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Rios SA, Oyervides S, Uribe D, Reyes AM, Fanniel V, Vazquez J, Keniry M. Emerging Therapies for Glioblastoma. Cancers (Basel) 2024; 16:1485. [PMID: 38672566 PMCID: PMC11048459 DOI: 10.3390/cancers16081485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2024] [Revised: 04/01/2024] [Accepted: 04/08/2024] [Indexed: 04/28/2024] Open
Abstract
Glioblastoma is most commonly a primary brain tumor and the utmost malignant one, with a survival rate of approximately 12-18 months. Glioblastoma is highly heterogeneous, demonstrating that different types of cells from the same tumor can manifest distinct gene expression patterns and biological behaviors. Conventional therapies such as temozolomide, radiation, and surgery have limitations. As of now, there is no cure for glioblastoma. Alternative treatment methods to eradicate glioblastoma are discussed in this review, including targeted therapies to PI3K, NFKβ, JAK-STAT, CK2, WNT, NOTCH, Hedgehog, and TGFβ pathways. The highly novel application of oncolytic viruses and nanomaterials in combating glioblastoma are also discussed. Despite scores of clinical trials for glioblastoma, the prognosis remains poor. Progress in breaching the blood-brain barrier with nanomaterials and novel avenues for targeted and combination treatments hold promise for the future development of efficacious glioblastoma therapies.
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Affiliation(s)
| | | | | | | | | | | | - Megan Keniry
- School of Integrative Biological and Chemical Sciences, College of Sciences, The University of Texas Rio Grande Valley, Edinburg, TX 78539, USA; (S.A.R.); (D.U.); (A.M.R.)
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2
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Candiota AP, Arús C. Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives. Metabolites 2022; 12:metabo12030243. [PMID: 35323686 PMCID: PMC8950145 DOI: 10.3390/metabo12030243] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/04/2022] [Accepted: 03/10/2022] [Indexed: 11/16/2022] Open
Abstract
This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients.
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Affiliation(s)
- Ana Paula Candiota
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, 08193 Barcelona, Spain;
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Edifici Cs, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
| | - Carles Arús
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, 08193 Barcelona, Spain;
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Edifici Cs, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Correspondence:
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3
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El-Abtah ME, Talati P, Dietrich J, Gerstner ER, Ratai EM. Magnetic resonance spectroscopic imaging for detecting metabolic changes in glioblastoma after anti-angiogenic therapy—a systematic literature review. Neurooncol Adv 2022; 4:vdac103. [PMID: 35892047 PMCID: PMC9307101 DOI: 10.1093/noajnl/vdac103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
The impact of anti-angiogenic therapy (AAT) on patients with glioblastoma (GBM) is unclear due to a disconnect between radiographic findings and overall survivorship. MR spectroscopy (MRS) can provide clinically relevant information regarding tumor metabolism in response to AAT. This review explores the use of MRS to track metabolic changes in patients with GBM treated with AAT.
Methods
We conducted a systematic literature review in accordance with PRISMA guidelines to identify primary research articles that reported metabolic changes in GBMs treated with AAT. Collected variables included single or multi-voxel MRS acquisition parameters, metabolic markers, reported metabolic changes in response to AAT, and survivorship data.
Results
Thirty-five articles were retrieved in the initial query. After applying inclusion and exclusion criteria, 11 studies with 262 patients were included for qualitative synthesis with all studies performed using multi-voxel 1H MRS. Two studies utilized 31P MRS. Post-AAT initiation, shorter-term survivors had increased choline (cellular proliferation marker), increased lactate (a hypoxia marker), and decreased levels of the short echo time (TE) marker, myo-inositol (an osmoregulator and gliosis marker). MRS detected metabolic changes as soon as 1-day after AAT, and throughout the course of AAT, to predict survival. There was substantial heterogeneity in the timing of scans, which ranged from 1-day to 6–9 months after AAT initiation.
Conclusions
Multi-voxel MRS at intermediate and short TE can serve as a robust prognosticator of outcomes of patients with GBM who are treated with AAT.
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Affiliation(s)
- Mohamed E El-Abtah
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital , Charlestown, Massachusetts , USA
| | - Pratik Talati
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital , Charlestown, Massachusetts , USA
- Department of Neurological Surgery, Massachusetts General Hospital , Boston, Massachusetts , USA
| | - Jorg Dietrich
- Massachusetts General Hospital, Cancer Center , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
| | - Elizabeth R Gerstner
- Massachusetts General Hospital, Cancer Center , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
| | - Eva-Maria Ratai
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital , Charlestown, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
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4
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Li X, Strasser B, Neuberger U, Vollmuth P, Bendszus M, Wick W, Dietrich J, Batchelor TT, Cahill DP, Andronesi OC. Deep learning super-resolution magnetic resonance spectroscopic imaging of brain metabolism and mutant isocitrate dehydrogenase glioma. Neurooncol Adv 2022; 4:vdac071. [PMID: 35911635 PMCID: PMC9332900 DOI: 10.1093/noajnl/vdac071] [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] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Magnetic resonance spectroscopic imaging (MRSI) can be used in glioma patients to map the metabolic alterations associated with IDH1,2 mutations that are central criteria for glioma diagnosis. The aim of this study was to achieve super-resolution (SR) MRSI using deep learning to image tumor metabolism in patients with mutant IDH glioma. METHODS We developed a deep learning method based on generative adversarial network (GAN) using Unet as generator network to upsample MRSI by a factor of 4. Neural networks were trained on simulated metabolic images from 75 glioma patients. The performance of deep neuronal networks was evaluated on MRSI data measured in 20 glioma patients and 10 healthy controls at 3T with a whole-brain 3D MRSI protocol optimized for detection of d-2-hydroxyglutarate (2HG). To further enhance structural details of metabolic maps we used prior information from high-resolution anatomical MR imaging. SR MRSI was compared to ground truth by Mann-Whitney U-test of peak signal-to-noise ratio (PSNR), structure similarity index measure (SSIM), feature-based similarity index measure (FSIM), and mean opinion score (MOS). RESULTS Deep learning SR improved PSNR by 17%, SSIM by 5%, FSIM by 7%, and MOS by 30% compared to conventional interpolation methods. In mutant IDH glioma patients proposed method provided the highest resolution for 2HG maps to clearly delineate tumor margins and tumor heterogeneity. CONCLUSIONS Our results indicate that proposed deep learning methods are effective in enhancing spatial resolution of metabolite maps. Patient results suggest that this may have great clinical potential for image guided precision oncology therapy.
