3, p < 0.001). The effect size (i.e., difference between lesion and cNAWM) for BH was found to be higher than for ISO (14 vs. 2). Diagnostic performance showed that APT was able to discriminate between all lesions and cNAWM with an accuracy of >75% (AUC = 0.79, SE = 0.014). Discrimination between ISO lesions and cNAWM was accomplished with an accuracy of >69% (AUC = 0.74, SE = 0.018), while discrimination between BH lesions and cNAWM was achieved at an accuracy of >80% (AUC = 0.87, SE = 0.021). CONCLUSIONS Our results highlight the potential of APTw imaging for use as a non-invasive technique that is able to provide essential molecular information to clinicians and researchers so that the stages of inflammation and degeneration in MS lesions can be better characterized.
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Affiliation(s)
- Ibrahim Khormi
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; College of Applied Medical Sciences, University of Jeddah, Jeddah, Saudi Arabia
| | - Oun Al-Iedani
- Hunter Medical Research Institute, New Lambton Heights, Australia; School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
| | | | | | - Abdulaziz Alshehri
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Radiology, King Fahd Hospital of the University, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia
| | - Rodney Lea
- Hunter Medical Research Institute, New Lambton Heights, Australia
| | | | - Saadallah Ramadan
- School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Hunter Medical Research Institute, New Lambton Heights, Australia.
| | - Jeannette Lechner-Scott
- Hunter Medical Research Institute, New Lambton Heights, Australia; Department of Neurology, John Hunter Hospital, New Lambton Heights, Australia; School of Medicine and Public Health, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia
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15
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Zhong Y, Guan J, Ma Y, Xu M, Cheng Y, Xu L, Lin Y, Zhang X, Wu R. Role of Imaging Modalities and N-Acetylcysteine Treatment in Sepsis-Associated Encephalopathy. ACS Chem Neurosci 2023; 14:2172-2182. [PMID: 37216423 PMCID: PMC10252850 DOI: 10.1021/acschemneuro.3c00180] [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: 03/19/2023] [Accepted: 05/04/2023] [Indexed: 05/24/2023] Open
Abstract
Sepsis-associated encephalopathy is a severe systemic infection complication. Although early stages involve pathophysiological changes, detection using conventional imaging is challenging. Glutamate chemical exchange saturation transfer and diffusion kurtosis imaging can noninvasively investigate cellular and molecular events in early disease stages using magnetic resonance imaging (MRI). N-Acetylcysteine, an antioxidant and precursor of glutathione, regulates neurotransmitter glutamate metabolism and participates in neuroinflammation. We investigated the protective role of n-acetylcysteine in sepsis-associated encephalopathy using a rat model and monitored changes in brain using magnetic resonance (MR) molecular imaging. Bacterial lipopolysaccharide was injected intraperitoneally to induce a sepsis-associated encephalopathy model. Behavioral performance was assessed using the open-field test. Tumor necrosis factor α and glutathione levels were detected biochemically. Imaging was performed using a 7.0-T MRI scanner. Protein expression, cellular damage, and changes in blood-brain barrier permeability were assessed using western blotting, pathological staining, and Evans blue staining, respectively. Lipopolysaccharide-induced rats showed reduced anxiety and depression after treatment with n-acetylcysteine. MR molecular imaging can identify pathological processes at different disease stages. Furthermore, rats treated with n-acetylcysteine showed increased glutathione levels and decreased tumor necrosis factor α, suggesting enhanced antioxidant capacity and inhibition of inflammatory processes, respectively. Western blot analysis showed reduced expression of nuclear factor kappa B (p50) protein after treatment, suggesting that n-acetylcysteine inhibits inflammation via this signaling pathway. Finally, n-acetylcysteine-treated rats showed reduced cellular damage by pathology and reduced extravasation of their blood-brain barrier by Evans Blue staining. Thus, n-acetylcysteine might be a therapeutic option for sepsis-associated encephalopathy and other neuroinflammatory diseases. Furthermore, noninvasive "dynamic visual monitoring" of physiological and pathological changes related to sepsis-associated encephalopathy was achieved using MR molecular imaging for the first time, providing a more sensitive imaging basis for early diagnosis, identification, and prognosis.
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Affiliation(s)
- Yazhi Zhong
- Department
of Radiology, The Second Affiliated Hospital,
Shantou University Medical College, Shantou 515041 Guangdong, China
- Department
of Radiology, Huizhou Central People’s
Hospital, Huizhou 516001 Guangdong, China
| | - Jitian Guan
- Department
of Radiology, The Second Affiliated Hospital,
Shantou University Medical College, Shantou 515041 Guangdong, China
| | - Yunfeng Ma
- Department
of Emergency, The Second Affiliated Hospital,
Shantou University Medical College, Shantou 515041 Guangdong, China
| | - Meiling Xu
- Department
of Emergency, The Second Affiliated Hospital,
Shantou University Medical College, Shantou 515041 Guangdong, China
| | - Yan Cheng
- Department
of Radiology, The Second Affiliated Hospital,
Shantou University Medical College, Shantou 515041 Guangdong, China
- Department
of Radiology, The Second Hospital of Shandong
University, Jinan 250033 Shandong, China
| | - Liang Xu
- Department
of Radiology, The Second Affiliated Hospital,
Shantou University Medical College, Shantou 515041 Guangdong, China
- Department
of Radiology, The Seventh Affiliated Hospital,
Sun Yat-sen University, Shenzhen 518100 Guangdong, China
| | - Yan Lin
- Department
of Radiology, The Second Affiliated Hospital,
Shantou University Medical College, Shantou 515041 Guangdong, China
| | - Xiaolei Zhang
- Department
of Radiology, The Second Affiliated Hospital,
Shantou University Medical College, Shantou 515041 Guangdong, China
| | - Renhua Wu
- Department
of Radiology, The Second Affiliated Hospital,
Shantou University Medical College, Shantou 515041 Guangdong, China
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16
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Bo S, Zhang D, Ma M, Mo X, Stabinska J, McMahon MT, Shi C, Luo L. Acyl Hydrazides and Acyl Hydrazones as High-Performance Chemical Exchange Saturation Transfer MRI Contrast Agents. Pharmaceuticals (Basel) 2023; 16:ph16050639. [PMID: 37242423 DOI: 10.3390/ph16050639] [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: 03/13/2023] [Revised: 04/17/2023] [Accepted: 04/20/2023] [Indexed: 05/28/2023] Open
Abstract
Chemical exchange saturation transfer (CEST) MRI is a versatile molecular imaging approach that holds great promise for clinical translation. A number of compounds have been identified as suitable for performing CEST MRI, including paramagnetic CEST (paraCEST) agents and diamagnetic CEST (diaCEST) agents. DiaCEST agents are very attractive because of their excellent biocompatibility and potential for biodegradation, such as glucose, glycogen, glutamate, creatine, nucleic acids, et al. However, the sensitivity of most diaCEST agents is limited because of small chemical shifts (1.0-4.0 ppm) from water. To expand the catalog of diaCEST agents with larger chemical shifts, herein, we have systematically investigated the CEST properties of acyl hydrazides with different substitutions, including aromatic and aliphatic substituents. We have tuned the labile proton chemical shifts from 2.8-5.0 ppm from water while exchange rates varied from ~680 to 2340 s-1 at pH 7.2, which allows strong CEST contrast on scanners down to B0 = 3 T. One acyl hydrazide, adipic acid dihydrazide (ADH), was tested on a mouse model of breast cancer and showed nice contrast in the tumor region. We also prepared a derivative, acyl hydrazone, which showed the furthest shifted labile proton (6.4 ppm from water) and excellent contrast properties. Overall, our study expands the catalog of diaCEST agents and their application in cancer diagnosis.
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Affiliation(s)
- Shaowei Bo
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou 510317, China
| | - Dong Zhang
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou 510632, China
| | - Mengjie Ma
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou 510632, China
| | - Xukai Mo
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou 510632, China
| | - Julia Stabinska
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21287, USA
| | - Michael T McMahon
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21287, USA
| | - Changzheng Shi
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou 510632, China
| | - Liangping Luo
- Department of Medical Imaging, The Affiliated Guangdong Second Provincial General Hospital of Jinan University, Guangzhou 510317, China
- Medical Imaging Center, The First Affiliated Hospital of Jinan University, Guangzhou 510632, China
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17
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Qi D, Li J, Quarles CC, Fonkem E, Wu E. Assessment and prediction of glioblastoma therapy response: challenges and opportunities. Brain 2023; 146:1281-1298. [PMID: 36445396 PMCID: PMC10319779 DOI: 10.1093/brain/awac450] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 11/03/2022] [Accepted: 11/10/2022] [Indexed: 11/30/2022] Open
Abstract
Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.
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Affiliation(s)
- Dan Qi
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
| | - Jing Li
- School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - C Chad Quarles
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX 77054, USA
| | - Ekokobe Fonkem
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
- Department of Medical Education, School of Medicine, Texas A&M University, Bryan, TX 77807, USA
| | - Erxi Wu
- Department of Neurosurgery and Neuroscience Institute, Baylor Scott & White Health, Temple, TX 76502, USA
- Department of Medical Education, School of Medicine, Texas A&M University, Bryan, TX 77807, USA
- Department of Pharmaceutical Sciences, Irma Lerma Rangel School of Pharmacy, Texas A&M University, College Station, TX 77843, USA
- Department of Oncology and LIVESTRONG Cancer Institutes, Dell Medical School, The University of Texas at Austin, Austin, TX 78712, USA
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Hunger L, Rajput JR, Klein K, Mennecke A, Fabian MS, Schmidt M, Glang F, Herz K, Liebig P, Nagel AM, Scheffler K, Dörfler A, Maier A, Zaiss M. DeepCEST 7 T: Fast and homogeneous mapping of 7 T CEST MRI parameters and their uncertainty quantification. Magn Reson Med 2023; 89:1543-1556. [PMID: 36377762 DOI: 10.1002/mrm.29520] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 09/30/2022] [Accepted: 10/19/2022] [Indexed: 11/16/2022]
Abstract
PURPOSE In this work, we investigated the ability of neural networks to rapidly and robustly predict Lorentzian parameters of multi-pool CEST MRI spectra at 7 T with corresponding uncertainty maps to make them quickly and easily available for routine clinical use. METHODS We developed a deepCEST 7 T approach that generates CEST contrasts from just 1 scan with robustness against B1 inhomogeneities. The input data for a neural feed-forward network consisted of 7 T in vivo uncorrected Z-spectra of a single B1 level, and a B1 map. The 7 T raw data were acquired using a 3D snapshot gradient echo multiple interleaved mode saturation CEST sequence. These inputs were mapped voxel-wise to target data consisting of Lorentzian amplitudes generated conventionally by 5-pool Lorentzian fitting of normalized, denoised, B0 - and B1 -corrected Z-spectra. The deepCEST network was trained with Gaussian negative log-likelihood loss, providing an uncertainty quantification in addition to the Lorentzian amplitudes. RESULTS The deepCEST 7 T network provides fast and accurate prediction of all Lorentzian parameters also when only a single B1 level is used. The prediction was highly accurate with respect to the Lorentzian fit amplitudes, and both healthy tissues and hyperintensities in tumor areas are predicted with a low uncertainty. In corrupted cases, high uncertainty indicated wrong predictions reliably. CONCLUSION The proposed deepCEST 7 T approach reduces scan time by 50% to now 6:42 min, but still delivers both B0 - and B1 -corrected homogeneous CEST contrasts along with an uncertainty map, which can increase diagnostic confidence. Multiple accurate 7 T CEST contrasts are delivered within seconds.
