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Librizzi G, Lombardi G, Bertoldo A, Manara R. Perioperative imaging predictors of tumor progression and pseudoprogression: A systematic review. Crit Rev Oncol Hematol 2024; 202:104445. [PMID: 38992848 DOI: 10.1016/j.critrevonc.2024.104445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2024] [Revised: 06/26/2024] [Accepted: 07/06/2024] [Indexed: 07/13/2024] Open
Abstract
In high-grade gliomas, pseudoprogression after radiation treatment might dramatically impact patient's management. We searched for perioperative imaging predictors of pseudoprogression in high-grade gliomas according to PRISMA guidelines, using MEDLINE/Pubmed and Embase (until January 2024). Study design, sample size, setting, diagnostic gold standard, imaging modalities and contrasts, and differences among variables or measures of diagnostic accuracy were recorded. Study quality was assessed through the QUADAS-2 tool. Twelve studies (11 with MRI, one with PET; 1058 patients) were reviewed. Most studies used a retrospective design (9/12), and structural MRI (7/12). Studies were heterogeneous in metrics and diagnostic reference standards; patient selection bias was a frequent concern. Pseudoprogression and progression showed some significant group differences in perioperative imaging metrics, although often with substantial overlap. Radiomics showed moderate accuracy but requires further validation. Current literature is scarce and limited by methodological concerns, highlighting the need of new predictors and multiparametric approaches.
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Affiliation(s)
- Giovanni Librizzi
- Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; Neuroradiology Unit, Padova University Hospital, Padova, Italy.
| | - Giuseppe Lombardi
- Department of Oncology, Oncology 1, Veneto Institute of Oncology IOV-IRCCS, Padova, Italy.
| | - Alessandra Bertoldo
- Padova Neuroscience Center (PNC), University of Padova, Padova, Italy; Department of Information Engineering, University of Padova, Padova, Italy.
| | - Renzo Manara
- Neuroradiology Unit, Padova University Hospital, Padova, Italy; DIMED, University of Padova, Padova, Italy.
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2
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Albert NL, Galldiks N, Ellingson BM, van den Bent MJ, Chang SM, Cicone F, de Groot J, Koh ES, Law I, Le Rhun E, Mair MJ, Minniti G, Rudà R, Scott AM, Short SC, Smits M, Suchorska B, Tolboom N, Traub-Weidinger T, Tonn JC, Verger A, Weller M, Wen PY, Preusser M. PET-based response assessment criteria for diffuse gliomas (PET RANO 1.0): a report of the RANO group. Lancet Oncol 2024; 25:e29-e41. [PMID: 38181810 DOI: 10.1016/s1470-2045(23)00525-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 10/03/2023] [Accepted: 10/06/2023] [Indexed: 01/07/2024]
Abstract
Response Assessment in Neuro-Oncology (RANO) response criteria have been established and were updated in 2023 for MRI-based response evaluation of diffuse gliomas in clinical trials. In addition, PET-based imaging with amino acid tracers is increasingly considered for disease monitoring in both clinical practice and clinical trials. So far, a standardised framework defining timepoints for baseline and follow-up investigations and response evaluation criteria for PET imaging of diffuse gliomas has not been established. Therefore, in this Policy Review, we propose a set of criteria for response assessment based on amino acid PET imaging in clinical trials enrolling participants with diffuse gliomas as defined in the 2021 WHO classification of tumours of the central nervous system. These proposed PET RANO criteria provide a conceptual framework that facilitates the structured implementation of PET imaging into clinical research and, ultimately, clinical routine. To this end, the PET RANO 1.0 criteria are intended to encourage specific investigations of amino acid PET imaging of gliomas.
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Affiliation(s)
- Nathalie L Albert
- Department of Nuclear Medicine, LMU Hospital, LMU Munich, Munich, Germany
| | - 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
| | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | | | - Susan M Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Francesco Cicone
- Nuclear Medicine Unit, Department of Experimental and Clinical Medicine, Magna Graecia University of Catanzaro, Catanzaro, Italy
| | - John de Groot
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Eng-Siew Koh
- Department of Radiation Oncology, Liverpool and Macarthur Cancer Therapy Centre, Liverpool, NSW, Australia; South Western Sydney Clinical School, University of New South Wales, Sydney, NSW, Australia
| | - Ian Law
- Department of Clinical Physiology and Nuclear Medicine, Rigshospitalet, Copenhagen, Denmark
| | - Emilie Le Rhun
- Department of Neurosurgery, University Hospital Zurich, Zurich, Switzerland; Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Maximilian J Mair
- Division of Oncology, Department of Medicine I, Medical University of Vienna, Vienna, Austria
| | - Giuseppe Minniti
- Department of Radiological Sciences, Oncology and Anatomical Pathology, Sapienza University of Rome, Policlinico Umberto I, Rome, Italy; IRCCS Neuromed, Pozzilli IS, Italy
| | - Roberta Rudà
- Division of Neuro-Oncology, Department of Neuroscience, University of Turin and City of Health and Science of Turin, Turin, Italy
| | - Andrew M Scott
- Department of Molecular Imaging and Therapy, Austin Health and University of Melbourne, Melbourne, VIC, Australia; Olivia Newton-John Cancer Research Institute and School of Cancer Medicine, La Trobe University, Melbourne, VIC, Australia
| | - Susan C Short
- Leeds Institute of Medical Research at St James's, The University of Leeds, Leeds, UK
| | - Marion Smits
- Department of Radiology & Nuclear Medicine, Erasmus MC-University Medical Centre Rotterdam, Rotterdam, Netherlands; Brain Tumour Centre, Erasmus MC Cancer Institute, Rotterdam, Netherlands; Medical Delta, Delft, Netherlands
| | - Bogdana Suchorska
- Department of Neurosurgery, Heidelberg University Hospital, Ruprecht-Karls-University Heidelberg, Heidelberg, Germany
| | - Nelleke Tolboom
- Department of Radiology and Nuclear Medicine, University Medical Center Utrecht, Utrecht, Netherlands
| | - Tatjana Traub-Weidinger
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | | | - Antoine Verger
- Department of Nuclear Medicine & Nancyclotep Imaging Platform, CHRU Nancy and IADI INSERM UMR 1254, Universitè de Lorraine, Nancy, France
| | - Michael Weller
- Department of Neurology, University Hospital Zurich, Zurich, Switzerland; Department of Neurology, University of Zurich, Zurich, Switzerland
| | - Patrick Y Wen
- Center For Neuro-Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Matthias Preusser
- Division of Oncology, Department of Medicine I, Medical University of Vienna, Vienna, Austria.
