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Cuccarini V, Savoldi F, Mardor Y, Last D, Pellegatta S, Mazzi F, Bruzzone MG, Anghileri E, Pollo B, Maddaloni L, Russo C, Bocchi E, Pinzi V, Eoli M, Aquino D. Response assessment of GBM during immunotherapy by delayed contrast treatment response assessment maps. Front Neurol 2024; 15:1374737. [PMID: 38651109 PMCID: PMC11033465 DOI: 10.3389/fneur.2024.1374737] [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: 01/22/2024] [Accepted: 03/18/2024] [Indexed: 04/25/2024] Open
Abstract
Introduction Assessing the treatment response of glioblastoma multiforme during immunotherapy (IT) is an open issue. Treatment response assessment maps (TRAMs) might help distinguish true tumor progression (TTP) and pseudoprogression (PsP) in this setting. Methods We recruited 16 naïve glioblastoma patients enrolled in a phase II trial consisting of the Stupp protocol (a standardized treatment for glioblastoma involving combined radiotherapy and chemotherapy with temozolomide, followed by adjuvant temozolomide) plus IT with dendritic cells. Patients were followed up till progression or death; seven underwent a second surgery for suspected progression. Clinical, immunological, and MRI data were collected from all patients and histology in case of second surgery. Patients were classified as responders (progression-free survival, PFS > 12 months), and non-responders (PFS ≤ 12), HIGH-NK (natural killer cells, i.e., immunological responders), and LOW-NK (immunological non-responders) based on immune cell counts in peripheral blood. TRAMs differentiate contrast-enhancing lesions with different washout dynamics into hypothesized tumoral (conventionally blue-colored) vs. treatment-related (red-colored). Results Using receiver operating characteristic (ROC) curves, a threshold of -0.066 in VBlue/VCE (volume of the blue portion of tumoral area/volume of contrast enhancement) variation between values obtained in the MRI performed before PsP/TTP and at TTP/PSP allowed to discriminate TTP from PsP with a sensitivity of 71.4% and a specificity of 100%. Among HIGH-NK patients, at month 6 there was a significant reduction compared to baseline and month 2 in median "blue" volumes. Discussion In conclusion, in our pilot study TRAMs support the discrimination between tumoral and treatment-related enhancing features in immunological responders vs. non-responders, the distinction between PsP and TTP, and might provide surrogate markers of immunological response.
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Affiliation(s)
- Valeria Cuccarini
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Filippo Savoldi
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Yael Mardor
- Advanced Technology Center, Sheba Medical Center, Ramat Gan, Israel
- Tel Aviv University, Tel Aviv, Israel
| | - David Last
- Advanced Technology Center, Sheba Medical Center, Ramat Gan, Israel
| | - Serena Pellegatta
- Molecular Neuro-Oncology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Federica Mazzi
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Maria Grazia Bruzzone
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Elena Anghileri
- Molecular Neuro-Oncology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Bianca Pollo
- Neuro-Pathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Luisa Maddaloni
- Molecular Neuro-Oncology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Camilla Russo
- Dipartimento di Ingegneria Elettrica e delle Tecnologie dell’Informazione (DIETI), Università Degli Studi di Napoli “Federico II”, Naples, Italy
| | - Elisa Bocchi
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Valentina Pinzi
- Radiotherapy Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Marica Eoli
- Molecular Neuro-Oncology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Domenico Aquino
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
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Veikutis V, Brazdziunas M, Keleras E, Basevicius A, Grib A, Skaudickas D, Lukosevicius S. Diagnostic Approaches to Adult-Type Diffuse Glial Tumors: Comparative Literature and Clinical Practice Study. Curr Oncol 2023; 30:7818-7835. [PMID: 37754483 PMCID: PMC10528153 DOI: 10.3390/curroncol30090568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Revised: 07/27/2023] [Accepted: 08/08/2023] [Indexed: 09/28/2023] Open
Abstract