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Affiliation(s)
- Xianqi Li
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Department of Mathematical Sciences, Florida Institute of Technology, Melbourne, Florida, USA
| | - Bernhard Strasser
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ulf Neuberger
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Department of Neurology, Heidelberg University Hospital, Heidelberg, Germany
| | - Jorg Dietrich
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Tracy T Batchelor
- Department of Neurology, Brigham and Women Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Dana-Farber Cancer Institute, Boston, Massachusetts, USA
| | - Daniel P Cahill
- Department of Neurosurgery, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Ovidiu C Andronesi
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
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5
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Thapa B, Mareyam A, Stockmann J, Strasser B, Keil B, Hoecht P, Carp S, Li X, Wang Z, Chang YV, Dietrich J, Uhlmann E, Cahill DP, Batchelor T, Wald L, Andronesi OC. In Vivo Absolute Metabolite Quantification Using a Multiplexed ERETIC-RX Array Coil for Whole-Brain MR Spectroscopic Imaging. J Magn Reson Imaging 2021; 56:121-133. [PMID: 34958166 DOI: 10.1002/jmri.28028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 12/01/2021] [Accepted: 12/03/2021] [Indexed: 11/06/2022] Open
Abstract
BACKGROUND Absolute quantification of metabolites in MR spectroscopic imaging (MRSI) requires a stable reference signal of known concentration. The Electronic REference To access In vivo Concentrations (ERETIC) has shown great promise but has not been applied in patients and 3D MRSI. ERETIC hardware has not been integrated with receive arrays due to technical challenges, such as coil combination and unwanted coupling between multiple ERETIC and receive channels, for which we developed mitigation strategies. PURPOSE To develop absolute quantification for whole-brain MRSI in glioma patients. STUDY TYPE Prospective. POPULATION Five healthy volunteers and three patients with isocitrate dehydrogenase mutant glioma (27% female). Calibration and coil loading phantoms. FIELD STRENGTH/SEQUENCE A 3 T; Adiabatic spin-echo spiral 3D MRSI with real-time motion correction, Fluid Attenuated Inversion Recovery (FLAIR), Gradient Recalled Echo (GRE), Multi-echo Magnetization Prepared Rapid Acquisition of Gradient Echo (MEMPRAGE). ASSESSMENT Absolute quantification was performed for five brain metabolites (total N-acetyl-aspartate [NAA]/creatine/choline, glutamine + glutamate, myo-inositol) and the oncometabolite 2-hydroxyglutarate using a custom-built 4x-ERETIC/8x-receive array coil. Metabolite quantification was performed with both EREIC and internal water reference methods. ERETIC signal was transmitted via optical link and used to correct coil loading. Inductive and radiative coupling between ERETIC and receive channels were measured. STATISTICAL TESTS ERETIC and internal water methods for metabolite quantification were compared using Bland-Altman (BA) analysis and the nonparametric Mann-Whitney test. P < 0.05 was considered statistically significant. RESULTS ERETIC could be integrated in receive arrays and inductive coupling dominated (5-886 times) radiative coupling. Phantoms show proportional scaling of the ERETIC signal with coil loading. The BA analysis demonstrated very good agreement (3.3% ± 1.6%) in healthy volunteers, while there was a large difference (36.1% ± 3.8%) in glioma tumors between metabolite concentrations by ERETIC and internal water quantification. CONCLUSION Our results indicate that ERETIC integrated with receive arrays and whole-brain MRSI is feasible for brain metabolites quantification. Further validation is required to probe that ERETIC provides more accurate metabolite concentration in glioma patients. EVIDENCE LEVEL 2 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Bijaya Thapa
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Azma Mareyam
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Jason Stockmann
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Bernhard Strasser
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection, TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | | | - Stefan Carp
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Xianqi Li
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Zhe Wang
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - Yulin V Chang
- Siemens Medical Solutions USA, Boston, Massachusetts, USA
| | - Jorg Dietrich
- Harvard Medical School, Boston, Massachusetts, USA.,Division of Neuro-Oncology, Department of Neurology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Erik Uhlmann
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Neurology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Daniel P Cahill
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Tracy Batchelor
- Harvard Medical School, Boston, Massachusetts, USA.,Department of Neurology, Brigham's and Women Hospital, Boston, Massachusetts, USA.,Dana Farber Cancer Institute, Boston, Massachusetts, USA
| | - Lawrence Wald
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Ovidiu C Andronesi
- A. A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
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6
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El-Abtah ME, Wenke MR, Talati P, Fu M, Kim D, Weerasekera A, He J, Vaynrub A, Vangel M, Rapalino O, Andronesi O, Arrillaga-Romany I, Forst DA, Yen YF, Rosen B, Batchelor TT, Gonzalez RG, Dietrich J, Gerstner ER, Ratai EM. Myo-Inositol Levels Measured with MR Spectroscopy Can Help Predict Failure of Antiangiogenic Treatment in Recurrent Glioblastoma. Radiology 2021; 302:410-418. [PMID: 34751617 PMCID: PMC8805659 DOI: 10.1148/radiol.2021210826] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Background Patients with recurrent glioblastoma (GBM) are often treated with antiangiogenic agents, such as bevacizumab (BEV). Despite therapeutic promise, conventional MRI methods fail to help determine which patients may not benefit from this treatment. Purpose To use MR spectroscopic imaging (MRSI) with intermediate and short echo time to measure corrected myo-inositol (mI)normalized by contralateral creatine (hereafter, mI/c-Cr) in participants with recurrent GBM treated with BEV and to investigate whether such measurements can help predict survivorship before BEV initiation (baseline) and at 1 day, 4 weeks, and 8 weeks thereafter. Materials and Methods In this prospective longitudinal study (2016-2020), spectroscopic data on mI-a glial marker and osmoregulator within the brain-normalized by contralateral creatine in the intratumoral, contralateral, and peritumoral volumes of patients with recurrent GBM were evaluated. Area under the receiver operating characteristic curve (AUC) was calculated for all volumes at baseline and 1 day, 4 weeks, and 8 weeks after treatment to determine the ability of mI/c-Cr to help predict survivorship. Results Twenty-one participants (median age ± standard deviation, 62 years ± 12; 15 men) were evaluated. Lower mI/c-Cr in the tumor before and during BEV treatment was predictive of poor survivorship, with receiver operating characteristic analyses showing an AUC of 0.75 at baseline, 0.87 at 1 day after treatment, and 1 at 8 weeks after. A similar result was observed in contralateral normal-appearing tissue and the peritumoral volume, with shorter-term survivors having lower levels of mI/c-Cr. In the contralateral volume, a lower ratio of mI to creatine (hereafter, mI/Cr) predicted shorter-term survival at baseline and all other time points. Within the peritumoral volume, lower mI/c-Cr levels were predictive of shorter-term survival at baseline (AUC, 0.80), at 1 day after treatment (AUC, 0.93), and at 4 weeks after treatment (AUC, 0.68). Conclusion Lower levels of myo-inositol normalized by contralateral creatine within intratumoral, contralateral, and peritumoral volumes were predictive of poor survivorship and antiangiogenic treatment failure as early as before bevacizumab treatment. Adapting MR spectroscopic imaging alongside conventional MRI modalities conveys critical information regarding the biologic characteristics of tumors to help better treat individuals with recurrent glioblastoma. Clinical trial registration no. NCT02843230 © RSNA, 2021 Online supplemental material is available for this article.