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Xiaoxue T, Yinzhong W, Meng Q, Lu X, Lei J. Diagnostic value of PET with different radiotracers and MRI for recurrent glioma: a Bayesian network meta-analysis. BMJ Open 2023; 13:e062555. [PMID: 36863738 PMCID: PMC9990663 DOI: 10.1136/bmjopen-2022-062555] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/04/2023] Open
Abstract
OBJECTIVE The purpose of this study was to evaluate the diagnostic accuracy of 6 different imaging modalities for differentiating glioma recurrence from postradiotherapy changes by performing a network meta-analysis (NMA) using direct comparison studies with 2 or more imaging techniques. DATA SOURCES PubMed, Scopus, EMBASE, the Web of Science and the Cochrane Library were searched from inception to August 2021. The Confidence In Network Meta-Analysis (CINeMA) tool was used to evaluate the quality of the included studies with the criterion for study inclusion being direct comparison using 2 or more imaging modalities. DATA EXTRACTION AND SYNTHESIS The consistency was evaluated by examining the agreement between direct and indirect effects. NMA was performed and the surface under the the cumulative ranking curve (SUCRA) values was obtained to calculate the probability of each imaging modality being the most effective diagnostic method. The CINeMA tool was used to evaluate the quality of the included studies. MAIN OUTCOMES AND MEASURES Direct comparison, inconsistency test, NMA and SUCRA values. RESULTS A total of 8853 potentially relevant articles were retrieved and 15 articles met the inclusion criteria. 18F-FET showed the highest SUCRA values for sensitivity, specificity, positive predictive value and accuracy, followed by 18F-FDOPA. The quality of the included evidence is classified as moderate. CONCLUSION AND RELEVANCE This review indicates that 18F-FET and 18F-FDOPA may have greater diagnostic value for glioma recurrence relative to other imaging modalities (Grading of Recommendations, Assessment, Development and Evaluations B). PROSPERO REGISTRATION NUMBER CRD42021293075.
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Affiliation(s)
- Tian Xiaoxue
- Department of Nuclear Medicine, the Second Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Wang Yinzhong
- Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Qi Meng
- Department of Radiology, No.2 Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, China
| | - Xingru Lu
- Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, Gansu, China
| | - Junqiang Lei
- Department of Radiology, the First Hospital of Lanzhou University, Lanzhou, Gansu, China
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Song X, Li J, Qian X. Diagnosis of Glioblastoma Multiforme Progression via Interpretable Structure-Constrained Graph Neural Networks. IEEE TRANSACTIONS ON MEDICAL IMAGING 2023; 42:380-390. [PMID: 36018877 DOI: 10.1109/tmi.2022.3202037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Glioblastoma multiforme (GBM) is the most common type of brain tumors with high recurrence and mortality rates. After chemotherapy treatment, GBM patients still show a high rate of differentiating pseudoprogression (PsP), which is often confused as true tumor progression (TTP) due to high phenotypical similarities. Thus, it is crucial to construct an automated diagnosis model for differentiating between these two types of glioma progression. However, attaining this goal is impeded by the limited data availability and the high demand for interpretability in clinical settings. In this work, we propose an interpretable structure-constrained graph neural network (ISGNN) with enhanced features to automatically discriminate between PsP and TTP. This network employs a metric-based meta-learning strategy to aggregate class-specific graph nodes, focus on meta-tasks associated with various small graphs, thus improving the classification performance on small-scale datasets. Specifically, a node feature enhancement module is proposed to account for the relative importance of node features and enhance their distinguishability through inductive learning. A graph generation constraint module enables learning reasonable graph structures to improve the efficiency of information diffusion while avoiding propagation errors. Furthermore, model interpretability can be naturally enhanced based on the learned node features and graph structures that are closely related to the classification results. Comprehensive experimental evaluation of our method demonstrated excellent interpretable results in the diagnosis of glioma progression. In general, our work provides a novel systematic GNN approach for dealing with data scarcity and enhancing decision interpretability. Our source codes will be released at https://github.com/SJTUBME-QianLab/GBM-GNN.
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Castello A, Castellani M, Florimonte L, Ciccariello G, Mansi L, Lopci E. PET radiotracers in glioma: a review of clinical indications and evidence. Clin Transl Imaging 2022. [DOI: 10.1007/s40336-022-00523-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022]
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6
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Mammadov O, Akkurt BH, Musigmann M, Ari AP, Blömer DA, Kasap DN, Henssen DJ, Nacul NG, Sartoretti E, Sartoretti T, Backhaus P, Thomas C, Stummer W, Heindel W, Mannil M. Radiomics for pseudoprogression prediction in high grade gliomas: added value of MR contrast agent. Heliyon 2022; 8:e10023. [PMID: 35965975 PMCID: PMC9364026 DOI: 10.1016/j.heliyon.2022.e10023] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2022] [Revised: 05/04/2022] [Accepted: 07/18/2022] [Indexed: 10/31/2022] Open
Abstract
Objective Material & methods Results Conclusion Radiomics allows for prediction of pseudoprogression in high-grade gliomas. Use of contrast media boosts the performance of the Radiomics prediction model.
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Chawla S, Bukhari S, Afridi OM, Wang S, Yadav SK, Akbari H, Verma G, Nath K, Haris M, Bagley S, Davatzikos C, Loevner LA, Mohan S. Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma. NMR IN BIOMEDICINE 2022; 35:e4719. [PMID: 35233862 PMCID: PMC9203929 DOI: 10.1002/nbm.4719] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2020] [Revised: 02/22/2022] [Accepted: 02/25/2022] [Indexed: 05/15/2023]
Abstract
Pseudoprogression (PsP) refers to treatment-related clinico-radiologic changes mimicking true progression (TP) that occurs in patients with glioblastoma (GBM), predominantly within the first 6 months after the completion of surgery and concurrent chemoradiation therapy (CCRT) with temozolomide. Accurate differentiation of TP from PsP is essential for making informed decisions on appropriate therapeutic intervention as well as for prognostication of these patients. Conventional neuroimaging findings are often equivocal in distinguishing between TP and PsP and present a considerable diagnostic dilemma to oncologists and radiologists. These challenges have emphasized the need for developing alternative imaging techniques that may aid in the accurate diagnosis of TP and PsP. In this review, we encapsulate the current state of knowledge in the clinical applications of commonly used metabolic and physiologic magnetic resonance (MR) imaging techniques such as diffusion and perfusion imaging and proton spectroscopy in distinguishing TP from PsP. We also showcase the potential of promising imaging techniques, such as amide proton transfer and amino acid-based positron emission tomography, in providing useful information about the treatment response. Additionally, we highlight the role of "radiomics", which is an emerging field of radiology that has the potential to change the way in which advanced MR techniques are utilized in assessing treatment response in GBM patients. Finally, we present our institutional experiences and discuss future perspectives on the role of multiparametric MR imaging in identifying PsP in GBM patients treated with "standard-of-care" CCRT as well as novel/targeted therapies.
