1
|
Patel KS, Yao J, Cho NS, Sanvito F, Tessema K, Alvarado A, Dudley L, Rodriguez F, Everson R, Cloughesy TF, Salamon N, Liau LM, Kornblum HI, Ellingson BM. pH-Weighted amine chemical exchange saturation transfer echo planar imaging visualizes infiltrating glioblastoma cells. Neuro Oncol 2024; 26:115-126. [PMID: 37591790 PMCID: PMC10768991 DOI: 10.1093/neuonc/noad150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2023] [Indexed: 08/19/2023] Open
Abstract
BACKGROUND Given the invasive nature of glioblastoma, tumor cells exist beyond the contrast-enhancing (CE) region targeted during treatment. However, areas of non-enhancing (NE) tumors are difficult to visualize and delineate from edematous tissue. Amine chemical exchange saturation transfer echo planar imaging (CEST-EPI) is a pH-sensitive molecular magnetic resonance imaging technique that was evaluated in its ability to identify infiltrating NE tumors and prognosticate survival. METHODS In this prospective study, CEST-EPI was obtained in 30 patients and areas with elevated CEST contrast ("CEST+" based on the asymmetry in magnetization transfer ratio: MTRasym at 3 ppm) within NE regions were quantitated. Median MTRasym at 3 ppm and volume of CEST + NE regions were correlated with progression-free survival (PFS). In 20 samples from 14 patients, image-guided biopsies of these areas were obtained to correlate MTRasym at 3 ppm to tumor and non-tumor cell burden using immunohistochemistry. RESULTS In 15 newly diagnosed and 15 recurrent glioblastoma, higher median MTRasym at 3ppm within CEST + NE regions (P = .007; P = .0326) and higher volumes of CEST + NE tumor (P = .020; P < .001) were associated with decreased PFS. CE recurrence occurred in areas of preoperative CEST + NE regions in 95.4% of patients. MTRasym at 3 ppm was correlated with presence of tumor, cell density, %Ki-67 positivity, and %CD31 positivity (P = .001; P < .001; P < .001; P = .001). CONCLUSIONS pH-weighted amine CEST-EPI allows for visualization of NE tumor, likely through surrounding acidification of the tumor microenvironment. The magnitude and volume of CEST + NE tumor correlates with tumor cell density, degree of proliferating or "active" tumor, and PFS.
Collapse
Affiliation(s)
- Kunal S Patel
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Francesco Sanvito
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Kaleab Tessema
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Alvaro Alvarado
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Lindsey Dudley
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Fausto Rodriguez
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Richard Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Harley I Kornblum
- The Intellectual and Developmental Disabilities Research Center and Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Benjamin M Ellingson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, California, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, California, USA
| |
Collapse
|
2
|
Dan Q, Jiang X, Wang R, Dai Z, Sun D. Biogenic Imaging Contrast Agents. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2023; 10:e2207090. [PMID: 37401173 PMCID: PMC10477908 DOI: 10.1002/advs.202207090] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 06/08/2023] [Indexed: 07/05/2023]
Abstract
Imaging contrast agents are widely investigated in preclinical and clinical studies, among which biogenic imaging contrast agents (BICAs) are developing rapidly and playing an increasingly important role in biomedical research ranging from subcellular level to individual level. The unique properties of BICAs, including expression by cells as reporters and specific genetic modification, facilitate various in vitro and in vivo studies, such as quantification of gene expression, observation of protein interactions, visualization of cellular proliferation, monitoring of metabolism, and detection of dysfunctions. Furthermore, in human body, BICAs are remarkably helpful for disease diagnosis when the dysregulation of these agents occurs and can be detected through imaging techniques. There are various BICAs matched with a set of imaging techniques, including fluorescent proteins for fluorescence imaging, gas vesicles for ultrasound imaging, and ferritin for magnetic resonance imaging. In addition, bimodal and multimodal imaging can be realized through combining the functions of different BICAs, which helps overcome the limitations of monomodal imaging. In this review, the focus is on the properties, mechanisms, applications, and future directions of BICAs.
Collapse
Affiliation(s)
- Qing Dan
- Shenzhen Key Laboratory for Drug Addiction and Medication SafetyDepartment of UltrasoundInstitute of Ultrasonic MedicinePeking University Shenzhen HospitalShenzhen Peking University‐The Hong Kong University of Science and Technology Medical CenterShenzhen518036P. R. China
| | - Xinpeng Jiang
- Department of Biomedical EngineeringCollege of Future TechnologyPeking UniversityBeijing100871P. R. China
| | - Run Wang
- Shenzhen Key Laboratory for Drug Addiction and Medication SafetyDepartment of UltrasoundInstitute of Ultrasonic MedicinePeking University Shenzhen HospitalShenzhen Peking University‐The Hong Kong University of Science and Technology Medical CenterShenzhen518036P. R. China
| | - Zhifei Dai
- Department of Biomedical EngineeringCollege of Future TechnologyPeking UniversityBeijing100871P. R. China
| | - Desheng Sun
- Shenzhen Key Laboratory for Drug Addiction and Medication SafetyDepartment of UltrasoundInstitute of Ultrasonic MedicinePeking University Shenzhen HospitalShenzhen Peking University‐The Hong Kong University of Science and Technology Medical CenterShenzhen518036P. R. China
| |
Collapse
|
3
|
Zhang Z, Wang K, Park S, Li A, Li Y, Weiss R, Xu J. The exchange rate of creatine CEST in mouse brain. Magn Reson Med 2023; 90:373-384. [PMID: 37036030 PMCID: PMC11054327 DOI: 10.1002/mrm.29662] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 03/19/2023] [Accepted: 03/20/2023] [Indexed: 04/11/2023]
Abstract
PURPOSE To estimate the exchange rate of creatine (Cr) CEST and to evaluate the pH sensitivity of guanidinium (Guan) CEST in the mouse brain. METHODS Polynomial and Lorentzian line-shape fitting (PLOF) were implemented to extract the amine, amide, and Guan CEST signals from the brain Z-spectrum at 11.7T. Wild-type (WT) and knockout mice with the guanidinoacetate N-methyltransferase deficiency (GAMT-/- ) that have low Cr and phosphocreatine (PCr) concentrations in the brain were used to extract the CrCEST signal. To quantify the CrCEST exchange rate, a two-step Bloch-McConnell (BM) fitting was used to fit the CrCEST line-shape, B1 -dependent CrCEST, and the pH response with different B1 values. The pH in the brain cells was altered by hypercapnia to measure the pH sensitivity of GuanCEST. RESULTS Comparison between the Z-spectra of WT and GAMT-/- mice suggest that the CrCEST is between 20% and 25% of the GuanCEST in the Z-spectrum at 1.95 ppm between B1 = 0.8 and 2 μT. The CrCEST exchange rate was found to be around 240-480 s-1 in the mouse brain, which is significantly lower than that in solutions (∼1000 s-1 ). The hypercapnia study on the mouse brain revealed that CrCEST at B1 = 2 μT and amineCEST at B1 = 0.8 μT are highly sensitive to pH change in the WT mouse brain. CONCLUSIONS The in vivo CrCEST exchange rate is slow, and the acquisition parameters for the CrCEST should be adjusted accordingly. CrCEST is the major contribution to the opposite pH-dependence of GuanCEST signal under different conditions of B1 in the brain.
Collapse
Affiliation(s)
- Ziqin Zhang
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Kexin Wang
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Sooyeon Park
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Department of Neuroscience, Johns Hopkins University, Baltimore, MD, USA
| | - Anna Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Yuguo Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Robert Weiss
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Cardiology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| |
Collapse
|
4
|
Xu J, Chung JJ, Jin T. Chemical exchange saturation transfer imaging of creatine, phosphocreatine, and protein arginine residue in tissues. NMR IN BIOMEDICINE 2023; 36:e4671. [PMID: 34978371 PMCID: PMC9250548 DOI: 10.1002/nbm.4671] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 11/06/2021] [Accepted: 12/02/2021] [Indexed: 05/05/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI has become a promising technique to assay target proteins and metabolites through their exchangeable protons, noninvasively. The ubiquity of creatine (Cr) and phosphocreatine (PCr) due to their pivotal roles in energy homeostasis through the creatine phosphate pathway has made them prime targets for CEST in the diagnosis and monitoring of disease pathologies, particularly in tissues heavily dependent on the maintenance of rich energy reserves. Guanidinium CEST from protein arginine residues (i.e. arginine CEST) can also provide information about the protein profile in tissue. However, numerous obfuscating factors stand as obstacles to the specificity of arginine, Cr, and PCr imaging through CEST, such as semisolid magnetization transfer, fast chemical exchanges such as primary amines, and the effects of nuclear Overhauser enhancement from aromatic and amide protons. In this review, the specific exchange properties of protein arginine residues, Cr, and PCr, along with their validation, are discussed, including the considerations necessary to target and tune their signal effects through CEST imaging. Additionally, strategies that have been employed to enhance the specificity of these exchanges in CEST imaging are described, along with how they have opened up possible applications of protein arginine residues, Cr and PCr CEST imaging in the study and diagnosis of pathology. A clear understanding of the capabilities and caveats of using CEST to image these vital metabolites and mitigation strategies is crucial to expanding the possibilities of this promising technology.
Collapse
Affiliation(s)
- Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
- Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Julius Juhyun Chung
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Tao Jin
- Department of Radiology, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| |
Collapse
|
5
|
Cho NS, Hagiwara A, Yao J, Nathanson DA, Prins RM, Wang C, Raymond C, Desousa BR, Divakaruni A, Morrow DH, Nghiemphu PL, Lai A, Liau LM, Everson RG, Salamon N, Pope WB, Cloughesy TF, Ellingson BM. Amine-weighted chemical exchange saturation transfer magnetic resonance imaging in brain tumors. NMR IN BIOMEDICINE 2023; 36:e4785. [PMID: 35704275 DOI: 10.1002/nbm.4785] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Revised: 05/31/2022] [Accepted: 06/10/2022] [Indexed: 05/23/2023]
Abstract
Amine-weighted chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) is particularly valuable as an amine- and pH-sensitive imaging technique in brain tumors, targeting the intrinsically high concentration of amino acids with exchangeable amine protons and reduced extracellular pH in brain tumors. Amine-weighted CEST MRI contrast is dependent on the glioma genotype, likely related to differences in degree of malignancy and metabolic behavior. Amine-weighted CEST MRI may provide complementary value to anatomic imaging in conventional and exploratory therapies in brain tumors, including chemoradiation, antiangiogenic therapies, and immunotherapies. Continual improvement and clinical testing of amine-weighted CEST MRI has the potential to greatly impact patients with brain tumors by understanding vulnerabilities in the tumor microenvironment that may be therapeutically exploited.
Collapse
Affiliation(s)
- Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California, USA
- Medical Scientist Training Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California, USA
| | - David A Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Robert M Prins
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Brandon R Desousa
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Ajit Divakaruni
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Danielle H Morrow
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Phioanh L Nghiemphu
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Albert Lai
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Richard G Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Timothy F Cloughesy
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California, USA
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- UCLA Brain Tumor Program, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
- Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| |
Collapse
|
6
|
Bie C, van Zijl P, Xu J, Song X, Yadav NN. Radiofrequency labeling strategies in chemical exchange saturation transfer MRI. NMR IN BIOMEDICINE 2023; 36:e4944. [PMID: 37002814 PMCID: PMC10312378 DOI: 10.1002/nbm.4944] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2023] [Revised: 03/19/2023] [Accepted: 03/27/2023] [Indexed: 05/23/2023]
Abstract
Chemical exchange saturation transfer (CEST) MRI has generated great interest for molecular imaging applications because it can image low-concentration solute molecules in vivo with enhanced sensitivity. CEST effects are detected indirectly through a reduction in the bulk water signal after repeated perturbation of the solute proton magnetization using one or more radiofrequency (RF) irradiation pulses. The parameters used for these RF pulses-frequency offset, duration, shape, strength, phase, and interpulse spacing-determine molecular specificity and detection sensitivity, thus their judicious selection is critical for successful CEST MRI scans. This review article describes the effects of applying RF pulses on spin systems and compares conventional saturation-based RF labeling with more recent excitation-based approaches that provide spectral editing capabilities for selectively detecting molecules of interest and obtaining maximal contrast.