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Affiliation(s)
- Leonie Hunger
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Junaid R Rajput
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany.,Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Kiril Klein
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Angelika Mennecke
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Moritz S Fabian
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Manuel Schmidt
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Felix Glang
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, 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
| | | | - Armin M Nagel
- Institute of Radiology, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, 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
| | - Arnd Dörfler
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Andreas Maier
- Pattern Recognition Lab, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany
| | - Moritz Zaiss
- Institute of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander-University Erlangen-Nürnberg, Erlangen, Germany.,Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
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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.
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20
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Cui J, Zheng J, Niu W, Bian W, Wang J, Niu J. Quantitative IVIM parameters evaluating perfusion changes in brain parenchyma in patients newly diagnosed with acute leukemia: Compared with healthy participants. Front Neurol 2023; 14:1093003. [PMID: 36816571 PMCID: PMC9932664 DOI: 10.3389/fneur.2023.1093003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 01/03/2023] [Indexed: 02/05/2023] Open
Abstract
Purpose To study the value of quantitative IVIM parameters in evaluating cerebral blood perfusion changes in patients newly diagnosed with acute leukemia (AL) by comparing them with healthy participants. Materials and methods This prospective study consecutively recruited 49 participants with newly diagnosed AL and 40 normal controls between July 2020 and September 2022. All participants underwent an MRI of the brain using an axial T1-weighted and an IVIM sequence. The IVIM parameters (water diffusion coefficient, sADC, pseudoperfusion fraction, f; diffusion coefficient, D, pseudodiffusion coefficient, D *, and perfusion-diffusion ratio, PDR) and peripheral white blood cell (WBC) counts were obtained. An unpaired t-test or the Mann-Whitney U-test was performed to compare the differences in gray matter (GM) and white matter (WM) of healthy participants and AL patients and the differences in IVIM parameters between healthy participants and patients with AL. In addition, multivariate (logistic regression) analyses were used to identify independent predictors and then, the receiver operating characteristic curve (ROC) analyses were performed. Results 40 healthy participants and 49 patients with newly diagnosed AL were evaluated. In healthy participants, sADC, PDR, D and f values of GM were significantly higher than those of WM (t = 5.844, t = 3.838, t = 7.711, z = -2.184, respectively, all P < 0.05). In AL patients, the D, f and sADC values of GM were significantly higher than those of WM (t = 3.450, t = 6.262, t = 4.053, respectively, all P < 0.05). The sADC and f value from AL patients were significantly lower than those from healthy participants in GM (z = -2.537, P = 0.011; and z = -2.583, P = 0.010, respectively) and WM (z = -2.969, P = 0.003; z = -2.923, P = 0.003, respectively). The WBC counts of AL patients were significantly higher than those of healthy participants (t = 3.147, P = 0.002). Multivariate analyses showed that the f values of GM and WM were independent predictors of AL (P = 0.030, and 0.010, respectively), with the optimal cut-off value at 7.08% (AUC ROC curve: 0.661, specificity: 11.4%, sensitivity: 98%) and 13.77% (AUC ROC curve: 0.682, specificity: 79.5%, sensitivity: 59.2%). Conclusion The IVIM parameters of brain parenchyma in patients newly diagnosed with AL differed from those of the healthy participants. The changes of cerebral blood flow perfusion are expected to provide new ideas for studying central nervous system infiltration in AL.
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Affiliation(s)
- Jianing Cui
- Medical Imaging Department, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jing Zheng
- School of Basic Medical Sciences, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Weiran Niu
- Department of Mental Health, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Wenjin Bian
- Medical Imaging Department, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jun Wang
- Department of Radiology, Second Hospital, Shanxi Medical University, Taiyuan, Shanxi, China
| | - Jinliang Niu
- Department of Radiology, Second Hospital, Shanxi Medical University, Taiyuan, Shanxi, China,*Correspondence: Jinliang Niu ✉
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21
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Qin X, Mu R, Zheng W, Li X, Liu F, Zhuang Z, Yang P, Zhu X. Comparison and combination of amide proton transfer magnetic resonance imaging and the apparent diffusion coefficient in differentiating the grades of prostate cancer. Quant Imaging Med Surg 2023; 13:812-824. [PMID: 36819246 PMCID: PMC9929395 DOI: 10.21037/qims-22-721] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Accepted: 11/29/2022] [Indexed: 12/13/2022]
Abstract
Background More effective risk stratification of prostate cancer (PCa) than that possible with current methods can reduce undertreatment and guard against overtreatment. The aim of this study is to validate the differences and combined effects of amide proton transfer (APT) imaging and apparent diffusion coefficient (ADC) in discriminating the PCa grade group (GG) ≤2 from GG ≥3 PCa. Methods This is an ongoing prospective study conducted in the radiology department of Nanxishan Hospital of Guangxi Zhuang Autonomous Region. Patients pathologically diagnosed with PCa were enrolled consecutively according to the eligibility criteria. A total of 180 patients (age range, 42-92 years) were included in this study. Using histopathology as the reference standard, we placed 71 cases in GG ≤2 (mean age 67.03±8.696 years) and 109 cases in GG ≥3 (age 69.60±9.638 years). Magnetic resonance imaging (MRI) parameters, including APT and ADC values, were analyzed using an independent samples t-test and binary logistic regression analysis stratified with GG. Receiver operating characteristic curve was used to analyze the diagnostic performance for different parameters distinguishing GG ≤2 and GG ≥3. Results APT [odds ratio (OR) for the transitional zone (TZ) PCa: 3.20, 95% CI: 1.14-8.98, P=0.02; OR for the peripheral zone (PZ) PCa: 86.32, 95% CI: 13.24-562.88, P=0.003] and ADC values (OR for TZ PCa: 89.79; 95% CI: 2.85-2,827.99, P=0.01; OR for PZ PCa: 39.92; 95% CI: 3.22-494.18, P=0.004) were independent predictors that differentiated the GG of patients. The sensitivity and specificity of the APT values were 61.1% and 81.0%, respectively, while the sensitivity and specificity of the ADC values were 83.3% and 61.9%, respectively. The optimal cutoff value of APT was 3.35% and which of ADC was 1.25×10-3 mm2/s in TZ origin PCa. At the optimal cutoff values of 3.31% (APT) and 0.79×10-3 mm2/s (ADC) in PZ PCa, the sensitivity and specificity of the APT values were 74.0% and 83.6%, respectively, while the sensitivity and specificity of the ADC values were 94.0% and 53.4%, respectively. The area under the curve of the combination of APT and ADC was significantly higher than either of APT or ADC alone in Delong test (TZ: P=0.002 and P=0.020; PZ: P=0.033 and P<0.001). Conclusions APT and ADC have complementary effects on the sensitivity and specificity for identifying different PCa GGs. A combination model of APT and ADC could improve the diagnostic efficacy of PCa differentiation.
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Affiliation(s)
- Xiaoyan Qin
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Ronghua Mu
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Wei Zheng
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China;,Department of Radiology, Graduate School of Guilin Medical University, Guilin, China
| | - Xin Li
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Fuzhen Liu
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Zeyu Zhuang
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China;,Department of Radiology, Graduate School of Guilin Medical University, Guilin, China
| | - Peng Yang
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
| | - Xiqi Zhu
- Department of Radiology, Nanxishan Hospital of Guangxi Zhuang Autonomous Region, Guilin, China
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Zhong Y, Guan J, Ma Y, Xu M, Cheng Y, Xu L, Lin Y, Zhang X, wu R. Role of imaging modalities and N-acetylcysteine treatment in sepsis-associated encephalopathy.. [DOI: 10.21203/rs.3.rs-2459747/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Abstract
Background
Sepsis-associated encephalopathy is a severe complication due to systemic infection. Although early stages involve pathophysiological changes, detection using conventional imaging is challenging. Glutamate chemical exchange saturation transfer and diffusion kurtosis imaging can noninvasively investigate cellular and molecular events in the early stage of the disease by MRI. N-acetylcysteine, an antioxidant and precursor of glutathione, regulates the metabolism of the neurotransmitter glutamate and participates in neuroinflammation. We aimed to investigate the protective role of n-acetylcysteine in sepsis-associated encephalopathy using a rat model and monitor changes in the brain using magnetic resonance molecular imaging.
Methods
Bacterial lipopolysaccharide was injected intraperitoneally into the rats to induce a sepsis-associated encephalopathy model. The behavioural performance was assessed using the open field test. Tumour necrosis factor alpha and glutathione levels were detected biochemically. Imaging was performed using a 7.0-T MRI scanner. Protein expressions and cellular damage were assessed by western blotting and pathological staining, respectively. We also evaluated changes in the blood-brain barrier permeability by the Evans blue staining.
Results
The lipopolysaccharide-induced rats showed reduced anxiety and depression after treatment with n-acetylcysteine. Magnetic resonance molecular imaging can identify pathological processes at different stages of the disease. Furthermore, rats treated with n-acetylcysteine showed increased glutathione levels and decreased tumour necrosis factor alpha, suggesting enhanced antioxidant capacity and inhibition of inflammatory processes, respectively. Western blot analysis showed a reduced expression of nuclear factor kappa B (p50) protein after treatment, suggesting that n-acetylcysteine inhibits inflammation via this signalling pathway. Finally, n-acetylcysteine treated rats also showed reduced cellular damage by pathology and reduced extravasation of their blood-brain barrier by Evan Blue staining.
Conclusion
This study showed that n-acetylcysteine might be a therapeutic option for sepsis-associated encephalopathy and other neuroinflammatory diseases. Furthermore, non-invasive ‘dynamic visual monitoring’ of the physiological and pathological changes related to sepsis-associated encephalopathy was achieved for the first time using magnetic resonance molecular imaging, which provides a more sensitive imaging basis for early clinical diagnosis, identification, and prognosis.