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Affiliation(s)
- Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sultan Bukhari
- Rowan School of Osteopathic Medicine at Rowan University, Voorhees, New Jersey, USA
| | - Omar M. Afridi
- Rowan School of Osteopathic Medicine at Rowan University, Voorhees, New Jersey, USA
| | - Sumei Wang
- Department of Cardiology, Lenox Hill Hospital, Northwell Health, New York, New York, USA
| | - Santosh K. Yadav
- Laboratory of Functional and Molecular Imaging, Sidra Medicine, Doha, Qatar
| | - Hamed Akbari
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Gaurav Verma
- Department of Radiology, Icahn School of Medicine at Mount Sinai, New York, USA
| | - Kavindra Nath
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mohammad Haris
- Laboratory of Functional and Molecular Imaging, Sidra Medicine, Doha, Qatar
| | - Stephen Bagley
- Department of Hematology-Oncology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Christos Davatzikos
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Laurie A. Loevner
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, USA
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8
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Galldiks N, Langen KJ, Albert NL, Law I, Kim MM, Villanueva-Meyer JE, Soffietti R, Wen PY, Weller M, Tonn JC. Investigational PET tracers in neuro-oncology-What's on the horizon? A report of the PET/RANO group. Neuro Oncol 2022; 24:1815-1826. [PMID: 35674736 DOI: 10.1093/neuonc/noac131] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Many studies in patients with brain tumors evaluating innovative PET tracers have been published in recent years, and the initial results are promising. Here, the Response Assessment in Neuro-Oncology (RANO) PET working group provides an overview of the literature on novel investigational PET tracers for brain tumor patients. Furthermore, newer indications of more established PET tracers for the evaluation of glucose metabolism, amino acid transport, hypoxia, cell proliferation, and others are also discussed. Based on the preliminary findings, these novel investigational PET tracers should be further evaluated considering their promising potential. In particular, novel PET probes for imaging of translocator protein and somatostatin receptor overexpression as well as for immune system reactions appear to be of additional clinical value for tumor delineation and therapy monitoring. Progress in developing these radiotracers may contribute to improving brain tumor diagnostics and advancing clinical translational research.
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Affiliation(s)
- Norbert Galldiks
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener St. 62, 50937 Cologne, Germany.,Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany.,Center of Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Düsseldorf, Germany
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany.,Center of Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Düsseldorf, Germany.,Department of Nuclear Medicine, University Hospital RWTH Aachen, Aachen, Germany
| | - Nathalie L Albert
- Department of Nuclear Medicine, Ludwig Maximilians-University of Munich, Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Ian Law
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Michelle M Kim
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, California, USA
| | - Riccardo Soffietti
- Department of Neuro-Oncology, University and City of Health and Science Hospital, Turin, Italy
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women's Cancer Center, Boston, Massachusetts, USA
| | - Michael Weller
- Department of Neurology, Clinical Neuroscience Center University Hospital and University of Zurich, Zurich, Switzerland
| | - Joerg C Tonn
- Department of Neurosurgery, University Hospital of Munich (LMU), Munich, Germany.,German Cancer Consortium (DKTK), Partner Site Munich, German Cancer Research Center (DKFZ), Heidelberg, Germany
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9
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Johnson DR, Glenn CA, Javan R, Olson JJ. Congress of Neurological Surgeons systematic review and evidence-based guidelines update on the role of imaging in the management of progressive glioblastoma in adults. J Neurooncol 2022; 158:139-165. [PMID: 34694565 DOI: 10.1007/s11060-021-03853-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 09/21/2021] [Indexed: 12/27/2022]
Abstract
TARGET POPULATION These recommendations apply to adults with glioblastoma who have been previously treated with first-line radiation or chemoradiotherapy and who are suspected of experiencing tumor progression. QUESTION In patients with previously treated glioblastoma, is standard contrast-enhanced magnetic resonance imaging including diffusion weighted imaging useful for diagnosing tumor progression and differentiating progression from treatment-related changes? LEVEL II Magnetic resonance imaging with and without gadolinium enhancement including diffusion weighted imaging is recommended as the imaging surveillance method to detect the progression of previously diagnosed glioblastoma. QUESTION In patients with previously treated glioblastoma, does magnetic resonance spectroscopy add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL II Magnetic resonance spectroscopy is recommended as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma. QUESTION In patients with previously treated glioblastoma, does magnetic resonance perfusion add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III Magnetic resonance perfusion is suggested as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma. QUESTION In patients with previously treated glioblastoma, does the addition of single-photon emission computed tomography (SPECT) provide additional useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III Single-photon emission computed tomography imaging is suggested as a diagnostic method to differentiate true tumor progression from treatment-related imaging changes or pseudo-progression in patients with suspected progressive glioblastoma. QUESTION In patients with previously treated glioblastoma, does 18F-fluorodeoxyglucose positron emission tomography add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III The routine use of 18F-fluorodeoxyglucose positron emission tomography to identify progression of glioblastoma is not recommended. QUESTION In patients with previously treated glioblastoma, does positron emission tomography with amino acid agents add useful information for diagnosing tumor progression and differentiating progression from treatment-related changes beyond that derived from standard magnetic resonance imaging with and without gadolinium enhancement? LEVEL III It is suggested that amino acid positron emission tomography be considered to assist in the differentiation of progressive glioblastoma from treatment related changes.
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Affiliation(s)
- Derek Richard Johnson
- Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
| | - Chad Allan Glenn
- Department of Neurosurgery, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Ramin Javan
- Department of Neuroradiology, George Washington University Hospital, Washington, DC, USA
| | - Jeffrey James Olson
- Department of Neurosurgery, Emory University School of Medicine, Atlanta, GA, USA
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10
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El-Abtah ME, Talati P, Fu M, Chun B, Clark P, Peters A, Ranasinghe A, He J, Rapalino O, Batchelor TT, Gilberto Gonzalez R, Curry WT, Dietrich J, Gerstner ER, Ratai EM. Magnetic resonance spectroscopy outperforms perfusion in distinguishing between pseudoprogression and disease progression in patients with glioblastoma. Neurooncol Adv 2022; 4:vdac128. [PMID: 36071927 PMCID: PMC9446677 DOI: 10.1093/noajnl/vdac128] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
There is a need to establish biomarkers that distinguish between pseudoprogression (PsP) and true tumor progression in patients with glioblastoma (GBM) treated with chemoradiation.