Collapse
Affiliation(s)
- Chongxue Bie
- Department of Information Science and Technology, Northwest University, No.1 Xuefu Avenue, Xi’an, Shaanxi 710127 (China)
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
| | - Peter van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
| | - Xiaolei Song
- Center for Biomedical Imaging Research, Department of Biomedical Engineering, Tsinghua University, Haidian District, Beijing 100084 (China)
| | - Nirbhay N. Yadav
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, 707 N. Broadway, Baltimore MD 21205 (USA)
- The Russell H. Morgan Department of Radiology, The Johns Hopkins University School of Medicine, 720 Rutland Ave, Baltimore, MD 21205 (USA)
| |
Collapse
|
7
|
Nabavizadeh A, Barkovich MJ, Mian A, Ngo V, Kazerooni AF, Villanueva-Meyer JE. Current state of pediatric neuro-oncology imaging, challenges and future directions. Neoplasia 2023; 37:100886. [PMID: 36774835 PMCID: PMC9945752 DOI: 10.1016/j.neo.2023.100886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Revised: 01/20/2023] [Accepted: 02/05/2023] [Indexed: 02/12/2023]
Abstract
Imaging plays a central role in neuro-oncology including primary diagnosis, treatment planning, and surveillance of tumors. The emergence of quantitative imaging and radiomics provided an uprecedented opportunity to compile mineable databases that can be utilized in a variety of applications. In this review, we aim to summarize the current state of conventional and advanced imaging techniques, standardization efforts, fast protocols, contrast and sedation in pediatric neuro-oncologic imaging, radiomics-radiogenomics, multi-omics and molecular imaging approaches. We will also address the existing challenges and discuss future directions.
Collapse
Affiliation(s)
- Ali Nabavizadeh
- Department of Radiology, Hospital of University of Pennsylvania, Perelman School of Medicine of the University of Pennsylvania, Philadelphia, Pennsylvania, USA; Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
| | - Matthew J Barkovich
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Ali Mian
- Division of Neuroradiology, Mallinckrodt Institute of Radiology, Washington University in St. Louis, Missouri, USA
| | - Van Ngo
- Saint Louis University School of Medicine, St. Louis, Missouri, USA
| | - Anahita Fathi Kazerooni
- Center for Data-Driven Discovery in Biomedicine (D3b), Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| |
Collapse
|
8
|
Larionova TD, Bastola S, Aksinina TE, Anufrieva KS, Wang J, Shender VO, Andreev DE, Kovalenko TF, Arapidi GP, Shnaider PV, Kazakova AN, Latyshev YA, Tatarskiy VV, Shtil AA, Moreau P, Giraud F, Li C, Wang Y, Rubtsova MP, Dontsova OA, Condro M, Ellingson BM, Shakhparonov MI, Kornblum HI, Nakano I, Pavlyukov MS. Alternative RNA splicing modulates ribosomal composition and determines the spatial phenotype of glioblastoma cells. Nat Cell Biol 2022; 24:1541-1557. [PMID: 36192632 PMCID: PMC10026424 DOI: 10.1038/s41556-022-00994-w] [Citation(s) in RCA: 29] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 08/15/2022] [Indexed: 02/08/2023]
Abstract
Glioblastoma (GBM) is characterized by exceptionally high intratumoral heterogeneity. However, the molecular mechanisms underlying the origin of different GBM cell populations remain unclear. Here, we found that the compositions of ribosomes of GBM cells in the tumour core and edge differ due to alternative RNA splicing. The acidic pH in the core switches before messenger RNA splicing of the ribosomal gene RPL22L1 towards the RPL22L1b isoform. This allows cells to survive acidosis, increases stemness and correlates with worse patient outcome. Mechanistically, RPL22L1b promotes RNA splicing by interacting with lncMALAT1 in the nucleus and inducing its degradation. Contrarily, in the tumour edge region, RPL22L1a interacts with ribosomes in the cytoplasm and upregulates the translation of multiple messenger RNAs including TP53. We found that the RPL22L1 isoform switch is regulated by SRSF4 and identified a compound that inhibits this process and decreases tumour growth. These findings demonstrate how distinct GBM cell populations arise during tumour growth. Targeting this mechanism may decrease GBM heterogeneity and facilitate therapy.
Collapse
Affiliation(s)
- Tatyana D Larionova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
| | - Soniya Bastola
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Tatiana E Aksinina
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
| | - Ksenia S Anufrieva
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical Biological Agency, Moscow, Russian Federation
- Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical and Biological Agency, Moscow, Russian Federation
| | - Jia Wang
- Department of Neurosurgery, Centre of Brain Science, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Victoria O Shender
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical Biological Agency, Moscow, Russian Federation
- Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical and Biological Agency, Moscow, Russian Federation
| | - Dmitriy E Andreev
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Tatiana F Kovalenko
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
| | - Georgij P Arapidi
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical Biological Agency, Moscow, Russian Federation
- Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical and Biological Agency, Moscow, Russian Federation
| | - Polina V Shnaider
- Center for Precision Genome Editing and Genetic Technologies for Biomedicine, Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical Biological Agency, Moscow, Russian Federation
- Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical and Biological Agency, Moscow, Russian Federation
| | - Anastasia N Kazakova
- Federal Research and Clinical Center of Physical-Chemical Medicine, Federal Medical and Biological Agency, Moscow, Russian Federation
| | - Yaroslav A Latyshev
- N.N. Burdenko National Medical Research Center of Neurosurgery, Ministry of Health of the Russian Federation, Moscow, Russian Federation
| | - Victor V Tatarskiy
- Institute of Gene Biology, Russian Academy of Sciences, Moscow, Russian Federation
| | - Alexander A Shtil
- Blokhin National Medical Research Center of Oncology, Moscow, Russian Federation
| | - Pascale Moreau
- Institute of Chemistry of Clermont-Ferrand, CNRS, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Francis Giraud
- Institute of Chemistry of Clermont-Ferrand, CNRS, Université Clermont Auvergne, Clermont-Ferrand, France
| | - Chaoxi Li
- Department of Neurosurgery, School of Medicine and O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Yichan Wang
- Department of Neurosurgery, Centre of Brain Science, First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China
| | - Maria P Rubtsova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russian Federation
| | - Olga A Dontsova
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
- Belozersky Institute of Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russian Federation
- Center of Life Sciences, Skolkovo Institute of Science and Technology, Moscow, Russian Federation
| | - Michael Condro
- Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, University of California Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry, University of California Los Angeles, Los Angeles, CA, USA
- Department of Neurosurgery, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Harley I Kornblum
- Intellectual and Developmental Disabilities Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ichiro Nakano
- Department of Neurosurgery, Medical Institute of Hokuto, Hokkaido, Japan.
| | - Marat S Pavlyukov
- Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation.
- Centre for Genomic Regulation, Barcelona Institute of Science and Technology, Barcelona, Spain.
| |
Collapse
|
9
|
Yao J, Hagiwara A, Oughourlian TC, Wang C, Raymond C, Pope WB, Salamon N, Lai A, Ji M, Nghiemphu PL, Liau LM, Cloughesy TF, Ellingson BM. Diagnostic and Prognostic Value of pH- and Oxygen-Sensitive Magnetic Resonance Imaging in Glioma: A Retrospective Study. Cancers (Basel) 2022; 14:2520. [PMID: 35626127 PMCID: PMC9139712 DOI: 10.3390/cancers14102520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 05/11/2022] [Accepted: 05/17/2022] [Indexed: 01/19/2023] Open
Abstract
Characterization of hypoxia and tissue acidosis could advance the understanding of glioma biology and improve patient management. In this study, we evaluated the ability of a pH- and oxygen-sensitive magnetic resonance imaging (MRI) technique to differentiate glioma genotypes, including isocitrate dehydrogenase (IDH) mutation, 1p/19q co-deletion, and epidermal growth factor receptor (EGFR) amplification, and investigated its prognostic value. A total of 159 adult glioma patients were scanned with pH- and oxygen-sensitive MRI at 3T. We quantified the pH-sensitive measure of magnetization transfer ratio asymmetry (MTRasym) and oxygen-sensitive measure of R2’ within the tumor region-of-interest. IDH mutant gliomas showed significantly lower MTRasym × R2’ (p < 0.001), which differentiated IDH mutation status with sensitivity and specificity of 90.0% and 71.9%. Within IDH mutants, 1p/19q codeletion was associated with lower tumor acidity (p < 0.0001, sensitivity 76.9%, specificity 91.3%), while IDH wild-type, EGFR-amplified gliomas were more hypoxic (R2’ p = 0.024, sensitivity 66.7%, specificity 76.9%). Both R2’ and MTRasym × R2’ were significantly associated with patient overall survival (R2’: p = 0.045; MTRasym × R2’: p = 0.002) and progression-free survival (R2’: p = 0.010; MTRasym × R2’: p < 0.0001), independent of patient age, treatment status, and IDH status. The pH- and oxygen-sensitive MRI is a clinically feasible and potentially valuable imaging technique for distinguishing glioma subtypes and providing additional prognostic value to clinical practice.
Collapse
Affiliation(s)
- Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Talia C. Oughourlian
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
- Neuroscience Interdepartmental Program, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Whitney B. Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
| | - Albert Lai
- UCLA Neuro-Oncology Program, University of California, Los Angeles, CA 90024, USA; (A.L.); (M.J.); (P.L.N.); (T.F.C.)
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA
| | - Matthew Ji
- UCLA Neuro-Oncology Program, University of California, Los Angeles, CA 90024, USA; (A.L.); (M.J.); (P.L.N.); (T.F.C.)
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA
| | - Phioanh L. Nghiemphu
- UCLA Neuro-Oncology Program, University of California, Los Angeles, CA 90024, USA; (A.L.); (M.J.); (P.L.N.); (T.F.C.)
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA
| | - Linda M. Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA;
| | - Timothy F. Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, CA 90024, USA; (A.L.); (M.J.); (P.L.N.); (T.F.C.)
- Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, CA 90024, USA; (J.Y.); (A.H.); (T.C.O.); (C.W.); (C.R.)
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA 90024, USA; (W.B.P.); (N.S.)
- UCLA Neuro-Oncology Program, University of California, Los Angeles, CA 90024, USA; (A.L.); (M.J.); (P.L.N.); (T.F.C.)
| |
Collapse
|
10
|
Chemical Exchange Saturation Transfer for Pancreatic Ductal Adenocarcinoma Evaluation. Pancreas 2022; 51:463-468. [PMID: 35858211 DOI: 10.1097/mpa.0000000000002059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/10/2022]
Abstract
OBJECTIVES The aims of the study are to evaluate the feasibility of using pH-sensitive magnetic resonance imaging, chemical exchange saturation transfer (CEST) in pancreatic imaging and to differentiate pancreatic ductal adenocarcinoma (PDAC) with the nontumor pancreas (upstream and downstream) and normal control pancreas. METHODS Sixteen CEST images with PDAC and 12 CEST images with normal volunteers were acquired and magnetization transfer ratio with asymmetric analysis were measured in areas of PDAC, upstream, downstream, and normal control pancreas. One-way analysis of variance and receiver operating characteristic curve were used to differentiate tumor from nontumor pancreas. RESULTS Areas with PDAC showed higher signal intensity than upstream and downstream on CEST images. The mean (standard deviation) values of magnetization transfer ratio with asymmetric analysis were 0.015 (0.034), -0.044 (0.030), -0.019 (0.027), and -0.037 (0.031), respectively, in PDAC area, upstream, downstream, and nontumor area in patient group and -0.008 (0.024) in normal pancreas. Significant differences were found between PDAC and upstream ( P < 0.001), between upstream and normal pancreas ( P = 0.04). Area under curve is 0.857 in differentiating PDAC with nontumor pancreas. CONCLUSIONS pH-sensitive CEST MRI is feasible in pancreatic imaging and can be used to differentiate PDAC from nontumor pancreas. This provides a novel metabolic imaging method in PDAC.
Collapse
|
11
|
Gonçalves SI, Simões RV, Shemesh N. Short TE downfield magnetic resonance spectroscopy in a mouse model of brain glioma. Magn Reson Med 2022; 88:524-536. [PMID: 35315536 DOI: 10.1002/mrm.29243] [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: 07/27/2021] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 11/11/2022]
Abstract
PURPOSE Enhanced cell proliferation in tumors can be associated with altered metabolic profiles and dramatic microenvironmental changes. Downfield magnetic resonance spectroscopy (MRS) has received increasing attention due to its ability to report on labile resonances of molecules not easily detected in upfield 1 H MRS. Image-selected-in-vivo-spectroscopy-relaxation enhanced MRS (iRE-MRS) was recently introduced for acquiring short echo-time (TE) spectra. Here, iRE-MRS was used to investigate in-vivo downfield spectra in glioma-bearing mice. METHODS Experiments were performed in vivo in an immunocompetent glioma mouse model at 9.4 T using a cryogenic coil. iRE-MRS spectra were acquired in N = 6 glioma-bearing mice (voxel size = 2.23 mm3 ) and N = 6 control mice. Spectra were modeled by a sum of Lorentzian peaks simulating known downfield resonances, and differences between controls and tumors were quantified using relative peak areas. RESULTS Short TE tumor spectra exhibited large qualitative differences compared to control spectra. Most peaks appeared modulated, with strong attenuation of NAA (∼7.82, 7.86 ppm) and changes in relative peak areas between 6.75 and 8.49 ppm. Peak areas tended to be smaller for DF6.83 , DF7.60 , DF8.18 and NAA; and larger for DF7.95 and DF8.24 . Differences were also detected in signals resonating above 8.5 ppm, assumed to arise from NAD+. CONCLUSIONS In-vivo downfield 1 H iRE-MRS of mouse glioma revealed differences between controls and tumor bearing mice, including in metabolites which are not easily detectable in the more commonly investigated upfield spectrum. These findings motivate future downfield MRS investigations exploring pH and exchange contributions to these differences.
