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Rejimon AC, Ramesh KK, Trivedi AG, Huang V, Schreibmann E, Weinberg BD, Kleinberg LR, Shu HKG, Shim H, Olson JJ. The Utility of Spectroscopic MRI in Stereotactic Biopsy and Radiotherapy Guidance in Newly Diagnosed Glioblastoma. Tomography 2024; 10:428-443. [PMID: 38535775 PMCID: PMC10975697 DOI: 10.3390/tomography10030033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 04/01/2024] Open
Abstract
Current diagnostic and therapeutic approaches for gliomas have limitations hindering survival outcomes. We propose spectroscopic magnetic resonance imaging as an adjunct to standard MRI to bridge these gaps. Spectroscopic MRI is a volumetric MRI technique capable of identifying tumor infiltration based on its elevated choline (Cho) and decreased N-acetylaspartate (NAA). We present the clinical translatability of spectroscopic imaging with a Cho/NAA ≥ 5x threshold for delineating a biopsy target in a patient diagnosed with non-enhancing glioma. Then, we describe the relationship between the undertreated tumor detected with metabolite imaging and overall survival (OS) from a pilot study of newly diagnosed GBM patients treated with belinostat and chemoradiation. Each cohort (control and belinostat) were split into subgroups using the median difference between pre-radiotherapy Cho/NAA ≥ 2x and the treated T1-weighted contrast-enhanced (T1w-CE) volume. We used the Kaplan-Meier estimator to calculate median OS for each subgroup. The median OS was 14.4 months when the difference between Cho/NAA ≥ 2x and T1w-CE volumes was higher than the median compared with 34.3 months when this difference was lower than the median. The T1w-CE volumes were similar in both subgroups. We find that patients who had lower volumes of undertreated tumors detected via spectroscopy had better survival outcomes.
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Affiliation(s)
- Abinand C. Rejimon
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Karthik K. Ramesh
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Anuradha G. Trivedi
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Vicki Huang
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Eduard Schreibmann
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
| | - Brent D. Weinberg
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA;
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| | - Lawrence R. Kleinberg
- Department of Radiation Oncology, Johns Hopkins University, Baltimore, MD 21218, USA;
| | - Hui-Kuo G. Shu
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA; (A.C.R.); (K.K.R.); (E.S.); (H.-K.G.S.); (H.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA;
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
| | - Jeffrey J. Olson
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA
- Department of Neurosurgery, Emory University, Atlanta, GA 30322, USA
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Chen X, Li J, Chen D, Zhou Y, Tu Z, Lin M, Kang T, Lin J, Gong T, Zhu L, Zhou J, Lin OY, Guo J, Dong J, Guo D, Qu X. CloudBrain-MRS: An intelligent cloud computing platform for in vivo magnetic resonance spectroscopy preprocessing, quantification, and analysis. JOURNAL OF MAGNETIC RESONANCE (SAN DIEGO, CALIF. : 1997) 2024; 358:107601. [PMID: 38039654 DOI: 10.1016/j.jmr.2023.107601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 11/26/2023] [Accepted: 11/27/2023] [Indexed: 12/03/2023]
Abstract
Magnetic resonance spectroscopy (MRS) is an important clinical imaging method for diagnosis of diseases. MRS spectrum is used to observe the signal intensity of metabolites or further infer their concentrations. Although the magnetic resonance vendors commonly provide basic functions of spectrum plots and metabolite quantification, the spread of clinical research of MRS is still limited due to the lack of easy-to-use processing software or platform. To address this issue, we have developed CloudBrain-MRS, a cloud-based online platform that provides powerful hardware and advanced algorithms. The platform can be accessed simply through a web browser, without the need of any program installation on the user side. CloudBrain-MRS also integrates the classic LCModel and advanced artificial intelligence algorithms and supports batch preprocessing, quantification, and analysis of MRS data from different vendors. Additionally, the platform offers useful functions: (1) Automatically statistical analysis to find biomarkers for diseases; (2) Consistency verification between the classic and artificial intelligence quantification algorithms; (3) Colorful three-dimensional visualization for easy observation of individual metabolite spectrum. Last, data of both healthy subjects and patients with mild cognitive impairment are used to demonstrate the functions of the platform. To the best of our knowledge, this is the first cloud computing platform for in vivo MRS with artificial intelligence processing. We have shared our cloud platform at MRSHub, providing at least two years of free access and service. If you are interested, please visit https://mrshub.org/software_all/#CloudBrain-MRS or https://csrc.xmu.edu.cn/CloudBrain.html.
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Affiliation(s)
- Xiaodie Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Jiayu Li
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Dicheng Chen
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Yirong Zhou
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Zhangren Tu
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Meijin Lin
- Department of Applied Marine Physics & Engineering, Xiamen University, Xiamen, China
| | - Taishan Kang
- Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China
| | - Jianzhong Lin
- Department of Radiology, Zhongshan Hospital Affiliated to Xiamen University, Xiamen, China
| | - Tao Gong
- Departments of Radiology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Liuhong Zhu
- Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China
| | - Jianjun Zhou
- Department of Radiology, Zhongshan Hospital (Xiamen), Fudan University, Xiamen, China
| | - Ou-Yang Lin
- Department of Medical Imaging of Southeast Hospital, Medical College of Xiamen University, Xiamen, China
| | - Jiefeng Guo
- Department of Microelectronics and Integrated Circuit, Xiamen University, Xiamen, China
| | - Jiyang Dong
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China
| | - Di Guo
- School of Computer and Information Engineering, Xiamen University of Technology, Xiamen, China
| | - Xiaobo Qu
- Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, China.
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Mahmoudi N, Dadak M, Bronzlik P, Maudsley AA, Sheriff S, Lanfermann H, Ding XQ. Microstructural and Metabolic Changes in Normal Aging Human Brain Studied with Combined Whole-Brain MR Spectroscopic Imaging and Quantitative MR Imaging. Clin Neuroradiol 2023; 33:993-1005. [PMID: 37336867 PMCID: PMC10654209 DOI: 10.1007/s00062-023-01300-3] [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: 02/28/2023] [Accepted: 04/27/2023] [Indexed: 06/21/2023]
Abstract
PURPOSE This study aimed to detect age-related brain metabolic and microstructural changes in healthy human brains by the use of whole-brain proton magnetic resonance spectroscopic imaging (1H‑MRSI) and quantitative MR imaging (qMRI). METHODS In this study, 60 healthy participants with evenly distributed ages (between 21 and 69 years) and sex underwent MRI examinations at 3T including whole-brain 1H‑MRSI. The concentrations of the metabolites N‑acetylaspartate (NAA), choline-containing compounds (Cho), total creatine and phosphocreatine (tCr), glutamine and glutamate (Glx), and myo-inositol (mI), as well as the brain relaxation times T2, T2' and T1 were measured in 12 regions of interest (ROI) in each hemisphere. Correlations between measured parameters and age were estimated with linear regression analysis and Pearson's correlation test. RESULTS Significant age-related changes of brain regional metabolite concentrations and tissue relaxation times were found: NAA decreased in eight of twelve ROIs, Cho increased in three ROIs, tCr in four ROIs, and mI in three ROIs. Glx displayed a significant decrease in one ROI and an increase in another ROI. T1 increased in four ROIs and T2 in one ROI, while T2' decreased in two ROIs. A negative correlation of tCr concentrations with T2' relaxation time was found in one ROI as well as the positive correlations of age-related T1 relaxation time with concentrations of tCr, mI, Glx and Cho in another ROI. CONCLUSION Normal aging in human brain is associated with coexistent brain regional metabolic alterations and microstructural changes, which may be related to age-related decline in cognitive, affective and psychomotor domains of life in the older population.