Methods
We analyzed magnetic resonance spectroscopic imaging (MRSI) and dynamic susceptibility contrast (DSC) MR perfusion data in patients with GBM with PsP or disease progression after chemoradiation. MRSI metabolites of interest included intratumoral choline (Cho), myo-inositol (mI), glutamate + glutamine (Glx), lactate (Lac), and creatine on the contralateral hemisphere (c-Cr). Student T-tests and area under the ROC curve analyses were used to detect group differences in metabolic ratios and their ability to predict clinical status, respectively.
Results
28 subjects (63 ± 9 years, 19 men) were evaluated. Subjects with true progression (n = 20) had decreased enhancing region mI/c-Cr (P = .011), a marker for more aggressive tumors, compared to those with PsP, which predicted tumor progression (AUC: 0.84 [0.76, 0.92]). Those with true progression had elevated Lac/Glx (P = .0009), a proxy of the Warburg effect, compared to those with PsP which predicted tumor progression (AUC: 0.84 [0.75, 0.92]). Cho/c-Cr did not distinguish between PsP and true tumor progression. Despite rCBV (AUC: 0.70 [0.60, 0.80]) and rCBF (AUC: 0.75 [0.65, 0.84]) being individually predictive of tumor response, they added no additional predictive value when combined with MRSI metabolic markers.
Conclusions
Incorporating enhancing lesion MRSI measures of mI/c-Cr and Lac/Glx into brain tumor imaging protocols can distinguish between PsP and true progression and inform patient management decisions.
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Affiliation(s)
- Mohamed E El-Abtah
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Pratik Talati
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Neurosurgery, Massachusetts General Hospital , Boston, Massachusetts , USA
| | - Melanie Fu
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Benjamin Chun
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Patrick Clark
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Anna Peters
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Anthony Ranasinghe
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Julian He
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
| | - Tracy T Batchelor
- Harvard Medical School , Boston, Massachusetts , USA
- Brigham and Women’s Hospital, Neurosciences Center , Boston, Massachusetts , USA
| | - R Gilberto Gonzalez
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
| | - William T Curry
- Department of Neurosurgery, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Jorg Dietrich
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Elizabeth R Gerstner
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Eva-Maria Ratai
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
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11
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Guglielmo P, Quartuccio N, Rossetti V, Celli M, Alongi P, Boero M, Arnone G, Baldari S, Matteucci F, Laudicella R. [ 18F] Fluorothymidine Positron Emission Tomography Imaging in Primary Brain Tumours: A Systematic Review. Curr Med Imaging 2022; 18:363-371. [PMID: 34533446 DOI: 10.2174/1573405617666210917123012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2020] [Revised: 06/15/2021] [Accepted: 06/22/2021] [Indexed: 02/07/2023]
Abstract
PURPOSE This review aimed to summarize the available literature on the clinical application of [18F] FLT PET imaging in primary brain tumours. METHODS A comprehensive search strategy based on Pubmed/Medline, Scopus, Web of Science, Cochrane Library, Google Scholar, and the Embase databases was carried on using the following search string: ('3` Fluorothymidine'/exp OR 'FLT' OR '[81F]-FLT' OR '[18F] Fluorothymidine') AND ('pet'/exp OR 'pet' OR 'positron emission tomography') AND ('glioma'/exp OR 'glioma' OR 'brain tumour'/exp OR 'brain tumour'). The search was updated till March 2021 and only articles in English and studies investigating the clinical applications of [18F] FLT PET and PET/CT in primary brain tumours were considered eligible for inclusion. RESULTS The literature search ultimately yielded 52 studies included in the systematic review, with main results as follows: a) the uptake of [18F] FLT may guide stereotactic biopsy but does not discriminate between grade II and III glioma. b) [18F] FLT uptake and texture parameters correlate with overall survival (OS) in newly diagnosed gliomas. c) In patients with recurrent glioma, proliferative volume (PV) and tumour-to-normal brain (T/N) uptake ratio are independent predictors of survival. d) Patients demonstrating response to therapy at [18F] FLT PET scan show longer OS compared to non-responders. e) [18F] FLT PET demonstrated good performance in discriminating tumour recurrence from radionecrosis. However, controversial results exist in comparative literature examining the performance of [18F] FLT vs. other radiotracers in the assessment of recurrence. CONCLUSION [18F] FLT PET imaging has demonstrated potential benefits for grading, diagnostic and prognostic purposes, despite the small sample size studies due to the relatively low availability of the radiotracer.
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Affiliation(s)
| | - Natale Quartuccio
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico Di Cristina Benfratelli, Italy
| | - Virginia Rossetti
- Nuclear Medicine Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Monica Celli
- Nuclear Medicine Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Pierpaolo Alongi
- Nuclear Medicine Unit, Fondazione Istituto G. Giglio, Ct. da Pietra Pollastra-pisciotto, Cefalù. Italy
| | - Michele Boero
- Nuclear Medicine Unit, AO Brotzu, 09134 Cagliari, Italy
| | - Gaspare Arnone
- Nuclear Medicine Unit, A.R.N.A.S. Ospedali Civico Di Cristina Benfratelli, Italy
| | - Sergio Baldari
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, Messina, Italy
| | - Federica Matteucci
- Nuclear Medicine Unit, Istituto Scientifico Romagnolo per lo Studio e la Cura dei Tumori (IRST) IRCCS, Via P. Maroncelli 40, 47014, Meldola, Italy
| | - Riccardo Laudicella
- Nuclear Medicine Unit, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, Messina, Italy
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12
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Collet S, Guillamo JS, Berro DH, Chakhoyan A, Constans JM, Lechapt-Zalcman E, Derlon JM, Hatt M, Visvikis D, Guillouet S, Perrio C, Bernaudin M, Valable S. Simultaneous Mapping of Vasculature, Hypoxia, and Proliferation Using Dynamic Susceptibility Contrast MRI, 18F-FMISO PET, and 18F-FLT PET in Relation to Contrast Enhancement in Newly Diagnosed Glioblastoma. J Nucl Med 2021; 62:1349-1356. [PMID: 34016725 PMCID: PMC8724903 DOI: 10.2967/jnumed.120.249524] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2020] [Accepted: 01/14/2021] [Indexed: 11/16/2022] Open
Abstract
Conventional MRI plays a key role in the management of patients with high-grade glioma, but multiparametric MRI and PET tracers could provide further information to better characterize tumor metabolism and heterogeneity by identifying regions having a high risk of recurrence. In this study, we focused on proliferation, hypervascularization, and hypoxia, all factors considered indicative of poor prognosis. They were assessed by measuring uptake of 18F-3'-deoxy-3'-18F-fluorothymidine (18F-FLT), relative cerebral blood volume (rCBV) maps, and uptake of 18F-fluoromisonidazole (18F-FMISO), respectively. For each modality, the volumes and high-uptake subvolumes (hot spots) were semiautomatically segmented and compared with the contrast enhancement (CE) volume on T1-weighted gadolinium-enhanced (T1w-Gd) images, commonly used in the management of patients with glioblastoma. Methods: Dynamic susceptibility contrast-enhanced MRI (31 patients), 18F-FLT PET (20 patients), or 18F-FMISO PET (20 patients), for a total of 31 patients, was performed on preoperative glioblastoma patients. Volumes and hot spots were segmented on SUV maps for 18F-FLT PET (using the fuzzy locally adaptive bayesian algorithm) and 18F-FMISO PET (using a mean contralateral image + 3.3 SDs) and on rCBV maps (using a mean contralateral image + 1.96 SDs) for dynamic susceptibility contrast-enhanced MRI and overlaid on T1w-Gd images. For each modality, the percentages of the peripheral volumes and the peripheral hot spots outside the CE volume were calculated. Results: All tumors showed highly proliferated, hypervascularized, and hypoxic regions. The images also showed pronounced heterogeneity of both tracers regarding their uptake and rCBV maps, within each individual patient. Overlaid volumes on T1w-Gd images showed that some proliferative, hypervascularized, and hypoxic regions extended beyond the CE volume but with marked differences between patients. The ranges of peripheral volume outside the CE volume were 1.6%-155.5%, 1.5%-89.5%, and 3.1%-78.0% for 18F-FLT, rCBV, and 18F-FMISO, respectively. All patients had hyperproliferative hot spots outside the CE volume, whereas hypervascularized and hypoxic hot spots were detected mainly within the enhancing region. Conclusion: Spatial analysis of multiparametric maps with segmented volumes and hot spots provides valuable information to optimize the management and treatment of patients with glioblastoma.