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7
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Talati P, El-Abtah M, Kim D, Dietrich J, Fu M, Wenke M, He J, Natheir SN, Vangel M, Rapalino O, Vaynrub A, Arrillaga-Romany I, Forst DA, Yen YF, Andronesi O, Kalpathy-Cramer J, Rosen B, Batchelor TT, Gonzalez RG, Gerstner ER, Ratai EM. MR spectroscopic imaging predicts early response to anti-angiogenic therapy in recurrent glioblastoma. Neurooncol Adv 2021; 3:vdab060. [PMID: 34131648 PMCID: PMC8193903 DOI: 10.1093/noajnl/vdab060] [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] [Indexed: 12/03/2022] Open
Abstract
Background Determining failure to anti-angiogenic therapy in recurrent glioblastoma (GBM) (rGBM) remains a challenge. The purpose of the study was to assess treatment response to bevacizumab-based therapy in patients with rGBM using MR spectroscopy (MRS). Methods We performed longitudinal MRI/MRS in 33 patients with rGBM to investigate whether changes in N-acetylaspartate (NAA)/Choline (Cho) and Lactate (Lac)/NAA from baseline to subsequent time points after treatment can predict early failures to bevacizumab-based therapies. Results After stratifying based on 9-month survival, longer-term survivors had increased NAA/Cho and decreased Lac/NAA levels compared to shorter-term survivors. ROC analyses for intratumoral NAA/Cho correlated with survival at 1 day, 2 weeks, 8 weeks, and 16 weeks. Intratumoral Lac/NAA ROC analyses were predictive of survival at all time points tested. At the 8-week time point, 88% of patients with decreased NAA/Cho did not survive 9 months; furthermore, 90% of individuals with an increased Lac/NAA from baseline did not survive at 9 months. No other metabolic ratios tested significantly predicted survival. Conclusions Changes in metabolic levels of tumoral NAA/Cho and Lac/NAA can serve as early biomarkers for predicting treatment failure to anti-angiogenic therapy as soon as 1 day after bevacizumab-based therapy. The addition of MRS to conventional MR methods can provide better insight into how anti-angiogenic therapy affects tumor microenvironment and predict patient outcomes.
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Affiliation(s)
- Pratik Talati
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Department of Neurosurgery, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Mohamed El-Abtah
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Daniel Kim
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Jorg Dietrich
- Harvard Medical School, Boston, Massachusetts, USA.,Massachusetts General Hospital, Cancer Center, Boston, Massachusetts, USA
| | - Melanie Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Michael Wenke
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Julian He
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Sharif N Natheir
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Mark Vangel
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Otto Rapalino
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Anna Vaynrub
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Isabel Arrillaga-Romany
- Harvard Medical School, Boston, Massachusetts, USA.,Massachusetts General Hospital, Cancer Center, Boston, Massachusetts, USA
| | - Deborah A Forst
- Massachusetts General Hospital, Cancer Center, Boston, Massachusetts, USA
| | - Yi-Fen Yen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Ovidiu Andronesi
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Jayashree Kalpathy-Cramer
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Bruce Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Tracy T Batchelor
- Harvard Medical School, Boston, Massachusetts, USA.,Massachusetts General Hospital, Cancer Center, Boston, Massachusetts, USA
| | - R Gilberto Gonzalez
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
| | - Elizabeth R Gerstner
- Harvard Medical School, Boston, Massachusetts, USA.,Massachusetts General Hospital, Cancer Center, Boston, Massachusetts, USA
| | - Eva-Maria Ratai
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
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8
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Weinberg BD, Kuruva M, Shim H, Mullins ME. Clinical Applications of Magnetic Resonance Spectroscopy in Brain Tumors: From Diagnosis to Treatment. Radiol Clin North Am 2021; 59:349-362. [PMID: 33926682 PMCID: PMC8272438 DOI: 10.1016/j.rcl.2021.01.004] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Magnetic resonance spectroscopy (MRS) is a valuable tool for imaging brain tumors, primarily as an adjunct to conventional imaging and clinical presentation. MRS is useful in initial diagnosis of brain tumors, helping differentiate tumors from possible mimics such as metastatic disease, lymphoma, demyelination, and infection, as well as in the subsequent follow-up of patients after resection and chemoradiation. Unfortunately, the spectroscopic appearance of many pathologies can overlap, and ultimately follow-up or biopsy may be required to make a definitive diagnosis. Future developments may continue to increase the value of MRS for initial diagnosis, treatment planning, and early detection of recurrence.
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Affiliation(s)
- Brent D Weinberg
- Radiology and Imaging Sciences, Emory University, 1364 Clifton Road Northeast BG20, Atlanta, GA 30322, USA.
| | - Manohar Kuruva
- Radiology and Imaging Sciences, Emory University, 1364 Clifton Road Northeast BG20, Atlanta, GA 30322, USA
| | - Hyunsuk Shim
- Radiation Oncology, Emory University, 1365 Clifton Road Northeast, Atlanta, GA 30322, USA
| | - Mark E Mullins
- Radiology and Imaging Sciences, Emory University, 1364 Clifton Road Northeast BG20, Atlanta, GA 30322, USA
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9
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Maudsley AA, Andronesi OC, Barker PB, Bizzi A, Bogner W, Henning A, Nelson SJ, Posse S, Shungu DC, Soher BJ. Advanced magnetic resonance spectroscopic neuroimaging: Experts' consensus recommendations. NMR IN BIOMEDICINE 2021; 34:e4309. [PMID: 32350978 PMCID: PMC7606742 DOI: 10.1002/nbm.4309] [Citation(s) in RCA: 47] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2019] [Revised: 02/01/2020] [Accepted: 03/10/2020] [Indexed: 05/04/2023]
Abstract
Magnetic resonance spectroscopic imaging (MRSI) offers considerable promise for monitoring metabolic alterations associated with disease or injury; however, to date, these methods have not had a significant impact on clinical care, and their use remains largely confined to the research community and a limited number of clinical sites. The MRSI methods currently implemented on clinical MRI instruments have remained essentially unchanged for two decades, with only incremental improvements in sequence implementation. During this time, a number of technological developments have taken place that have already greatly benefited the quality of MRSI measurements within the research community and which promise to bring advanced MRSI studies to the point where the technique becomes a true imaging modality, while making the traditional review of individual spectra a secondary requirement. Furthermore, the increasing use of biomedical MR spectroscopy studies has indicated clinical areas where advanced MRSI methods can provide valuable information for clinical care. In light of this rapidly changing technological environment and growing understanding of the value of MRSI studies for biomedical studies, this article presents a consensus from a group of experts in the field that reviews the state-of-the-art for clinical proton MRSI studies of the human brain, recommends minimal standards for further development of vendor-provided MRSI implementations, and identifies areas which need further technical development.