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Affiliation(s)
- N Mahmoudi
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany.
| | - M Dadak
- Department of Diagnostic and Interventional Radiology and Neuroradiology, St. Vincenz Hospital Paderborn, Paderborn, Germany
| | - P Bronzlik
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - A A Maudsley
- Department of Radiology, University of Miami School of Medicine, Miami, FL, USA
| | - S Sheriff
- Department of Radiology, University of Miami School of Medicine, Miami, FL, USA
| | - H Lanfermann
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
| | - X-Q Ding
- Institute of Diagnostic and Interventional Neuroradiology, Hannover Medical School, Hannover, Germany
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Trivedi AG, Ramesh KK, Huang V, Mellon EA, Barker PB, Kleinberg LR, Weinberg BD, Shu HKG, Shim H. Spectroscopic MRI-Based Biomarkers Predict Survival for Newly Diagnosed Glioblastoma in a Clinical Trial. Cancers (Basel) 2023; 15:3524. [PMID: 37444634 PMCID: PMC10340675 DOI: 10.3390/cancers15133524] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 06/22/2023] [Accepted: 07/05/2023] [Indexed: 07/15/2023] Open
Abstract
Despite aggressive treatment, glioblastoma has a poor prognosis due to its infiltrative nature. Spectroscopic MRI-measured brain metabolites, particularly the choline to N-acetylaspartate ratio (Cho/NAA), better characterizes the extent of tumor infiltration. In a previous pilot trial (NCT03137888), brain regions with Cho/NAA ≥ 2x normal were treated with high-dose radiation for newly diagnosed glioblastoma patients. This report is a secondary analysis of that trial where spectroscopic MRI-based biomarkers are evaluated for how they correlate with progression-free and overall survival (PFS/OS). Subgroups were created within the cohort based on pre-radiation treatment (pre-RT) median cutoff volumes of residual enhancement (2.1 cc) and metabolically abnormal volumes used for treatment (19.2 cc). We generated Kaplan-Meier PFS/OS curves and compared these curves via the log-rank test between subgroups. For the subgroups stratified by metabolic abnormality, statistically significant differences were observed for PFS (p = 0.019) and OS (p = 0.020). Stratification by residual enhancement did not lead to observable differences in the OS (p = 0.373) or PFS (p = 0.286) curves. This retrospective analysis shows that patients with lower post-surgical Cho/NAA volumes had significantly superior survival outcomes, while residual enhancement, which guides high-dose radiation in standard treatment, had little significance in PFS/OS. This suggests that the infiltrating, non-enhancing component of glioblastoma is an important factor in patient outcomes and should be treated accordingly.
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Affiliation(s)
- Anuradha G. Trivedi
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Karthik K. Ramesh
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Vicki Huang
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Eric A. Mellon
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL 45056, USA
| | - Peter B. Barker
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Lawrence R. Kleinberg
- Department of Radiation Oncology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Brent D. Weinberg
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Hui-Kuo G. Shu
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
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5
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Aldawsari AM, Al-Qaisieh B, Broadbent DA, Bird D, Murray L, Speight R. The role and potential of using quantitative MRI biomarkers for imaging guidance in brain cancer radiotherapy treatment planning: A systematic review. Phys Imaging Radiat Oncol 2023; 27:100476. [PMID: 37565088 PMCID: PMC10410581 DOI: 10.1016/j.phro.2023.100476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Revised: 07/15/2023] [Accepted: 07/19/2023] [Indexed: 08/12/2023] Open
Abstract
Background and purpose Improving the accuracy of brain tumour radiotherapy (RT) treatment planning is important to optimise patient outcomes. This systematic review investigates primary studies providing clinical evidence for the integration of quantitative magnetic resonance imaging (qMRI) biomarkers and MRI radiomics to optimise brain tumour RT planning. Materials and methods PubMed, Scopus, Embase and Web of Science databases were searched for all years until June 21, 2022. The search identified original articles demonstrating clinical evidence for the use of qMRI biomarkers and MRI radiomics for the optimization of brain cancer RT planning. Relevant information was extracted and tabulated, including qMRI metrics and techniques, impact on RT plan optimization and changes in target and normal tissue contouring and dose distribution. Results Nineteen articles met the inclusion criteria. Studies were grouped according to the qMRI biomarkers into: 1) diffusion-weighted imaging (DWI) and perfusion-weighted imaging (PWI; five studies); 2) diffusion tensor imaging (DTI; seven studies); and 3) MR spectroscopic imaging (MRSI; seven studies). No relevant MRI-based radiomics studies were identified. Integration of DTI maps offers the potential for improved organs at risk (OAR) sparing. MRSI metabolic maps are a promising technique for improving delineation accuracy in terms of heterogeneity and infiltration, with OAR sparing. No firm conclusions could be drawn regarding the integration of DWI metrics and PWI maps. Conclusions Integration of qMRI metrics into RT planning offers the potential to improve delineation and OAR sparing. Clinical trials and consensus guidelines are required to demonstrate the clinical benefits of such approaches.
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Affiliation(s)
- Abeer M. Aldawsari
- Leeds Institute of Cardiovascular & Metabolic Medicine (LICAMM), University of Leeds, Woodhouse, Leeds LS2 9JT, United Kingdom
- Radiological Sciences Department, College of Applied Medical Sciences, King Saud University, Riyadh 12371, Saudi Arabia
| | - Bashar Al-Qaisieh
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
| | - David A. Broadbent
- Leeds Institute of Cardiovascular & Metabolic Medicine (LICAMM), University of Leeds, Woodhouse, Leeds LS2 9JT, United Kingdom
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
| | - David Bird
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
| | - Louise Murray
- Department of Clinical Oncology, Leeds Teaching Hospitals NHS Trust, St James’s University Hospital, Leeds LS9 7LP, United Kingdom
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9JT, United Kingdom
| | - Richard Speight
- Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds LS9 7TF, United Kingdom
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Trivedi AG, Kim SH, Ramesh KK, Giuffrida AS, Weinberg BD, Mellon EA, Kleinberg LR, Barker PB, Han H, Shu HKG, Shim H, Schreibmann E. Applying a Radiation Therapy Volume Analysis Pipeline to Determine the Utility of Spectroscopic MRI-Guided Adaptive Radiation Therapy for Glioblastoma. Tomography 2023; 9:1052-1061. [PMID: 37218946 PMCID: PMC10204497 DOI: 10.3390/tomography9030086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 05/12/2023] [Accepted: 05/19/2023] [Indexed: 05/24/2023] Open
Abstract
Accurate radiation therapy (RT) targeting is crucial for glioblastoma treatment but may be challenging using clinical imaging alone due to the infiltrative nature of glioblastomas. Precise targeting by whole-brain spectroscopic MRI, which maps tumor metabolites including choline (Cho) and N-acetylaspartate (NAA), can quantify early treatment-induced molecular changes that other traditional modalities cannot measure. We developed a pipeline to determine how spectroscopic MRI changes during early RT are associated with patient outcomes to provide insight into the utility of adaptive RT planning. Data were obtained from a study (NCT03137888) where glioblastoma patients received high-dose RT guided by the pre-RT Cho/NAA twice normal (Cho/NAA ≥ 2x) volume, and received spectroscopic MRI scans pre- and mid-RT. Overlap statistics between pre- and mid-RT scans were used to quantify metabolic activity changes after two weeks of RT. Log-rank tests were used to quantify the relationship between imaging metrics and patient overall and progression-free survival (OS/PFS). Patients with lower Jaccard/Dice coefficients had longer PFS (p = 0.045 for both), and patients with lower Jaccard/Dice coefficients had higher OS trending towards significance (p = 0.060 for both). Cho/NAA ≥ 2x volumes changed significantly during early RT, putting healthy tissue at risk of irradiation, and warranting further study into using adaptive RT planning.
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Affiliation(s)
- Anuradha G. Trivedi
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Su Hyun Kim
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Karthik K. Ramesh
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Alexander S. Giuffrida
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Brent D. Weinberg
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Eric A. Mellon
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL 45056, USA
| | - Lawrence R. Kleinberg
- Department of Radiation Oncology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Peter B. Barker
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | - Hui-Kuo G. Shu
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Eduard Schreibmann
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
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7
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Huang V, Rejimon A, Reddy K, Trivedi AG, Ramesh KK, Giuffrida AS, Muiruri R, Shim H, Eaton BR. Spectroscopic MRI-Guided Proton Therapy in Non-Enhancing Pediatric High-Grade Glioma. Tomography 2023; 9:633-646. [PMID: 36961010 PMCID: PMC10037577 DOI: 10.3390/tomography9020051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2022] [Revised: 02/24/2023] [Accepted: 03/06/2023] [Indexed: 03/12/2023] Open
Abstract
Radiation therapy (RT) is a critical part of definitive therapy for pediatric high-grade glioma (pHGG). RT is designed to treat residual tumor defined on conventional MRI (cMRI), though pHGG lesions may be ill-characterized on standard imaging. Spectroscopic MRI (sMRI) measures endogenous metabolite concentrations in the brain, and Choline (Cho)/N-acetylaspartate (NAA) ratio is a highly sensitive biomarker for metabolically active tumor. We provide a preliminary report of our study introducing a novel treatment approach of whole brain sMRI-guided proton therapy for pHGG. An observational cohort (c1 = 10 patients) receives standard of care RT; a therapeutic cohort (c2 = 15 patients) receives sMRI-guided proton RT. All patients undergo cMRI and sMRI, a high-resolution 3D whole-brain echo-planar spectroscopic imaging (EPSI) sequence (interpolated resolution of 12 µL) prior to RT and at several follow-up timepoints integrated into diagnostic scans. Treatment volumes are defined by cMRI for c1 and by cMRI and Cho/NAA ≥ 2x for c2. A longitudinal imaging database is used to quantify changes in lesion and metabolite volumes. Four subjects have been enrolled (c1 = 1/c2 = 3) with sMRI imaging follow-up of 4-18 months. Preliminary data suggest sMRI improves identification of pHGG infiltration based on abnormal metabolic activity, and using proton therapy to target sMRI-defined high-risk regions is safe and feasible.