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Affiliation(s)
- Solène Collet
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, GIP Cyceron, Caen, France
- Radiophysics Department, Centre François Baclesse, Caen, France
| | - Jean-Sébastien Guillamo
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, GIP Cyceron, Caen, France
- Department of Neurology, CHU de Caen, Caen, France
- Department of Neurology, CHU de Nimes, Nimes, France
| | - David Hassanein Berro
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, GIP Cyceron, Caen, France
- Department of Neurosurgery, CHU de Caen, Caen, France
| | - Ararat Chakhoyan
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, GIP Cyceron, Caen, France
| | - Jean-Marc Constans
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, GIP Cyceron, Caen, France
- Department of Neuroradiology, CHU de Caen, Caen, France
| | - Emmanuèle Lechapt-Zalcman
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, GIP Cyceron, Caen, France
- Department of Pathology, CHU de Caen, Caen, France
- Department of Neuropathology, GHU Paris Psychiatry and Neuroscience, Paris, France
| | - Jean-Michel Derlon
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, GIP Cyceron, Caen, France
| | - Mathieu Hatt
- LaTIM, INSERM, UMR 1101, University of Brest, Brest, France; and
| | | | - Stéphane Guillouet
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/LDM-TEP Group, GIP Cyceron, Caen, France
| | - Cécile Perrio
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/LDM-TEP Group, GIP Cyceron, Caen, France
| | - Myriam Bernaudin
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, GIP Cyceron, Caen, France
| | - Samuel Valable
- Normandie University, UNICAEN, CEA, CNRS, ISTCT/CERVOxy Group, GIP Cyceron, Caen, France;
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13
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Govaerts CW, van Dijken BR, Stormezand GN, van der Weide HL, Wagemakers M, Enting RH, van der Hoorn A. 11C-methyl-L-methionine PET measuring parameters for the diagnosis of tumour progression against radiation-induced changes in brain metastases. Br J Radiol 2021; 94:20210275. [PMID: 34233489 PMCID: PMC9327750 DOI: 10.1259/bjr.20210275] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022] Open
Abstract
Objectives: Radiation-induced changes (RIC) secondary to focal radiotherapy can imitate tumour progression in brain metastases and make follow-up clinical decision making unreliable. 11C-methyl-L-methionine-PET (MET-PET) is widely used for the diagnosis of RIC in brain metastases, but minimal literature exists regarding the optimum PET measuring parameter to be used. We analysed the diagnostic performance of different MET-PET measuring parameters in distinguishing between RIC and tumour progression in a retrospective cohort of brain metastasis patients. Methods: 26 patients with 31 metastatic lesions were included on the basis of having undergone a PET scan due to radiological uncertainty of disease progression. The PET images were analysed and methionine uptake quantified using standardised-uptake-values (SUV) and tumour-to-normal tissue (T/N) ratios, generated as SUVmean, SUVmax, SUVpeak, T/Nmean, T/Nmax-mean and T/Npeak-mean. Metabolic-tumour-volume and total-lesion methionine metabolism were also computed. A definitive diagnosis of either RIC or tumour progression was established by clinicoradiological follow-up of least 4 months subsequent to the investigative PET scan. Results: All MET-PET parameters except metabolic-tumour-volume showed statistically significant differences between tumour progression and lesions with RIC. Receiver-operating-characteristic curve and area-under the-curve analysis demonstrated the highest value of 0.834 for SUVmax with a corresponding optimum threshold of 3.29. This associated with sensitivity, specificity, positive predictive and negative predictive values of 78.57, 70.59%, 74.32 and 75.25% respectively. Conclusions MET-PET is a useful modality for the diagnosis of RIC in brain metastases. SUVmax was the PET parameter with the greatest diagnostic performance. Advances in knowledge: More robust comparisons between SUVmax and SUVpeak could enhance follow-up treatment planning.