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Affiliation(s)
| | - Jitian Guan
- Second Affiliated Hospital of Shantou University Medical College
| | - Yunfeng Ma
- Second Affiliated Hospital of Shantou University Medical College
| | - Meiling Xu
- Second Affiliated Hospital of Shantou University Medical College
| | - Yan Cheng
- Second Affiliated Hospital of Shantou University Medical College
| | - Liang Xu
- The Seventh Affiliated Hospital of Sun Yat-sen University
| | - Yan Lin
- The Second Hospital of Shandong University
| | - Xiaolei Zhang
- Second Affiliated Hospital of Shantou University Medical College
| | - renhua wu
- Second Affiliated Hospital of Shantou University Medical College
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23
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Wamelink IJ, Kuijer JP, Padrela BE, Zhang Y, Barkhof F, Mutsaerts HJ, Petr J, van de Giessen E, Keil VC. Reproducibility of 3 T APT-CEST in Healthy Volunteers and Patients With Brain Glioma. J Magn Reson Imaging 2023; 57:206-215. [PMID: 35633282 PMCID: PMC10084114 DOI: 10.1002/jmri.28239] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2022] [Revised: 04/28/2022] [Accepted: 04/29/2022] [Indexed: 02/03/2023] Open
Abstract
BACKGROUND Amide proton transfer (APT) imaging is a chemical exchange saturation transfer (CEST) technique offering potential clinical applications such as diagnosis, characterization, and treatment planning and monitoring in glioma patients. While APT-CEST has demonstrated high potential, reproducibility remains underexplored. PURPOSE To investigate whether cerebral APT-CEST with clinically feasible scan time is reproducible in healthy tissue and glioma for clinical use at 3 T. STUDY TYPE Prospective, longitudinal. SUBJECTS Twenty-one healthy volunteers (11 females; mean age ± SD: 39 ± 11 years) and 6 glioma patients (3 females; 50 ± 17 years: 4 glioblastomas, 1 oligodendroglioma, 1 radiologically suspected low-grade glioma). FIELD STRENGTH/SEQUENCE 3 T, Turbo Spin Echo - ampling perfection with application optimized contrasts using different flip angle evolution - chemical exchange saturation transfer (TSE SPACE-CEST). ASSESSMENT APT-CEST measurement reproducibility was assessed within-session (glioma patients, scan session 1; healthy volunteers scan sessions 1, 2, and 3), between-sessions (healthy volunteers scan sessions 1 and 2), and between-days (healthy volunteers, scan sessions 1 and 3). The mean APTCEST values and standard deviation of the within-subject difference (SDdiff ) were calculated in whole tumor enclosed by regions of interest (ROIs) in patients, and eight ROIs in healthy volunteers-whole-brain, cortical gray matter, putamen, thalami, orbitofrontal gyri, occipital lobes, central brain-and compared. STATISTICAL TESTS Brown-Forsythe tests and variance component analysis (VCA) were used to assess the reproducibility of ROIs for the three time intervals. Significance was set at P < 0.003 after Bonferroni correction. RESULTS Intratumoral mean APTCEST was significantly higher than APTCEST in healthy-appearing tissue in patients (0.5 ± 0.46%). The average within-session, between-sessions, and between-days SDdiff of healthy control brains was 0.2% and did not differ significantly with each other (0.76 > P > 0.22). The within-session SDdiff of whole-brain was 0.2% in both healthy volunteers and patients, and 0.21% in the segmented tumor. VCA showed that within-session factors were the most important (60%) for scanning variance. DATA CONCLUSION Cerebral APT-CEST imaging may show good scan-rescan reproducibility in healthy tissue and tumors with clinically feasible scan times at 3 T. Short-term measurement effects may be the dominant components for reproducibility. LEVEL OF EVIDENCE 2 TECHNICAL EFFICACY: Stage 2.
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Affiliation(s)
- Ivar J.H.G. Wamelink
- Department of Radiology and Nuclear MedicineCancer Center Amsterdam, Amsterdam University Medical CenterAmsterdamThe Netherlands
| | - Joost P.A. Kuijer
- Department of Radiology and Nuclear MedicineAmsterdam Neuroscience, Amsterdam University Medical CenterAmsterdamThe Netherlands
| | - Beatriz E. Padrela
- Department of Radiology and Nuclear MedicineAmsterdam Neuroscience, Amsterdam University Medical CenterAmsterdamThe Netherlands
| | - Yi Zhang
- Key Laboratory for Biomedical Engineering of Ministry of Education, Department of Biomedical Engineering, College of Biomedical Engineering & Instrument ScienceZhejiang UniversityHangzhouChina
| | - Frederik Barkhof
- Department of Radiology and Nuclear MedicineAmsterdam Neuroscience, Amsterdam University Medical CenterAmsterdamThe Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image ComputingUniversity College LondonLondonUK
| | - Henk J.M.M. Mutsaerts
- Department of Radiology and Nuclear MedicineAmsterdam Neuroscience, Amsterdam University Medical CenterAmsterdamThe Netherlands
| | - Jan Petr
- Department of Radiology and Nuclear MedicineCancer Center Amsterdam, Amsterdam University Medical CenterAmsterdamThe Netherlands
- Helmholtz‐Zentrum Dresden‐RossendorfInstitute of Radiopharmaceutical Cancer ResearchDresdenGermany
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear MedicineCancer Center Amsterdam, Amsterdam University Medical CenterAmsterdamThe Netherlands
- Department of Radiology and Nuclear MedicineAmsterdam Neuroscience, Amsterdam University Medical CenterAmsterdamThe Netherlands
| | - Vera C. Keil
- Department of Radiology and Nuclear MedicineCancer Center Amsterdam, Amsterdam University Medical CenterAmsterdamThe Netherlands
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Kurz FT, Schlemmer HP. Imaging in translational cancer research. Cancer Biol Med 2022; 19:j.issn.2095-3941.2022.0677. [PMID: 36476372 PMCID: PMC9724222 DOI: 10.20892/j.issn.2095-3941.2022.0677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Accepted: 11/11/2022] [Indexed: 12/12/2022] Open
Abstract
This review is aimed at presenting some of the recent developments in translational cancer imaging research, with a focus on novel, recently established, or soon to be established cross-sectional imaging techniques for computed tomography (CT), magnetic resonance imaging (MRI), and positron-emission tomography (PET) imaging, including computational investigations based on machine-learning techniques.
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Affiliation(s)
- Felix T. Kurz
- Department of Radiology, German Cancer Research Center, Heidelberg 69120, Germany
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25
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Jackson LR, Masi MR, Selman BM, Sandusky GE, Zarrinmayeh H, Das SK, Maharjan S, Wang N, Zheng QH, Pollok KE, Snyder SE, Sun PZ, Hutchins GD, Butch ER, Veronesi MC. Use of multimodality imaging, histology, and treatment feasibility to characterize a transgenic Rag2-null rat model of glioblastoma. Front Oncol 2022; 12:939260. [PMID: 36483050 PMCID: PMC9722958 DOI: 10.3389/fonc.2022.939260] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2022] [Accepted: 10/20/2022] [Indexed: 11/23/2022] Open
Abstract
Many drugs that show potential in animal models of glioblastoma (GBM) fail to translate to the clinic, contributing to a paucity of new therapeutic options. In addition, animal model development often includes histologic assessment, but multiparametric/multimodality imaging is rarely included despite increasing utilization in patient cancer management. This study developed an intracranial recurrent, drug-resistant, human-derived glioblastoma tumor in Sprague-Dawley Rag2-Rag2 tm1Hera knockout rat and was characterized both histologically and using multiparametric/multimodality neuroimaging. Hybrid 18F-fluoroethyltyrosine positron emission tomography and magnetic resonance imaging, including chemical exchange saturation transfer (18F-FET PET/CEST MRI), was performed for full tumor viability determination and characterization. Histological analysis demonstrated human-like GBM features of the intracranially implanted tumor, with rapid tumor cell proliferation (Ki67 positivity: 30.5 ± 7.8%) and neovascular heterogeneity (von Willebrand factor VIII:1.8 to 5.0% positivity). Early serial MRI followed by simultaneous 18F-FET PET/CEST MRI demonstrated consistent, predictable tumor growth, with exponential tumor growth most evident between days 35 and 49 post-implantation. In a second, larger cohort of rats, 18F-FET PET/CEST MRI was performed in mature tumors (day 49 post-implantation) for biomarker determination, followed by evaluation of single and combination therapy as part of the model development and validation. The mean percentage of the injected dose per mL of 18F-FET PET correlated with the mean %CEST (r = 0.67, P < 0.05), but there was also a qualitative difference in hot spot location within the tumor, indicating complementary information regarding the tumor cell demand for amino acids and tumor intracellular mobile phase protein levels. Finally, the use of this glioblastoma animal model for therapy assessment was validated by its increased overall survival after treatment with combination therapy (temozolomide and idasanutlin) (P < 0.001). Our findings hold promise for a more accurate tumor viability determination and novel therapy assessment in vivo in a recently developed, reproducible, intracranial, PDX GBM.