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Affiliation(s)
- Vicki Huang
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Abinand Rejimon
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Kartik Reddy
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Radiology, Children’s Healthcare of Atlanta, Atlanta, GA 30342, USA
| | - Anuradha G. Trivedi
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Karthik K. Ramesh
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Alexander S. Giuffrida
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Robert Muiruri
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, GA 30332, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Bree R. Eaton
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Radiology, Children’s Healthcare of Atlanta, Atlanta, GA 30342, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
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8
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Bell JB, Jin W, Goryawala MZ, Azzam GA, Abramowitz MC, Diwanji T, Ivan ME, del Pilar Guillermo Prieto Eibl M, de la Fuente MI, Mellon EA. Delineation of recurrent glioblastoma by whole brain spectroscopic magnetic resonance imaging. Radiat Oncol 2023; 18:37. [PMID: 36814267 PMCID: PMC9948314 DOI: 10.1186/s13014-023-02219-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 01/31/2023] [Indexed: 02/24/2023] Open
Abstract
BACKGROUND Glioblastoma (GBM) cellularity correlates with whole brain spectroscopic MRI (sMRI) generated relative choline to N-Acetyl-Aspartate ratio (rChoNAA) mapping. In recurrent GBM (rGBM), tumor volume (TV) delineation is challenging and rChoNAA maps may assist with re-RT targeting. METHODS Fourteen rGBM patients underwent sMRI in a prospective study. Whole brain sMRI was performed to generate rChoNAA maps. TVs were delineated by the union of rChoNAA ratio over 2 (rChoNAA > 2) on sMRI and T1PC. rChoNAA > 2 volumes were compared with multiparametric MRI sequences including T1PC, T2/FLAIR, diffusion-restriction on apparent diffusion coefficient (ADC) maps, and perfusion relative cerebral blood volume (rCBV). RESULTS rChoNAA > 2 (mean 27.6 cc, range 6.6-79.1 cc) was different from other imaging modalities (P ≤ 0.05). Mean T1PC volumes were 10.7 cc (range 1.2-31.4 cc). The mean non-overlapping volume of rChoNAA > 2 and T1PC was 29.2 cm3. rChoNAA > 2 was 287% larger (range 23% smaller-873% larger) than T1PC. T2/FLAIR volumes (mean 111.7 cc, range 19.0-232.7 cc) were much larger than other modalities. rCBV volumes (mean 6.2 cc, range 0.2-19.1 cc) and ADC volumes were tiny (mean 0.8 cc, range 0-3.7 cc). Eight in-field failures were observed. Three patients failed outside T1PC but within rChoNAA > 2. No grade 3 toxicities attributable to re-RT were observed. Median progression-free and overall survival for re-RT patients were 6.5 and 7.1 months, respectively. CONCLUSIONS Treatment of rGBM may be optimized by sMRI, and failure patterns suggest benefit for dose-escalation within sMRI-delineated volumes. Dose-escalation and radiologic-pathologic studies are underway to confirm the utility of sMRI in rGBM.
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Affiliation(s)
- Jonathan B. Bell
- grid.26790.3a0000 0004 1936 8606Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, 1475 NW 12th Ave, Miami, FL 33136 USA
| | - William Jin
- grid.26790.3a0000 0004 1936 8606Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, 1475 NW 12th Ave, Miami, FL 33136 USA
| | - Mohammed Z. Goryawala
- grid.26790.3a0000 0004 1936 8606Department of Radiology, Miller School of Medicine, University of Miami, Miami, FL USA
| | - Gregory A. Azzam
- grid.26790.3a0000 0004 1936 8606Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, 1475 NW 12th Ave, Miami, FL 33136 USA
| | - Matthew C. Abramowitz
- grid.26790.3a0000 0004 1936 8606Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, 1475 NW 12th Ave, Miami, FL 33136 USA
| | - Tejan Diwanji
- grid.26790.3a0000 0004 1936 8606Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, 1475 NW 12th Ave, Miami, FL 33136 USA
| | - Michael E. Ivan
- grid.26790.3a0000 0004 1936 8606Department of Neurological Surgery, Miller School of Medicine, University of Miami, Miami, FL USA
| | - Maria del Pilar Guillermo Prieto Eibl
- grid.26790.3a0000 0004 1936 8606Department of Neurology and Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL USA
| | - Macarena I. de la Fuente
- grid.26790.3a0000 0004 1936 8606Department of Neurology and Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL USA
| | - Eric A. Mellon
- grid.26790.3a0000 0004 1936 8606Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, 1475 NW 12th Ave, Miami, FL 33136 USA
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9
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Ramesh KK, Huang V, Rosenthal J, Mellon EA, Goryawala M, Barker PB, Gurbani SS, Trivedi AG, Giuffrida AS, Schreibmann E, Han H, de le Fuente M, Dunbar EM, Holdhoff M, Kleinberg LR, Shu HKG, Shim H, Weinberg BD. A Novel Approach to Determining Tumor Progression Using a Three-Site Pilot Clinical Trial of Spectroscopic MRI-Guided Radiation Dose Escalation in Glioblastoma. Tomography 2023; 9:362-374. [PMID: 36828381 PMCID: PMC9964256 DOI: 10.3390/tomography9010029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Revised: 02/01/2023] [Accepted: 02/02/2023] [Indexed: 02/09/2023] Open
Abstract
Glioblastoma (GBM) is a fatal disease, with poor prognosis exacerbated by difficulty in assessing tumor extent with imaging. Spectroscopic MRI (sMRI) is a non-contrast imaging technique measuring endogenous metabolite levels of the brain that can serve as biomarkers for tumor extension. We completed a three-site study to assess survival benefits of GBM patients when treated with escalated radiation dose guided by metabolic abnormalities in sMRI. Escalated radiation led to complex post-treatment imaging, requiring unique approaches to discern tumor progression from radiation-related treatment effect through our quantitative imaging platform. The purpose of this study is to determine true tumor recurrence timepoints for patients in our dose-escalation multisite study using novel methodology and to report on median progression-free survival (PFS). Follow-up imaging for all 30 trial patients were collected, lesion volumes segmented and graphed, and imaging uploaded to our platform for visual interpretation. Eighteen months post-enrollment, the median PFS was 16.6 months with a median time to follow-up of 20.3 months. With this new treatment paradigm, incidence rate of tumor recurrence one year from treatment is 30% compared to 60-70% failure under standard care. Based on the delayed tumor progression and improved survival, a randomized phase II trial is under development (EAF211).
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Affiliation(s)
- Karthik K. Ramesh
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Vicki Huang
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Jeffrey Rosenthal
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Eric A. Mellon
- Department of Radiation Oncology, University of Miami, Miami, FL 45056, USA
| | | | - Peter B. Barker
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Saumya S. Gurbani
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Anuradha G. Trivedi
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Alexander S. Giuffrida
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA
| | - Eduard Schreibmann
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Hui Han
- Biomedical Imaging Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA 90048, USA
| | | | - Erin M. Dunbar
- Department of Neuro-Oncology and Neurosurgery, Piedmont Atlanta Hospital, Atlanta, GA 30309, USA
| | - Matthias Holdhoff
- Department of Oncology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Lawrence R. Kleinberg
- Department of Radiation Oncology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Hui-Kuo G. Shu
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30322, USA
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Brent D. Weinberg
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA 30322, USA
- Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA 30322, USA
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10
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Ramakrishnan D, von Reppert M, Krycia M, Sala M, Mueller S, Aneja S, Nabavizadeh A, Galldiks N, Lohmann P, Raji C, Ikuta I, Memon F, Weinberg BD, Aboian MS. Evolution and implementation of radiographic response criteria in neuro-oncology. Neurooncol Adv 2023; 5:vdad118. [PMID: 37860269 PMCID: PMC10584081 DOI: 10.1093/noajnl/vdad118] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2023] Open
Abstract
Radiographic response assessment in neuro-oncology is critical in clinical practice and trials. Conventional criteria, such as the MacDonald and response assessment in neuro-oncology (RANO) criteria, rely on bidimensional (2D) measurements of a single tumor cross-section. Although RANO criteria are established for response assessment in clinical trials, there is a critical need to address the complexity of brain tumor treatment response with multiple new approaches being proposed. These include volumetric analysis of tumor compartments, structured MRI reporting systems like the Brain Tumor Reporting and Data System, and standardized approaches to advanced imaging techniques to distinguish tumor response from treatment effects. In this review, we discuss the strengths and limitations of different neuro-oncology response criteria and summarize current research findings on the role of novel response methods in neuro-oncology clinical trials and practice.