Collapse
Affiliation(s)
| | - Rui V Simões
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
| | - Noam Shemesh
- Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal
| |
Collapse
|
12
|
Booth TC, Wiegers EC, Warnert EAH, Schmainda KM, Riemer F, Nechifor RE, Keil VC, Hangel G, Figueiredo P, Álvarez-Torres MDM, Henriksen OM. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 2: Spectroscopy, Chemical Exchange Saturation, Multiparametric Imaging, and Radiomics. Front Oncol 2022; 11:811425. [PMID: 35340697 PMCID: PMC8948428 DOI: 10.3389/fonc.2021.811425] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Accepted: 12/28/2021] [Indexed: 01/16/2023] Open
Abstract
Objective To summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and to highlight the latest bench-to-bedside developments. Methods The current evidence regarding the potential for monitoring biomarkers was reviewed and individual modalities of metabolism and/or chemical composition imaging discussed. Perfusion, permeability, and microstructure imaging were similarly analyzed in Part 1 of this two-part review article and are valuable reading as background to this article. We appraise the clinic readiness of all the individual modalities and consider methodologies involving machine learning (radiomics) and the combination of MRI approaches (multiparametric imaging). Results The biochemical composition of high-grade gliomas is markedly different from healthy brain tissue. Magnetic resonance spectroscopy allows the simultaneous acquisition of an array of metabolic alterations, with choline-based ratios appearing to be consistently discriminatory in treatment response assessment, although challenges remain despite this being a mature technique. Promising directions relate to ultra-high field strengths, 2-hydroxyglutarate analysis, and the use of non-proton nuclei. Labile protons on endogenous proteins can be selectively targeted with chemical exchange saturation transfer to give high resolution images. The body of evidence for clinical application of amide proton transfer imaging has been building for a decade, but more evidence is required to confirm chemical exchange saturation transfer use as a monitoring biomarker. Multiparametric methodologies, including the incorporation of nuclear medicine techniques, combine probes measuring different tumor properties. Although potentially synergistic, the limitations of each individual modality also can be compounded, particularly in the absence of standardization. Machine learning requires large datasets with high-quality annotation; there is currently low-level evidence for monitoring biomarker clinical application. Conclusion Advanced MRI techniques show huge promise in treatment response assessment. The clinical readiness analysis highlights that most monitoring biomarkers require standardized international consensus guidelines, with more facilitation regarding technique implementation and reporting in the clinic.
Collapse
Affiliation(s)
- Thomas C. Booth
- School of Biomedical Engineering and Imaging Sciences, King’s College London, St. Thomas’ Hospital, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
| | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | | | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Ruben E. Nechifor
- Department of Clinical Psychology and Psychotherapy International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, Netherlands
| | - Gilbert Hangel
- Department of Neurosurgery & High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University Vienna, Vienna, Austria
| | - Patrícia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics - Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | | | - Otto M. Henriksen
- Department of Clinical Physiology, Nuclear medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| |
Collapse
|
13
|
Bender B, Herz K, Deshmane A, Richter V, Tabatabai G, Schittenhelm J, Skardelly M, Scheffler K, Ernemann U, Kim M, Golay X, Zaiss M, Lindig T. GLINT: GlucoCEST in neoplastic tumors at 3 T-clinical results of GlucoCEST in gliomas. MAGMA (NEW YORK, N.Y.) 2022; 35:77-85. [PMID: 34890014 PMCID: PMC8901469 DOI: 10.1007/s10334-021-00982-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 11/24/2021] [Accepted: 11/26/2021] [Indexed: 11/30/2022]
Abstract
Objective Clinical relevance of dynamic glucose enhanced (DGE) chemical exchange saturation transfer (CEST) imaging has mostly been demonstrated at ultra-high field (UHF) due to low effect size. Results of a cohort study at clinical field strength are shown herein. Materials and methods Motion and field inhomogeneity corrected T1ρ‐based DGE (DGE⍴) images were acquired before, during and after a d-glucose injection with 6.3 s temporal resolution to detect accumulation in the brain. Six glioma patients with clear blood–brain barrier (BBB) leakage, two glioma patients with suspected BBB leakage, and three glioma patients without BBB leakage were scanned at 3 T. Results In high-grade gliomas with BBB leakage, d-glucose uptake could be detected in the gadolinium (Gd) enhancing region as well as in the tumor necrosis with a maximum increase of ∆DGE⍴ around 0.25%, whereas unaffected white matter did not show any significant DGE⍴ increase. Glioma patients without Gd enhancement showed no detectable DGE⍴ effect within the tumor. Conclusion First application of DGE⍴ in a patient cohort shows an association between BBB leakage and DGE signal irrespective of the tumor grade. This indicates that glucoCEST corresponds more to the disruptions of BBB with Gd uptake than to the molecular tumor profile or tumor grading. Supplementary Information The online version contains supplementary material available at 10.1007/s10334-021-00982-5.
Collapse
Affiliation(s)
- Benjamin Bender
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany.,Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Kai Herz
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department of Biomedical Magnetic Resonance, University Hospital Tübingen, Tübingen, Germany
| | - Anagha Deshmane
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany
| | - Vivien Richter
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Ghazaleh Tabatabai
- Department of Neurology and Interdisciplinary Neuro-Oncology, University Hospital Tübingen, Tübingen, Germany.,Hertie Institute for Clinical Brain Research, Eberhard Karls University Tübingen, Tübingen, Germany.,Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany.,Cluster of Excellence iFIT (EXC 2180) "Image Guided and Functionally Instructed Tumor Therapies", Eberhard Karls University Tübingen, Tübingen, Germany.,German Consortium for Translational Cancer Research (DKTK), Partner Site Tübingen, German Cancer Research Center (DKFZ), Tübingen, Germany
| | - Jens Schittenhelm
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany.,Department of Neuropathology, University Hospital Tübingen, Tübingen, Germany
| | - Marco Skardelly
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany.,Department of Neurosurgery, University Hospital Tübingen, Tübingen, Germany.,Department of Neurosurgery, Klinikum am Steinenberg, Reutlingen, Germany
| | - Klaus Scheffler
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department of Biomedical Magnetic Resonance, University Hospital Tübingen, Tübingen, Germany
| | - Ulrike Ernemann
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany
| | - Mina Kim
- Institute of Neurology, University College London, London, UK
| | - Xavier Golay
- Institute of Neurology, University College London, London, UK
| | - Moritz Zaiss
- Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.,Department of Neuroradiology, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nürnberg (FAU), Erlangen, Germany
| | - Tobias Lindig
- Department of Diagnostic and Interventional Neuroradiology, University Hospital Tübingen, Hoppe-Seyler-Str. 3, 72076, Tübingen, Germany. .,Magnetic Resonance Center, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
| |
Collapse
|
14
|
Wu Y, Wood TC, Arzanforoosh F, Hernandez-Tamames JA, Barker GJ, Smits M, Warnert EAH. 3D APT and NOE CEST-MRI of healthy volunteers and patients with non-enhancing glioma at 3 T. MAGMA (NEW YORK, N.Y.) 2022; 35:63-73. [PMID: 34994858 PMCID: PMC8901510 DOI: 10.1007/s10334-021-00996-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2021] [Revised: 12/17/2021] [Accepted: 12/23/2021] [Indexed: 11/28/2022]
Abstract
OBJECTIVE Clinical application of chemical exchange saturation transfer (CEST) can be performed with investigation of amide proton transfer (APT) and nuclear Overhauser enhancement (NOE) effects. Here, we investigated APT- and NOE-weighted imaging based on advanced CEST metrics to map tumor heterogeneity of non-enhancing glioma at 3 T. MATERIALS AND METHODS APT- and NOE-weighted maps based on Lorentzian difference (LD) and inverse magnetization transfer ratio (MTRREX) were acquired with a 3D snapshot CEST acquisition at 3 T. Saturation power was investigated first by varying B1 (0.5-2 µT) in 5 healthy volunteers then by applying B1 of 0.5 and 1.5 µT in 10 patients with non-enhancing glioma. Tissue contrast (TC) and contrast-to-noise ratios (CNR) were calculated between glioma and normal appearing white matter (NAWM) and grey matter, in APT- and NOE-weighted images. Volume percentages of the tumor showing hypo/hyperintensity (VPhypo/hyper,CEST) in APT/NOE-weighted images were calculated for each patient. RESULTS LD APT resulting from using a B1 of 1.5 µT was found to provide significant positive TCtumor,NAWM and MTRREX NOE (B1 of 1.5 µT) provided significant negative TCtumor,NAWM in tissue differentiation. MTRREX-based NOE imaging under 1.5 µT provided significantly larger VPhypo,CEST than MTRREX APT under 1.5 µT. CONCLUSION This work showed that with a rapid CEST acquisition using a B1 saturation power of 1.5 µT and covering the whole tumor, analysis of both LD APT and MTRREX NOE allows for observing tumor heterogeneity, which will be beneficial in future studies using CEST-MRI to improve imaging diagnostics for non-enhancing glioma.
Collapse
Affiliation(s)
- Yulun Wu
- Department of Radiology and Nuclear Medicine, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
| | - Tobias C Wood
- Centre for Neuroimaging Science, King's College London, London, UK
| | - Fatemeh Arzanforoosh
- Department of Radiology and Nuclear Medicine, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Juan A Hernandez-Tamames
- Department of Radiology and Nuclear Medicine, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
| | - Gareth J Barker
- Centre for Neuroimaging Science, King's College London, London, UK
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | - Esther A H Warnert
- Department of Radiology and Nuclear Medicine, Erasmus MC, Dr. Molewaterplein 40, 3015 GD, Rotterdam, The Netherlands.
- Brain Tumor Centre, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
| |
Collapse
|
15
|
Hagiwara A, Yao J, Raymond C, Cho NS, Everson R, Patel K, Morrow DH, Desousa BR, Mareninov S, Chun S, Nathanson DA, Yong WH, Andrei G, Divakaruni AS, Salamon N, Pope WB, Nghiemphu PL, Liau LM, Cloughesy TF, Ellingson BM. "Aerobic glycolytic imaging" of human gliomas using combined pH-, oxygen-, and perfusion-weighted magnetic resonance imaging. Neuroimage Clin 2022; 32:102882. [PMID: 34911188 PMCID: PMC8609049 DOI: 10.1016/j.nicl.2021.102882] [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: 06/17/2021] [Revised: 11/10/2021] [Accepted: 11/11/2021] [Indexed: 01/24/2023]
Abstract
Aerobic glycolytic imaging combines pH-, oxygen-, and perfusion-weighted MRI. Aerobic glycolytic imaging depicts abnormal glucose metabolism of gliomas. IDH wild-type gliomas show higher aerobic glycolytic index compared with mutants. Aerobic glycolytic index in IDH wild-type glioma is correlated with glucose uptake. Aerobic glycolytic index in IDH mutant glioma is correlated to lactate transporters.