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Affiliation(s)
- Luke R. Jackson
- Department of Radiology and Imaging Sciences, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Megan R. Masi
- Department of Radiology and Imaging Sciences, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Bryce M. Selman
- Department of Pathology and Laboratory Medicine, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - George E. Sandusky
- Department of Pathology and Laboratory Medicine, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Hamideh Zarrinmayeh
- Department of Radiology and Imaging Sciences, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Sudip K. Das
- Department of Pharmaceutical Sciences, Butler University, Indianapolis, IN, United States
| | - Surendra Maharjan
- Department of Radiology and Imaging Sciences, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Qi-Huang Zheng
- Department of Radiology and Imaging Sciences, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Karen E. Pollok
- Department of Pediatrics, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Scott E. Snyder
- Department of Radiology and Imaging Sciences, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Phillip Zhe Sun
- Department of Radiology and Imaging Sciences, Emory School of Medicine, Atlanta, GA, United States
| | - Gary D. Hutchins
- Department of Radiology and Imaging Sciences, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Elizabeth R. Butch
- Department of Radiology and Imaging Sciences, Indiana University (IU) School of Medicine, Indianapolis, IN, United States
| | - Michael C. Veronesi
- Department of Radiology and Imaging Sciences, Indiana University (IU) School of Medicine, Indianapolis, IN, United States,*Correspondence: Michael C. Veronesi,
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26
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B 0 Correction for 3T Amide Proton Transfer (APT) MRI Using a Simplified Two-Pool Lorentzian Model of Symmetric Water and Asymmetric Solutes. Tomography 2022; 8:1974-1986. [PMID: 36006063 PMCID: PMC9412582 DOI: 10.3390/tomography8040165] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 07/17/2022] [Accepted: 07/27/2022] [Indexed: 11/16/2022] Open
Abstract
Amide proton transfer (APT)-weighted MRI is a promising molecular imaging technique that has been employed in clinic for detection and grading of brain tumors. MTRasym, the quantification method of APT, is easily influenced by B0 inhomogeneity and causes artifacts. Current model-free interpolation methods have enabled moderate B0 correction for middle offsets, but have performed poorly at limbic offsets. To address this shortcoming, we proposed a practical B0 correction approach that is suitable under time-limited sparse acquisition scenarios and for B1 ≥ 1 μT under 3T. In this study, this approach employed a simplified Lorentzian model containing only two pools of symmetric water and asymmetric solutes, to describe the Z-spectral shape with wide and ‘invisible’ CEST peaks. The B0 correction was then performed on the basis of the fitted two-pool Lorentzian lines, instead of using conventional model-free interpolation. The approach was firstly evaluated on densely sampled Z-spectra data by using the spline interpolation of all acquired 16 offsets as the gold standard. When only six offsets were available for B0 correction, our method outperformed conventional methods. In particular, the errors at limbic offsets were significantly reduced (n = 8, p < 0.01). Secondly, our method was assessed on the six-offset APT data of nine brain tumor patients. Our MTRasym (3.5 ppm), using the two-pool model, displayed a similar contrast to the vendor-provided B0-orrected MTRasym (3.5 ppm). While the vendor failed in correcting B0 at 4.3 and 2.7 ppm for a large portion of voxels, our method enabled well differentiation of B0 artifacts from tumors. In conclusion, the proposed approach could alleviate analysis errors caused by B0 inhomogeneity, which is useful for facilitating the comprehensive metabolic analysis of brain tumors.
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27
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Wang HJ, Cai Q, Huang YP, Li MQ, Wen ZH, Lin YY, Ouyang LY, Qian L, Guo Y. Amide Proton Transfer-weighted MRI in Predicting Histologic Grade of Bladder Cancer. Radiology 2022; 305:127-134. [PMID: 35762886 DOI: 10.1148/radiol.211804] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Background Bladder cancer is classified into high and low grades with different clinical treatments and prognoses. Thus, accurate preoperative evaluation of the histologic grade through imaging techniques is essential. Purpose To investigate the potential of amide proton transfer-weighted (APTw) MRI in evaluating the grade of bladder cancer and to evaluate whether APTw MRI can add value to diffusion-weighted imaging (DWI) at MRI. Materials and Methods In this single-center prospective study, participants with pathologic analysis-confirmed bladder cancer with no previous treatment, lesions larger than 10 mm, and adequate MRI quality were enrolled from July 2020 to September 2021 in a university teaching hospital. All participants underwent preoperative multiparametric MRI, including APTw MRI and DWI. The mean APTw and apparent diffusion coefficient (ADC) values of the primary tumor were measured independently by two radiologists. Receiver operating characteristic curves were generated to evaluate the diagnostic performance of these quantitative parameters. Results In total, 83 participants (mean age, 64 years ± 13 [SD]; 72 men) were evaluated: 51 with high-grade and 32 with low-grade bladder cancer. High-grade bladder cancer showed higher APTw values (6% [IQR, 4%-12%] vs 2% [IQR, 1%-3%]; P < .001) and lower ADC values (0.92 × 10-3 mm2/sec ± 0.17 vs 1.21 × 10-3 mm2/sec ± 0.25; P < .001) than low-grade bladder cancer. The area under the receiver operating characteristic curve (AUC) of APTw and ADC for differentiating low- and high-grade bladder cancer was similar (0.84 for both; P = .94). Moreover, the combination of the two techniques improved the diagnostic performance (AUC, 0.93; all P = .01). Conclusion The combination of amide proton transfer-weighted and diffusion-weighted MRI has the potential to improve the histologic characterization of bladder cancer by differentiating low- from high-grade cancers. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Milot in this issue.
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Affiliation(s)
- Huanjun J Wang
- From the Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou 510080, PR China (H.J.W., Q.C., Y.H., M.L., Z.W., Y.L., L.O., Y.G.); and Department of MR Research, GE Healthcare, Beijing, PR China (L.Q.)
| | - Qian Cai
- From the Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou 510080, PR China (H.J.W., Q.C., Y.H., M.L., Z.W., Y.L., L.O., Y.G.); and Department of MR Research, GE Healthcare, Beijing, PR China (L.Q.)
| | - Yiping P Huang
- From the Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou 510080, PR China (H.J.W., Q.C., Y.H., M.L., Z.W., Y.L., L.O., Y.G.); and Department of MR Research, GE Healthcare, Beijing, PR China (L.Q.)
| | - Meiqin Q Li
- From the Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou 510080, PR China (H.J.W., Q.C., Y.H., M.L., Z.W., Y.L., L.O., Y.G.); and Department of MR Research, GE Healthcare, Beijing, PR China (L.Q.)
| | - Zhihua H Wen
- From the Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou 510080, PR China (H.J.W., Q.C., Y.H., M.L., Z.W., Y.L., L.O., Y.G.); and Department of MR Research, GE Healthcare, Beijing, PR China (L.Q.)
| | - Yingyu Y Lin
- From the Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou 510080, PR China (H.J.W., Q.C., Y.H., M.L., Z.W., Y.L., L.O., Y.G.); and Department of MR Research, GE Healthcare, Beijing, PR China (L.Q.)
| | - Longyuan Y Ouyang
- From the Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou 510080, PR China (H.J.W., Q.C., Y.H., M.L., Z.W., Y.L., L.O., Y.G.); and Department of MR Research, GE Healthcare, Beijing, PR China (L.Q.)
| | - Long Qian
- From the Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou 510080, PR China (H.J.W., Q.C., Y.H., M.L., Z.W., Y.L., L.O., Y.G.); and Department of MR Research, GE Healthcare, Beijing, PR China (L.Q.)
| | - Yan Guo
- From the Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58 Zhongshan Road 2, Guangzhou 510080, PR China (H.J.W., Q.C., Y.H., M.L., Z.W., Y.L., L.O., Y.G.); and Department of MR Research, GE Healthcare, Beijing, PR China (L.Q.)
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28
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Okada T, Fujimoto K, Fushimi Y, Akasaka T, Thuy DHD, Shima A, Sawamoto N, Oishi N, Zhang Z, Funaki T, Nakamoto Y, Murai T, Miyamoto S, Takahashi R, Isa T. Neuroimaging at 7 Tesla: a pictorial narrative review. Quant Imaging Med Surg 2022; 12:3406-3435. [PMID: 35655840 PMCID: PMC9131333 DOI: 10.21037/qims-21-969] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2021] [Accepted: 02/05/2022] [Indexed: 01/26/2024]
Abstract
Neuroimaging using the 7-Tesla (7T) human magnetic resonance (MR) system is rapidly gaining popularity after being approved for clinical use in the European Union and the USA. This trend is the same for functional MR imaging (MRI). The primary advantages of 7T over lower magnetic fields are its higher signal-to-noise and contrast-to-noise ratios, which provide high-resolution acquisitions and better contrast, making it easier to detect lesions and structural changes in brain disorders. Another advantage is the capability to measure a greater number of neurochemicals by virtue of the increased spectral resolution. Many structural and functional studies using 7T have been conducted to visualize details in the white matter and layers of the cortex and hippocampus, the subnucleus or regions of the putamen, the globus pallidus, thalamus and substantia nigra, and in small structures, such as the subthalamic nucleus, habenula, perforating arteries, and the perivascular space, that are difficult to observe at lower magnetic field strengths. The target disorders for 7T neuroimaging range from tumoral diseases to vascular, neurodegenerative, and psychiatric disorders, including Alzheimer's disease, Parkinson's disease, multiple sclerosis, epilepsy, major depressive disorder, and schizophrenia. MR spectroscopy has also been used for research because of its increased chemical shift that separates overlapping peaks and resolves neurochemicals more effectively at 7T than a lower magnetic field. This paper presents a narrative review of these topics and an illustrative presentation of images obtained at 7T. We expect 7T neuroimaging to provide a new imaging biomarker of various brain disorders.
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Affiliation(s)
- Tomohisa Okada
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Koji Fujimoto
- Department of Real World Data Research and Development, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yasutaka Fushimi
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Thai Akasaka
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Dinh H. D. Thuy
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Atsushi Shima
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Nobukatsu Sawamoto
- Department of Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoya Oishi
- Medial Innovation Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Zhilin Zhang
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeshi Funaki
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yuji Nakamoto
- Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toshiya Murai
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Ryosuke Takahashi
- Department of Neurology, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tadashi Isa
- Human Brain Research Center, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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29
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Liu Y, Li J, Ji H, Zhuang J. Comparisons of Glutamate in the Brains of Alzheimer’s Disease Mice Under Chemical Exchange Saturation Transfer Imaging Based on Machine Learning Analysis. Front Neurosci 2022; 16:838157. [PMID: 35592256 PMCID: PMC9112835 DOI: 10.3389/fnins.2022.838157] [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: 12/17/2021] [Accepted: 03/14/2022] [Indexed: 11/17/2022] Open
Abstract
Chemical exchange saturation transfer (CEST) is one of the molecular magnetic resonance imaging (MRI) techniques that indirectly measures low-concentration metabolite or free protein signals that are difficult to detect by conventional MRI techniques. We applied CEST to Alzheimer’s disease (AD) and analyzed both region of interest (ROI) and pixel dimensions. Through the analysis of the ROI dimension, we found that the content of glutamate in the brains of AD mice was higher than that of normal mice of the same age. In the pixel-dimensional analysis, we obtained a map of the distribution of glutamate in the mouse brain. According to the experimental data of this study, we designed an algorithm framework based on data migration and used Resnet neural network to classify the glutamate distribution images of AD mice, with an accuracy rate of 75.6%. We evaluate the possibility of glutamate imaging as a biomarker for AD detection for the first time, with important implications for the detection and treatment of AD.