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Affiliation(s)
- Divya Ramakrishnan
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Marc von Reppert
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Mark Krycia
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Matthew Sala
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
- Tulane University School of Medicine, New Orleans, Louisiana, USA
| | - Sabine Mueller
- Department of Neurology, Neurosurgery, and Pediatrics, University of California San Francisco, San Francisco, California, USA
| | - Sanjay Aneja
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Ali Nabavizadeh
- Department of Radiology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA
| | - Norbert Galldiks
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Institute of Neuroscience and Medicine (INM-3), Research Center Juelich, Juelich, Germany
- Center for Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Cologne, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine (INM-4), Research Center Juelich, Juelich, Germany
| | - Cyrus Raji
- Department of Radiology, Washington University in St. Louis School of Medicine, St. Louis, Missouri, USA
| | - Ichiro Ikuta
- Department of Radiology, Mayo Clinic, Phoenix, Arizona, USA
| | - Fatima Memon
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
| | - Brent D Weinberg
- Department of Radiology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Mariam S Aboian
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut, USA
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11
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Ryan JT, Nakayama M, Gleeson I, Mannion L, Geso M, Kelly J, Ng SP, Hardcastle N. Functional brain imaging interventions for radiation therapy planning in patients with glioblastoma: a systematic review. Radiat Oncol 2022; 17:178. [PMID: 36371225 PMCID: PMC9653002 DOI: 10.1186/s13014-022-02146-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 10/14/2022] [Indexed: 11/15/2022] Open
Abstract
RATIONALE This systematic review aims to synthesise the outcomes of different strategies of incorporating functional biological markers in the radiation therapy plans of patients with glioblastoma to support clinicians and further research. METHODS The systematic review protocol was registered on PROSPERO (CRD42021221021). A structured search for publications was performed following PRISMA guidelines. Quality assessment was performed using the Newcastle-Ottawa Scale. Study characteristics, intervention methodology and outcomes were extracted using Covidence. Data analysis focused on radiation therapy target volumes, toxicity, dose distributions, recurrence and survival mapped to functional image-guided radiotherapy interventions. RESULTS There were 5733 citations screened, with 53 citations (n = 32 studies) meeting review criteria. Studies compared standard radiation therapy planning volumes with functional image-derived volumes (n = 20 studies), treated radiation therapy volumes with recurrences (n = 15 studies), the impact on current standard target delineations (n = 9 studies), treated functional volumes and survival (n = 8 studies), functionally guided dose escalation (n = 8 studies), radiomics (n = 4 studies) and optimal organ at risk sparing (n = 3 studies). The approaches to target outlining and dose escalation were heterogeneous. The analysis indicated an improvement in median overall survival of over two months compared with a historical control group. Simultaneous-integrated-boost dose escalation of 72-76 Gy in 30 fractions appeared to have an acceptable toxicity profile when delivered with inverse planning to a volume smaller than 100 cm[Formula: see text]. CONCLUSION There was significant heterogeneity between the approaches taken by different study groups when implementing functional image-guided radiotherapy. It is recommended that functional imaging data be incorporated into the gross tumour volume with appropriate technology-specific margins used to create the clinical target volume when designing radiation therapy plans for patients with glioblastoma.
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Affiliation(s)
- John T Ryan
- Department of Medical Imaging and Radiation Sciences, Monash University, Clayton, Melbourne, Australia
- Medical Radiations Department, School of Health and Biomedical Sciences, STEM College, RMIT University Bundoora, Melbourne, Australia
| | - Masao Nakayama
- Division of Radiation Oncology, Kobe University Graduate School of Medicine, 7-5-2 Kusunokicho, Chuou-ku, Kobe, Japan
| | - Ian Gleeson
- Cancer Research UK RadNet Cambridge, Medical Physics, NHS Foundation Trust, Addenbrookes Hospital, Cambridge, CB2 0QQ UK
| | - Liam Mannion
- Division of Midwifery and Radiography, School of Health Sciences, University of London, Northampton Square, London, UK
| | - Moshi Geso
- Medical Radiations Department, School of Health and Biomedical Sciences, STEM College, RMIT University Bundoora, Melbourne, Australia
| | - Jennifer Kelly
- Medical Radiations Department, School of Health and Biomedical Sciences, STEM College, RMIT University Bundoora, Melbourne, Australia
| | - Sweet Ping Ng
- Department of Radiation Oncology, Olivia Newton-John Cancer Wellness and Research Centre, 145 Studley Rd, Heidelberg, Melbourne, Australia
| | - Nicholas Hardcastle
- Department of Physical Sciences, Peter MacCallum Cancer Centre, 305 Grattan St, Melbourne, Australia
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12
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Kotecha RR, Mehta MP. Optimizing the radiotherapy treatment planning process for glioblastoma. Neurooncol Pract 2022; 9:351-353. [DOI: 10.1093/nop/npac051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Affiliation(s)
- Rupesh R Kotecha
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida , Miami, Florida , USA
- Herbert Wertheim College of Medicine, Florida International University , Miami, Florida , USA
| | - Minesh P Mehta
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida , Miami, Florida , USA
- Herbert Wertheim College of Medicine, Florida International University , Miami, Florida , USA
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13
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Xu K, Ramesh K, Huang V, Gurbani SS, Cordova JS, Schreibmann E, Weinberg BD, Sengupta S, Voloschin AD, Holdhoff M, Barker PB, Kleinberg LR, Olson JJ, Shu HKG, Shim H. Final Report on Clinical Outcomes and Tumor Recurrence Patterns of a Pilot Study Assessing Efficacy of Belinostat (PXD-101) with Chemoradiation for Newly Diagnosed Glioblastoma. Tomography 2022; 8:688-700. [PMID: 35314634 PMCID: PMC8938806 DOI: 10.3390/tomography8020057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2022] [Revised: 02/24/2022] [Accepted: 02/28/2022] [Indexed: 11/16/2022] Open
Abstract
Glioblastoma (GBM) is highly aggressive and has a poor prognosis. Belinostat is a histone deacetylase inhibitor with blood–brain barrier permeability, anti-GBM activity, and the potential to enhance chemoradiation. The purpose of this clinical trial was to assess the efficacy of combining belinostat with standard-of-care therapy. Thirteen patients were enrolled in each of control and belinostat cohorts. The belinostat cohort was given a belinostat regimen (500–750 mg/m2 1×/day × 5 days) every three weeks (weeks 0, 3, and 6 of RT). All patients received temozolomide and radiation therapy (RT). RT margins of 5–10 mm were added to generate clinical tumor volumes and 3 mm added to create planning target volumes. Median overall survival (OS) was 15.8 months for the control cohort and 18.5 months for the belinostat cohort (p = 0.53). The recurrence volumes (rGTVs) for the control cohort occurred in areas that received higher radiation doses than that in the belinostat cohort. For those belinostat patients who experienced out-of-field recurrence, tumors were detectable by spectroscopic MRI before RT. Recurrence analysis suggests better in-field control with belinostat. This study highlights the potential of belinostat as a synergistic therapeutic agent for GBM. It may be particularly beneficial to combine this radio-sensitizing effect with spectroscopic MRI-guided RT.
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Affiliation(s)
- Karen Xu
- Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA; (K.X.); (K.R.); (V.H.); (S.S.G.); (J.S.C.); (E.S.)
| | - Karthik Ramesh
- Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA; (K.X.); (K.R.); (V.H.); (S.S.G.); (J.S.C.); (E.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Vicki Huang
- Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA; (K.X.); (K.R.); (V.H.); (S.S.G.); (J.S.C.); (E.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - Saumya S. Gurbani
- Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA; (K.X.); (K.R.); (V.H.); (S.S.G.); (J.S.C.); (E.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
| | - James Scott Cordova
- Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA; (K.X.); (K.R.); (V.H.); (S.S.G.); (J.S.C.); (E.S.)
| | - Eduard Schreibmann
- Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA; (K.X.); (K.R.); (V.H.); (S.S.G.); (J.S.C.); (E.S.)
| | - Brent D. Weinberg
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA;
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA;
| | - Soma Sengupta
- Department of Hematology and Medical Oncology, Emory University, Atlanta, GA 30322, USA; (S.S.); (A.D.V.)
| | - Alfredo D. Voloschin
- Department of Hematology and Medical Oncology, Emory University, Atlanta, GA 30322, USA; (S.S.); (A.D.V.)
| | - Matthias Holdhoff
- Department of Oncology, Johns Hopkins University, Baltimore, MD 21218, USA;
| | - Peter B. Barker
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD 21205, USA;
| | - Lawrence R. Kleinberg
- Department of Radiation Oncology, Johns Hopkins University, Baltimore, MD 21218, USA;
| | - Jeffrey J. Olson
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA;
- Department of Neurosurgery, Emory University, Atlanta, GA 30322, USA
| | - Hui-Kuo G. Shu
- Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA; (K.X.); (K.R.); (V.H.); (S.S.G.); (J.S.C.); (E.S.)
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA;
- Correspondence: (H.-K.G.S.); (H.S.); Tel.: +1-(404)-778-4564 (H.S.)