Gliomas are the most frequent intrinsic central nervous system tumors. The new 2021 WHO Classification of Central Nervous System Tumors brought significant changes into the classification of gliomas, that underline the role of molecular diagnostics, with the adult-type diffuse glial tumors now identified primarily by their biomarkers rather than histology. The status of the isocitrate dehydrogenase (IDH) 1 or 2 describes tumors at their molecular level and together with the presence or absence of 1p/19q codeletion are the most important biomarkers used for the classification of adult-type diffuse glial tumors. In recent years terminology has also changed. IDH-mutant, as previously known, is diagnostically used as astrocytoma and IDH-wildtype is used as glioblastoma. A comprehensive understanding of these tumors not only gives patients a more proper treatment and better prognosis but also highlights new difficulties. MR imaging is of the utmost importance for diagnosing and supervising the response to treatment. By monitoring the tumor on followup exams better results can be achieved. Correlations are seen between tumor diagnostic and clinical manifestation and surgical administration, followup care, oncologic treatment, and outcomes. Minimal resection site use of functional imaging (fMRI) and diffusion tensor imaging (DTI) have become indispensable tools in invasive treatment. Perfusion imaging provides insightful information about the vascularity of the tumor, spectroscopy shows metabolic activity, and nuclear medicine imaging displays tumor metabolism. To accommodate better treatment the differentiation of pseudoprogression, pseudoresponse, or radiation necrosis is needed. In this report, we present a literature review of diagnostics of gliomas, the differences in their imaging features, and our radiology's departments accumulated experience concerning gliomas.
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Affiliation(s)
- Vincentas Veikutis
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
| | - Mindaugas Brazdziunas
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
- Faculty of Medicine, Kaunas University of Applied Sciences, LT44162 Kaunas, Lithuania
| | - Evaldas Keleras
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
| | - Algidas Basevicius
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
| | - Andrei Grib
- Department of Internal Medicine, Nicolae Testemitanu State University of Medicine and Pharmacy, MD2004 Chisinau, Moldova;
| | - Darijus Skaudickas
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
| | - Saulius Lukosevicius
- Medical Academy, Lithuanian University of Health Sciences, LT50161 Kaunas, Lithuania; (M.B.); (E.K.); (A.B.); (D.S.); (S.L.)
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de Godoy LL, Chawla S, Brem S, Mohan S. Taming Glioblastoma in "Real Time": Integrating Multimodal Advanced Neuroimaging/AI Tools Towards Creating a Robust and Therapy Agnostic Model for Response Assessment in Neuro-Oncology. Clin Cancer Res 2023; 29:2588-2592. [PMID: 37227179 DOI: 10.1158/1078-0432.ccr-23-0009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/20/2023] [Accepted: 05/04/2023] [Indexed: 05/10/2023]
Abstract
The highly aggressive nature of glioblastoma carries a dismal prognosis despite aggressive multimodal therapy. Alternative treatment regimens, such as immunotherapies, are known to intensify the inflammatory response in the treatment field. Follow-up imaging in these scenarios often mimics disease progression on conventional MRI, making accurate evaluation extremely challenging. To this end, revised criteria for assessment of treatment response in high-grade gliomas were successfully proposed by the RANO Working Group to distinguish pseudoprogression from true progression, with intrinsic constraints related to the postcontrast T1-weighted MRI sequence. To address these existing limitations, our group proposes a more objective and quantifiable "treatment agnostic" model, integrating into the RANO criteria advanced multimodal neuroimaging techniques, such as diffusion tensor imaging (DTI), dynamic susceptibility contrast-perfusion weighted imaging (DSC-PWI), dynamic contrast enhanced (DCE)-MRI, MR spectroscopy, and amino acid-based positron emission tomography (PET) imaging tracers, along with artificial intelligence (AI) tools (radiomics, radiogenomics, and radiopathomics) and molecular information to address this complex issue of treatment-related changes versus tumor progression in "real-time", particularly in the early posttreatment window. Our perspective delineates the potential of incorporating multimodal neuroimaging techniques to improve consistency and automation for the assessment of early treatment response in neuro-oncology.