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Affiliation(s)
- Yixuan Liu
- Shanghai Yangzhi Rehabilitation Hospital Shanghai Sunshine Rehabilitation Center, College of Electronics and Information Engineering, Tongji University, Shanghai, China
| | - Jie Li
- Shanghai Yangzhi Rehabilitation Hospital Shanghai Sunshine Rehabilitation Center, College of Electronics and Information Engineering, Tongji University, Shanghai, China
- *Correspondence: Jie Li,
| | - Hongfei Ji
- Shanghai Yangzhi Rehabilitation Hospital Shanghai Sunshine Rehabilitation Center, College of Electronics and Information Engineering, Tongji University, Shanghai, China
- Hongfei Ji, ; orcid.org/0000-0002-2759-7084
| | - Jie Zhuang
- School of Psychology, Shanghai University of Sport, Shanghai, China
- Jie Zhuang, ; orcid.org/0000-0002-3316-5536
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30
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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: 101] [Impact Index Per Article: 33.7] [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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31
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Kumar M, Nanga RPR, Verma G, Wilson N, Brisset JC, Nath K, Chawla S. Emerging MR Imaging and Spectroscopic Methods to Study Brain Tumor Metabolism. Front Neurol 2022; 13:789355. [PMID: 35370872 PMCID: PMC8967433 DOI: 10.3389/fneur.2022.789355] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2021] [Accepted: 01/31/2022] [Indexed: 11/13/2022] Open
Abstract
Proton magnetic resonance spectroscopy (1H-MRS) provides a non-invasive biochemical profile of brain tumors. The conventional 1H-MRS methods present a few challenges mainly related to limited spatial coverage and low spatial and spectral resolutions. In the recent past, the advent and development of more sophisticated metabolic imaging and spectroscopic sequences have revolutionized the field of neuro-oncologic metabolomics. In this review article, we will briefly describe the scientific premises of three-dimensional echoplanar spectroscopic imaging (3D-EPSI), two-dimensional correlation spectroscopy (2D-COSY), and chemical exchange saturation technique (CEST) MRI techniques. Several published studies have shown how these emerging techniques can significantly impact the management of patients with glioma by determining histologic grades, molecular profiles, planning treatment strategies, and assessing the therapeutic responses. The purpose of this review article is to summarize the potential clinical applications of these techniques in studying brain tumor metabolism.
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Affiliation(s)
- Manoj Kumar
- Department of Neuroimaging and Interventional Radiology, National Institute of Mental Health and Neurosciences, Bengaluru, India
| | - Ravi Prakash Reddy Nanga
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Gaurav Verma
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, United States
| | - Neil Wilson
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | | | - Kavindra Nath
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
- *Correspondence: Sanjeev Chawla
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32
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Lingl JP, Wunderlich A, Goerke S, Paech D, Ladd ME, Liebig P, Pala A, Kim SY, Braun M, Schmitz BL, Beer M, Rosskopf J. The Value of APTw CEST MRI in Routine Clinical Assessment of Human Brain Tumor Patients at 3T. Diagnostics (Basel) 2022; 12:diagnostics12020490. [PMID: 35204583 PMCID: PMC8871436 DOI: 10.3390/diagnostics12020490] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2022] [Revised: 02/08/2022] [Accepted: 02/10/2022] [Indexed: 12/10/2022] Open
Abstract
Background. With fast-growing evidence in literature for clinical applications of chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI), this prospective study aimed at applying amide proton transfer-weighted (APTw) CEST imaging in a clinical setting to assess its diagnostic potential in differentiation of intracranial tumors at 3 tesla (T). Methods. Using the asymmetry magnetization transfer ratio (MTRasym) analysis, CEST signals were quantitatively investigated in the tumor areas and in a similar sized region of the normal-appearing white matter (NAWM) on the contralateral hemisphere of 27 patients with intracranial tumors. Area under curve (AUC) analyses were used and results were compared to perfusion-weighted imaging (PWI). Results. Using APTw CEST, contrast-enhancing tumor areas showed significantly higher APTw CEST metrics than contralateral NAWM (AUC = 0.82; p < 0.01). In subgroup analyses of each tumor entity vs. NAWM, statistically significant effects were yielded for glioblastomas (AUC = 0.96; p < 0.01) and for meningiomas (AUC = 1.0; p < 0.01) but not for lymphomas as well as metastases (p > 0.05). PWI showed results comparable to APTw CEST in glioblastoma (p < 0.01). Conclusions. This prospective study confirmed the high diagnostic potential of APTw CEST imaging in a routine clinical setting to differentiate brain tumors.
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Affiliation(s)
- Julia P. Lingl
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
| | - Arthur Wunderlich
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
| | - Steffen Goerke
- German Cancer Research Center (DKFZ), Department of Medical Physics in Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany; (S.G.); (M.E.L.)
| | - Daniel Paech
- German Cancer Research Center (DKFZ), Division of Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany;
- Department of Neuroradiology, Venusberg-Campus 1, Bonn University, 53127 Bonn, Germany
| | - Mark E. Ladd
- German Cancer Research Center (DKFZ), Department of Medical Physics in Radiology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany; (S.G.); (M.E.L.)
- Faculty of Medicine, University of Heidelberg, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
- Faculty of Physics and Astronomy, University of Heidelberg, Im Neuenheimer Feld 226, 69120 Heidelberg, Germany
| | - Patrick Liebig
- Siemens Healthcare GmbH, Henkestraße 127, 91052 Erlangen, Germany;
| | - Andrej Pala
- Department of Neurosurgery, Bezirkskrankenhaus Guenzburg, Lindenallee 2, 89312 Guenzburg, Germany;
| | - Soung Yung Kim
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
- Section of Neuroradiology, Bezirkskrankenhaus Guenzburg, Lindenallee 2, 89312 Guenzburg, Germany
| | - Michael Braun
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
- Section of Neuroradiology, Bezirkskrankenhaus Guenzburg, Lindenallee 2, 89312 Guenzburg, Germany
| | - Bernd L. Schmitz
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
- Section of Neuroradiology, Bezirkskrankenhaus Guenzburg, Lindenallee 2, 89312 Guenzburg, Germany
| | - Meinrad Beer
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
| | - Johannes Rosskopf
- Department of Radiology, Ulm University, Albert-Einstein-Allee 23, 89081 Ulm, Germany; (J.P.L.); (A.W.); (S.Y.K.); (M.B.); (B.L.S.); (M.B.)
- Section of Neuroradiology, Bezirkskrankenhaus Guenzburg, Lindenallee 2, 89312 Guenzburg, Germany
- Correspondence:
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Ye X, Schreck KC, Ozer BH, Grossman SA. High-grade glioma therapy: adding flexibility in trial design to improve patient outcomes. Expert Rev Anticancer Ther 2022; 22:275-287. [PMID: 35130447 DOI: 10.1080/14737140.2022.2038138] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Outcomes for patients with high grade gliomas have changed little over the past thirty years. This realization prompted renewed efforts to increase flexibility in the design and conduct of clinical brain tumor trials. AREAS COVERED This manuscript reviews the development of clinical trial methods, challenges and considerations of flexible clinical trial designs, approaches to improve identification and testing of active agents for high grade gliomas, and evaluation of their delivery to the central nervous system. EXPERT OPINION Flexibility can be introduced in clinical trials in several ways. Flexible designs tout smaller sample sizes, adaptive modifications, fewer control arms, and inclusion of multiple arms in one study. Unfortunately, modifications in study designs cannot address two challenges that are largely responsible for the lack of progress in treating high grade gliomas: 1) the identification of active pharmaceutical agents and 2) the delivery of these agents to brain tumor tissue in therapeutic concentrations. To improve the outcomes of patients with high grade gliomas efforts must be focused on the pre-clinical screening of drugs for activity, the ability of these agents to achieve therapeutic concentrations in non-enhancing tumors, and a willingness to introduce novel compounds in minimally pre-treated patient populations.
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Affiliation(s)
- Xiaobu Ye
- The Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore MD, USA
| | - Karisa C Schreck
- The Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore MD, USA
| | - Byram H Ozer
- The Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore MD, USA
| | - Stuart A Grossman
- The Johns Hopkins University School of Medicine and Sidney Kimmel Comprehensive Cancer Center, Baltimore MD, USA
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Yuan J, Poon DMC, Lo G, Wong OL, Cheung KY, Yu SK. A narrative review of MRI acquisition for MR-guided-radiotherapy in prostate cancer. Quant Imaging Med Surg 2022; 12:1585-1607. [PMID: 35111651 PMCID: PMC8739116 DOI: 10.21037/qims-21-697] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2021] [Accepted: 08/20/2021] [Indexed: 08/24/2023]
Abstract
Magnetic resonance guided radiotherapy (MRgRT), enabled by the clinical introduction of the integrated MRI and linear accelerator (MR-LINAC), is a novel technique for prostate cancer (PCa) treatment, promising to further improve clinical outcome and reduce toxicity. The role of prostate MRI has been greatly expanded from the traditional PCa diagnosis to also PCa screening, treatment and surveillance. Diagnostic prostate MRI has been relatively familiar in the community, particularly with the development of Prostate Imaging - Reporting and Data System (PI-RADS). But, on the other hand, the use of MRI in the emerging clinical practice of PCa MRgRT, which is substantially different from that in PCa diagnosis, has been so far sparsely presented in the medical literature. This review attempts to give a comprehensive overview of MRI acquisition techniques currently used in the clinical workflows of PCa MRgRT, from treatment planning to online treatment guidance, in order to promote MRI practice and research for PCa MRgRT. In particular, the major differences in the MRI acquisition of PCa MRgRT from that of diagnostic prostate MRI are demonstrated and explained. Limitations in the current MRI acquisition for PCa MRgRT are analyzed. The future developments of MRI in the PCa MRgRT are also discussed.
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Affiliation(s)
- Jing Yuan
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Darren M. C. Poon
- Comprehensive Oncology Centre, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Gladys Lo
- Department of Diagnostic & Interventional Radiology, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Oi Lei Wong
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Kin Yin Cheung
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
| | - Siu Ki Yu
- Medical Physics and Research Department, Hong Kong Sanatorium & Hospital, Hong Kong, China
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35
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Rezaeian N. Cardiac MRI imaging in heart failure with preserved ejection fraction. Trends Cardiovasc Med 2022; 33:148-149. [PMID: 34986428 DOI: 10.1016/j.tcm.2021.12.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 12/28/2021] [Indexed: 10/19/2022]
Affiliation(s)
- Nahid Rezaeian
- Rajaie Cardiovascular Medical and Research Center, Iran University of Medical sciences, Tehran, Iran.