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Affiliation(s)
- Andrew A Maudsley
- Department of Radiology, Miller School of Medicine, University of Miami, Miami, Florida, USA
| | - Ovidiu C Andronesi
- Department of Radiology, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, Harvard Medical School, Boston, Massachusetts
| | - Peter B Barker
- The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, and the Kennedy Krieger Institute, F.M. Kirby Center for Functional Brain Imaging, Baltimore, Maryland
| | - Alberto Bizzi
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Wolfgang Bogner
- High Field MR Center, Department of Biomedical Imaging and Image-guided Therapy, Medical University Vienna, Vienna, Austria
| | - Anke Henning
- Max Planck Institute for Biological Cybernetics, Tübingen, Germany
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Stefan Posse
- Department of Neurology, University of New Mexico, Albuquerque, New Mexico
| | - Dikoma C Shungu
- Department of Neuroradiology, Weill Cornell Medical College, New York, New York
| | - Brian J Soher
- Department of Radiology, Duke University Medical Center, Durham, North Carolina
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10
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Mishkovsky M, Gusyatiner O, Lanz B, Cudalbu C, Vassallo I, Hamou MF, Bloch J, Comment A, Gruetter R, Hegi ME. Hyperpolarized 13C-glucose magnetic resonance highlights reduced aerobic glycolysis in vivo in infiltrative glioblastoma. Sci Rep 2021; 11:5771. [PMID: 33707647 PMCID: PMC7952603 DOI: 10.1038/s41598-021-85339-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2020] [Accepted: 02/28/2021] [Indexed: 12/15/2022] Open
Abstract
Glioblastoma (GBM) is the most aggressive brain tumor type in adults. GBM is heterogeneous, with a compact core lesion surrounded by an invasive tumor front. This front is highly relevant for tumor recurrence but is generally non-detectable using standard imaging techniques. Recent studies demonstrated distinct metabolic profiles of the invasive phenotype in GBM. Magnetic resonance (MR) of hyperpolarized 13C-labeled probes is a rapidly advancing field that provides real-time metabolic information. Here, we applied hyperpolarized 13C-glucose MR to mouse GBM models. Compared to controls, the amount of lactate produced from hyperpolarized glucose was higher in the compact GBM model, consistent with the accepted "Warburg effect". However, the opposite response was observed in models reflecting the invasive zone, with less lactate produced than in controls, implying a reduction in aerobic glycolysis. These striking differences could be used to map the metabolic heterogeneity in GBM and to visualize the infiltrative front of GBM.
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Affiliation(s)
- Mor Mishkovsky
- Laboratory of Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland.
| | - Olga Gusyatiner
- Neuroscience Research Center, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Service of Neurosurgery Lausanne, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Bernard Lanz
- Laboratory of Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Cristina Cudalbu
- Center for Biomedical Imaging (CIBM), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Irene Vassallo
- Neuroscience Research Center, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Service of Neurosurgery Lausanne, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Marie-France Hamou
- Neuroscience Research Center, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Service of Neurosurgery Lausanne, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Jocelyne Bloch
- Neuroscience Research Center, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
- Service of Neurosurgery Lausanne, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland
| | - Arnaud Comment
- General Electric Healthcare, Chalfont St Giles, Buckinghamshire, HP8 4SP, UK
| | - Rolf Gruetter
- Laboratory of Functional and Metabolic Imaging, École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Center for Biomedical Imaging (CIBM), École Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
- Department of Radiology, University of Geneva (UNIGE), Geneva, Switzerland
- Department of Radiology, University of Lausanne (UNIL), Lausanne, Switzerland
| | - Monika E Hegi
- Neuroscience Research Center, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
- Service of Neurosurgery Lausanne, Lausanne University Hospital (CHUV) and University of Lausanne (UNIL), Lausanne, Switzerland.
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11
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Ruiz-Rodado V, Brender JR, Cherukuri MK, Gilbert MR, Larion M. Magnetic resonance spectroscopy for the study of cns malignancies. PROGRESS IN NUCLEAR MAGNETIC RESONANCE SPECTROSCOPY 2021; 122:23-41. [PMID: 33632416 PMCID: PMC7910526 DOI: 10.1016/j.pnmrs.2020.11.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2020] [Revised: 11/20/2020] [Accepted: 11/22/2020] [Indexed: 05/04/2023]
Abstract
Despite intensive research, brain tumors are amongst the malignancies with the worst prognosis; therefore, a prompt diagnosis and thoughtful assessment of the disease is required. The resistance of brain tumors to most forms of conventional therapy has led researchers to explore the underlying biology in search of new vulnerabilities and biomarkers. The unique metabolism of brain tumors represents one potential vulnerability and the basis for a system of classification. Profiling this aberrant metabolism requires a method to accurately measure and report differences in metabolite concentrations. Magnetic resonance-based techniques provide a framework for examining tumor tissue and the evolution of disease. Nuclear Magnetic Resonance (NMR) analysis of biofluids collected from patients suffering from brain cancer can provide biological information about disease status. In particular, urine and plasma can serve to monitor the evolution of disease through the changes observed in the metabolic profiles. Moreover, cerebrospinal fluid can be utilized as a direct reporter of cerebral activity since it carries the chemicals exchanged with the brain tissue and the tumor mass. Metabolic reprogramming has recently been included as one of the hallmarks of cancer. Accordingly, the metabolic rewiring experienced by these tumors to sustain rapid growth and proliferation can also serve as a potential therapeutic target. The combination of 13C tracing approaches with the utilization of different NMR spectral modalities has allowed investigations of the upregulation of glycolysis in the aggressive forms of brain tumors, including glioblastomas, and the discovery of the utilization of acetate as an alternative cellular fuel in brain metastasis and gliomas. One of the major contributions of magnetic resonance to the assessment of brain tumors has been the non-invasive determination of 2-hydroxyglutarate (2HG) in tumors harboring a mutation in isocitrate dehydrogenase 1 (IDH1). The mutational status of this enzyme already serves as a key feature in the clinical classification of brain neoplasia in routine clinical practice and pilot studies have established the use of in vivo magnetic resonance spectroscopy (MRS) for monitoring disease progression and treatment response in IDH mutant gliomas. However, the development of bespoke methods for 2HG detection by MRS has been required, and this has prevented the wider implementation of MRS methodology into the clinic. One of the main challenges for improving the management of the disease is to obtain an accurate insight into the response to treatment, so that the patient can be promptly diverted into a new therapy if resistant or maintained on the original therapy if responsive. The implementation of 13C hyperpolarized magnetic resonance spectroscopic imaging (MRSI) has allowed detection of changes in tumor metabolism associated with a treatment, and as such has been revealed as a remarkable tool for monitoring response to therapeutic strategies. In summary, the application of magnetic resonance-based methodologies to the diagnosis and management of brain tumor patients, in addition to its utilization in the investigation of its tumor-associated metabolic rewiring, is helping to unravel the biological basis of malignancies of the central nervous system.