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA; (K.X.); (K.R.); (V.H.); (S.S.G.); (J.S.C.); (E.S.)
- Department of Biomedical Engineering, Georgia Institute of Technology, Atlanta, GA 30332, USA
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA;
- Winship Cancer Institute, Emory University, Atlanta, GA 30322, USA;
- Correspondence: (H.-K.G.S.); (H.S.); Tel.: +1-(404)-778-4564 (H.S.)
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14
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Grogan D, Bray DP, Cosgrove M, Boucher A, Erwood A, Linder DF, Mendoza P, Morales B, Pradilla G, Nduom EK, Neill S, Olson JJ, Hoang KB. Clinical and radiographic characteristics of diffuse astrocytic glioma, IDH-wildtype, with molecular features of glioblastoma: a single institution review. J Neurooncol 2022; 157:187-195. [PMID: 35212929 PMCID: PMC9703358 DOI: 10.1007/s11060-022-03961-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 02/03/2022] [Indexed: 11/28/2022]
Abstract
PURPOSE Genetic analyses of gliomas have identified key molecular features that impact treatment paradigms beyond conventional histomorphology. Despite at-times lower grade histopathologic appearances, IDH-wildtype infiltrating gliomas expressing certain molecular markers behave like higher-grade tumors. For IDH-wildtype infiltrating gliomas lacking traditional features of glioblastoma, these markers form the basis for the novel diagnosis of diffuse astrocytic glioma, IDH-wildtype (wt), with molecular features of glioblastoma (GBM), WHO grade-IV (DAG-G). However, given the novelty of this approach to diagnosis, literature detailing the exact clinical, radiographic, and histopathologic findings associated with these tumors remain in development. METHODS Data for 25 patients matching the DAG-G diagnosis were obtained from our institution's retrospective database. Information regarding patient demographics, treatment regimens, radiographic imaging, and genetic pathology were analyzed to determine association with clinical outcomes. RESULTS The initial radiographic findings, histopathology, and symptomatology of patients with DAG-G were similar to lower-grade astrocytomas (WHO grade 2/3). Overall survival (OS) and progression free survival (PFS) associated with our cohort, however, were similar to that of IDH-wt GBM, indicating a more severe clinical course than expected from other associated features (15.1 and 5.39 months respectively). CONCLUSION Despite multiple features similar to lower-grade gliomas, patients with DAG-G experience clinical courses similar to GBM. Such findings reinforce the need for biopsy and subsequent analysis of molecular features associated with any astrocytoma regardless of presenting characteristics.
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Affiliation(s)
- Dayton Grogan
- The Medical College of Georgia at Augusta University, Augusta, GA, USA
| | - David P. Bray
- Department of Neurosurgery, Emory University School of Medicine, 1365 Clifton Road, Atlanta, GA 30322, USA
| | - Megan Cosgrove
- Department of Neurosurgery, Emory University School of Medicine, 1365 Clifton Road, Atlanta, GA 30322, USA
| | - Andrew Boucher
- Department of Neurosurgery, Emory University School of Medicine, 1365 Clifton Road, Atlanta, GA 30322, USA
| | - Andrew Erwood
- Department of Neurosurgery, Emory University School of Medicine, 1365 Clifton Road, Atlanta, GA 30322, USA
| | - Daniel F. Linder
- Division of Biostatistics, Medical College of Georgia at Augusta University, Augusta, GA, USA
| | - Pia Mendoza
- Department of Pathology & Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Bryan Morales
- Department of Pathology & Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Gustavo Pradilla
- Department of Neurosurgery, Emory University School of Medicine, 1365 Clifton Road, Atlanta, GA 30322, USA
| | - Edjah K. Nduom
- Department of Neurosurgery, Emory University School of Medicine, 1365 Clifton Road, Atlanta, GA 30322, USA
| | - Stewart Neill
- Department of Pathology & Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Jeffrey J. Olson
- Department of Neurosurgery, Emory University School of Medicine, 1365 Clifton Road, Atlanta, GA 30322, USA
| | - Kimberly B. Hoang
- Department of Neurosurgery, Emory University School of Medicine, 1365 Clifton Road, Atlanta, GA 30322, USA
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15
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Chen G, Cui J, Qian J, Zhu J, Zhao L, Luo B, Cui T, Zhong L, Yang F, Yang G, Zhao X, Zhou Y, Geng M, Sun J. Rapid Progress in Intelligent Radiotherapy and Future Implementation. Cancer Invest 2022; 40:425-436. [PMID: 35225723 DOI: 10.1080/07357907.2022.2044842] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
Radiotherapy is one of the major approaches to cancer treatment. Artificial intelligence in radiotherapy (shortly, Intelligent radiotherapy) mainly involves big data, deep learning, extended reality, digital twin, radiomics, Internet plus and Internet of Things (IoT), which establish an automatic and intelligent network platform consisting of radiotherapy preparation, target volume delineation, treatment planning, radiation delivery, quality assurance (QA) and quality control (QC), prognosis judgment and post-treatment follow-up. Intelligent radiotherapy is an interdisciplinary frontier discipline in infancy. The review aims to summary the important implements of intelligent radiotherapy in various areas and put forward the future of unmanned radiotherapy center.
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Affiliation(s)
- Guangpeng Chen
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
| | - Jianxiong Cui
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China.,Department of Oncology, Sichuan Provincial Crops Hospital of Chinese People's Armed Police Forces, Leshan 614000, Sichuan, P.R. China
| | - Jindong Qian
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
| | - Jianbo Zhu
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
| | - Lirong Zhao
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
| | - Bangyu Luo
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
| | - Tianxiang Cui
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
| | - Liangzhi Zhong
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
| | - Fan Yang
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
| | - Guangrong Yang
- Qijiang District People's Hospital, Chongqing 401420, P.R. China
| | - Xianlan Zhao
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
| | - Yibing Zhou
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
| | - Mingying Geng
- Department of Cancer Center, Daping Hospital, Army Medical University, Chongqing 400042, P.R. China
| | - Jianguo Sun
- Department of Oncology, Xinqiao Hospital, Army Medical University, Chongqing 400037, P.R. China
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16
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Ramesh K, Mellon EA, Gurbani SS, Weinberg BD, Schreibmann E, Sheriff SA, Goryawala M, de le Fuente M, Eaton BR, Zhong J, Voloschin AD, Sengupta S, Dunbar EM, Holdhoff M, Barker PB, Maudsley AA, Kleinberg LR, Shim H, Shu HKG. A multi-institutional pilot clinical trial of spectroscopic MRI-guided radiation dose escalation for newly diagnosed glioblastoma. Neurooncol Adv 2022; 4:vdac006. [PMID: 35382436 PMCID: PMC8976280 DOI: 10.1093/noajnl/vdac006] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Background Glioblastomas (GBMs) are aggressive brain tumors despite radiation therapy (RT) to 60 Gy and temozolomide (TMZ). Spectroscopic magnetic resonance imaging (sMRI), which measures levels of specific brain metabolites, can delineate regions at high risk for GBM recurrence not visualized on contrast-enhanced (CE) MRI. We conducted a clinical trial to assess the feasibility, safety, and efficacy of sMRI-guided RT dose escalation to 75 Gy for newly diagnosed GBMs. Methods Our pilot trial (NCT03137888) enrolled patients at 3 institutions (Emory University, University of Miami, Johns Hopkins University) from September 2017 to June 2019. For RT, standard tumor volumes based on T2-FLAIR and T1w-CE MRIs with margins were treated in 30 fractions to 50.1 and 60 Gy, respectively. An additional high-risk volume based on residual CE tumor and Cho/NAA (on sMRI) ≥2× normal was treated to 75 Gy. Survival curves were generated by the Kaplan-Meier method. Toxicities were assessed according to CTCAE v4.0. Results Thirty patients were treated in the study. The median age was 59 years. 30% were MGMT promoter hypermethylated; 7% harbored IDH1 mutation. With a median follow-up of 21.4 months for censored patients, median overall survival (OS) and progression-free survival were 23.0 and 16.6 months, respectively. This regimen appeared well-tolerated with 70% of grade 3 or greater toxicity ascribed to TMZ and 23% occurring at least 1 year after RT. Conclusion Dose-escalated RT to 75 Gy guided by sMRI appears feasible and safe for patients with newly diagnosed GBMs. OS outcome is promising and warrants additional testing. Based on these results, a randomized phase II trial is in development.