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Affiliation(s)
- Chris W Govaerts
- Department of Radiology (EB44), Medical Imaging Centre (MIC), University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Bart Rj van Dijken
- Department of Radiology (EB44), Medical Imaging Centre (MIC), University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Gilles N Stormezand
- Department of Nuclear Medicine and Molecular Imaging, Medical Imaging Centre (MIC), University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Hiske L van der Weide
- Department of Radiotherapy, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Michiel Wagemakers
- Department of Neurosurgery, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Roelien H Enting
- Department of Neurology, University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands
| | - Anouk van der Hoorn
- Department of Radiology (EB44), Medical Imaging Centre (MIC), University Medical Centre Groningen, University of Groningen, Groningen, The Netherlands.,Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neuroscience, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK.,Department of Radiology, University of Cambridge, Addenbrooke's Hospital, Cambridge, UK
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14
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Physiological Imaging Methods for Evaluating Response to Immunotherapies in Glioblastomas. Int J Mol Sci 2021; 22:ijms22083867. [PMID: 33918043 PMCID: PMC8069140 DOI: 10.3390/ijms22083867] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Revised: 04/05/2021] [Accepted: 04/05/2021] [Indexed: 12/19/2022] Open
Abstract
Glioblastoma (GBM) is the most malignant brain tumor in adults, with a dismal prognosis despite aggressive multi-modal therapy. Immunotherapy is currently being evaluated as an alternate treatment modality for recurrent GBMs in clinical trials. These immunotherapeutic approaches harness the patient's immune response to fight and eliminate tumor cells. Standard MR imaging is not adequate for response assessment to immunotherapy in GBM patients even after using refined response assessment criteria secondary to amplified immune response. Thus, there is an urgent need for the development of effective and alternative neuroimaging techniques for accurate response assessment. To this end, some groups have reported the potential of diffusion and perfusion MR imaging and amino acid-based positron emission tomography techniques in evaluating treatment response to different immunotherapeutic regimens in GBMs. The main goal of these techniques is to provide definitive metrics of treatment response at earlier time points for making informed decisions on future therapeutic interventions. This review provides an overview of available immunotherapeutic approaches used to treat GBMs. It discusses the limitations of conventional imaging and potential utilities of physiologic imaging techniques in the response assessment to immunotherapies. It also describes challenges associated with these imaging methods and potential solutions to avoid them.
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15
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Solnes LB, Jacobs AH, Coughlin JM, Du Y, Goel R, Hammoud DA, Pomper MG. Central Nervous System Molecular Imaging. Mol Imaging 2021. [DOI: 10.1016/b978-0-12-816386-3.00088-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022] Open
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16
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Tsakiris C, Siempis T, Alexiou GA, Zikou A, Sioka C, Voulgaris S, Argyropoulou MI. Differentiation Between True Tumor Progression of Glioblastoma and Pseudoprogression Using Diffusion-Weighted Imaging and Perfusion-Weighted Imaging: Systematic Review and Meta-analysis. World Neurosurg 2020; 144:e100-e109. [DOI: 10.1016/j.wneu.2020.07.218] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 07/28/2020] [Accepted: 07/30/2020] [Indexed: 01/08/2023]
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17
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Sorace AG, Elkassem AA, Galgano SJ, Lapi SE, Larimer BM, Partridge SC, Quarles CC, Reeves K, Napier TS, Song PN, Yankeelov TE, Woodard S, Smith AD. Imaging for Response Assessment in Cancer Clinical Trials. Semin Nucl Med 2020; 50:488-504. [PMID: 33059819 PMCID: PMC7573201 DOI: 10.1053/j.semnuclmed.2020.05.001] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
The use of biomarkers is integral to the routine management of cancer patients, including diagnosis of disease, clinical staging and response to therapeutic intervention. Advanced imaging metrics with computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) are used to assess response during new drug development and in cancer research for predictive metrics of response. Key components and challenges to identifying an appropriate imaging biomarker are selection of integral vs integrated biomarkers, choosing an appropriate endpoint and modality, and standardization of the imaging biomarkers for cooperative and multicenter trials. Imaging biomarkers lean on the original proposed quantified metrics derived from imaging such as tumor size or longest dimension, with the most commonly implemented metrics in clinical trials coming from the Response Evaluation Criteria in Solid Tumors (RECIST) criteria, and then adapted versions such as immune-RECIST (iRECIST) and Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) for immunotherapy response and PET imaging, respectively. There have been many widely adopted biomarkers in clinical trials derived from MRI including metrics that describe cellularity and vascularity from diffusion-weighted (DW)-MRI apparent diffusion coefficient (ADC) and Dynamic Susceptibility Contrast (DSC) or dynamic contrast enhanced (DCE)-MRI (Ktrans, relative cerebral blood volume (rCBV)), respectively. Furthermore, Fluorodexoyglucose (FDG), fluorothymidine (FLT), and fluoromisonidazole (FMISO)-PET imaging, which describe molecular markers of glucose metabolism, proliferation and hypoxia have been implemented into various cancer types to assess therapeutic response to a wide variety of targeted- and chemotherapies. Recently, there have been many functional and molecular novel imaging biomarkers that are being developed that are rapidly being integrated into clinical trials (with anticipation of being implemented into clinical workflow in the future), such as artificial intelligence (AI) and machine learning computational strategies, antibody and peptide specific molecular imaging, and advanced diffusion MRI. These include prostate-specific membrane antigen (PSMA) and trastuzumab-PET, vascular tumor burden extracted from contrast-enhanced CT, diffusion kurtosis imaging, and CD8 or Granzyme B PET imaging. Further excitement surrounds theranostic procedures such as the combination of 68Ga/111In- and 177Lu-DOTATATE to use integral biomarkers to direct care and personalize therapy. However, there are many challenges in the implementation of imaging biomarkers that remains, including understand the accuracy, repeatability and reproducibility of both acquisition and analysis of these imaging biomarkers. Despite the challenges associated with the biological and technical validation of novel imaging biomarkers, a distinct roadmap has been created that is being implemented into many clinical trials to advance the development and implementation to create specific and sensitive novel imaging biomarkers of therapeutic response to continue to transform medical oncology.
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Affiliation(s)
- Anna G Sorace
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL; Department of Biomedical Engineering, University of Alabama at Birmingham, Birmingham, AL; O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL.
| | - Asser A Elkassem
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL
| | - Samuel J Galgano
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL; O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL
| | - Suzanne E Lapi
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL; O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL; Department of Chemistry, University of Alabama at Birmingham, Birmingham, AL
| | - Benjamin M Larimer
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL; O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL
| | | | - C Chad Quarles
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ
| | - Kirsten Reeves
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL; Cancer Biology, University of Alabama at Birmingham, Birmingham, AL
| | - Tiara S Napier
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL; Cancer Biology, University of Alabama at Birmingham, Birmingham, AL
| | - Patrick N Song
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL
| | - Thomas E Yankeelov
- Department of Biomedical Engineering, University of Texas at Austin, Austin, TX; Department of Diagnostic Medicine, University of Texas at Austin, Austin, TX; Institute for Computational Engineering and Sciences, University of Texas at Austin, Austin, TX
| | - Stefanie Woodard
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL
| | - Andrew D Smith
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL; O'Neal Comprehensive Cancer Center, University of Alabama at Birmingham, Birmingham, AL
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18
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Ardaya M, Joya A, Padro D, Plaza-García S, Gómez-Vallejo V, Sánchez M, Garbizu M, Cossío U, Matute C, Cavaliere F, Llop J, Martín A. In vivo PET Imaging of Gliogenesis After Cerebral Ischemia in Rats. Front Neurosci 2020; 14:793. [PMID: 32848565 PMCID: PMC7406641 DOI: 10.3389/fnins.2020.00793] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2020] [Accepted: 07/06/2020] [Indexed: 11/13/2022] Open
Abstract
In vivo positron emission tomography of neuroinflammation has mainly focused on the evaluation of glial cell activation using radiolabeled ligands. However, the non-invasive imaging of neuroinflammatory cell proliferation has been scarcely evaluated so far. In vivo and ex vivo assessment of gliogenesis after transient middle cerebral artery occlusion (MCAO) in rats was carried out using PET imaging with the marker of cell proliferation 3′-Deoxy-3′-[18F] fluorothymidine ([18F]FLT), magnetic resonance imaging (MRI) and fluorescence immunohistochemistry. MRI-T2W studies showed the presence of the brain infarction at 24 h after MCAO affecting cerebral cortex and striatum. In vivo PET imaging showed a significant increase in [18F]FLT uptake in the ischemic territory at day 7 followed by a progressive decline from day 14 to day 28 after ischemia onset. In addition, immunohistochemistry studies using Ki67, CD11b, and GFAP to evaluate proliferation of microglia and astrocytes confirmed the PET findings showing the increase of glial proliferation at day 7 after ischemia followed by decrease later on. Hence, these results show that [18F]FLT provides accurate quantitative information on the time course of glial proliferation in experimental stroke. Finally, this novel brain imaging method might guide on the imaging evaluation of the role of gliogenesis after stroke.