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Affiliation(s)
- Victor Ruiz-Rodado
- Neuro-Oncology Branch, National Cancer Institute, Center for Cancer Research, National Institute of Health, Bethesda, United States.
| | - Jeffery R Brender
- Radiation Biology Branch, Center for Cancer Research, National Institute of Health, Bethesda, United States
| | - Murali K Cherukuri
- Radiation Biology Branch, Center for Cancer Research, National Institute of Health, Bethesda, United States
| | - Mark R Gilbert
- Neuro-Oncology Branch, National Cancer Institute, Center for Cancer Research, National Institute of Health, Bethesda, United States
| | - Mioara Larion
- Neuro-Oncology Branch, National Cancer Institute, Center for Cancer Research, National Institute of Health, Bethesda, United States.
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12
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van Houdt PJ, Yang Y, van der Heide UA. Quantitative Magnetic Resonance Imaging for Biological Image-Guided Adaptive Radiotherapy. Front Oncol 2021; 10:615643. [PMID: 33585242 PMCID: PMC7878523 DOI: 10.3389/fonc.2020.615643] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2020] [Accepted: 12/08/2020] [Indexed: 12/20/2022] Open
Abstract
MRI-guided radiotherapy systems have the potential to bring two important concepts in modern radiotherapy together: adaptive radiotherapy and biological targeting. Based on frequent anatomical and functional imaging, monitoring the changes that occur in volume, shape as well as biological characteristics, a treatment plan can be updated regularly to accommodate the observed treatment response. For this purpose, quantitative imaging biomarkers need to be identified that show changes early during treatment and predict treatment outcome. This review provides an overview of the current evidence on quantitative MRI measurements during radiotherapy and their potential as an imaging biomarker on MRI-guided radiotherapy systems.
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Affiliation(s)
- Petra J van Houdt
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Yingli Yang
- Department of Radiation Oncology, University of California, Los Angeles, CA, United States
| | - Uulke A van der Heide
- Department of Radiation Oncology, The Netherlands Cancer Institute, Amsterdam, Netherlands
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13
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14
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Chen HY, Autry AW, Brender JR, Kishimoto S, Krishna MC, Vareth M, Bok RA, Reed GD, Carvajal L, Gordon JW, van Criekinge M, Korenchan DE, Chen AP, Xu D, Li Y, Chang SM, Kurhanewicz J, Larson PEZ, Vigneron DB. Tensor image enhancement and optimal multichannel receiver combination analyses for human hyperpolarized 13 C MRSI. Magn Reson Med 2020; 84:3351-3365. [PMID: 32501614 PMCID: PMC7718428 DOI: 10.1002/mrm.28328] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 04/25/2020] [Accepted: 04/27/2020] [Indexed: 02/06/2023]
Abstract
PURPOSE With the initiation of human hyperpolarized 13 C (HP-13 C) trials at multiple sites and the development of improved acquisition methods, there is an imminent need to maximally extract diagnostic information to facilitate clinical interpretation. This study aims to improve human HP-13 C MR spectroscopic imaging through means of Tensor Rank truncation-Image enhancement (TRI) and optimal receiver combination (ORC). METHODS A data-driven processing framework for dynamic HP 13 C MR spectroscopic imaging (MRSI) was developed. Using patient data sets acquired with both multichannel arrays and single-element receivers from the brain, abdomen, and pelvis, we examined the theory and application of TRI, as well as 2 ORC techniques: whitened singular value decomposition (WSVD) and first-point phasing. Optimal conditions for TRI were derived based on bias-variance trade-off. RESULTS TRI and ORC techniques together provided a 63-fold mean apparent signal-to-noise ratio (aSNR) gain for receiver arrays and a 31-fold gain for single-element configurations, which particularly improved quantification of the lower-SNR-[13 C]bicarbonate and [1-13 C]alanine signals that were otherwise not detectable in many cases. Substantial SNR enhancements were observed for data sets that were acquired even with suboptimal experimental conditions, including delayed (114 s) injection (8× aSNR gain solely by TRI), or from challenging anatomy or geometry, as in the case of a pediatric patient with brainstem tumor (597× using combined TRI and WSVD). Improved correlation between elevated pyruvate-to-lactate conversion, biopsy-confirmed cancer, and mp-MRI lesions demonstrated that TRI recovered quantitative diagnostic information. CONCLUSION Overall, this combined approach was effective across imaging targets and receiver configurations and could greatly benefit ongoing and future HP 13 C MRI research through major aSNR improvements.
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Affiliation(s)
- Hsin-Yu Chen
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Adam W. Autry
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Jeffrey R. Brender
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Shun Kishimoto
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Murali C. Krishna
- Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Maryam Vareth
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Robert A. Bok
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | | | - Lucas Carvajal
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Jeremy W. Gordon
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Mark van Criekinge
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - David E. Korenchan
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | | | - Duan Xu
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Yan Li
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Susan M. Chang
- Department of Neurological Surgery, University of California, San Francisco, California, USA
| | - John Kurhanewicz
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Peder E. Z. Larson
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
| | - Daniel B. Vigneron
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, California, USA
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15
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Advanced magnetic resonance imaging to support clinical drug development for malignant glioma. Drug Discov Today 2020; 26:429-441. [PMID: 33249294 DOI: 10.1016/j.drudis.2020.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/23/2020] [Accepted: 11/18/2020] [Indexed: 11/22/2022]
Abstract
Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.
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16
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Mendel JT, Jaster AW, Yu FF, Morris LC, Lynch PT, Shah BR, Agarwal A, Timmerman RD, Nedzi LA, Raj KM. Fundamentals of Radiation Oncology for Neurologic Imaging. Radiographics 2020; 40:827-858. [PMID: 32216705 DOI: 10.1148/rg.2020190138] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
Although the physical and biologic principles of radiation therapy have remained relatively unchanged, a technologic renaissance has led to continuous and ever-changing growth in the field of radiation oncology. As a result, medical devices, techniques, and indications have changed considerably during the past 20-30 years. For example, advances in CT and MRI have revolutionized the treatment planning process for a variety of central nervous system diseases, including primary and metastatic tumors, vascular malformations, and inflammatory diseases. The resultant improved ability to delineate normal from abnormal tissue has enabled radiation oncologists to achieve more precise targeting and helped to mitigate treatment-related complications. Nevertheless, posttreatment complications still occur and can pose a diagnostic challenge for radiologists. These complications can be divided into acute, early-delayed, and late-delayed complications on the basis of the time that they manifest after radiation therapy and include leukoencephalopathy, vascular complications, and secondary neoplasms. The different irradiation technologies and applications of these technologies in the brain, current concepts used in treatment planning, and essential roles of the radiation oncologist in the setting of brain disease are reviewed. In addition, relevant imaging findings that can be used to delineate the extent of disease before treatment, and the expected posttreatment imaging changes are described. Common and uncommon complications related to radiation therapy and the associated imaging manifestations also are discussed. Familiarity with these entities may aid the radiologist in making the diagnosis and help guide appropriate management. ©RSNA, 2020.