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Affiliation(s)
- Karthik Ramesh
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA,Department of Biomedical Engineering, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Eric A Mellon
- Department of Radiation Oncology, University of Miami, Miami, Florida, USA
| | - Saumya S Gurbani
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA,Department of Biomedical Engineering, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Brent D Weinberg
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA,Winship Cancer Institute, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Eduard Schreibmann
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA
| | | | | | | | - Bree R Eaton
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Jim Zhong
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Alfredo D Voloschin
- Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Soma Sengupta
- Department of Hematology and Medical Oncology, Emory University School of Medicine, Atlanta, Georgia, USA,Present affiliation: Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, Ohio, USA
| | | | - Matthias Holdhoff
- Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Peter B Barker
- Department of Radiology and Radiological Science, Johns Hopkins University, Baltimore, Maryland, USA
| | | | - Lawrence R Kleinberg
- Department of Radiation Oncology, Johns Hopkins University, Baltimore, Maryland, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA,Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia, USA,Department of Biomedical Engineering, Emory University School of Medicine, Atlanta, Georgia, USA,Winship Cancer Institute, Emory University School of Medicine, Atlanta, Georgia, USA,Corresponding Authors: Hyunsuk Shim, PhD and Hui-Kuo G. Shu, MD, PhD, Department of Radiation Oncology, Winship Cancer Institute of Emory University, 1701 Uppergate Drive, Atlanta, GA 30322, USA (. )
| | - Hui-Kuo G Shu
- Department of Radiation Oncology, Emory University School of Medicine, Atlanta, Georgia, USA,Winship Cancer Institute, Emory University School of Medicine, Atlanta, Georgia, USA
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17
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Tensaouti F, Desmoulin F, Gilhodes J, Martin E, Ken S, Lotterie JA, Noël G, Truc G, Sunyach MP, Charissoux M, Magné N, Lubrano V, Péran P, Cohen-Jonathan Moyal E, Laprie A. Quality control of 3D MRSI data in glioblastoma: Can we do without the experts? Magn Reson Med 2021; 87:1688-1699. [PMID: 34825724 DOI: 10.1002/mrm.29098] [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] [Received: 06/18/2021] [Revised: 11/05/2021] [Accepted: 11/05/2021] [Indexed: 12/23/2022]
Abstract
PURPOSE Proton magnetic resonance spectroscopic imaging (1H MRSI) is a noninvasive technique for assessing tumor metabolism. Manual inspection is still the gold standard for quality control (QC) of spectra, but it is both time-consuming and subjective. The aim of the present study was to assess automatic QC of glioblastoma MRSI data using random forest analysis. METHODS Data for 25 patients, acquired prospectively in a preradiotherapy examination, were submitted to postprocessing with syngo.MR Spectro (VB40A; Siemens) or Java-based magnetic resonance user interface (jMRUI) software. A total of 28 features were extracted from each spectrum for the automatic QC. Three spectroscopists also performed manual inspections, labeling each spectrum as good or poor quality. All statistical analyses, with addressing unbalanced data, were conducted with R 3.6.1 (R Foundation for Statistical Computing; https://www.r-project.org). RESULTS The random forest method classified the spectra with an area under the curve of 95.5%, sensitivity of 95.8%, and specificity of 81.7%. The most important feature for the classification was Residuum_Lipids_Versus_Fit, obtained with syngo.MR Spectro. CONCLUSION The automatic QC method was able to distinguish between good- and poor-quality spectra, and can be used by radiation oncologists who are not spectroscopy experts. This study revealed a novel set of MRSI signal features that are closely correlated with spectral quality.
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Affiliation(s)
- Fatima Tensaouti
- Department of Radiation Oncology, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France.,ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Franck Desmoulin
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Julia Gilhodes
- Department of Biostatistics, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France
| | - Elodie Martin
- Department of Biostatistics, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France
| | - Soleakhena Ken
- Department of Engineering and Medical Physics, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France
| | - Jean-Albert Lotterie
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France.,Department of Nuclear Medicine, CHU Toulouse, Toulouse, France
| | - Georges Noël
- ICANS-Radiation Oncology Strasbourg, Strasbourg, France
| | - Gilles Truc
- Department of Radiation Oncology, Centre Georges-François Leclerc, Dijon, France
| | | | - Marie Charissoux
- Department of Radiation Oncology, Institut du Cancer de Montpellier, Montpellier, France
| | - Nicolas Magné
- Department of Radiation Oncology, Institut de Cancérologie de la Loire Lucien Neuwirth, Saint-Priest-en-Jarez, France
| | - Vincent Lubrano
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Patrice Péran
- ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
| | - Elizabeth Cohen-Jonathan Moyal
- Department of Radiation Oncology, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France.,Inserm U1037-Centre de Recherches Contre le Cancer de Toulouse, Toulouse, France
| | - Anne Laprie
- Department of Radiation Oncology, Institut Claudius Regaud/Institut Universitaire du Cancer de Toulouse-Oncopôle, Toulouse, France.,ToNIC, Toulouse NeuroImaging Center, Université de Toulouse, Inserm, UPS, Toulouse, France
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18
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Advanced Imaging and Computational Techniques for the Diagnostic and Prognostic Assessment of Malignant Gliomas. Cancer J 2021; 27:344-352. [PMID: 34570448 DOI: 10.1097/ppo.0000000000000545] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
ABSTRACT Advanced imaging techniques provide a powerful tool to assess the intratumoral and intertumoral heterogeneity of gliomas. Advances in the molecular understanding of glioma subgroups may allow improved diagnostic assessment combining imaging and molecular tumor features, with enhanced prognostic utility and implications for patient treatment. In this article, a comprehensive overview of the physiologic basis for conventional and advanced imaging techniques is presented, and clinical applications before and after treatment are discussed. An introduction to the principles of radiomics and the advanced integration of imaging, clinical outcomes, and genomic data highlights the future potential for this field of research to better stratify and select patients for standard as well as investigational therapies.
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19
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van Zijl PCM, Brindle K, Lu H, Barker PB, Edden R, Yadav N, Knutsson L. Hyperpolarized MRI, functional MRI, MR spectroscopy and CEST to provide metabolic information in vivo. Curr Opin Chem Biol 2021; 63:209-218. [PMID: 34298353 PMCID: PMC8384704 DOI: 10.1016/j.cbpa.2021.06.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2020] [Revised: 06/12/2021] [Accepted: 06/15/2021] [Indexed: 12/13/2022]
Abstract
Access to metabolic information in vivo using magnetic resonance (MR) technologies has generally been the niche of MR spectroscopy (MRS) and spectroscopic imaging (MRSI). Metabolic fluxes can be studied using the infusion of substrates labeled with magnetic isotopes, with the use of hyperpolarization especially powerful. Unfortunately, these promising methods are not yet accepted clinically, where fast, simple, and reliable measurement and diagnosis are key. Recent advances in functional MRI and chemical exchange saturation transfer (CEST) MRI allow the use of water imaging to study oxygen metabolism and tissue metabolite levels. These, together with the use of novel data analysis approaches such as machine learning for all of these metabolic MR approaches, are increasing the likelihood of their clinical translation.
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Affiliation(s)
- Peter C M van Zijl
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA.
| | - Kevin Brindle
- Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK
| | - Hanzhang Lu
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Peter B Barker
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Richard Edden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Nirbhay Yadav
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Research Institute, Baltimore, MD, USA
| | - Linda Knutsson
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, USA; Department of Medical Radiation Physics, Lund University, Lund, Sweden
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20
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Ramesh K, Gurbani SS, Mellon EA, Huang V, Goryawala M, Barker PB, Kleinberg L, Shu HKG, Shim H, Weinberg BD. The Longitudinal Imaging Tracker (BrICS-LIT):A Cloud Platform for Monitoring Treatment Response in Glioblastoma Patients. ACTA ACUST UNITED AC 2021; 6:93-100. [PMID: 32548285 PMCID: PMC7289246 DOI: 10.18383/j.tom.2020.00001] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Glioblastoma is a common and aggressive form of brain cancer affecting up to 20,000 new patients in the US annually. Despite rigorous therapies, current median survival is only 15-20 months. Patients who complete initial treatment undergo follow-up imaging at routine intervals to assess for tumor recurrence. Imaging is a central part of brain tumor management, but MRI findings in patients with brain tumor can be challenging to interpret and are further confounded by interpretation variability. Disease-specific structured reporting attempts to reduce variability in imaging results by implementing well-defined imaging criteria and standardized language. The Brain Tumor Reporting and Data System (BT-RADS) is one such framework streamlined for clinical workflows and includes quantitative criteria for more objective evaluation of follow-up imaging. To facilitate accurate and objective monitoring of patients during the follow-up period, we developed a cloud platform, the Brain Imaging Collaborative Suite's Longitudinal Imaging Tracker (BrICS-LIT). BrICS-LIT uses semiautomated tumor segmentation algorithms of both T2-weighted FLAIR and contrast-enhanced T1-weighted MRI to assist clinicians in quantitative assessment of brain tumors. The LIT platform can ultimately guide clinical decision-making for patients with glioblastoma by providing quantitative metrics for BT-RADS scoring. Further, this platform has the potential to increase objectivity when measuring efficacy of novel therapies for patients with brain tumor during their follow-up. Therefore, LIT will be used to track patients in a dose-escalated clinical trial, where spectroscopic MRI has been used to guide radiation therapy (Clinicaltrials.gov NCT03137888), and compare patients to a control group that received standard of care.