Purpose To quantify abnormal metabolism of diffuse gliomas using “aerobic glycolytic imaging” and investigate its biological correlation. Methods All subjects underwent a pH-weighted amine chemical exchange saturation transfer spin-and-gradient-echo echoplanar imaging (CEST-SAGE-EPI) and dynamic susceptibility contrast perfusion MRI. Relative oxygen extraction fraction (rOEF) was estimated as the ratio of reversible transverse relaxation rate R2′ to normalized relative cerebral blood volume. An aerobic glycolytic index (AGI) was derived by the ratio of pH-weighted image contrast (MTRasym at 3.0 ppm) to rOEF. AGI was compared between different tumor types (N = 51, 30 IDH mutant and 21 IDH wild type). Metabolic MR parameters were correlated with 18F-FDG uptake (N = 8, IDH wild-type glioblastoma), expression of key glycolytic proteins using immunohistochemistry (N = 38 samples, 21 from IDH mutant and 17 from IDH wild type), and bioenergetics analysis on purified tumor cells (N = 7, IDH wild-type high grade). Results AGI was significantly lower in IDH mutant than wild-type gliomas (0.48 ± 0.48 vs. 0.70 ± 0.48; P = 0.03). AGI was strongly correlated with 18F-FDG uptake both in non-enhancing tumor (Spearman, ρ = 0.81; P = 0.01) and enhancing tumor (ρ = 0.81; P = 0.01). AGI was significantly correlated with glucose transporter 3 (ρ = 0.71; P = 0.004) and hexokinase 2 (ρ = 0.73; P = 0.003) in IDH wild-type glioma, and monocarboxylate transporter 1 (ρ = 0.59; P = 0.009) in IDH mutant glioma. Additionally, a significant correlation was found between AGI derived from bioenergetics analysis and that estimated from MRI (ρ = 0.79; P = 0.04). Conclusion AGI derived from molecular MRI was correlated with glucose uptake (18F-FDG and glucose transporter 3/hexokinase 2) and cellular AGI in IDH wild-type gliomas, whereas AGI in IDH mutant gliomas appeared associated with monocarboxylate transporter density.
Collapse
Affiliation(s)
- Akifumi Hagiwara
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Nicholas S Cho
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA; Medical Scientist Training Program, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Richard Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kunal Patel
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Danielle H Morrow
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Brandon R Desousa
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Sergey Mareninov
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Saewon Chun
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA
| | - David A Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - William H Yong
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Gafita Andrei
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ajit S Divakaruni
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA; Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA; Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA; UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA, USA; Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
| |
Collapse
|
16
|
Hagiwara A, Tatekawa H, Yao J, Raymond C, Everson R, Patel K, Mareninov S, Yong WH, Salamon N, Pope WB, Nghiemphu PL, Liau LM, Cloughesy TF, Ellingson BM. Visualization of tumor heterogeneity and prediction of isocitrate dehydrogenase mutation status for human gliomas using multiparametric physiologic and metabolic MRI. Sci Rep 2022; 12:1078. [PMID: 35058510 PMCID: PMC8776874 DOI: 10.1038/s41598-022-05077-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 12/10/2021] [Indexed: 01/19/2023] Open
Abstract
This study aimed to differentiate isocitrate dehydrogenase (IDH) mutation status with the voxel-wise clustering method of multiparametric magnetic resonance imaging (MRI) and to discover biological underpinnings of the clusters. A total of 69 patients with treatment-naïve diffuse glioma were scanned with pH-sensitive amine chemical exchange saturation transfer MRI, diffusion-weighted imaging, fluid-attenuated inversion recovery, and contrast-enhanced T1-weighted imaging at 3 T. An unsupervised two-level clustering approach was used for feature extraction from acquired images. The logarithmic ratio of the labels in each class within tumor regions was applied to a support vector machine to differentiate IDH status. The highest performance to predict IDH mutation status was found for 10-class clustering, with a mean area under the curve, accuracy, sensitivity, and specificity of 0.94, 0.91, 0.90, and 0.91, respectively. Targeted biopsies revealed that the tissues with labels 7-10 showed high expression levels of hypoxia-inducible factor 1-alpha, glucose transporter 3, and hexokinase 2, which are typical of IDH wild-type glioma, whereas those with labels 1 showed low expression of these proteins. In conclusion, A machine learning model successfully predicted the IDH mutation status of gliomas, and the resulting clusters properly reflected the metabolic status of the tumors.
Collapse
Affiliation(s)
- Akifumi Hagiwara
- grid.19006.3e0000 0000 9632 6718UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024 USA ,grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA ,grid.258269.20000 0004 1762 2738Department of Radiology, Juntendo University School of Medicine, Tokyo, Japan
| | - Hiroyuki Tatekawa
- grid.19006.3e0000 0000 9632 6718UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024 USA ,grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA ,grid.261445.00000 0001 1009 6411Department of Diagnostic and Interventional Radiology, Osaka City University Graduate School of Medicine, Osaka, Japan
| | - Jingwen Yao
- grid.19006.3e0000 0000 9632 6718UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024 USA ,grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA USA
| | - Catalina Raymond
- grid.19006.3e0000 0000 9632 6718UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024 USA ,grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Richard Everson
- grid.19006.3e0000 0000 9632 6718Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Kunal Patel
- grid.19006.3e0000 0000 9632 6718Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Sergey Mareninov
- grid.19006.3e0000 0000 9632 6718Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| | - William H. Yong
- grid.19006.3e0000 0000 9632 6718Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| | - Noriko Salamon
- grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Whitney B. Pope
- grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Phioanh L. Nghiemphu
- grid.19006.3e0000 0000 9632 6718UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| | - Linda M. Liau
- grid.19006.3e0000 0000 9632 6718Department of Neurosurgery, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA
| | - Timothy F. Cloughesy
- grid.19006.3e0000 0000 9632 6718UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| | - Benjamin M. Ellingson
- grid.19006.3e0000 0000 9632 6718UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA 90024 USA ,grid.19006.3e0000 0000 9632 6718Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718UCLA Neuro-Oncology Program, University of California, Los Angeles, Los Angeles, CA USA ,grid.19006.3e0000 0000 9632 6718Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA USA
| |
Collapse
|
17
|
Boyd PS, Breitling J, Korzowski A, Zaiss M, Franke VL, Mueller-Decker K, Glinka A, Ladd ME, Bachert P, Goerke S. Mapping intracellular pH in tumors using amide and guanidyl CEST-MRI at 9.4 T. Magn Reson Med 2021; 87:2436-2452. [PMID: 34958684 DOI: 10.1002/mrm.29133] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2021] [Revised: 11/26/2021] [Accepted: 12/07/2021] [Indexed: 12/11/2022]
Abstract
PURPOSE In principle, non-invasive mapping of the intracellular pH (pHi ) in vivo is possible using endogenous chemical exchange saturation transfer (CEST)-MRI of the amide and guanidyl signals. However, the application for cancer imaging is still impeded, as current state-of-the-art approaches do not allow for simultaneous compensation of concomitant effects that vary within tumors. In this study, we present a novel method for absolute pHi mapping using endogenous CEST-MRI, which simultaneously compensates for concentration changes, superimposing CEST signals, magnetization transfer contrast, and spillover dilution. THEORY AND METHODS Compensation of the concomitant effects was achieved by a ratiometric approach (i.e. the ratio of one CEST signal at different B1 ) in combination with the relaxation-compensated inverse magnetization transfer ratio MTRRex and a separate first-order polynomial-Lorentzian fit of the amide and guanidyl signals at 9.4 T. Calibration of pH values was accomplished using in vivo-like model suspensions from porcine brain lysates. Applicability of the presented method in vivo was demonstrated in n = 19 tumor-bearing mice. RESULTS In porcine brain lysates, measurement of pH was feasible over a broad range of physiologically relevant pH values of 6.2 to 8.0, while being independent of changes in concentration. A median pHi of approximately 7.2 was found in the lesions of 19 tumor-bearing mice. CONCLUSION The presented method enables non-invasive mapping of absolute pHi values in tumors using CEST-MRI, which was so far prevented by concomitant effects. Consequently, pre-clinical studies on pHi changes in tumors are possible allowing the assessment of pHi in vivo as a biomarker for cancer diagnosis or treatment monitoring.
Collapse
Affiliation(s)
- Philip S Boyd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Johannes Breitling
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andreas Korzowski
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Moritz Zaiss
- Division of Neuroradiology in Radiological Institute, University Hospital of Erlangen, Erlangen, Germany
| | - Vanessa L Franke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Karin Mueller-Decker
- Core Facility Tumor Models (Center for Preclinical Research), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andrey Glinka
- Division of Molecular Embryology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Mark E Ladd
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany.,Faculty of Medicine, University of Heidelberg, Heidelberg, Germany
| | - Peter Bachert
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany.,Faculty of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Steffen Goerke
- Division of Medical Physics in Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| |
Collapse
|
18
|
Saturation transfer MRI is sensitive to neurochemical changes in the rat brain due to chronic unpredictable mild stress. Sci Rep 2021; 11:19040. [PMID: 34561488 PMCID: PMC8463565 DOI: 10.1038/s41598-021-97991-0] [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: 05/14/2021] [Accepted: 08/31/2021] [Indexed: 02/08/2023] Open
Abstract
Chemical exchange saturation transfer (CEST) MRI was performed for the evaluation of cerebral metabolic changes in a rat model of depressive-like disease induced by chronic unpredictable mild stress (CUMS). CEST Z-spectra were acquired on a 7 T MRI with two saturation B1 amplitudes (0.5 and 0.75 µT) to measure the magnetization transfer ratio (MTR), CEST and relayed nuclear Overhauser effect (rNOE). Cerebral cortex and hippocampus were examined in two groups of animals: healthy control (n = 10) and stressed (n = 14), the latter of which was exposed to eight weeks of the CUMS protocol. The stressed group Z-spectrum parameters, primarily MTRs, were significantly lower than in controls, at all selected frequency offsets (3.5, 3.0, 2.0, - 3.2, - 3.6 ppm) in the cortex (the largest difference of ~ 3.5% at - 3.6 ppm, p = 0.0005) and the hippocampus (MTRs measured with a B1 = 0.5 µT). The hippocampal rNOE contributions decreased significantly in the stressed brains. Glutamate concentration (assessed using ELISA) and MTR at 3 ppm correlated positively in both brain regions. GABA concentration also correlated positively with CEST contributions in both cerebral areas, while such correlation with MTR was positive in hippocampus, and nonsignificant in cortex. Results indicate that CEST is sensitive to neurometabolic changes following chronic stress exposure.
Collapse
|
19
|
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: 0.7] [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.
Collapse
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.
| |
Collapse
|
20
|
Ellingson BM, Wen PY, Cloughesy TF. Therapeutic Response Assessment of High-Grade Gliomas During Early-Phase Drug Development in the Era of Molecular and Immunotherapies. Cancer J 2021; 27:395-403. [PMID: 34570454 PMCID: PMC8480435 DOI: 10.1097/ppo.0000000000000543] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
ABSTRACT Several new therapeutic strategies have emerged over the past decades to address unmet clinical needs in high-grade gliomas, including targeted molecular agents and various forms of immunotherapy. Each of these strategies requires addressing fundamental questions, depending on the stage of drug development, including ensuring drug penetration into the brain, engagement of the drug with the desired target, biologic effects downstream from the target including metabolic and/or physiologic changes, and identifying evidence of clinical activity that could be expanded upon to increase the likelihood of a meaningful survival benefit. The current review article highlights these strategies and outlines how imaging technology can be used for therapeutic response evaluation in both targeted and immunotherapies in early phases of drug development in high-grade gliomas.
Collapse
Affiliation(s)
- Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Harvard University, Boston, MA
| | - Timothy F. Cloughesy
- UCLA Neuro Oncology Program, Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| |
Collapse
|
21
|
Akbari H, Kazerooni AF, Ware JB, Mamourian E, Anderson H, Guiry S, Sako C, Raymond C, Yao J, Brem S, O'Rourke DM, Desai AS, Bagley SJ, Ellingson BM, Davatzikos C, Nabavizadeh A. Quantification of tumor microenvironment acidity in glioblastoma using principal component analysis of dynamic susceptibility contrast enhanced MR imaging. Sci Rep 2021; 11:15011. [PMID: 34294864 PMCID: PMC8298590 DOI: 10.1038/s41598-021-94560-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2021] [Accepted: 06/28/2021] [Indexed: 11/22/2022] Open
Abstract
Glioblastoma (GBM) has high metabolic demands, which can lead to acidification of the tumor microenvironment. We hypothesize that a machine learning model built on temporal principal component analysis (PCA) of dynamic susceptibility contrast-enhanced (DSC) perfusion MRI can be used to estimate tumor acidity in GBM, as estimated by pH-sensitive amine chemical exchange saturation transfer echo-planar imaging (CEST-EPI). We analyzed 78 MRI scans in 32 treatment naïve and post-treatment GBM patients. All patients were imaged with DSC-MRI, and pH-weighting that was quantified from CEST-EPI estimation of the magnetization transfer ratio asymmetry (MTRasym) at 3 ppm. Enhancing tumor (ET), non-enhancing core (NC), and peritumoral T2 hyperintensity (namely, edema, ED) were used to extract principal components (PCs) and to build support vector machines regression (SVR) models to predict MTRasym values using PCs. Our predicted map correlated with MTRasym values with Spearman's r equal to 0.66, 0.47, 0.67, 0.71, in NC, ET, ED, and overall, respectively (p < 0.006). The results of this study demonstrates that PCA analysis of DSC imaging data can provide information about tumor pH in GBM patients, with the strongest association within the peritumoral regions.