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36
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Dennis EL, Baron D, Bartnik‐Olson B, Caeyenberghs K, Esopenko C, Hillary FG, Kenney K, Koerte IK, Lin AP, Mayer AR, Mondello S, Olsen A, Thompson PM, Tate DF, Wilde EA. ENIGMA brain injury: Framework, challenges, and opportunities. Hum Brain Mapp 2022; 43:149-166. [PMID: 32476212 PMCID: PMC8675432 DOI: 10.1002/hbm.25046] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2019] [Revised: 04/23/2020] [Accepted: 05/03/2020] [Indexed: 12/19/2022] Open
Abstract
Traumatic brain injury (TBI) is a major cause of disability worldwide, but the heterogeneous nature of TBI with respect to injury severity and health comorbidities make patient outcome difficult to predict. Injury severity accounts for only some of this variance, and a wide range of preinjury, injury-related, and postinjury factors may influence outcome, such as sex, socioeconomic status, injury mechanism, and social support. Neuroimaging research in this area has generally been limited by insufficient sample sizes. Additionally, development of reliable biomarkers of mild TBI or repeated subconcussive impacts has been slow, likely due, in part, to subtle effects of injury and the aforementioned variability. The ENIGMA Consortium has established a framework for global collaboration that has resulted in the largest-ever neuroimaging studies of multiple psychiatric and neurological disorders. Here we describe the organization, recent progress, and future goals of the Brain Injury working group.
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Affiliation(s)
- Emily L. Dennis
- Department of NeurologyUniversity of Utah School of MedicineSalt Lake CityUtahUSA
- George E. Wahlen Veterans Affairs Medical CenterSalt Lake CityUtahUSA
- Imaging Genetics CenterStevens Neuroimaging & Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
| | - David Baron
- Western University of Health SciencesPomonaCaliforniaUSA
| | - Brenda Bartnik‐Olson
- Department of RadiologyLoma Linda University Medical CenterLoma LindaCaliforniaUSA
| | - Karen Caeyenberghs
- Cognitive Neuroscience Unit, School of PsychologyDeakin UniversityBurwoodVictoriaAustralia
| | - Carrie Esopenko
- Department of Rehabilitation and Movement SciencesRutgers Biomedical Health SciencesNewarkNew JerseyUSA
| | - Frank G. Hillary
- Department of PsychologyPennsylvania State UniversityUniversity ParkPennsylvaniaUSA
- Social Life and Engineering Sciences Imaging CenterUniversity ParkPennsylvaniaUSA
| | - Kimbra Kenney
- Department of NeurologyUniformed Services University of the Health SciencesBethesdaMarylandUSA
- National Intrepid Center of ExcellenceWalter Reed National Military Medical CenterBethesdaMarylandUSA
| | - Inga K. Koerte
- Psychiatry Neuroimaging LaboratoryBrigham and Women's HospitalBostonMassachusettsUSA
- Department of Child and Adolescent Psychiatry, Psychosomatics and PsychotherapyLudwig‐Maximilians‐UniversitätMunichGermany
| | - Alexander P. Lin
- Center for Clinical SpectroscopyBrigham and Women's Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Andrew R. Mayer
- Mind Research NetworkAlbuquerqueNew MexicoUSA
- Department of Neurology and PsychiatryUniversity of New Mexico School of MedicineAlbuquerqueNew MexicoUSA
| | - Stefania Mondello
- Department of Biomedical and Dental Sciences and Morphofunctional ImagingUniversity of MessinaMessinaItaly
| | - Alexander Olsen
- Department of PsychologyNorwegian University of Science and TechnologyTrondheimNorway
- Department of Physical Medicine and RehabilitationSt. Olavs Hospital, Trondheim University HospitalTrondheimNorway
| | - Paul M. Thompson
- Imaging Genetics CenterStevens Neuroimaging & Informatics Institute, Keck School of Medicine of USCMarina del ReyCaliforniaUSA
- Department of Neurology, Pediatrics, Psychiatry, Radiology, Engineering, and OphthalmologyUniversity of Southern California (USC)Los AngelesCaliforniaUSA
| | - David F. Tate
- Department of NeurologyUniversity of Utah School of MedicineSalt Lake CityUtahUSA
- George E. Wahlen Veterans Affairs Medical CenterSalt Lake CityUtahUSA
| | - Elisabeth A. Wilde
- Department of NeurologyUniversity of Utah School of MedicineSalt Lake CityUtahUSA
- George E. Wahlen Veterans Affairs Medical CenterSalt Lake CityUtahUSA
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Chen S, Liu X, Lin J, Mei Y, Deng K, Xue Q, Song X, Xu Y. Application of amide proton transfer imaging for the diagnosis of neonatal hypoxic-ischemic encephalopathy. Front Pediatr 2022; 10:996949. [PMID: 36440343 PMCID: PMC9691961 DOI: 10.3389/fped.2022.996949] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 10/25/2022] [Indexed: 11/13/2022] Open
Abstract
OBJECTIVE This study aimed to evaluate cerebral amide proton transfer signal intensity (SI) among controls, hypoxic-ischemic encephalopathy (HIE) neonates with normal conventional magnetic resonance imaging (HIE/MRI-) findings, and HIE neonates with abnormal conventional MRI (HIE/MRI+) findings. METHODS Forty neonates diagnosed with neonatal HIE and sixteen normal neonates were evaluated. All neonates underwent conventional MRI scans and APT imaging. Cerebral APT SIs were compared to identify cerebral regions with significant APT changes among sixteen controls, thirteen HIE/MRI- patients, and twenty-seven HIE/MRI+ patients. RESULTS Significantly increased APT SIs were observed in the HIE/MRI- group compared with controls, in the left insula, right occipital lobe, left cingulate gyrus (posterior part), and corpus callosum. Significantly increased APT SIs were found in the HIE/MRI+ group compared with controls, in the right anterior temporal lobe (medial part), anterior parts of the right parahippocampal and ambient gyri, left superior temporal gyrus (middle part), left insula, left cingulate gyrus (posterior part), and right lentiform nucleus. No significant APT SI differences were observed in the cerebellum and brainstem among the three groups. CONCLUSION Amide proton transfer imaging plays an important role in detecting hypoxic-ischemic encephalopathy regardless of conventional MRI findings. Changes in APT signal intensity may provide important insights into the characterization of the cerebral internal environment. This study suggests that APT imaging could be used as a complement to conventional MRI in the detection of hypoxic-ischemic encephalopathy in clinical practice.
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Affiliation(s)
- Sijin Chen
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China.,Department of Obstetrics & Gynecology, Nanfang Hospital Baiyun Branch, Southern Medical University, Guangzhou, China
| | - Xilong Liu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jie Lin
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yingjie Mei
- School of Biomedical Engineering, Southern Medical University, Guangzhou, China
| | - Kan Deng
- C&TS MR Clinical Science, Philips Healthcare, Guangzhou, China
| | - Qiao Xue
- Helong Street Community Health Service Center, Guangzhou, China
| | - Xiaoyan Song
- Department of Neonatology, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yikai Xu
- Department of Medical Imaging Center, Nanfang Hospital, Southern Medical University, Guangzhou, China
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Heart failure with preserved ejection fraction assessed by cardiac magnetic resonance: From clinical uses to emerging techniques. Trends Cardiovasc Med 2021; 33:141-147. [PMID: 34933114 DOI: 10.1016/j.tcm.2021.12.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2021] [Revised: 12/07/2021] [Accepted: 12/15/2021] [Indexed: 12/30/2022]
Abstract
Patients with heart failure with preserved ejection fraction (HFpEF) account for approximately 50% of those with heart failure (HF) and have increased morbidity and mortality when compared to those with HF with reduced ejection fraction. Currently, the pathophysiology and diagnostic criteria for HFpEF remain unclear, contributing significantly to delays in creating a beneficial and tailored treatment that can improve the prognosis of HFpEF. A multitude of studies have exclusively tested and illustrated the diagnostic value of echocardiography imaging in HFpEF; however, a widely-accepted criterion to identify HFpEF using cardiovascular magnetic resonance (CMR) imaging has not been established. As the gold standard for cardiac structural, functional measurement, and tissue characterization, CMR holds great potential for the early discovery of the pathophysiology, diagnosis, and risk stratification of HFpEF. This review aims to comprehensively discuss the diagnostic and prognostic role of CMR parameters in the setting of HFpEF through validated routine and prospective emerging techniques, and provide clinical perspectives for CMR imaging application in HFpEF.
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39
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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: 13] [Impact Index Per Article: 3.3] [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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40
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Schmitz-Abecassis B, Vinogradov E, Wijnen JP, van Harten T, Wiegers EC, Hoogduin H, van Osch MJP, Ercan E. The use of variable delay multipulse chemical exchange saturation transfer for separately assessing different CEST pools in the human brain at 7T. Magn Reson Med 2021; 87:872-883. [PMID: 34520077 PMCID: PMC9290048 DOI: 10.1002/mrm.29005] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 08/19/2021] [Accepted: 08/23/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE Current challenges of in vivo CEST imaging include overlapping signals from different pools. The overlap arises from closely resonating pools and/or the broad magnetization transfer contrast (MTC) from macromolecules. This study aimed to evaluate the feasibility of variable delay multipulse (VDMP) CEST to separately assess solute pools with different chemical exchange rates in the human brain in vivo, while mitigating the MTC. METHODS VDMP saturation buildup curves were simulated for amines, amides, and relayed nuclear Overhauser effect. VDMP data were acquired from glutamate and bovine serum albumin phantoms, and from six healthy volunteers at 7T. For the in vivo data, MTC removal was performed via a three-pool Lorentzian fitting. Different B1 amplitudes and mixing times were used to evaluate CEST pools with different exchange rates. RESULTS The results show the importance of removing MTC when applying VDMP in vivo and the influence of B1 for distinguishing different pools. Finally, the optimal B1 and mixing times to effectively saturate slow- and fast-exchanging components are also reported. Slow-exchanging amides and rNOE components could be distinguished when using B1 = 1 μT and tmix = 10 ms and 40 ms, respectively. Fast-exchanging components reached the highest saturation when using a B1 = 2.8 μT and tmix = 0 ms. CONCLUSION VDMP is a powerful CEST-editing tool, exploiting chemical exchange-rate differences. After MTC removal, it allows separate assessment of slow- and fast-exchanging solute pools in in vivo human brain.
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Affiliation(s)
- Bárbara Schmitz-Abecassis
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Elena Vinogradov
- Department of Radiology, UT Southwestern Medical Center, Dallas, Texas, USA.,Advanced Imaging Research Center, UT Southwestern Medical Center, Dallas, Texas, USA
| | - Jannie P Wijnen
- Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Thijs van Harten
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Evita C Wiegers
- Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Hans Hoogduin
- Imaging Division, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Matthias J P van Osch
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
| | - Ece Ercan
- C.J. Gorter Center for High Field MRI, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
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Morrison MA, Lupo JM. 7-T Magnetic Resonance Imaging in the Management of Brain Tumors. Magn Reson Imaging Clin N Am 2021; 29:83-102. [PMID: 33237018 DOI: 10.1016/j.mric.2020.09.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
This article provides an overview of the current status of ultrahigh-field 7-T magnetic resonance (MR) imaging in neuro-oncology, specifically for the management of patients with brain tumors. It includes a discussion of areas across the pretherapeutic, peritherapeutic, and posttherapeutic stages of patient care where 7-T MR imaging is currently being exploited and holds promise. This discussion includes existing technical challenges, barriers to clinical integration, as well as our impression of the future role of 7-T MR imaging as a clinical tool in neuro-oncology.