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Affiliation(s)
- Karthik Ramesh
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA.,Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University School of Medicine, Atlanta, GA
| | - Saumya S Gurbani
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA.,Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University School of Medicine, Atlanta, GA
| | - Eric A Mellon
- Departments of Radiation Oncology, Sylvester Comprehensive Cancer Center; and
| | - Vicki Huang
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA.,Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University School of Medicine, Atlanta, GA
| | | | | | | | - Hui-Kuo G Shu
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Atlanta, GA.,Coulter Department of Biomedical Engineering, Georgia Institute of Technology & Emory University School of Medicine, Atlanta, GA.,Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
| | - Brent D Weinberg
- Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, GA
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21
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Zhong J, Huang V, Gurbani SS, Ramesh K, Scott Cordova J, Schreibmann E, Shu HKG, Olson J, Han H, Giuffrida A, Shim H, Weinberg BD. 3D whole-brain metabolite imaging to improve characterization of low-to-intermediate grade gliomas. J Neurooncol 2021; 153:303-311. [PMID: 33983570 PMCID: PMC8237861 DOI: 10.1007/s11060-021-03770-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2021] [Accepted: 05/03/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE MRI is the standard imaging modality used for diagnosis, treatment planning, and post-treatment management of gliomas. Contrast-enhanced T1-weighted (CE-T1w) MRI is used to plan biopsy and radiation for grade IV gliomas but is less effective for grade II and III gliomas (i.e., low-to-intermediate grade gliomas) which may have minimal or no enhancement. Magnetic resonance spectroscopic imaging (MRSI) is an advanced MRI technique that has been shown, to improve diagnostic yield of biopsy and target delineation for grade IV glioma. The purpose of this study is to determine if MRSI can improve characterization and tissue sampling of low-to-intermediate grade gliomas. METHODS Prospective grade II and grade III glioma patients were enrolled to undergo whole brain high-resolution MRSI prior to tissue sampling. Choline/N-acetyl-aspartate (Cho/NAA) maps were overlaid on anatomic imaging and imported into stereotactic biopsy software. Patients were treated with standard-of-care surgery and radiation. Volumes of spectroscopically abnormal tissue were generated and compared with anatomic imaging and areas of enhancing recurrence on follow-up imaging. RESULTS Ten patients had pathologic diagnosis of grade II (n = 4) or grade III (n = 6) with a median follow-up of 27.3 months. Five patients had recurrence, and regions of recurrence were found to overlap with metabolically abnormal regions on MRSI at the time of diagnosis. CONCLUSION MRSI in low-to-intermediate grade glioma patients is predictive of areas of subsequent recurrence. Larger studies are needed to determine if MRSI can be used to guide surgical and radiation treatment planning in these patients.
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Affiliation(s)
- Jim Zhong
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Vicki Huang
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Saumya S Gurbani
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Karthik Ramesh
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - J Scott Cordova
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Eduard Schreibmann
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Hui-Kuo G Shu
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA
| | - Jeffrey Olson
- Department of Neurosurgery, Winship Cancer Institute of Emory University, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Hui Han
- Biomedical Sciences and Biomedical Imaging Research Institute, Cedars Sinai, Los Angeles, CA, 90048, USA
| | - Alexander Giuffrida
- Department of Biomedical Engineering, Winship Cancer Institute of Emory University, Emory University School of Medicine, Atlanta, GA, 30322, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA.
| | - Brent D Weinberg
- Department of Radiology and Imaging Sciences, Winship Cancer Institute of Emory University, Emory University School of Medicine, 1701 Uppergate Drive, C5018, Atlanta, GA, 30322, USA.
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22
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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: 22] [Impact Index Per Article: 7.3] [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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23
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Abstract
The standard of care treatment for glioblastoma is surgical resection followed by radiotherapy to 60 Gy with concurrent and adjuvant temozolomide with or without tumor-treating fields. Advanced imaging techniques are under evaluation to better guide radiotherapy target volume delineation and allow for dose escalation. Particle therapy, in the form of protons, carbon ions, and boron neutron capture therapy, are being assessed as strategies to improve the radiotherapeutic ratio. Stereotactic, hypofractionated, pulsed-reduced dose-rate, and particle radiotherapy are re-irradiation techniques each uniquely suited for different clinical scenarios. Novel radiotherapy approaches, such as FLASH, represent promising advancements in radiotherapy for glioblastoma.
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Affiliation(s)
- Rupesh Kotecha
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, FL, USA; Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA.
| | - Martin C Tom
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, FL, USA; Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA
| | - Minesh P Mehta
- Department of Radiation Oncology, Miami Cancer Institute, Baptist Health South Florida, Miami, FL, USA; Herbert Wertheim College of Medicine, Florida International University, Miami, FL, USA
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24
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Maziero D, Straza MW, Ford JC, Bovi JA, Diwanji T, Stoyanova R, Paulson ES, Mellon EA. MR-Guided Radiotherapy for Brain and Spine Tumors. Front Oncol 2021; 11:626100. [PMID: 33763361 PMCID: PMC7982530 DOI: 10.3389/fonc.2021.626100] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 02/12/2021] [Indexed: 12/19/2022] Open
Abstract
MRI is the standard modality to assess anatomy and response to treatment in brain and spine tumors given its superb anatomic soft tissue contrast (e.g., T1 and T2) and numerous additional intrinsic contrast mechanisms that can be used to investigate physiology (e.g., diffusion, perfusion, spectroscopy). As such, hybrid MRI and radiotherapy (RT) devices hold unique promise for Magnetic Resonance guided Radiation Therapy (MRgRT). In the brain, MRgRT provides daily visualizations of evolving tumors that are not seen with cone beam CT guidance and cannot be fully characterized with occasional standalone MRI scans. Significant evolving anatomic changes during radiotherapy can be observed in patients with glioblastoma during the 6-week fractionated MRIgRT course. In this review, a case of rapidly changing symptomatic tumor is demonstrated for possible therapy adaptation. For stereotactic body RT of the spine, MRgRT acquires clear isotropic images of tumor in relation to spinal cord, cerebral spinal fluid, and nearby moving organs at risk such as bowel. This visualization allows for setup reassurance and the possibility of adaptive radiotherapy based on anatomy in difficult cases. A review of the literature for MR relaxometry, diffusion, perfusion, and spectroscopy during RT is also presented. These techniques are known to correlate with physiologic changes in the tumor such as cellularity, necrosis, and metabolism, and serve as early biomarkers of chemotherapy and RT response correlating with patient survival. While physiologic tumor investigations during RT have been limited by the feasibility and cost of obtaining frequent standalone MRIs, MRIgRT systems have enabled daily and widespread physiologic measurements. We demonstrate an example case of a poorly responding tumor on the 0.35 T MRIgRT system with relaxometry and diffusion measured several times per week. Future studies must elucidate which changes in MR-based physiologic metrics and at which timepoints best predict patient outcomes. This will lead to early treatment intensification for tumors identified to have the worst physiologic responses during RT in efforts to improve glioblastoma survival.
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Affiliation(s)
- Danilo Maziero
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Michael W Straza
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - John C Ford
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Joseph A Bovi
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Tejan Diwanji
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Radka Stoyanova
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Eric S Paulson
- Department of Radiation Oncology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Eric A Mellon
- Department of Radiation Oncology, Sylvester Comprehensive Cancer Center, Miller School of Medicine, University of Miami, Miami, FL, United States
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25
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Castellano A, Bailo M, Cicone F, Carideo L, Quartuccio N, Mortini P, Falini A, Cascini GL, Minniti G. Advanced Imaging Techniques for Radiotherapy Planning of Gliomas. Cancers (Basel) 2021; 13:cancers13051063. [PMID: 33802292 PMCID: PMC7959155 DOI: 10.3390/cancers13051063] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2021] [Revised: 02/24/2021] [Accepted: 02/26/2021] [Indexed: 02/07/2023] Open
Abstract
The accuracy of target delineation in radiation treatment (RT) planning of cerebral gliomas is crucial to achieve high tumor control, while minimizing treatment-related toxicity. Conventional magnetic resonance imaging (MRI), including contrast-enhanced T1-weighted and fluid-attenuated inversion recovery (FLAIR) sequences, represents the current standard imaging modality for target volume delineation of gliomas. However, conventional sequences have limited capability to discriminate treatment-related changes from viable tumors, owing to the low specificity of increased blood-brain barrier permeability and peritumoral edema. Advanced physiology-based MRI techniques, such as MR spectroscopy, diffusion MRI and perfusion MRI, have been developed for the biological characterization of gliomas and may circumvent these limitations, providing additional metabolic, structural, and hemodynamic information for treatment planning and monitoring. Radionuclide imaging techniques, such as positron emission tomography (PET) with amino acid radiopharmaceuticals, are also increasingly used in the workup of primary brain tumors, and their integration in RT planning is being evaluated in specialized centers. This review focuses on the basic principles and clinical results of advanced MRI and PET imaging techniques that have promise as a complement to RT planning of gliomas.