Collapse
Affiliation(s)
- Hamed Akbari
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Anahita Fathi Kazerooni
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jeffrey B Ware
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
| | - Elizabeth Mamourian
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Hannah Anderson
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
| | - Samantha Guiry
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
| | - Chiharu Sako
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Donald M O'Rourke
- Department of Neurosurgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arati S Desai
- Division of Hematology-Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Stephen J Bagley
- Division of Hematology-Oncology, Department of Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Christos Davatzikos
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ali Nabavizadeh
- Department of Radiology, Perelman School of Medicine, Hospital of University of Pennsylvania, University of Pennsylvania, Philadelphia, PA, USA.
| |
Collapse
|
22
|
McGee KP, Hwang KP, Sullivan DC, Kurhanewicz J, Hu Y, Wang J, Li W, Debbins J, Paulson E, Olsen JR, Hua CH, Warner L, Ma D, Moros E, Tyagi N, Chung C. Magnetic resonance biomarkers in radiation oncology: The report of AAPM Task Group 294. Med Phys 2021; 48:e697-e732. [PMID: 33864283 PMCID: PMC8361924 DOI: 10.1002/mp.14884] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 03/24/2021] [Accepted: 03/28/2021] [Indexed: 12/16/2022] Open
Abstract
A magnetic resonance (MR) biologic marker (biomarker) is a measurable quantitative characteristic that is an indicator of normal biological and pathogenetic processes or a response to therapeutic intervention derived from the MR imaging process. There is significant potential for MR biomarkers to facilitate personalized approaches to cancer care through more precise disease targeting by quantifying normal versus pathologic tissue function as well as toxicity to both radiation and chemotherapy. Both of which have the potential to increase the therapeutic ratio and provide earlier, more accurate monitoring of treatment response. The ongoing integration of MR into routine clinical radiation therapy (RT) planning and the development of MR guided radiation therapy systems is providing new opportunities for MR biomarkers to personalize and improve clinical outcomes. Their appropriate use, however, must be based on knowledge of the physical origin of the biomarker signal, the relationship to the underlying biological processes, and their strengths and limitations. The purpose of this report is to provide an educational resource describing MR biomarkers, the techniques used to quantify them, their strengths and weakness within the context of their application to radiation oncology so as to ensure their appropriate use and application within this field.
Collapse
Affiliation(s)
- Kiaran P McGee
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Ken-Pin Hwang
- Department of Imaging Physics, Division of Diagnostic Imaging, MD Anderson Cancer Center, University of Texas, Houston, Texas, USA
| | - Daniel C Sullivan
- Department of Radiology, Duke University, Durham, North Carolina, USA
| | - John Kurhanewicz
- Department of Radiology, University of California, San Francisco, California, USA
| | - Yanle Hu
- Department of Radiation Oncology, Mayo Clinic, Scottsdale, Arizona, USA
| | - Jihong Wang
- Department of Radiation Oncology, MD Anderson Cancer Center, University of Texas, Houston, Texas, USA
| | - Wen Li
- Department of Radiation Oncology, University of Arizona, Tucson, Arizona, USA
| | - Josef Debbins
- Department of Radiology, Barrow Neurologic Institute, Phoenix, Arizona, USA
| | - Eric Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
| | - Jeffrey R Olsen
- Department of Radiation Oncology, University of Colorado Denver - Anschutz Medical Campus, Denver, Colorado, USA
| | - Chia-Ho Hua
- Department of Radiation Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
| | | | - Daniel Ma
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota, USA
| | - Eduardo Moros
- Department of Radiation Oncology, Moffitt Cancer Center, Tampa, Florida, USA
| | - Neelam Tyagi
- Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Caroline Chung
- Department of Radiation Oncology, MD Anderson Cancer Center, University of Texas, Houston, Texas, USA
| |
Collapse
|
23
|
Sui R, Chen L, Li Y, Huang J, Chan KWY, Xu X, van Zijl PCM, Xu J. Whole-brain amide CEST imaging at 3T with a steady-state radial MRI acquisition. Magn Reson Med 2021; 86:893-906. [PMID: 33772859 DOI: 10.1002/mrm.28770] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 02/15/2021] [Accepted: 02/18/2021] [Indexed: 02/06/2023]
Abstract
PURPOSE To develop a steady-state saturation with radial readout chemical exchange saturation transfer (starCEST) for acquiring CEST images at 3 Tesla (T). The polynomial Lorentzian line-shape fitting approach was further developed for extracting amideCEST intensities at this field. METHOD StarCEST MRI using periodically rotated overlapping parallel lines with enhanced reconstruction-based spatial sampling was implemented to acquire Z-spectra that are robust to brain motion. Multi-linear singular value decomposition postprocessing was applied to enhance the CEST SNR. The egg white phantom studies were performed at 3T to reveal the contributions to the 3.5 ppm CEST signal. Based on the phantom validation, the amideCEST peak was quantified using the polynomial Lorentzian line-shape fitting, which exploits the inverse relationship between Z-spectral intensity and the longitudinal relaxation rate in the rotating frame. The 3D turbo spin echo CEST was also performed to compare with the starCEST method. RESULTS The amideCEST peak showed a negligible peak B1 dependence between 1.2 µT and 2.4 µT. The amideCEST images acquired with starCEST showed much improved image quality, SNR, and motion robustness compared to the conventional 3D turbo spin echo CEST method with the same scan time. The amideCEST contrast extracted by the polynomial Lorentzian line-shape fitting method trended toward a stronger gray matter signal (1.32% ± 0.30%) than white matter (0.92% ± 0.08%; P = .02, n = 5). When calculating the magnetization transfer contrast and T1 -corrected rotating frame relaxation rate maps, amideCEST again was not significantly different for white matter and gray matter. CONCLUSION Rapid multi-slice amideCEST mapping can be achieved by the starCEST method (< 5 min) at 3T by combing with the polynomial Lorentzian line-shape fitting method.
Collapse
Affiliation(s)
- Ran Sui
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA
| | - Lin Chen
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, People's Republic of China
| | - Yuguo Li
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jianpan Huang
- Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, People's Republic of China
| | - Kannie W Y Chan
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,Department of Biomedical Engineering, City University of Hong Kong, Hong Kong, People's Republic of China
| | - Xiang Xu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.,BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Peter C M van Zijl
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Jiadi Xu
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, Maryland, USA.,Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| |
Collapse
|
24
|
Yao J, Wang C, Raymond C, Bergstrom B, Chen X, Das K, Dinh H, Kim ZS, Le AN, Lim MWJ, Pham JAN, Prusan JD, Rao SS, Nathanson DA, Ellingson BM. A physical phantom for amine chemical exchange saturation transfer (CEST) MRI. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2021; 34:569-580. [PMID: 33484366 DOI: 10.1007/s10334-020-00902-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Revised: 11/13/2020] [Accepted: 12/09/2020] [Indexed: 11/26/2022]
Abstract
OBJECTIVE To develop a robust amine chemical exchange saturation transfer (CEST) physical phantom, validate the temporal stability, and create a supporting software for automatic image processing and quality assurance. MATERIALS AND METHODS The phantom was designed as an assembled laser-cut acrylic rack and 18 vials of phantom solutions, prepared with different pHs, glycine concentrations, and gadolinium concentrations. We evaluated glycine concentrations using ultraviolet absorbance for 70 days and measured the pH, relaxation rates, and CEST contrast for 94 days after preparation. We used Spearman's correlation to determine if glycine degraded over time. Linear regression and Bland-Altman analysis were performed between baseline and follow-up measurements of pH and MRI properties. RESULTS No degradation of glycine was observed (p > 0.05). The pH and MRI measurements stayed stable for 3 months and showed high consistency across time points (R2 = 1.00 for pH, R1, R2, and CEST contrast), which was further validated by the Bland-Altman plots. Examples of automatically generated reports are provided. DISCUSSION We designed a physical phantom for amine CEST-MRI, which is easy to assemble and transfer, holds 18 different solutions, and has excellent short-term chemical and MRI stability. We believe this robust phantom will facilitate the development of novel sequences and cross-scanners validations.
Collapse
Affiliation(s)
- Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Departments of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Departments of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA
- Departments of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA
| | - Blake Bergstrom
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Xing Chen
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kaveri Das
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Bioengineering Innovation and Design, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA
| | - Huy Dinh
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Zoe S Kim
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Angela N Le
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Matthew W J Lim
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Jane A N Pham
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph D Prusan
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sriram S Rao
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - David A Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, CA, USA.
- Departments of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, 924 Westwood Blvd., Suite 615, Los Angeles, CA, 90024, USA.
- Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, CA, USA.
| |
Collapse
|
25
|
Liu G, van Zijl PC. CEST (Chemical Exchange Saturation Transfer) MR Molecular Imaging. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00012-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
|
26
|
Boyd NH, Tran AN, Bernstock JD, Etminan T, Jones AB, Gillespie GY, Friedman GK, Hjelmeland AB. Glioma stem cells and their roles within the hypoxic tumor microenvironment. Theranostics 2021; 11:665-683. [PMID: 33391498 PMCID: PMC7738846 DOI: 10.7150/thno.41692] [Citation(s) in RCA: 96] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2019] [Accepted: 08/04/2020] [Indexed: 02/07/2023] Open
Abstract
Tumor microenvironments are the result of cellular alterations in cancer that support unrestricted growth and proliferation and result in further modifications in cell behavior, which are critical for tumor progression. Angiogenesis and therapeutic resistance are known to be modulated by hypoxia and other tumor microenvironments, such as acidic stress, both of which are core features of the glioblastoma microenvironment. Hypoxia has also been shown to promote a stem-like state in both non-neoplastic and tumor cells. In glial tumors, glioma stem cells (GSCs) are central in tumor growth, angiogenesis, and therapeutic resistance, and further investigation of the interplay between tumor microenvironments and GSCs is critical to the search for better treatment options for glioblastoma. Accordingly, we summarize the impact of hypoxia and acidic stress on GSC signaling and biologic phenotypes, and potential methods to inhibit these pathways.
Collapse
|
27
|
Yao J, Chakhoyan A, Nathanson DA, Yong WH, Salamon N, Raymond C, Mareninov S, Lai A, Nghiemphu PL, Prins RM, Pope WB, Everson RG, Liau LM, Cloughesy TF, Ellingson BM. Metabolic characterization of human IDH mutant and wild type gliomas using simultaneous pH- and oxygen-sensitive molecular MRI. Neuro Oncol 2020; 21:1184-1196. [PMID: 31066901 DOI: 10.1093/neuonc/noz078] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Isocitrate dehydrogenase 1 (IDH1) mutant gliomas are thought to have distinct metabolic characteristics, including a blunted response to hypoxia and lower glycolytic flux. We hypothesized that non-invasive quantification of abnormal metabolic behavior in human IDH1 mutant gliomas could be performed using a new pH- and oxygen-sensitive molecular MRI technique. METHODS Simultaneous pH- and oxygen-sensitive MRI was obtained at 3T using amine CEST-SAGE-EPI. The pH-dependent measure of the magnetization transfer ratio asymmetry (MTRasym) at 3 ppm and oxygen-sensitive measure of R2' were quantified in 90 patients with gliomas. Additionally, stereotactic, image-guided biopsies were performed in 20 patients for a total of 52 samples. The association between imaging measurements and hypoxia-inducible factor 1 alpha (HIF1α) expression was identified using Pearson correlation analysis. RESULTS IDH1 mutant gliomas exhibited significantly lower MTRasym at 3 ppm, R2', and MTRasymxR2' (P = 0.007, P = 0.003, and P = 0.001, respectively). MTRasymxR2' could identify IDH1 mutant gliomas with a high sensitivity (81.0%) and specificity (81.3%). HIF1α was positively correlated with MTRasym at 3 ppm, R2' and MTRasymxR2' in IDH1 wild type (r = 0.610, P = 0.003; r = 0.667, P = 0.008; r = 0.635, P = 0.006), but only MTRasymxR2' in IDH1 mutant gliomas (r = 0.727, P = 0.039). CONCLUSIONS IDH1 mutant gliomas have distinct metabolic and microenvironment characteristics compared with wild type gliomas. An imaging biomarker combining tumor acidity and hypoxia (MTRasymxR2') can differentiate IDH1 mutation status and is correlated with tumor acidity and hypoxia.