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Affiliation(s)
- J Travis Mendel
- From the Departments of Radiation Oncology (J.T.M., P.T.L., R.D.T., L.A.N.) and Radiology (A.W.J., F.F.Y., L.C.M., B.R.S., A.A., K.M.R.), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Adam W Jaster
- From the Departments of Radiation Oncology (J.T.M., P.T.L., R.D.T., L.A.N.) and Radiology (A.W.J., F.F.Y., L.C.M., B.R.S., A.A., K.M.R.), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Fang F Yu
- From the Departments of Radiation Oncology (J.T.M., P.T.L., R.D.T., L.A.N.) and Radiology (A.W.J., F.F.Y., L.C.M., B.R.S., A.A., K.M.R.), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Lee C Morris
- From the Departments of Radiation Oncology (J.T.M., P.T.L., R.D.T., L.A.N.) and Radiology (A.W.J., F.F.Y., L.C.M., B.R.S., A.A., K.M.R.), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Patrick T Lynch
- From the Departments of Radiation Oncology (J.T.M., P.T.L., R.D.T., L.A.N.) and Radiology (A.W.J., F.F.Y., L.C.M., B.R.S., A.A., K.M.R.), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Bhavya R Shah
- From the Departments of Radiation Oncology (J.T.M., P.T.L., R.D.T., L.A.N.) and Radiology (A.W.J., F.F.Y., L.C.M., B.R.S., A.A., K.M.R.), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Amit Agarwal
- From the Departments of Radiation Oncology (J.T.M., P.T.L., R.D.T., L.A.N.) and Radiology (A.W.J., F.F.Y., L.C.M., B.R.S., A.A., K.M.R.), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Robert D Timmerman
- From the Departments of Radiation Oncology (J.T.M., P.T.L., R.D.T., L.A.N.) and Radiology (A.W.J., F.F.Y., L.C.M., B.R.S., A.A., K.M.R.), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Lucien A Nedzi
- From the Departments of Radiation Oncology (J.T.M., P.T.L., R.D.T., L.A.N.) and Radiology (A.W.J., F.F.Y., L.C.M., B.R.S., A.A., K.M.R.), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
| | - Karuna M Raj
- From the Departments of Radiation Oncology (J.T.M., P.T.L., R.D.T., L.A.N.) and Radiology (A.W.J., F.F.Y., L.C.M., B.R.S., A.A., K.M.R.), The University of Texas Southwestern Medical Center, 5323 Harry Hines Blvd, Dallas, TX 75390
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17
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Julià-Sapé M, Candiota AP, Arús C. Cancer metabolism in a snapshot: MRS(I). NMR IN BIOMEDICINE 2019; 32:e4054. [PMID: 30633389 DOI: 10.1002/nbm.4054] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 11/02/2018] [Accepted: 11/05/2018] [Indexed: 06/09/2023]
Abstract
The contribution of MRS(I) to the in vivo evaluation of cancer-metabolism-derived metrics, mostly since 2016, is reviewed here. Increased carbon consumption by tumour cells, which are highly glycolytic, is now being sampled by 13 C magnetic resonance spectroscopic imaging (MRSI) following the injection of hyperpolarized [1-13 C] pyruvate (Pyr). Hot-spots of, mostly, increased lactate dehydrogenase activity or flow between Pyr and lactate (Lac) have been seen with cancer progression in prostate (preclinical and in humans), brain and pancreas (both preclinical) tumours. Therapy response is usually signalled by decreased Lac/Pyr 13 C-labelled ratio with respect to untreated or non-responding tumour. For therapeutic agents inducing tumour hypoxia, the 13 C-labelled Lac/bicarbonate ratio may be a better metric than the Lac/Pyr ratio. 31 P MRSI may sample intracellular pH changes from brain tumours (acidification upon antiangiogenic treatment, basification at fast proliferation and relapse). The steady state tumour metabolome pattern is still in use for cancer evaluation. Metrics used for this range from quantification of single oncometabolites (such as 2-hydroxyglutarate in mutant IDH1 glial brain tumours) to selected metabolite ratios (such as total choline to N-acetylaspartate (plain ratio or CNI index)) or the whole 1 H MRSI(I) pattern through pattern recognition analysis. These approaches have been applied to address different questions such as tumour subtype definition, following/predicting the response to therapy or defining better resection or radiosurgery limits.
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Affiliation(s)
- Margarida Julià-Sapé
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
| | - Ana Paula Candiota
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
| | - Carles Arús
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, Spain
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona (UAB), Cerdanyola del Vallès, Spain
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18
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Tyurina AN, Pronin IN, Fadeeva LM, Batalov AI, Zakharova NE, Podoprigora AE, Shults EI, Kornienko VN. Proton 3D MR spectroscopy in the diagnosis of glial brain tumors. ACTA ACUST UNITED AC 2019. [DOI: 10.24835/1607-0763-2019-3-8-18] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
The purpose of this study was an assessment of the proton 3D MR spectroscopy efficacy in diagnosis of primary glial brain tumors.Material and methods. Sixty three patients aged from 20 to 60 years with primary glial brain tumors of varying degrees of malignancy were examined. The ratios of main metabolites indices were evaluated with following comparison with the metabolites obtained in gray and white matter of the opposite hemisphere.The ratios of main metabolites: Cho/Cr, NAA/Cr, Cho/NAA showed significant (p <0.005) differences in the groups of patients with low and high grade gliomas.Results. The obtained data proved the efficacy of the proton 3D MR-spectroscopy in predicting of the glial brain tumors malignancy.