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Affiliation(s)
- María Ardaya
- Achucarro Basque Center for Neuroscience, Leioa, Spain.,Department of Neuroscience, University of Basque Country (UPV/EHU) and CIBERNED, Leioa, Spain
| | - Ana Joya
- Achucarro Basque Center for Neuroscience, Leioa, Spain.,CIC biomaGUNE, Basque Research and Technology Alliance, San Sebastian, Spain
| | - Daniel Padro
- CIC biomaGUNE, Basque Research and Technology Alliance, San Sebastian, Spain
| | - Sandra Plaza-García
- CIC biomaGUNE, Basque Research and Technology Alliance, San Sebastian, Spain
| | | | | | | | - Unai Cossío
- CIC biomaGUNE, Basque Research and Technology Alliance, San Sebastian, Spain
| | - Carlos Matute
- Achucarro Basque Center for Neuroscience, Leioa, Spain.,Department of Neuroscience, University of Basque Country (UPV/EHU) and CIBERNED, Leioa, Spain
| | - Fabio Cavaliere
- Achucarro Basque Center for Neuroscience, Leioa, Spain.,Department of Neuroscience, University of Basque Country (UPV/EHU) and CIBERNED, Leioa, Spain
| | - Jordi Llop
- CIC biomaGUNE, Basque Research and Technology Alliance, San Sebastian, Spain.,Centro de Investigación Biomédica en Red - Enfermedades Respiratorias, CIBERES, Madrid, Spain
| | - Abraham Martín
- Achucarro Basque Center for Neuroscience, Leioa, Spain.,Ikerbasque Basque Foundation for Science, Bilbao, Spain
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19
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Shiri I, Hajianfar G, Sohrabi A, Abdollahi H, P Shayesteh S, Geramifar P, Zaidi H, Oveisi M, Rahmim A. Repeatability of radiomic features in magnetic resonance imaging of glioblastoma: Test-retest and image registration analyses. Med Phys 2020; 47:4265-4280. [PMID: 32615647 DOI: 10.1002/mp.14368] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2019] [Revised: 06/17/2020] [Accepted: 06/18/2020] [Indexed: 02/06/2023] Open
Abstract
PURPOSE To assess the repeatability of radiomic features in magnetic resonance (MR) imaging of glioblastoma (GBM) tumors with respect to test-retest, different image registration approaches and inhomogeneity bias field correction. METHODS We analyzed MR images of 17 GBM patients including T1- and T2-weighted images (performed within the same imaging unit on two consecutive days). For image segmentation, we used a comprehensive segmentation approach including entire tumor, active area of tumor, necrotic regions in T1-weighted images, and edema regions in T2-weighted images (test studies only; registration to retest studies is discussed next). Analysis included N3, N4 as well as no bias correction performed on raw MR images. We evaluated 20 image registration approaches, generated by cross-combination of four transformation and five cost function methods. In total, 714 images (17 patients × 2 images × ((4 transformations × 5 cost functions) + 1 test image) and 2856 segmentations (714 images × 4 segmentations) were prepared for feature extraction. Various radiomic features were extracted, including the use of preprocessing filters, specifically wavelet (WAV) and Laplacian of Gaussian (LOG), as well as discretization into fixed bin width and fixed bin count (16, 32, 64, 128, and 256), Exponential, Gradient, Logarithm, Square and Square Root scales. Intraclass correlation coefficients (ICC) were calculated to assess the repeatability of MRI radiomic features (high repeatability defined as ICC ≥ 95%). RESULTS In our ICC results, we observed high repeatability (ICC ≥ 95%) with respect to image preprocessing, different image registration algorithms, and test-retest analysis, for example: RLNU and GLNU from GLRLM, GLNU and DNU from GLDM, Coarseness and Busyness from NGTDM, GLNU and ZP from GLSZM, and Energy and RMS from first order. Highest fraction (percent) of repeatable features was observed, among registration techniques, for the method Full Affine transformation with 12 degrees of freedom using Mutual Information cost function (mean 32.4%), and among image processing methods, for the method Laplacian of Gaussian (LOG) with Sigma (2.5-4.5 mm) (mean 78.9%). The trends were relatively consistent for N4, N3, or no bias correction. CONCLUSION Our results showed varying performances in repeatability of MR radiomic features for GBM tumors due to test-retest and image registration. The findings have implications for appropriate usage in diagnostic and predictive models.