Collapse
Affiliation(s)
- Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, California
| | - Ararat Chakhoyan
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - David A Nathanson
- Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - William H Yong
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Sergey Mareninov
- Department of Pathology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Albert Lai
- UCLA Neuro-Oncology Program, University of California Los Angeles, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Phioanh L Nghiemphu
- UCLA Neuro-Oncology Program, University of California Los Angeles, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Robert M Prins
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Richard G Everson
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Linda M Liau
- Department of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program, University of California Los Angeles, Los Angeles, California.,Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, University of California Los Angeles, Los Angeles, California.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, California.,UCLA Neuro-Oncology Program, University of California Los Angeles, Los Angeles, California
| |
Collapse
|
28
|
Abstract
Magnetic resonance imaging (MRI) has been the cornerstone of imaging of brain tumors in the past 4 decades. Conventional MRI remains the workhorse for neuro-oncologic imaging, not only for basic information such as location, extent, and navigation but also able to provide information regarding proliferation and infiltration, angiogenesis, hemorrhage, and more. More sophisticated MRI sequences have extended the ability to assess and quantify these features; for example, permeability and perfusion acquisitions can assess blood-brain barrier disruption and angiogenesis, diffusion techniques can assess cellularity and infiltration, and spectroscopy can address metabolism. Techniques such as fMRI and diffusion fiber tracking can be helpful in diagnostic planning for resection and radiation therapy, and more sophisticated iterations of these techniques can extend our understanding of neurocognitive effects of these tumors and associated treatment responses and effects. More recently, MRI has been used to go beyond such morphological, physiological, and functional characteristics to assess the tumor microenvironment. The current review highlights multiple recent and emerging approaches in MRI to characterize the tumor microenvironment.
Collapse
|
29
|
Yao J, Wang C, Ellingson BM. Influence of phosphate concentration on amine, amide, and hydroxyl CEST contrast. Magn Reson Med 2020; 85:1062-1078. [PMID: 32936483 DOI: 10.1002/mrm.28481] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 07/24/2020] [Accepted: 07/27/2020] [Indexed: 12/11/2022]
Abstract
PURPOSE To evaluate the influence of phosphate on amine, amide, and hydroxyl CEST contrast using Bloch-McConnell simulations applied to physical phantom data. METHODS Phantom solutions of 4 representative metabolites with exchangeable protons-glycine (α-amine protons), Cr (η-amine protons), egg white protein (amide protons), and glucose (hydroxyl protons)-were prepared at different pH levels (5.6 to 8.9) and phosphate concentrations (5 to 80 mM). CEST images of the phantom were collected with CEST-EPI sequence at 3 tesla. The CEST data were then fitted to full Bloch-McConnell equation simulations to estimate the exchange rate constants. With the fitted parameters, simulations were performed to evaluate the intracellular and extracellular contributions of CEST signals in normal brain tissue and brain tumors, as well as in dynamic glucose-enhanced experiments. RESULTS The exchange rates of α-amine and hydroxyl protons were found to be highly dependent on both pH and phosphate concentrations, whereas the exchange rates of η-amine and amide protons were pH-dependent, albeit not catalyzed by phosphate. With phosphate being predominantly intracellular, CEST contrast of α-amine exhibited a higher sensitivity to changes in the extracellular microenvironment. Simulations of dynamic glucose-enhanced signals demonstrated that the contrast between normal and tumor tissue was mostly due to the extracellular CEST effect. CONCLUSION The proton exchange rates in some metabolites can be greatly catalyzed by the presence of phosphate at physiological concentrations, which substantially alters the CEST contrast. Catalytic agents should be considered as confounding factors in future CEST-MRI research. This new dimension may also benefit the development of novel phosphate-sensitive imaging methods.
Collapse
Affiliation(s)
- Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California, USA
| | - Chencai Wang
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, University of California, Los Angeles, Los Angeles, California, USA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California, USA.,Department of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, USA
| |
Collapse
|
30
|
Human IDH mutant 1p/19q co-deleted gliomas have low tumor acidity as evidenced by molecular MRI and PET: a retrospective study. Sci Rep 2020; 10:11922. [PMID: 32681084 PMCID: PMC7367867 DOI: 10.1038/s41598-020-68733-5] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2020] [Accepted: 06/01/2020] [Indexed: 01/19/2023] Open
Abstract
Co-deletion of 1p/19q is a hallmark of oligodendroglioma and predicts better survival. However, little is understood about its metabolic characteristics. In this study, we aimed to explore the extracellular acidity of WHO grade II and III gliomas associated with 1p/19q co-deletion. We included 76 glioma patients who received amine chemical exchange saturation transfer (CEST) imaging at 3 T. Magnetic transfer ratio asymmetry (MTRasym) at 3.0 ppm was used as the pH-sensitive CEST biomarker, with higher MTRasym indicating lower pH. To control for the confounder factors, T2 relaxometry and l-6-18F-fluoro-3,4-dihydroxyphenylalnine (18F-FDOPA) PET data were collected in a subset of patients. We found a significantly lower MTRasym in 1p/19q co-deleted gliomas (co-deleted, 1.17% ± 0.32%; non-co-deleted, 1.72% ± 0.41%, P = 1.13 × 10−7), while FDOPA (P = 0.92) and T2 (P = 0.61) were not significantly affected. Receiver operating characteristic analysis confirmed that MTRasym could discriminate co-deletion status with an area under the curve of 0.85. In analysis of covariance, 1p/19q co-deletion status was the only significant contributor to the variability in MTRasym when controlling for age and FDOPA (P = 2.91 × 10−3) or T2 (P = 8.03 × 10−6). In conclusion, 1p/19q co-deleted gliomas were less acidic, which may be related to better prognosis. Amine CEST-MRI may serve as a non-invasive biomarker for identifying 1p/19q co-deletion status.
Collapse
|
31
|
Foo LS, Yap WS, Hum YC, Manan HA, Tee YK. Analysis of model-based and model-free CEST effect quantification methods for different medical applications. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2020; 310:106648. [PMID: 31760147 DOI: 10.1016/j.jmr.2019.106648] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Revised: 11/11/2019] [Accepted: 11/12/2019] [Indexed: 06/10/2023]
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) holds great potential to provide new metabolic information for clinical applications such as tumor, stroke and Parkinson's Disease diagnosis. Many active research and developments have been conducted to translate this emerging MRI technique for routine clinical applications. In general, there are two CEST quantification techniques: (i) model-free and (ii) model-based techniques. The reliability of these quantification techniques depends heavily on the experimental conditions and quality of the collected data. Errors such as noise may lead to misleading quantification results and thus inaccurate diagnosis when CEST imaging becomes a standard or routine imaging scan in the future. This paper investigates the accuracy and robustness of these quantification techniques under different signal-to-noise (SNR) levels and magnetic field strengths. The quantified CEST effect before and after adding random Gaussian White Noise using model-free and model-based quantification techniques were compared. It was found that the model-free technique consistently yielded larger average percentage error across all tested parameters compared to its model-based counterpart, and that the model-based technique could withstand SNR of about 3 times lower than the model-free technique. When applied on noisy brain tumor, ischemic stroke, and Parkinson's Disease clinical data, the model-free technique failed to produce significant differences between normal and abnormal tissue whereas the model-based technique consistently generated significant differences. Although the model-free technique was less accurate and robust, its simplicity and thus speed would still make it a good approximate when the SNR was high (>50) or when the CEST effect was large and well-defined. For more accurate CEST quantification, model-based techniques should be considered. When SNR was low (<50) and the CEST effect was small such as those acquired from clinical field strength scanners, which are generally 3T and below, model-based techniques should be considered over model-free counterpart to maintain an average percentage error of less than 44% even under very noisy condition as tested in this work.
Collapse
Affiliation(s)
- Lee Sze Foo
- Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
| | - Wun-She Yap
- Department of Electrical and Electronic Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
| | - Yan Chai Hum
- Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia
| | - Hanani Abdul Manan
- Department of Radiology, Universiti Kebangsaan Malaysia Medical Centre, Malaysia
| | - Yee Kai Tee
- Department of Mechatronics and Biomedical Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Malaysia.
| |
Collapse
|
32
|
Okuchi S, Hammam A, Golay X, Kim M, Thust S. Endogenous Chemical Exchange Saturation Transfer MRI for the Diagnosis and Therapy Response Assessment of Brain Tumors: A Systematic Review. Radiol Imaging Cancer 2020; 2:e190036. [PMID: 33778693 PMCID: PMC7983695 DOI: 10.1148/rycan.2020190036] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2019] [Revised: 09/13/2019] [Accepted: 10/21/2019] [Indexed: 01/09/2023]
Abstract
Purpose To generate a narrative synthesis of published data on the use of endogenous chemical exchange saturation transfer (CEST) MRI in brain tumors. Materials and Methods A systematic database search (PubMed, Ovid Embase, Cochrane Library) was used to collate eligible studies. Two researchers independently screened publications according to predefined exclusion and inclusion criteria, followed by comprehensive data extraction. All included studies were subjected to a bias risk assessment using the Quality Assessment of Diagnostic Accuracy Studies tool. Results The electronic database search identified 430 studies, of which 36 fulfilled the inclusion criteria. The final selection of included studies was categorized into five groups as follows: grading gliomas, 19 studies (area under the receiver operating characteristic curve [AUC], 0.500-1.000); predicting molecular subtypes of gliomas, five studies (AUC, 0.610-0.920); distinction of different brain tumor types, seven studies (AUC, 0.707-0.905); therapy response assessment, three studies (AUC not given); and differentiating recurrence from treatment-related changes, five studies (AUC, 0.880-0.980). A high bias risk was observed in a substantial proportion of studies. Conclusion Endogenous CEST MRI offers valuable, potentially unique information in brain tumors, but its diagnostic accuracy remains incompletely known. Further research is required to assess the method's role in support of molecular genetic diagnosis, to investigate its use in the posttreatment phase, and to compare techniques with a view to standardization.Keywords: Brain/Brain Stem, MR-Imaging, Neuro-OncologySupplemental material is available for this article.© RSNA, 2020.
Collapse
Affiliation(s)
- Sachi Okuchi
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Ahmed Hammam
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Xavier Golay
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Mina Kim
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| | - Stefanie Thust
- From the Department of Brain Repair and Rehabilitation, University College London, Institute of Neurology, London, England (S.O., A.H., X.G., M.K., S.T.); Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin-Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan (S.O.); and Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, London, England (S.T.)
| |
Collapse
|
33
|
Goldenberg JM, Pagel MD. Assessments of tumor metabolism with CEST MRI. NMR IN BIOMEDICINE 2019; 32:e3943. [PMID: 29938857 PMCID: PMC7377947 DOI: 10.1002/nbm.3943] [Citation(s) in RCA: 56] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2018] [Revised: 04/13/2018] [Accepted: 04/18/2018] [Indexed: 05/06/2023]
Abstract
Chemical exchange saturation transfer (CEST) is a relatively new contrast mechanism for MRI. CEST MRI exploits a specific MR frequency (chemical shift) of a molecule while generating an image with good spatial resolution using standard MRI techniques, combining the specificity of MRS with the spatial resolution of MRI. Many CEST MRI acquisition methods have been developed to improve analyses of tumor metabolism. GluCEST, CrCEST, and LATEST can map glutamate, creatine, and lactate, which are important metabolites involved in tumor metabolism. GlucoCEST MRI tracks the pharmacokinetics of glucose transport and cell internalization within tumors. CatalyCEST MRI detects enzyme catalysis that changes a substrate CEST agent. AcidoCEST MRI measures extracellular pH of the tumor microenvironment by exploiting a ratio of two pH-dependent CEST signals. This review describes each technique, the technical issues involved with CEST MRI and each specific technique, and the merits and challenges associated with applying each CEST MRI technique to study tumor metabolism.
Collapse
Affiliation(s)
- Joshua M. Goldenberg
- Department of Pharmaceutical Sciences, The University of Arizona, Tucson, AZ, USA
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Mark D. Pagel
- Department of Cancer Systems Imaging, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| |
Collapse
|
34
|
Rivlin M, Navon G. Molecular imaging of tumors by chemical exchange saturation transfer MRI of glucose analogs. Quant Imaging Med Surg 2019; 9:1731-1746. [PMID: 31728315 DOI: 10.21037/qims.2019.09.12] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Early detection of the cancerous process would benefit greatly from imaging at the cellular and molecular level. Increased glucose demand has been recognized as one of the hallmarks of cancerous cells (the "Warburg effect"), hence glucose and its analogs are commonly used for cancer imaging. One example is FDG-PET technique, that led to the use of chemical exchange saturation transfer (CEST) MRI of glucose ("glucoCEST") for tumor imaging. This technique combines high-resolution MRI obtained by conventional imaging with simultaneous molecular information obtained from the exploitation of agents with exchangeable protons from amine, amide or hydroxyl residues with the water signal. In the case of glucoCEST, these agents are based on glucose or its analogs. Recently, preclinical glucoCEST studies demonstrated the ability to increase the sensitivity of MRI to the level of metabolic activity, enabling identification of tumor staging, biologic potential, treatment planning, therapy response and local recurrence, in addition to guiding target biopsy for clinically suspected cancer. However, natural glucose limits this method because of its rapid conversion to lactic acid, leading to reduced CEST effect and short signal duration. For that reason, a variety of glucose analogs have been tested as alternatives to the original glucoCEST. This review discusses the merits of these analogs, including new data on glucose analogs heretofore not reported in the literature. This summarized preclinical data may help strengthen the translation of CEST MRI of glucose analogs into the clinic, improving cancer imaging to enable early intervention without the need for invasive techniques. The data should also broaden our knowledge of fundamental biological processes.