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Affiliation(s)
- A. N. Tyurina
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - I. N. Pronin
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - L. M. Fadeeva
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - A. I. Batalov
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - N. E. Zakharova
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - A. E. Podoprigora
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - E. I. Shults
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
| | - V. N. Kornienko
- Federal State Autonomous Institution “N.N. Burdenko National Medical Research Center of Neurosurgery” of the Ministry of Health of the Russian Federation
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19
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Meissner J, Korzowski A, Regnery S, Goerke S, Breitling J, Floca RO, Debus J, Schlemmer H, Ladd ME, Bachert P, Adeberg S, Paech D. Early response assessment of glioma patients to definitive chemoradiotherapy using chemical exchange saturation transfer imaging at 7 T. J Magn Reson Imaging 2019; 50:1268-1277. [DOI: 10.1002/jmri.26702] [Citation(s) in RCA: 36] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Revised: 02/15/2019] [Accepted: 02/15/2019] [Indexed: 12/17/2022] Open
Affiliation(s)
- Jan‐Eric Meissner
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Andreas Korzowski
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Sebastian Regnery
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
| | - Steffen Goerke
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
| | - Johannes Breitling
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
- MPI for Nuclear PhysicsMax‐Planck‐Society Heidelberg Germany
| | - Ralf Omar Floca
- Division of Medical Image ComputingGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Heidelberg Institute of Radiation Oncology (HIRO)National Center for Radiation Research in Oncology (NCRO) Heidelberg Germany
| | - Jürgen Debus
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
| | | | - Mark Edward Ladd
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
- Faculty of MedicineUniversity of Heidelberg Heidelberg Germany
| | - Peter Bachert
- Division of Medical Physics in RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
- Faculty of Physics and AstronomyUniversity of Heidelberg Heidelberg Germany
| | - Sebastian Adeberg
- Department of Radiation OncologyUniversity Hospital Heidelberg Heidelberg Germany
- Heidelberg Institute of Radiation Oncology (HIRO)National Center for Radiation Research in Oncology (NCRO) Heidelberg Germany
| | - Daniel Paech
- Division of RadiologyGerman Cancer Research Center (DKFZ) Heidelberg Germany
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20
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Yu FF, Rapalino O. Treated Gliomas. Neuroradiology 2019. [DOI: 10.1016/b978-0-323-44549-8.00015-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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21
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An Z, Tiwari V, Baxter J, Levy M, Hatanpaa KJ, Pan E, Maher EA, Patel TR, Mickey BE, Choi C. 3D high-resolution imaging of 2-hydroxyglutarate in glioma patients using DRAG-EPSI at 3T in vivo. Magn Reson Med 2018; 81:795-802. [PMID: 30277274 DOI: 10.1002/mrm.27482] [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: 05/08/2018] [Revised: 07/13/2018] [Accepted: 07/16/2018] [Indexed: 12/24/2022]
Abstract
PURPOSE To develop 3D high-resolution imaging of 2-hydroxyglutarate (2HG) at 3T in vivo. METHODS Echo-planar spectroscopic imaging with dual-readout alternated-gradients (DRAG-EPSI), which was recently reported for 2D imaging of 2HG at 7T, was tested for 3D imaging of 2HG at 3T. The frequency drifts and acoustic noise induced by DRAG-EPSI were investigated in comparison with conventional EPSI. Four patients with IDH-mutant gliomas were enrolled for 3D imaging of 2HG and other metabolites. A previously reported 2HG-tailored TE 97-ms PRESS sequence preceded the DRAG-EPSI readout gradients. Unsuppressed water, acquired with EPSI, was used as reference for multi-channel combination, eddy-current compensation, and metabolite quantification. Spectral fitting was conducted with the LCModel using in-house basis sets. RESULTS With gradient strength of 4 mT/m and slew rate of 20 mT/m/ms, DRAG-EPSI produced frequency drifts smaller by 5.5-fold and acoustic noise lower by 25 dB compared to conventional EPSI. In a 19-min scan, 3D DRAG-EPSI provided images of 2HG with precision (CRLB <10%) at a resolution of 10 × 10 × 10 mm3 for a field of view of 240 × 180 × 80 mm3 . 2HG was estimated to be 5 mM in a pre-treatment patient. In 3 post-surgery patients, 2HG estimates were 3-6 mM, and the 2HG distribution was different from the water-T2 image pattern or highly concentrated in the post-contrast enhancing region. CONCLUSION Together with 2HG-optimized PRESS, DRAG-EPSI provides an effective tool for reliable 3D high-resolution imaging of 2HG at 3T in vivo.
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Affiliation(s)
- Zhongxu An
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Vivek Tiwari
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Jeannie Baxter
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Michael Levy
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Kimmo J Hatanpaa
- Department of Pathology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Edward Pan
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, Texas.,Harold C. Simmons Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Elizabeth A Maher
- Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, Texas.,Harold C. Simmons Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, Texas.,Annette Strauss Center for Neuro-Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Toral R Patel
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Bruce E Mickey
- Department of Neurological Surgery, University of Texas Southwestern Medical Center, Dallas, Texas.,Harold C. Simmons Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas.,Annette Strauss Center for Neuro-Oncology, University of Texas Southwestern Medical Center, Dallas, Texas
| | - Changho Choi
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, Texas.,Harold C. Simmons Cancer Center, University of Texas Southwestern Medical Center, Dallas, Texas.,Department of Radiology, University of Texas Southwestern Medical Center, Dallas, Texas
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22
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Chen BB, Lu YS, Yu CW, Lin CH, Chen TWW, Wei SY, Cheng AL, Shih TTF. Imaging biomarkers from multiparametric magnetic resonance imaging are associated with survival outcomes in patients with brain metastases from breast cancer. Eur Radiol 2018; 28:4860-4870. [PMID: 29770848 DOI: 10.1007/s00330-018-5448-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2017] [Revised: 03/02/2018] [Accepted: 03/23/2018] [Indexed: 01/06/2023]
Abstract
OBJECTIVES The aim of this study is to investigate the correlation of survival outcomes with imaging biomarkers from multiparametric magnetic resonance imaging (MRI) in patients with brain metastases from breast cancer (BMBC). METHODS This study was approved by the institutional review board. Twenty-two patients with BMBC who underwent treatment involving bevacizumab on day 1, etoposide on days 2-4, and cisplatin on day 2 in 21-day cycles were prospectively enrolled for a phase II study. Three brain MRIs were performed: before the treatment, on day 1, and on day 21. Eight imaging biomarkers were derived from dynamic contrast-enhanced MRI (Peak, IAUC60, Ktrans, kep, ve), diffusion-weighted imaging [apparent diffusion coefficient (ADC)], and MR spectroscopy (choline/N-acetylaspartate and choline/creatine ratios). The relative changes (Δ) in these biomarkers were correlated with the central nervous system (CNS)-specific progression-free survival (PFS) and overall survival (OS) using the Kaplan-Meier and Cox proportional hazard models. RESULTS There were no significant differences in the survival outcomes as per the changes in the biomarkers on day 1. On day 21, those with a low ΔKtrans (p = 0.024) or ΔADC (p = 0.053) reduction had shorter CNS-specific PFS; further, those with a low ΔPeak (p = 0.012) or ΔIAUC60 (p = 0.04) reduction had shorter OS compared with those with high reductions. In multivariate analyses, ΔKtrans and ΔPeak were independent prognostic factors for CNS-specific PFS and OS, respectively, after controlling for age, size, hormone receptors, and performance status. CONCLUSIONS Multiparametric MRI may help predict the survival outcomes in patients with BMBC. KEY POINTS • Decreased angiogenesis after chemotherapy on day 21 indicated good survival outcome. • ΔK trans was an independent prognostic factors for CNS-specific PFS. • ΔPeak was an independent prognostic factors for OS. • Multiparametric MRI helps clinicians to assess patients with BMBC. • High-risk patients may benefit from more intensive follow-up or treatment strategies.