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Affiliation(s)
- Antonella Castellano
- Neuroradiology Unit, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (A.C.); (A.F.)
| | - Michele Bailo
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.B.); (P.M.)
| | - Francesco Cicone
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, and Nuclear Medicine Unit, University Hospital “Mater Domini”, 88100 Catanzaro, Italy;
- Correspondence: ; Tel.: +39-0-961-369-4155
| | - Luciano Carideo
- National Cancer Institute, G. Pascale Foundation, 80131 Naples, Italy;
| | - Natale Quartuccio
- A.R.N.A.S. Ospedale Civico Di Cristina Benfratelli, 90144 Palermo, Italy;
| | - Pietro Mortini
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (M.B.); (P.M.)
| | - Andrea Falini
- Neuroradiology Unit, IRCCS Ospedale San Raffaele and Vita-Salute San Raffaele University, 20132 Milan, Italy; (A.C.); (A.F.)
| | - Giuseppe Lucio Cascini
- Department of Experimental and Clinical Medicine, “Magna Graecia” University of Catanzaro, and Nuclear Medicine Unit, University Hospital “Mater Domini”, 88100 Catanzaro, Italy;
| | - Giuseppe Minniti
- Radiation Oncology Unit, Department of Medicine, Surgery and Neurosciences, University of Siena, Policlinico Le Scotte, 53100 Siena, Italy;
- IRCCS Neuromed, 86077 Pozzilli (IS), Italy
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Cifarelli CP, Jacques A, Bobko A. Heterogeneity of radiation response in mesenchymal subtype glioblastoma: molecular profiling and reactive oxygen species generation. J Neurooncol 2021; 152:245-255. [PMID: 33566263 DOI: 10.1007/s11060-021-03707-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Accepted: 01/22/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Radiotherapy-induced tumor death remains critical in the successful first-line management of glioblastoma, whereas resistance to radiation serves as a major factor in disease progression. Mesenchymal shift has been identified as a driver in GBM recurrence, with gene expression associated with enhanced repair of macromolecular damage caused by radiation. METHODS Using distinct mesenchymal subtype GBM cells lines, radiation response was assessed by clonogenic assay and orthotopic mouse tumor model. RNA-sequencing was performed in the setting of increasing radiation dosing while real-time assessment of ROS generation was achieved by the measurement of hydroxyl spin trap adducts via electron paramagnetic resonance. RESULTS Radiation-induced cell death determined by clonogenic assay was significantly different at low dose (4-8 Gy) between the resistant U3035 cells and the sensitive U3020 cells. Similar trends were present in the in vivo NSG mouse model following radiation dosing on post-implantation day 7-10, with the rate of reduction in tumor bioluminescence reversing between the U3020 and U3035 cells after the third dose of radiation. Changes in gene expression following radiation determined by RNA-sequencing indicate both U3035 and U3020 cells demonstrate a shift toward more mesenchymal profiles, with concurrent shift away from pro-neural subtype gene expression in the U3020 cells that appeared to develop resistance to radiation in vivo. Persistence of ROS generated following radiation was greater in U3020 cells shown to be more sensitive to radiation. CONCLUSIONS Despite the same molecular classification, distinct GBM cell lines can demonstrate differential response to radiation and potential for mesenchymal shift associated with radiation resistance.
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Affiliation(s)
- Christopher P Cifarelli
- Department of Neurosurgery, West Virginia University, 1 Medical Center Drive, Suite 4300, Morgantown, WV, 26506-9183, USA. .,Department of Radiation Oncology, West Virginia University, Morgantown, WV, USA.
| | - Angelica Jacques
- Department of Neurosurgery, West Virginia University, 1 Medical Center Drive, Suite 4300, Morgantown, WV, 26506-9183, USA
| | - Andrey Bobko
- Department of Biochemistry, West Virginia University, Morgantown, WV, USA
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28
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Laino ME, Young R, Beal K, Haque S, Mazaheri Y, Corrias G, Bitencourt AG, Karimi S, Thakur SB. Magnetic resonance spectroscopic imaging in gliomas: clinical diagnosis and radiotherapy planning. BJR Open 2020; 2:20190026. [PMID: 33178960 PMCID: PMC7594883 DOI: 10.1259/bjro.20190026] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2019] [Revised: 01/13/2020] [Accepted: 03/18/2020] [Indexed: 12/23/2022] Open
Abstract
The reprogramming of cellular metabolism is a hallmark of cancer diagnosis and prognosis. Proton magnetic resonance spectroscopic imaging (MRSI) is a non-invasive diagnostic technique for investigating brain metabolism to establish cancer diagnosis and IDH gene mutation diagnosis as well as facilitate pre-operative planning and treatment response monitoring. By allowing tissue metabolism to be quantified, MRSI provides added value to conventional MRI. MRSI can generate metabolite maps from a single volume or multiple volume elements within the whole brain. Metabolites such as NAA, Cho and Cr, as well as their ratios Cho:NAA ratio and Cho:Cr ratio, have been used to provide tumor diagnosis and aid in radiation therapy planning as well as treatment assessment. In addition to these common metabolites, 2-hydroxygluterate (2HG) has also been quantified using MRSI following the recent discovery of IDH mutations in gliomas. This has opened up targeted drug development to inhibit the mutant IDH pathway. This review provides guidance on MRSI in brain gliomas, including its acquisition, analysis methods, and evolving clinical applications.
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Affiliation(s)
| | - Robert Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
| | - Kathryn Beal
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
| | - Sofia Haque
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
| | | | - Giuseppe Corrias
- Department of Radiology, University of Cagliari, 40 Via Università, 09124 Cagliari, Italy
| | | | - Sasan Karimi
- Department of Radiology, Memorial Sloan Kettering Cancer Center, 1275 York Ave, New York, NY 10065, USA
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Abstract
The National Cancer Institute's Quantitative Imaging Network (QIN) has thrived over the past 12 years with an emphasis on the development of image-based decision support software tools for improving measurements of imaging metrics. An overarching goal has been to develop advanced tools that could be translated into clinical trials to provide for improved prediction of response to therapeutic interventions. This article provides an overview of the successes in development and translation of new algorithms into the clinical workflow by the many research teams of the Quantitative Imaging Network.
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30
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Cicka D, Ford CL, Templin E, Pitts Z, Gurbani S, Eaton B, Lowder L, Olson J, Weinberg BD, Shim H, Sengupta S. Presentation of treatment effect in glioblastoma after dose-escalation radiation therapy. Oxf Med Case Reports 2019; 2019:omz085. [PMID: 31772751 PMCID: PMC6765376 DOI: 10.1093/omcr/omz085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2019] [Accepted: 07/14/2019] [Indexed: 01/08/2023] Open
Abstract
Glioblastoma is the most aggressive primary brain tumor in adults. Limited treatment options and the intense nature of therapy make determining the appropriate treatment course for each patient difficult. The appearance of transient worsening of imaging findings, known as treatment effect, after chemoradiation further complicates clinical decision-making. Accurately differentiating treatment effects from true progression is critical as subsequent treatment decisions are based largely on radiographic evidence of tumor progression. As chemoradiation can cause worsening of imaging findings, it is possible that the use of new treatments and modified chemoradiation regimens may alter the presentation of treatment effect. Therefore, physicians should be aware that atypical presentations of treatment effects can occur, and may be more likely, when treatment regimens are modified. Here, we present the case of a patient with isocitrate dehydrogenase 1 wild type, O-6-methylguanine-DNA methyltransferase-methylated glioblastoma who underwent dose-escalation radiation therapy (to 75 Gy) and exhibited worsened imaging findings at 8 months post-radiation.
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Affiliation(s)
- Danielle Cicka
- School of Medicine, Emory University, Atlanta, GA 30322, USA
| | | | - Erica Templin
- Department of Medical Oncology, Emory University, Atlanta, GA 30322, USA
| | - Zachary Pitts
- Department of Medical Oncology, Emory University, Atlanta, GA 30322, USA
| | - Saumya Gurbani
- School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Bree Eaton
- Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA
| | - Lindsey Lowder
- Department of Pathology & Laboratory Medicine, Emory University, Atlanta, GA 30322, USA
| | - Jeffrey Olson
- Department of Neurosurgery, Emory University, Atlanta, GA 30322, USA
| | - Brent D Weinberg
- Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA
| | - Hyunsuk Shim
- Department of Radiation Oncology, Emory University, Atlanta, GA 30322, USA.,Department of Radiology and Imaging Sciences, Emory University, Atlanta, GA 30322, USA
| | - Soma Sengupta
- Departments of Neurology and Medical Oncology, Emory University, Atlanta, GA 30322, USA
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