Collapse
Affiliation(s)
- Michal Rivlin
- School of Chemistry, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel
| | - Gil Navon
- School of Chemistry, Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel
| |
Collapse
|
35
|
Chan RW, Myrehaug S, Stanisz GJ, Sahgal A, Lau AZ. Quantification of pulsed saturation transfer at 1.5T and 3T. Magn Reson Med 2019; 82:1684-1699. [DOI: 10.1002/mrm.27856] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2019] [Revised: 05/12/2019] [Accepted: 05/21/2019] [Indexed: 12/22/2022]
Affiliation(s)
- Rachel W. Chan
- Department of Physical Sciences Sunnybrook Research Institute Toronto Canada
| | - Sten Myrehaug
- Department of Radiation Oncology Sunnybrook Health Sciences Centre Toronto Canada
- Department of Radiation Oncology University of Toronto Toronto Canada
| | - Greg J. Stanisz
- Department of Physical Sciences Sunnybrook Research Institute Toronto Canada
- Department of Medical Biophysics University of Toronto Toronto Canada
- Department of Neurosurgery and Pediatric Neurosurgery Medical University Lublin Poland
| | - Arjun Sahgal
- Department of Physical Sciences Sunnybrook Research Institute Toronto Canada
- Department of Radiation Oncology Sunnybrook Health Sciences Centre Toronto Canada
- Department of Radiation Oncology University of Toronto Toronto Canada
| | - Angus Z. Lau
- Department of Physical Sciences Sunnybrook Research Institute Toronto Canada
- Department of Medical Biophysics University of Toronto Toronto Canada
| |
Collapse
|
36
|
Wang YL, Yao J, Chakhoyan A, Raymond C, Salamon N, Liau LM, Nghiemphu PL, Lai A, Pope WB, Nguyen N, Ji M, Cloughesy TF, Ellingson BM. Association between Tumor Acidity and Hypervascularity in Human Gliomas Using pH-Weighted Amine Chemical Exchange Saturation Transfer Echo-Planar Imaging and Dynamic Susceptibility Contrast Perfusion MRI at 3T. AJNR Am J Neuroradiol 2019; 40:979-986. [PMID: 31097430 DOI: 10.3174/ajnr.a6063] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Accepted: 04/10/2019] [Indexed: 01/15/2023]
Abstract
BACKGROUND AND PURPOSE Acidification of the tumor microenvironment from abnormal metabolism along with angiogenesis to meet metabolic demands are both hallmarks of malignant brain tumors; however, the interdependency of tumor acidity and vascularity has not been explored. Therefore, our aim was to investigate the association between pH-sensitive amine chemical exchange saturation transfer echoplanar imaging (CEST-EPI) and relative cerebral blood volume (CBV) measurements obtained from dynamic susceptibility contrast (DSC) perfusion MRI in patients with gliomas. MATERIALS AND METHODS In this retrospective study, 90 patients with histologically confirmed gliomas were scanned between 2015 and 2018 (median age, 50.3 years; male/female ratio = 59:31). pH-weighting was obtained using chemical exchange saturation transfer echo-planar imaging estimation of the magnetization transfer ratio asymmetry at 3 ppm, and CBV was estimated using DSC-MR imaging. The voxelwise correlation and patient-wise median value correlation between the magnetization transfer ratio asymmetry at 3 ppm and CBV within T2-hyperintense lesions and contrast-enhancing lesions were evaluated using the Pearson correlation analysis. RESULTS General colocalization of elevated perfusion and high acidity was observed in tumors, with local intratumor heterogeneity. For patient-wise analysis, median CBV and magnetization transfer ratio asymmetry at 3 ppm within T2-hyperintense lesions were significantly correlated (R = 0.3180, P = .002), but not in areas of contrast enhancement (P = .52). The positive correlation in T2-hyperintense lesions remained within high-grade gliomas (R = 0.4128, P = .001) and in isocitrate dehydrogenase wild-type gliomas (R = 0.4300, P = .002), but not in World Health Organization II or in isocitrate dehydrogenase mutant tumors. Both magnetization transfer ratio asymmetry at 3 ppm and the voxelwise correlation between magnetization transfer ratio asymmetry and CBV were higher in high-grade gliomas compared with low-grade gliomas in T2-hyperintense tumors (magnetization transfer ratio asymmetry, P = .02; Pearson correlation, P = .01). The same trend held when comparing isocitrate dehydrogenase wild-type gliomas and isocitrate dehydrogenase mutant gliomas (magnetization transfer ratio asymmetry, P = .04; Pearson correlation, P = .01). CONCLUSIONS A positive linear correlation between CBV and acidity in areas of T2-hyperintense, nonenhancing tumor, but not enhancing tumor, was observed across patients. Local heterogeneity was observed within individual tumors.
Collapse
Affiliation(s)
- Y-L Wang
- From the UCLA Brain Tumor Imaging Laboratory (Y.-L.W., J.Y., A.C., C.R., B.M.E.).,Department of Radiology (Y.-L.W.), People's Liberation Army General Hospital, Beijing, China
| | - J Yao
- From the UCLA Brain Tumor Imaging Laboratory (Y.-L.W., J.Y., A.C., C.R., B.M.E.).,Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.).,Department of Bioengineering (J.Y., B.M.E.), Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California
| | - A Chakhoyan
- From the UCLA Brain Tumor Imaging Laboratory (Y.-L.W., J.Y., A.C., C.R., B.M.E.).,Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.)
| | - C Raymond
- From the UCLA Brain Tumor Imaging Laboratory (Y.-L.W., J.Y., A.C., C.R., B.M.E.).,Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.)
| | - N Salamon
- Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.)
| | - L M Liau
- UCLA Brain Research Institute (L.M.L., A.L., B.M.E.).,Department of Neurosurgery (L.M.L.), David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California
| | - P L Nghiemphu
- Department of Neurology (P.L.N., A.L., N.N., M.J., T.F.C.)
| | - A Lai
- Department of Neurology (P.L.N., A.L., N.N., M.J., T.F.C.).,UCLA Brain Research Institute (L.M.L., A.L., B.M.E.)
| | - W B Pope
- Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.)
| | - N Nguyen
- Department of Neurology (P.L.N., A.L., N.N., M.J., T.F.C.)
| | - M Ji
- Department of Neurology (P.L.N., A.L., N.N., M.J., T.F.C.)
| | - T F Cloughesy
- Department of Neurology (P.L.N., A.L., N.N., M.J., T.F.C.)
| | - B M Ellingson
- From the UCLA Brain Tumor Imaging Laboratory (Y.-L.W., J.Y., A.C., C.R., B.M.E.) .,Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences (J.Y., A.C., C.R., N.S., W.B.P., B.M.E.).,Physics and Biology in Medicine (B.M.E.).,Department of Psychiatry and Biobehavioral Sciences (B.M.E.).,UCLA Brain Research Institute (L.M.L., A.L., B.M.E.).,Department of Bioengineering (J.Y., B.M.E.), Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, Los Angeles, California
| |
Collapse
|
37
|
Chemical exchange saturation transfer (CEST) as a new method of signal obtainment in magnetic resonance molecular imaging in clinical and research practice. Pol J Radiol 2019; 84:e147-e152. [PMID: 31019609 PMCID: PMC6479148 DOI: 10.5114/pjr.2019.84242] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2019] [Accepted: 02/14/2019] [Indexed: 01/04/2023] Open
Abstract
The work describes the physical basis of the chemical exchange saturation transfer (CEST) technique; it presents the beginnings of the implementation of the method and its possible applications. The principles of correct data acquisition and possible solutions used during the design of the CEST sequence are shown. The main problems related to data analysis are indicated, and an example Z-spectrum from in vivo study of the rat brain is introduced. Furthermore, the parameters related to spectrum analyses such as magnetisation transfer asymmetry (MTRasym) and amide proton transfer asymmetry (APTasym) are presented. In the following part, different types of the CEST method often mentioned in the literature are discussed. Subsequently, the possible applications of the CEST method in both clinical and experimental practice are described.
Collapse
|
38
|
Ellingson BM, Yao J, Raymond C, Chakhoyan A, Khatibi K, Salamon N, Villablanca JP, Wanner I, Real CR, Laiwalla A, McArthur DL, Monti MM, Hovda DA, Vespa PM. pH-weighted molecular MRI in human traumatic brain injury (TBI) using amine proton chemical exchange saturation transfer echoplanar imaging (CEST EPI). Neuroimage Clin 2019; 22:101736. [PMID: 30826686 PMCID: PMC6396390 DOI: 10.1016/j.nicl.2019.101736] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2018] [Revised: 01/09/2019] [Accepted: 02/24/2019] [Indexed: 12/28/2022]
Abstract
Cerebral acidosis is a consequence of secondary injury mechanisms following traumatic brain injury (TBI), including excitotoxicity and ischemia, with potentially significant clinical implications. However, there remains an unmet clinical need for technology for non-invasive, high resolution pH imaging of human TBI for studying metabolic changes following injury. The current study examined 17 patients with TBI and 20 healthy controls using amine chemical exchange saturation transfer echoplanar imaging (CEST EPI), a novel pH-weighted molecular MR imaging technique, on a clinical 3T MR scanner. Results showed significantly elevated pH-weighted image contrast (MTRasym at 3 ppm) in areas of T2 hyperintensity or edema (P < 0.0001), and a strong negative correlation with Glasgow Coma Scale (GCS) at the time of the MRI exam (R2 = 0.4777, P = 0.0021), Glasgow Outcome Scale - Extended (GOSE) at 6 months from injury (R2 = 0.5334, P = 0.0107), and a non-linear correlation with the time from injury to MRI exam (R2 = 0.6317, P = 0.0004). This evidence suggests clinical feasibility and potential value of pH-weighted amine CEST EPI as a high-resolution imaging tool for identifying tissue most at risk for long-term damage due to cerebral acidosis.
Collapse
Affiliation(s)
- Benjamin M Ellingson
- UCLA Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA.
| | - Jingwen Yao
- UCLA Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Dept. of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA, USA
| | - Catalina Raymond
- UCLA Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ararat Chakhoyan
- UCLA Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Kasra Khatibi
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Noriko Salamon
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - J Pablo Villablanca
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Ina Wanner
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Courtney R Real
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Azim Laiwalla
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - David L McArthur
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Martin M Monti
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA; Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - David A Hovda
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Paul M Vespa
- Dept. of Neurosurgery, UCLA Brain Injury Research Center, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| |
Collapse
|
39
|
Harris RJ, Yao J, Chakhoyan A, Raymond C, Leu K, Liau LM, Nghiemphu PL, Lai A, Salamon N, Pope WB, Cloughesy TF, Ellingson BM. Simultaneous pH-sensitive and oxygen-sensitive MRI of human gliomas at 3 T using multi-echo amine proton chemical exchange saturation transfer spin-and-gradient echo echo-planar imaging (CEST-SAGE-EPI). Magn Reson Med 2018; 80:1962-1978. [PMID: 29626359 PMCID: PMC6107417 DOI: 10.1002/mrm.27204] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2017] [Revised: 03/05/2018] [Accepted: 03/11/2018] [Indexed: 01/09/2023]
Abstract
PURPOSE To introduce a new pH-sensitive and oxygen-sensitive MRI technique using amine proton CEST echo spin-and-gradient echo (SAGE) EPI (CEST-SAGE-EPI). METHODS pH-weighting was obtained using CEST estimations of magnetization transfer ratio asymmetry (MTRasym ) at 3 ppm, and oxygen-weighting was obtained using R2' measurements. Glutamine concentration, pH, and relaxation rates were varied in phantoms to validate simulations and estimate relaxation rates. The values of MTRasym and R2' in normal-appearing white matter, T2 hyperintensity, contrast enhancement, and macroscopic necrosis were measured in 47 gliomas. RESULTS Simulation and phantom results confirmed an increase in MTRasym with decreasing pH. The CEST-SAGE-EPI estimates of R2 , R2*, and R2' varied linearly with gadolinium diethylenetriamine penta-acetic acid concentration (R2 = 6.2 mM-1 ·sec-1 and R2* = 6.9 mM-1 ·sec-1 ). The CEST-SAGE-EPI and Carr-Purcell-Meiboom-Gill estimates of R2 (R2 = 0.9943) and multi-echo gradient-echo estimates of R2* (R2 = 0.9727) were highly correlated. T2 lesions had lower R2' and higher MTRasym compared with normal-appearing white matter, suggesting lower hypoxia and high acidity, whereas contrast-enhancement tumor regions had elevated R2' and MTRasym , indicating high hypoxia and acidity. CONCLUSION The CEST-SAGE-EPI technique provides simultaneous pH-sensitive and oxygen-sensitive image contrasts for evaluation of the brain tumor microenvironment. Advantages include fast whole-brain acquisition, in-line B0 correction, and simultaneous estimation of CEST effects, R2 , R2*, and R2' at 3 T.