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Affiliation(s)
- Isaac Shiri
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva 4, CH-1211, Switzerland
| | - Ghasem Hajianfar
- Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Science, Tehran, Iran
| | - Ahmad Sohrabi
- Cancer Control Research Center, Cancer Control Foundation, Iran University of Medical Sciences, Tehran, Iran
| | - Hamid Abdollahi
- Department of Radiologic Sciences and Medical Physics, Faculty of Allied Medicine, Kerman University of Medical Science, Kerman, Iran
| | - Sajad P Shayesteh
- Department of Physiology, Pharmacology and Medical Physics, Faculty of Medicine, Alborz University of Medical Sciences, Karaj, Iran
| | - Parham Geramifar
- Research Center for Nuclear Medicine, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
| | - Habib Zaidi
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva 4, CH-1211, Switzerland.,Geneva University Neurocenter, Geneva University, Geneva, Switzerland.,Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, Netherlands.,Department of Nuclear Medicine, University of Southern Denmark, Odense, Denmark
| | - Mehrdad Oveisi
- Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Science, Tehran, Iran.,Department of Computer Science, University of British Columbia, Vancouver, BC, Canada
| | - Arman Rahmim
- Departments of Radiology and Physics, University of British Columbia, Vancouver, BC, Canada.,Department of Integrative Oncology, BC Cancer Research Centre, Vancouver, BC, Canada
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20
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Unterrainer M, Eze C, Ilhan H, Marschner S, Roengvoraphoj O, Schmidt-Hegemann NS, Walter F, Kunz WG, Rosenschöld PMA, Jeraj R, Albert NL, Grosu AL, Niyazi M, Bartenstein P, Belka C. Recent advances of PET imaging in clinical radiation oncology. Radiat Oncol 2020; 15:88. [PMID: 32317029 PMCID: PMC7171749 DOI: 10.1186/s13014-020-01519-1] [Citation(s) in RCA: 66] [Impact Index Per Article: 16.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Accepted: 03/19/2020] [Indexed: 12/25/2022] Open
Abstract
Radiotherapy and radiation oncology play a key role in the clinical management of patients suffering from oncological diseases. In clinical routine, anatomic imaging such as contrast-enhanced CT and MRI are widely available and are usually used to improve the target volume delineation for subsequent radiotherapy. Moreover, these modalities are also used for treatment monitoring after radiotherapy. However, some diagnostic questions cannot be sufficiently addressed by the mere use standard morphological imaging. Therefore, positron emission tomography (PET) imaging gains increasing clinical significance in the management of oncological patients undergoing radiotherapy, as PET allows the visualization and quantification of tumoral features on a molecular level beyond the mere morphological extent shown by conventional imaging, such as tumor metabolism or receptor expression. The tumor metabolism or receptor expression information derived from PET can be used as tool for visualization of tumor extent, for assessing response during and after therapy, for prediction of patterns of failure and for definition of the volume in need of dose-escalation. This review focuses on recent and current advances of PET imaging within the field of clinical radiotherapy / radiation oncology in several oncological entities (neuro-oncology, head & neck cancer, lung cancer, gastrointestinal tumors and prostate cancer) with particular emphasis on radiotherapy planning, response assessment after radiotherapy and prognostication.
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Affiliation(s)
- M Unterrainer
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany. .,Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany. .,German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany.
| | - C Eze
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - H Ilhan
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - S Marschner
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - O Roengvoraphoj
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - N S Schmidt-Hegemann
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - F Walter
- Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - W G Kunz
- Department of Radiology, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany
| | - P Munck Af Rosenschöld
- Radiation Physics, Department of Hematology, Oncology and Radiation Physics, Skåne University Hospital, and Lund University, Lund, Sweden
| | - R Jeraj
- Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, USA
| | - N L Albert
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.,German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - A L Grosu
- Department of Radiation Oncology, Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,German Cancer Consortium (DKTK), partner Site Freiburg, Freiburg, Germany
| | - M Niyazi
- German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
| | - P Bartenstein
- Department of Nuclear Medicine, University Hospital, LMU Munich, Marchioninistr. 15, 81377, Munich, Germany.,German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - C Belka
- German Cancer Consortium (DKTK), partner site Munich; and German Cancer Research Center (DKFZ), Heidelberg, Germany.,Department of Radiation Oncology, University Hospital, LMU Munich, Munich, Germany
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21
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Novy Z, Stepankova J, Hola M, Flasarova D, Popper M, Petrik M. Preclinical Evaluation of Radiolabeled Peptides for PET Imaging of Glioblastoma Multiforme. Molecules 2019; 24:molecules24132496. [PMID: 31288488 PMCID: PMC6651196 DOI: 10.3390/molecules24132496] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 07/02/2019] [Accepted: 07/07/2019] [Indexed: 01/09/2023] Open
Abstract
In this study, we have compared four 68Ga-labeled peptides (three Arg-Gly-Asp (RGD) peptides and substance-P) with two 18F-tracers clinically approved for tumor imaging. We have studied in vitro and in vivo characteristics of selected radiolabeled tracers in a glioblastoma multiforme tumor model. The in vitro part of the study was mainly focused on the evaluation of radiotracers stability under various conditions. We have also determined in vivo stability of studied 68Ga-radiotracers by analysis of murine urine collected at various time points after injection. The in vivo behavior of tested 68Ga-peptides was evaluated through ex vivo biodistribution studies and PET/CT imaging. The obtained data were compared with clinically used 18F-tracers. 68Ga-RGD peptides showed better imaging properties compared to 18F-tracers, i.e., higher tumor/background ratios and no accumulation in non-target organs except for excretory organs.
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Affiliation(s)
- Zbynek Novy
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University Olomouc, 77900 Olomouc, Czech Republic.
| | - Jana Stepankova
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University Olomouc, 77900 Olomouc, Czech Republic
| | - Michaela Hola
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University Olomouc, 77900 Olomouc, Czech Republic
| | - Dominika Flasarova
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University Olomouc, 77900 Olomouc, Czech Republic
| | - Miroslav Popper
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University Olomouc, 77900 Olomouc, Czech Republic
| | - Milos Petrik
- Institute of Molecular and Translational Medicine, Faculty of Medicine and Dentistry, Palacky University Olomouc, 77900 Olomouc, Czech Republic.
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Radiation Necrosis, Pseudoprogression, Pseudoresponse, and Tumor Recurrence: Imaging Challenges for the Evaluation of Treated Gliomas. CONTRAST MEDIA & MOLECULAR IMAGING 2018; 2018:6828396. [PMID: 30627060 PMCID: PMC6305027 DOI: 10.1155/2018/6828396] [Citation(s) in RCA: 112] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 07/09/2018] [Accepted: 10/15/2018] [Indexed: 01/16/2023]
Abstract
Glioblastoma (GBM) is the most common primary malignant type of brain neoplasm in adults and carries a dismal prognosis. The current standard of care for GBM is surgical excision followed by radiation therapy (RT) with concurrent and adjuvant temozolomide-based chemotherapy (TMZ) by six additional cycles. In addition, antiangiogenic therapy with an antivascular endothelial growth factor (VEGF) agent has been used for recurrent glioblastoma. Over the last years, new posttreatment entities such as pseudoprogression and pseudoresponse have been recognized, apart from radiation necrosis. This review article focuses on the role of different imaging techniques such as conventional magnetic resonance imaging (MRI), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), dynamic contrast enhancement (DCE-MRI) and dynamic susceptibility contrast (DSE-MRI) perfusion, magnetic resonance spectroscopy (MRS), and PET/SPECT in differentiation of such treatment-related changes from tumor recurrence.
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