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Affiliation(s)
- Melanie A Morrison
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, 505 Parnassus Avenue, San Francisco, CA 94143, USA
| | - Janine M Lupo
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, 505 Parnassus Avenue, San Francisco, CA 94143, USA.
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Zaccagna F, Grist JT, Quartuccio N, Riemer F, Fraioli F, Caracò C, Halsey R, Aldalilah Y, Cunningham CH, Massoud TF, Aloj L, Gallagher FA. Imaging and treatment of brain tumors through molecular targeting: Recent clinical advances. Eur J Radiol 2021; 142:109842. [PMID: 34274843 DOI: 10.1016/j.ejrad.2021.109842] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Accepted: 06/24/2021] [Indexed: 02/07/2023]
Abstract
Molecular imaging techniques have rapidly progressed over recent decades providing unprecedented in vivo characterization of metabolic pathways and molecular biomarkers. Many of these new techniques have been successfully applied in the field of neuro-oncological imaging to probe tumor biology. Targeting specific signaling or metabolic pathways could help to address several unmet clinical needs that hamper the management of patients with brain tumors. This review aims to provide an overview of the recent advances in brain tumor imaging using molecular targeting with positron emission tomography and magnetic resonance imaging, as well as the role in patient management and possible therapeutic implications.
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Affiliation(s)
- Fulvio Zaccagna
- Division of Neuroimaging, Department of Medical Imaging, University of Toronto, Toronto, Canada.
| | - James T Grist
- Department of Physiology, Anatomy, and Genetics, University of Oxford, Oxford, United Kingdom; Oxford Centre for Clinical Magnetic Resonance Research, University of Oxford, Oxford, United Kingdom; Department of Radiology, Oxford University Hospitals NHS Foundation Trust, Oxford, United Kingdom; Institute of Cancer and Genomic Sciences, University of Birmingham, Birmingham, United Kingdom
| | - Natale Quartuccio
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico Di Cristina Benfratelli, Palermo, Italy
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre, University of Bergen, Bergen, Norway; Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Francesco Fraioli
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Corradina Caracò
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom
| | - Richard Halsey
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom
| | - Yazeed Aldalilah
- Institute of Nuclear Medicine, University College London, London, United Kingdom; NIHR University College London Hospitals Biomedical Research Centre, London, United Kingdom; Department of Radiology, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia
| | - Charles H Cunningham
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Physical Sciences, Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Tarik F Massoud
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, USA
| | - Luigi Aloj
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
| | - Ferdia A Gallagher
- Department of Radiology, University of Cambridge, Cambridge, United Kingdom; Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, United Kingdom
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BADE AN, GENDELMAN HE, MCMILLAN J, LIU Y. Chemical exchange saturation transfer for detection of antiretroviral drugs in brain tissue. AIDS 2021; 35:1733-1741. [PMID: 34049358 PMCID: PMC8373768 DOI: 10.1097/qad.0000000000002960] [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] [Indexed: 10/21/2022]
Abstract
OBJECTIVE Antiretroviral drug theranostics facilitates the monitoring of biodistribution and efficacy of therapies designed to target HIV type-1 (HIV-1) reservoirs. To this end, we have now deployed intrinsic drug chemical exchange saturation transfer (CEST) contrasts to detect antiretroviral drugs within the central nervous system (CNS). DESIGN AND METHODS CEST effects for lamivudine (3TC) and emtricitabine (FTC) were measured by asymmetric magnetization transfer ratio analyses. The biodistribution of 3TC in different brain sub-regions of C57BL/6 mice treated with lipopolysaccharides was determined using MRI. CEST effects of 3TC protons were quantitated by Lorentzian fitting analysis. 3TC levels in plasma and brain regions were measured using ultraperformance liquid chromatography tandem mass spectrometry to affirm the CEST test results. RESULTS CEST effects of the hydroxyl and amino protons in 3TC and FTC linearly correlated to drug concentrations. 3TC was successfully detected in vivo in brain sub-regions by MRI. The imaging results were validated by measurements of CNS drug concentrations. CONCLUSION CEST contrasts can be used to detect antiretroviral drugs using MRI. Such detection can be used to assess spatial--temporal drug biodistribution. This is most notable within the CNS where drug biodistribution may be more limited with the final goal of better understanding antiretroviral drug-associated efficacy and potential toxicity.
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Affiliation(s)
- Aditya N. BADE
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE 68198 USA
| | - Howard E. GENDELMAN
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE 68198 USA
| | - JoEllyn MCMILLAN
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE 68198 USA
| | - Yutong LIU
- Department of Pharmacology and Experimental Neuroscience, University of Nebraska Medical Center, Omaha, NE 68198 USA
- Department of Radiology, University of Nebraska Medical Center, Omaha, NE 68198 USA
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44
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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: 1.0] [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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Su C, Li S, Chen X, Liu C, Shaghaghi M, Jiang J, Zhang S, Qin Y, Cai K. Predicting cancer malignancy and proliferation in glioma patients: intra-subject inter-metabolite correlation analyses using MRI and MRSI contrast scans. Quant Imaging Med Surg 2021; 11:2721-2732. [PMID: 34079736 DOI: 10.21037/qims-20-1163] [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: 11/06/2022]
Abstract
Background The non-invasive characterization of glioma metabolites would greatly assist the management of glioma patients in the clinical setting. This study investigated the applicability of intra-subject inter-metabolite correlation analyses for differentiating glioma malignancy and proliferation. Methods A total of 17 negative controls (NCs), 39 low-grade gliomas (LGGs) patients, and 25 high-grade gliomas (HGGs) subjects were included in this retrospective study. Amide proton transfer (APT) and magnetization transfer contrast (MTC) imaging contrasts, as well as total choline/total creatine (tCho/tCr) and total N-acetylaspartate/total creatine (tNAA/tCr) ratios quantified from magnetic resonance spectroscopic imaging (MRSI) were co-registered voxel-wise and used to produce three intra-subject inter-metabolite correlation coefficients (IMCCs), namely, RAPT vs . MTC, RAPT vs . tCho/tCr, and RMTC vs . tNAA/tCr. The correlation between the IMCCs and tumor grade and Ki-67 labeling index (LI) for tumor proliferation were explored. The differences in the IMCCs between the three groups were compared with one-way analysis of variance (ANOVA). Finally, regression analysis was used to build a combined model with multiple IMCCs to improve the diagnostic performance for tumor grades based on receiver operator characteristic curves. Results Compared with the NCs, gliomas showed stronger inter-metabolic correlations. RAPT vs . MTC was significantly different among the three groups (NC vs. LGGs vs. HGGs: -0.18±0.38 vs. -0.40±0.34 vs. -0.70±0.29, P<0.0001). No significant differences were detected in RMTC vs . tNAA/tCr among the three groups. RAPT vs . MTC and RAPT vs . tCho/tCr correlated significantly with tumor grade (R=-0.41, P=0.001 and R=0.448, P<0.001, respectively). However, only RAPT vs . MTC was mildly correlated with Ki-67 (R=-0.33, P=0.02). RAPT vs . MTC and RAPT vs . tCho/tCr achieved areas under the curve (AUCs) of 0.754 and 0.71, respectively, for differentiating NCs from gliomas; and 0.77 and 0.78, respectively, for differentiating LGGs from HGGs. The combined multi-IMCCs model improved the correlation with the Ki-67 LI (R=0.46, P=0.0008) and the tumor-grade stratification with AUC increased to 0.85 (sensitivity: 80.0%, specificity: 79.5%). Conclusions This study demonstrated that glioma patients showed stronger inter-metabolite correlations than control subjects, and the IMCCs were significantly correlated with glioma grade and proliferation. The multi-IMCCs combined model further improved the performance of clinical diagnosis.
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Affiliation(s)
- Changliang Su
- Department of Medical Imaging, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Shihui Li
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xiaowei Chen
- Department of Radiology, The Central Hospital of Wuhan, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chengxia Liu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Mehran Shaghaghi
- Department of Radiology, the University of Illinois at Chicago, Chicago, Illinois, USA
| | - Jingjing Jiang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shun Zhang
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuanyuan Qin
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kejia Cai
- Department of Radiology, the University of Illinois at Chicago, Chicago, Illinois, USA
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Chen Y, Wang X, Su T, Xu Z, Wang Y, Zhang Z, Xue H, Zhuo Z, Zhu Y, Jin Z, Zhang T. Feasibility evaluation of amide proton transfer-weighted imaging in the parotid glands: a strategy to recognize artifacts and measure APT value. Quant Imaging Med Surg 2021; 11:2279-2291. [PMID: 34079701 DOI: 10.21037/qims-20-675] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Background The feasibility and image quality of three-dimensional (3D) amide proton transfer (APT)-weighted (APTw) in parotid tumor lesions have not been well established in previous studies. This study aimed to evaluate the utility of APT imaging in parotid lesions and glands. Methods Patients with parotid lesions received 3D turbo spin echo (TSE) APTw on a 3.0T scanner. Two radiologists, who were blinded to the clinical data, independently evaluated the APTw image quality using 4-point Likert scales (1= poor, 4= excellent) in terms of integrity and hyperintensity artifacts. An image quality selection protocol was built based on the two scores. Evaluable images (integrity score >1) and trustable images (integrity score >3 and hyperintensity artifacts score >2) were then enrolled for APTw value comparison between parotid lesions and glands. Results Forty consecutive patients were included in this study. Four patients were excluded due to severe motion (n=3) or dental (n=1) artifacts, and 36 patients received the APT sequence. Among these, more parotid tumor lesions (34/36, 94.4%) than normal parotid glands (23/31, 74.2%) revealed excellent integrity scores (score =4) (P=0.034). Most parotid tumor lesions (24/34, 70.6%) and glands (16/28, 57.1%) revealed no or little hyperintensity artifacts for diagnosis (scores 3 and 4). APT values of parotid lesions and glands in the evaluable groups were 2.11%±1.15% and 1.60%±1.56%, respectively, and the difference was not significant (P=0.197). APT values of parotid lesions and glands in the trustable groups were 1.99%±1.18% and 1.03%±1.09%, respectively, and the difference was statistically significant (P=0.018). Conclusions 3D APTw could be used to differentiate parotid tumors and normal parotid glands; however, the technology still needs to be improved to remove artifacts. In our study, most APTw images of tumor lesions in parotid glands had acceptable image quality, and these APTw images are feasible for diagnostic use.