Collapse
Affiliation(s)
- Robert J. Harris
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Physics and Biology in Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA
| | - Ararat Chakhoyan
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Kevin Leu
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Physics and Biology in Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Linda M. Liau
- UCLA Brain Research Institute (BRI), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Phioanh L. Nghiemphu
- Dept. of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Albert Lai
- Dept. of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- UCLA Brain Research Institute (BRI), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Noriko Salamon
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Whitney B. Pope
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Timothy F. Cloughesy
- Dept. of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Benjamin M. Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Physics and Biology in Medicine, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- Dept. of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA
- Dept. of Psychiatry and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
- UCLA Brain Research Institute (BRI), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| |
Collapse
|
40
|
Abstract
Magnetic resonance spectroscopy (MRS) can be performed in vivo using commercial MRI systems to obtain biochemical information about tissues and cancers. Applications in brain, prostate and breast aid lesion detection and characterisation (differential diagnosis), treatment planning and response assessment. Multi-centre clinical trials have been performed in all these tissues. Single centre studies have been performed in many other tissues including cervix, uterus, musculoskeletal and liver. While generally MRS is used to study endogenous metabolites it has also been used in drug studies, for example those that include 19F as part of their structure. Recently the hyperpolarisation of compounds enriched with 13C such as [1-13C] pyruvate has been demonstrated in animal models and now in preliminary clinical studies, permitting the monitoring of biochemical processes with unprecedented sensitivity. This review briefly introduces the underlying methods and then discusses the current status of these applications.
Collapse
Affiliation(s)
- Geoffrey S Payne
- University Hospitals Southampton NHS Foundation Trust, Tremona Road, Southampton SO16 6YD, United Kingdom
| |
Collapse
|
41
|
Yao J, Ruan D, Raymond C, Liau LM, Salamon N, Pope WB, Nghiemphu PL, Lai A, Cloughesy TF, Ellingson BM. Improving B 0 Correction for pH-Weighted Amine Proton Chemical Exchange Saturation Transfer (CEST) Imaging by Use of k-Means Clustering and Lorentzian Estimation. ACTA ACUST UNITED AC 2018; 4:123-137. [PMID: 30320212 PMCID: PMC6173788 DOI: 10.18383/j.tom.2018.00017] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Amine chemical exchange saturation transfer (CEST) echoplanar imaging (EPI) provides unique pH and amino acid MRI contrast, enabling sensitive detection of altered microenvironment properties in various diseases. However, CEST contrast is sensitive to static magnetic field (B0) inhomogeneities. Here we propose 2 new B0 correction algorithms for use in correcting pH-weighted amine CEST EPI based on k-means clustering and Lorentzian fitting of CEST data: the iterative downsampling estimation using Lorentzian fitting and the 2-stage Lorentzian estimation with 4D polynomial fitting. Higher quality images of asymmetric magnetization transfer ratio (MTRasym) at 3.0 ppm could be obtained with the proposed algorithms than with the existing B0 correction methods. In particular, the proposed methods are shown to improve the intertissue consistency, interpatient consistency, and tumor region signal-to-noise ratio of MTRasym at 3.0 ppm images, with nonexcessive computation time.
Collapse
Affiliation(s)
- Jingwen Yao
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA.,Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California Los Angeles, Los Angeles, CA
| | - Dan Ruan
- Departments of Radiation Oncology
| | - Catalina Raymond
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA.,Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Linda M Liau
- Neurosurgery, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Noriko Salamon
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | - Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| | | | | | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory (BTIL), Center for Computer Vision and Imaging Biomarkers, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA
| |
Collapse
|
42
|
Hybrid MR-PET of brain tumours using amino acid PET and chemical exchange saturation transfer MRI. Eur J Nucl Med Mol Imaging 2018; 45:1031-1040. [PMID: 29478081 DOI: 10.1007/s00259-018-3940-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2017] [Accepted: 01/04/2018] [Indexed: 10/18/2022]
Abstract
PURPOSE PET using radiolabelled amino acids has become a promising tool in the diagnostics of gliomas and brain metastasis. Current research is focused on the evaluation of amide proton transfer (APT) chemical exchange saturation transfer (CEST) MR imaging for brain tumour imaging. In this hybrid MR-PET study, brain tumours were compared using 3D data derived from APT-CEST MRI and amino acid PET using O-(2-18F-fluoroethyl)-L-tyrosine (18F-FET). METHODS Eight patients with gliomas were investigated simultaneously with 18F-FET PET and APT-CEST MRI using a 3-T MR-BrainPET scanner. CEST imaging was based on a steady-state approach using a B1 average power of 1μT. B0 field inhomogeneities were corrected a Prametric images of magnetisation transfer ratio asymmetry (MTRasym) and differences to the extrapolated semi-solid magnetisation transfer reference method, APT# and nuclear Overhauser effect (NOE#), were calculated. Statistical analysis of the tumour-to-brain ratio of the CEST data was performed against PET data using the non-parametric Wilcoxon test. RESULTS A tumour-to-brain ratio derived from APT# and 18F-FET presented no significant differences, and no correlation was found between APT# and 18F-FET PET data. The distance between local hot spot APT# and 18F-FET were different (average 20 ± 13 mm, range 4-45 mm). CONCLUSION For the first time, CEST images were compared with 18F-FET in a simultaneous MR-PET measurement. Imaging findings derived from18F-FET PET and APT CEST MRI seem to provide different biological information. The validation of these imaging findings by histological confirmation is necessary, ideally using stereotactic biopsy.
Collapse
|
43
|
Abstract
Magnetic resonance imaging (MRI) is the cornerstone for evaluating patients with brain masses such as primary and metastatic tumors. Important challenges in effectively detecting and diagnosing brain metastases and in accurately characterizing their subsequent response to treatment remain. These difficulties include discriminating metastases from potential mimics such as primary brain tumors and infection, detecting small metastases, and differentiating treatment response from tumor recurrence and progression. Optimal patient management could be benefited by improved and well-validated prognostic and predictive imaging markers, as well as early response markers to identify successful treatment prior to changes in tumor size. To address these fundamental needs, newer MRI techniques including diffusion and perfusion imaging, MR spectroscopy, and positron emission tomography (PET) tracers beyond traditionally used 18-fluorodeoxyglucose are the subject of extensive ongoing investigations, with several promising avenues of added value already identified. These newer techniques provide a wealth of physiologic and metabolic information that may supplement standard MR evaluation, by providing the ability to monitor and characterize cellularity, angiogenesis, perfusion, pH, hypoxia, metabolite concentrations, and other critical features of malignancy. This chapter reviews standard and advanced imaging of brain metastases provided by computed tomography, MRI, and amino acid PET, focusing on potential biomarkers that can serve as problem-solving tools in the clinical management of patients with brain metastases.
Collapse
Affiliation(s)
- Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, CA, United States.
| |
Collapse
|
44
|
Jones KM, Pollard AC, Pagel MD. Clinical applications of chemical exchange saturation transfer (CEST) MRI. J Magn Reson Imaging 2017; 47:11-27. [PMID: 28792646 DOI: 10.1002/jmri.25838] [Citation(s) in RCA: 184] [Impact Index Per Article: 26.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2017] [Accepted: 05/30/2017] [Indexed: 02/06/2023] Open
Abstract
Chemical exchange saturation transfer (CEST) magnetic resonance imaging (MRI) has been developed and employed in multiple clinical imaging research centers worldwide. Selective radiofrequency (RF) saturation pulses with standard 2D and 3D MRI acquisition schemes are now routinely performed, and CEST MRI can produce semiquantitative results using magnetization transfer ratio asymmetry (MTRasym ) analysis while accounting for B0 inhomogeneity. Faster clinical CEST MRI acquisition methods and more quantitative acquisition and analysis routines are under development. Endogenous biomolecules with amide, amine, and hydroxyl groups have been detected during clinical CEST MRI studies, and exogenous CEST agents have also been administered to patients. These CEST MRI tools show promise for contributing to assessments of cerebral ischemia, neurological disorders, lymphedema, osteoarthritis, muscle physiology, and solid tumors. This review summarizes the salient features of clinical CEST MRI protocols and critically evaluates the utility of CEST MRI for these clinical imaging applications. LEVEL OF EVIDENCE 5 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2018;47:11-27.
Collapse
Affiliation(s)
- Kyle M Jones
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona, USA
| | | | - Mark D Pagel
- Department of Biomedical Engineering, University of Arizona, Tucson, Arizona, USA.,Department of Chemistry, Rice University, Houston, Texas, USA.,Department of Cancer Systems Imaging, MD Anderson Cancer Center, Houston, Texas, USA
| |
Collapse
|
45
|
Wenger KJ, Hattingen E, Franz K, Steinbach JP, Bähr O, Pilatus U. Intracellular pH measured by 31 P-MR-spectroscopy might predict site of progression in recurrent glioblastoma under antiangiogenic therapy. J Magn Reson Imaging 2017; 46:1200-1208. [PMID: 28165649 DOI: 10.1002/jmri.25619] [Citation(s) in RCA: 31] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2016] [Accepted: 12/15/2016] [Indexed: 01/05/2023] Open
Abstract
PURPOSE In solid tumors, changes in the expression/activity of plasma membrane ion transporters facilitate proton efflux and enable tumor cells to maintain a higher intracellular pH (pHi ), while the microenvironment (pHe ) is commonly more acidic. This supports various tumor-promoting mechanisms. We propose that these changes in pH take place before a magnetic resonance imaging (MRI)-detectable brain tumor recurrence occurs. MATERIALS AND METHODS We enrolled 66 patients with recurrent glioblastoma, treated with bevacizumab. Patients received a baseline and 8-week follow-up MRI including 1 H/31 P MRSI (spectroscopy) on a 3T clinical scanner, until progressive disease according to Response Assessment in Neuro-Oncology (RANO) criteria occurred. Fourteen patients showed a distant or diffuse tumor recurrence (subsequent tumor) during treatment and were therefore selected for further evaluation. At the site of the subsequent tumor, an area of interest for MRSI voxel selection was retrospectively defined on radiographically unaffected baseline MRI sequences. RESULTS Before treatment, pHi in the area of interest (subsequent tumor) was significantly higher than pHi of the contralateral normal-appearing tissue (control; P < 0.001). It decreased at the time of best response (P = 0.06), followed by a significant increase at progression (P = 0.03; baseline mean: 7.06, median: 7.068, SD: 0.032; best response mean: 7.044, median: 7.036, SD: 0.025; progression mean: 7.08, median: 7.095, SD 0.035). Until progression, the subsequent tumor was not detectable on standard MRI sequences. The area of existing tumor responded similar, but changes were not significant (decrease P = 0.22; increase P = 0.28). CONCLUSION Elevated pHi in radiographically unaffected tissue at baseline might precede MRI-detectable progression in patients with recurrent glioblastoma treated with bevacizumab. LEVEL OF EVIDENCE 2 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2017;46:1200-1208.
Collapse
Affiliation(s)
- Katharina J Wenger
- Dr. Senckenberg Institute of Neurooncology, University Hospital Frankfurt, Goethe University, Frankfurt, Germany.,German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Elke Hattingen
- Institute of Neuroradiology, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Kea Franz
- Department of Neurosurgery, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| | - Joachim P Steinbach
- Dr. Senckenberg Institute of Neurooncology, University Hospital Frankfurt, Goethe University, Frankfurt, Germany.,German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Oliver Bähr
- Dr. Senckenberg Institute of Neurooncology, University Hospital Frankfurt, Goethe University, Frankfurt, Germany.,German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ulrich Pilatus
- Institute of Neuroradiology, University Hospital Frankfurt, Goethe University, Frankfurt, Germany
| |
Collapse
|