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Affiliation(s)
- Bang-Bin Chen
- Department of Radiology, College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Medical Imaging, National Taiwan University Hospital, No. 7, Chung-Shan South Rd, Taipei, 10016, Taiwan
| | - Yen-Shen Lu
- Department of Oncology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Chih-Wei Yu
- Department of Radiology, College of Medicine, National Taiwan University, Taipei, Taiwan
- Department of Medical Imaging, National Taiwan University Hospital, No. 7, Chung-Shan South Rd, Taipei, 10016, Taiwan
| | - Ching-Hung Lin
- Department of Oncology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Tom Wei-Wu Chen
- Department of Oncology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Shwu-Yuan Wei
- Department of Radiology, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Ann-Lii Cheng
- Department of Oncology, National Taiwan University Hospital, Taipei, Taiwan
- Department of Internal Medicine, College of Medicine, National Taiwan University, Taipei, Taiwan
| | - Tiffany Ting-Fang Shih
- Department of Radiology, College of Medicine, National Taiwan University, Taipei, Taiwan.
- Department of Medical Imaging, National Taiwan University Hospital, No. 7, Chung-Shan South Rd, Taipei, 10016, Taiwan.
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23
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Li Y, Lafontaine M, Chang S, Nelson SJ. Comparison between Short and Long Echo Time Magnetic Resonance Spectroscopic Imaging at 3T and 7T for Evaluating Brain Metabolites in Patients with Glioma. ACS Chem Neurosci 2018; 9:130-137. [PMID: 29035503 DOI: 10.1021/acschemneuro.7b00286] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Abstract
Three-dimensional proton magnetic resonance spectroscopic imaging (MRSI) is a powerful non-invasive tool for characterizing spatial variations in metabolic profiles for patients with glioma. Metabolic parameters obtained using this technique have been shown to predict treatment response, disease progression, and transformation to a more malignant phenotype. The availability of ultra-high-field MR systems has the potential to improve the characterization of metabolites. The purpose of this study was to compare the metabolite profiles acquired with conventional long echo time (TE) MRSI at 3T with those obtained with short TE MRSI at 3T and 7T in patients with glioma. The data acquisition parameters were optimized separately for each echo time and field strength to obtain volumetric coverage within clinically feasible data acquisition times of 5-10 min. While a higher field strength did provide better detection of metabolites with overlapping peaks, spatial coverage was reduced and the use of inversion recovery to reduce lipid precluded the detection of lipid in regions of necrosis. For serial evaluation of large, heterogeneous lesions, the use of 3T short TE MRSI may thus be preferred. Despite the limited number of metabolites that it is able to detect, the use of 3T long TE MRSI gives the best contrast in choline/N-acetyl aspartate between normal appearing brain and tumor and also allows the separate detection of lactate and lipid. It may therefore be preferred for serial evaluation of patients with high-grade glioma and for detection of malignant transformation in patients with low-grade glioma.
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Affiliation(s)
- Yan Li
- Department of Radiology
and Biomedical Imaging, University of California, San Francisco, California 94143, United States
| | - Marisa Lafontaine
- Department of Radiology
and Biomedical Imaging, University of California, San Francisco, California 94143, United States
| | - Susan Chang
- Department of Neurological Surgery, University of California, San Francisco, California 94122, United States
| | - Sarah J. Nelson
- Department of Radiology
and Biomedical Imaging, University of California, San Francisco, California 94143, United States
- Department of Bioengineering and Therapeutic
Sciences, University of California, San Francisco, California 94158, United States
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24
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Andronesi OC, Esmaeili M, Borra RJH, Emblem K, Gerstner ER, Pinho MC, Plotkin SR, Chi AS, Eichler AF, Dietrich J, Ivy SP, Wen PY, Duda DG, Jain R, Rosen BR, Sorensen GA, Batchelor TT. Early changes in glioblastoma metabolism measured by MR spectroscopic imaging during combination of anti-angiogenic cediranib and chemoradiation therapy are associated with survival. NPJ Precis Oncol 2017; 1:20. [PMID: 29202103 PMCID: PMC5708878 DOI: 10.1038/s41698-017-0020-3] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 04/18/2017] [Accepted: 04/19/2017] [Indexed: 12/13/2022] Open
Abstract
Precise assessment of treatment response in glioblastoma during combined anti-angiogenic and chemoradiation remains a challenge. In particular, early detection of treatment response by standard anatomical imaging is confounded by pseudo-response or pseudo-progression. Metabolic changes may be more specific for tumor physiology and less confounded by changes in blood-brain barrier permeability. We hypothesize that metabolic changes probed by magnetic resonance spectroscopic imaging can stratify patient response early during combination therapy. We performed a prospective longitudinal imaging study in newly diagnosed glioblastoma patients enrolled in a phase II clinical trial of the pan-vascular endothelial growth factor receptor inhibitor cediranib in combination with standard fractionated radiation and temozolomide (chemoradiation). Forty patients were imaged weekly during therapy with an imaging protocol that included magnetic resonance spectroscopic imaging, perfusion magnetic resonance imaging, and anatomical magnetic resonance imaging. Data were analyzed using receiver operator characteristics, Cox proportional hazards model, and Kaplan-Meier survival plots. We observed that the ratio of total choline to healthy creatine after 1 month of treatment was significantly associated with overall survival, and provided as single parameter: (1) the largest area under curve (0.859) in receiver operator characteristics, (2) the highest hazard ratio (HR = 85.85, P = 0.006) in Cox proportional hazards model, (3) the largest separation (P = 0.004) in Kaplan-Meier survival plots. An inverse correlation was observed between total choline/healthy creatine and cerebral blood flow, but no significant relation to tumor volumetrics was identified. Our results suggest that in vivo metabolic biomarkers obtained by magnetic resonance spectroscopic imaging may be an early indicator of response to anti-angiogenic therapy combined with standard chemoradiation in newly diagnosed glioblastoma.
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Affiliation(s)
- Ovidiu C. Andronesi
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Morteza Esmaeili
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: Department of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
| | - Ronald J. H. Borra
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Medical Imaging Centre of Southwest Finland, Department of Diagnostic Radiology, Turku University Hospital, Turku, Finland
- Present Address: Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Kyrre Emblem
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: The Intervention Centre, Clinic for Diagnostics and Intervention, Oslo University Hospital, Oslo, Norway
| | - Elizabeth R. Gerstner
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Marco C. Pinho
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX 75235 USA
| | - Scott R. Plotkin
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Andrew S. Chi
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: Brain Tumor Center, Laura and Isaac Perlmutter Cancer Center, New York University Langone Medical Center and School of Medicine, New York, NY 10016 USA
| | - April F. Eichler
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: Department of Neurology, Maine Medical Center, Portland, ME 04074 USA
| | - Jorg Dietrich
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - S. Percy Ivy
- Cancer Therapy Evaluation Program, National Cancer Institute, Bethesda, MD 20892 USA
| | - Patrick Y. Wen
- Center for Neuro-Oncology, Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA 02114 USA
| | - Dan G. Duda
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Rakesh Jain
- Department of Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Bruce R. Rosen
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
| | - Gregory A. Sorensen
- Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
- Present Address: IMRIS, Deerfield Imaging, Minnetonka, MN 55343 USA
| | - Tracy T. Batchelor
- Stephen E. and Catherine Pappas Center of Neuro-Oncology, Departments of Neurology, Radiation Oncology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114 USA
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