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Affiliation(s)
- Yu Chen
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | | | - Tong Su
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhentan Xu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Yunting Wang
- Department of Stomatology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhuhua Zhang
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Huadan Xue
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | | | - Yuanli Zhu
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Zhengyu Jin
- Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
| | - Tao Zhang
- Department of Stomatology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, China
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Abstract
Magnetic resonance (MR) imaging is a crucial tool for evaluation of the skull base, enabling characterization of complex anatomy by utilizing multiple image contrasts. Recent technical MR advances have greatly enhanced radiologists' capability to diagnose skull base pathology and help direct management. In this paper, we will summarize cutting-edge clinical and emerging research MR techniques for the skull base, including high-resolution, phase-contrast, diffusion, perfusion, vascular, zero echo-time, elastography, spectroscopy, chemical exchange saturation transfer, PET/MR, ultra-high-field, and 3D visualization. For each imaging technique, we provide a high-level summary of underlying technical principles accompanied by relevant literature review and clinical imaging examples.
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Affiliation(s)
- Claudia F Kirsch
- Division Chief, Neuroradiology, Professor of Neuroradiology and Otolaryngology, Department of Radiology, Northwell Health, Zucker Hofstra School of Medicine at Northwell, North Shore University Hospital, Manhasset, NY
| | - Mai-Lan Ho
- Associate Professor of Radiology, Director of Research, Department of Radiology, Director, Advanced Neuroimaging Core, Chair, Asian Pacific American Network, Secretary, Association for Staff and Faculty Women, Nationwide Children's Hospital and The Ohio State University, Columbus, OH; Division Chief, Neuroradiology, Professor of Neuroradiology and Otolaryngology, Department of Radiology, Northwell Health, Zucker Hofstra School of Medicine at Northwell, North Shore University Hospital, Manhasset, NY.
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Autissier R, Mazuel L, Maubert E, Bonny JM, Auzeloux P, Schmitt S, Traoré A, Peyrode C, Miot-Noirault E, Pagés G. Simultaneous proteoglycans and hypoxia mapping of chondrosarcoma environment by frequency selective CEST MRI. Magn Reson Med 2021; 86:1008-1018. [PMID: 33772858 DOI: 10.1002/mrm.28781] [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: 12/17/2020] [Revised: 03/01/2021] [Accepted: 03/04/2021] [Indexed: 11/10/2022]
Abstract
PURPOSE To evaluate the relevance of CEST frequency selectivity in simultaneous in vivo imaging of both of chondrosarcoma's phenotypic features, that are, its high proteoglycan concentration and its hypoxic core. METHODS Swarm rat chondrosarcomas were implanted subcutaneously in NMRI nude mice. When tumors were measurable (12-16 days postoperative), mice were submitted to GAG, guanidyl, and APT CEST imaging. Proteoglycans and hypoxia were assessed in parallel by nuclear imaging exploiting 99m Tc-NTP 15-5 and 18 F-FMISO, respectively. Data were completed by ex vivo analysis of proteoglycans (histology and biochemical assay) and hypoxia (immunofluorescence). RESULTS Quantitative analysis of GAG CEST evidenced a significantly higher signal for tumor tissues than for muscles. These results were in agreement with nuclear imaging and ex vivo data. For imaging tumoral pH in vivo, the CEST ratio of APT/guanidyl was studied. This highlighted an important heterogeneity inside the tumor. The hypoxic status was confirmed by 18 F-FMISO PET imaging and ex vivo immunofluorescence. CONCLUSION CEST MRI simultaneously imaged both chondrosarcoma properties during a single experimental run and without the injection of any contrast agent. Both MR and nuclear imaging as well as ex vivo data were in agreement and showed that this chondrosarcoma animal model was rich in proteoglycans. However, even if tumors were lightly hypoxic at the stage studied, acidic areas were highlighted and mapped inside the tumor.
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Affiliation(s)
- Roxane Autissier
- INRAE, UR QuaPA, Saint-Genès-Champanelle, France.,Université Clermont Auvergne, INSERM, U1240 Imagerie Moléculaire et Stratégies Théranostiques, Clermont-Ferrand, France.,INRAE, ISC AgroResonance, Saint-Genès-Champanelle, France
| | - Leslie Mazuel
- INRAE, UR QuaPA, Saint-Genès-Champanelle, France.,Université Clermont Auvergne, INSERM, U1240 Imagerie Moléculaire et Stratégies Théranostiques, Clermont-Ferrand, France.,INRAE, ISC AgroResonance, Saint-Genès-Champanelle, France
| | - Elise Maubert
- Université Clermont Auvergne, INSERM, U1240 Imagerie Moléculaire et Stratégies Théranostiques, Clermont-Ferrand, France
| | - Jean-Marie Bonny
- INRAE, UR QuaPA, Saint-Genès-Champanelle, France.,INRAE, ISC AgroResonance, Saint-Genès-Champanelle, France
| | - Philippe Auzeloux
- Université Clermont Auvergne, INSERM, U1240 Imagerie Moléculaire et Stratégies Théranostiques, Clermont-Ferrand, France
| | - Sébastien Schmitt
- Université Clermont Auvergne, INSERM, U1240 Imagerie Moléculaire et Stratégies Théranostiques, Clermont-Ferrand, France
| | - Amidou Traoré
- INRAE, UR QuaPA, Saint-Genès-Champanelle, France.,INRAE, ISC AgroResonance, Saint-Genès-Champanelle, France
| | - Caroline Peyrode
- Université Clermont Auvergne, INSERM, U1240 Imagerie Moléculaire et Stratégies Théranostiques, Clermont-Ferrand, France
| | - Elisabeth Miot-Noirault
- Université Clermont Auvergne, INSERM, U1240 Imagerie Moléculaire et Stratégies Théranostiques, Clermont-Ferrand, France
| | - Guilhem Pagés
- INRAE, UR QuaPA, Saint-Genès-Champanelle, France.,INRAE, ISC AgroResonance, Saint-Genès-Champanelle, France
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49
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Overcast WB, Davis KM, Ho CY, Hutchins GD, Green MA, Graner BD, Veronesi MC. Advanced imaging techniques for neuro-oncologic tumor diagnosis, with an emphasis on PET-MRI imaging of malignant brain tumors. Curr Oncol Rep 2021; 23:34. [PMID: 33599882 PMCID: PMC7892735 DOI: 10.1007/s11912-021-01020-2] [Citation(s) in RCA: 41] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/11/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE OF REVIEW This review will explore the latest in advanced imaging techniques, with a focus on the complementary nature of multiparametric, multimodality imaging using magnetic resonance imaging (MRI) and positron emission tomography (PET). RECENT FINDINGS Advanced MRI techniques including perfusion-weighted imaging (PWI), MR spectroscopy (MRS), diffusion-weighted imaging (DWI), and MR chemical exchange saturation transfer (CEST) offer significant advantages over conventional MR imaging when evaluating tumor extent, predicting grade, and assessing treatment response. PET performed in addition to advanced MRI provides complementary information regarding tumor metabolic properties, particularly when performed simultaneously. 18F-fluoroethyltyrosine (FET) PET improves the specificity of tumor diagnosis and evaluation of post-treatment changes. Incorporation of radiogenomics and machine learning methods further improve advanced imaging. The complementary nature of combining advanced imaging techniques across modalities for brain tumor imaging and incorporating technologies such as radiogenomics has the potential to reshape the landscape in neuro-oncology.
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Affiliation(s)
- Wynton B. Overcast
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Korbin M. Davis
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, 550 N University Blvd. Room 0663, Indianapolis, IN 46202 USA
| | - Chang Y. Ho
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Gary D. Hutchins
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Mark A. Green
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E124, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
| | - Brian D. Graner
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Goodman Hall, 355 West 16th Street, Suite 4100, Indianapolis, IN 46202 USA
| | - Michael C. Veronesi
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Research 2 Building (R2), Room E174, 920 W. Walnut Street, Indianapolis, IN 46202-5181 USA
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50
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Prasad S, Chandra A, Cavo M, Parasido E, Fricke S, Lee Y, D'Amone E, Gigli G, Albanese C, Rodriguez O, Del Mercato LL. Optical and magnetic resonance imaging approaches for investigating the tumour microenvironment: state-of-the-art review and future trends. NANOTECHNOLOGY 2021; 32:062001. [PMID: 33065554 DOI: 10.1088/1361-6528/abc208] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
The tumour microenvironment (TME) strongly influences tumorigenesis and metastasis. Two of the most characterized properties of the TME are acidosis and hypoxia, both of which are considered hallmarks of tumours as well as critical factors in response to anticancer treatments. Currently, various imaging approaches exist to measure acidosis and hypoxia in the TME, including magnetic resonance imaging (MRI), positron emission tomography and optical imaging. In this review, we will focus on the latest fluorescent-based methods for optical sensing of cell metabolism and MRI as diagnostic imaging tools applied both in vitro and in vivo. The primary emphasis will be on describing the current and future uses of systems that can measure intra- and extra-cellular pH and oxygen changes at high spatial and temporal resolution. In addition, the suitability of these approaches for mapping tumour heterogeneity, and assessing response or failure to therapeutics will also be covered.
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Affiliation(s)
- Saumya Prasad
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
| | - Anil Chandra
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
| | - Marta Cavo
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
| | - Erika Parasido
- Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
- Center for Translational Imaging, Georgetown University Medical Center, Washington, DC, United States of America
| | - Stanley Fricke
- Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
- Center for Translational Imaging, Georgetown University Medical Center, Washington, DC, United States of America
- Department of Radiology, Georgetown University Medical Center, Washington, DC, United States of America
| | - Yichien Lee
- Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
| | - Eliana D'Amone
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
| | - Giuseppe Gigli
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
- Department of Mathematics and Physics 'Ennio De Giorgi', University of Salento, via Arnesano, 73100, Lecce, Italy
| | - Chris Albanese
- Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
- Center for Translational Imaging, Georgetown University Medical Center, Washington, DC, United States of America
- Department of Radiology, Georgetown University Medical Center, Washington, DC, United States of America
| | - Olga Rodriguez
- Department of Oncology, Georgetown University Medical Center, Washington, DC, United States of America
- Center for Translational Imaging, Georgetown University Medical Center, Washington, DC, United States of America
| | - Loretta L Del Mercato
- Institute of Nanotechnology, National Research Council (CNR-NANOTEC), c/o Campus Ecotekne, via Monteroni, 73100, Lecce, Italy
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