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Affiliation(s)
- Laiz Laura de Godoy
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania
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Kersch CN, Muldoon LL, Claunch CJ, Fu R, Schwartz D, Cha S, Starkey J, Neuwelt EA, Barajas RF. Multiparametric magnetic resonance imaging discerns glioblastoma immune microenvironmental heterogeneity. Neuroradiol J 2023:19714009231163560. [PMID: 37306690 DOI: 10.1177/19714009231163560] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/13/2023] Open
Abstract
RATIONALE AND OBJECTIVE Poor clinical outcomes for patients with glioblastoma are in part due to dysfunction of the tumor-immune microenvironment. An imaging approach able to characterize immune microenvironmental signatures could provide a framework for biologically based patient stratification and response assessment. We hypothesized spatially distinct gene expression networks can be distinguished by multiparametric Magnetic Resonance Imaging (MRI) phenotypes. MATERIALS AND METHODS Patients with newly diagnosed glioblastoma underwent image-guided tissue sampling allowing for co-registration of MRI metrics with gene expression profiles. MRI phenotypes based on gadolinium contrast enhancing lesion (CEL) and non-enhancing lesion (NCEL) regions were subdivided based on imaging parameters (relative cerebral blood volume (rCBV) and apparent diffusion coefficient (ADC)). Gene set enrichment analysis and immune cell type abundance was estimated using CIBERSORT methodology. Significance thresholds were set at a p-value cutoff 0.005 and an FDR q-value cutoff of 0.1. RESULTS Thirteen patients (eight men, five women, mean age 58 ± 11 years) provided 30 tissue samples (16 CEL and 14 NCEL). Six non-neoplastic gliosis samples differentiated astrocyte repair from tumor associated gene expression. MRI phenotypes displayed extensive transcriptional variance reflecting biological networks, including multiple immune pathways. CEL regions demonstrated higher immunologic signature expression than NCEL, while NCEL regions demonstrated stronger immune signature expression levels than gliotic non-tumor brain. Incorporation of rCBV and ADC metrics identified sample clusters with differing immune microenvironmental signatures. CONCLUSION Taken together, our study demonstrates that MRI phenotypes provide an approach for non-invasively characterizing tumoral and immune microenvironmental glioblastoma gene expression networks.
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Affiliation(s)
- Cymon N Kersch
- Department of Neurology, Blood-Brain Barrier Program, Oregon Health & Sciences University, USA
- Department of Radiation Medicine, Oregon Health & Sciences University, USA
| | - Leslie L Muldoon
- Department of Neurology, Blood-Brain Barrier Program, Oregon Health & Sciences University, USA
| | - Cheryl J Claunch
- Department of Biomedical Engineering, Knight Cancer Institute, OHSU Center for Spatial Systems Biomedicine, Oregon Health & Sciences University, USA
| | - Rongwei Fu
- OHSU-PSU School of Public Health, Oregon Health & Sciences University, USA
| | - Daniel Schwartz
- Advanced Imaging Research Center, Oregon Health & Sciences University, USA
- Department of Neurology, Layton Aging and Alzheimer's Disease Center, Oregon Health & Sciences University, USA
| | - Soonmee Cha
- Department of Radiology and Biomedical Imaging, University of California San Francisco, USA
| | - Jay Starkey
- Department of Radiology, Oregon Health & Sciences University, USA
| | - Edward A Neuwelt
- Department of Neurology, Blood-Brain Barrier Program, Oregon Health & Sciences University, USA
- Department of Neurosurgery, Oregon Health & Sciences University, USA
- Office of Research and Development, Department of Veterans Affairs Medical Center, USA
| | - Ramon F Barajas
- Advanced Imaging Research Center, Oregon Health & Sciences University, USA
- Department of Radiology, Oregon Health & Sciences University, USA
- Knight Cancer Institute, Oregon Health & Sciences University, USA
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de Godoy LL, Chawla S, Brem S, Wang S, O'Rourke DM, Nasrallah MP, Desai A, Loevner LA, Liau LM, Mohan S. Assessment of treatment response to dendritic cell vaccine in patients with glioblastoma using a multiparametric MRI-based prediction model. J Neurooncol 2023; 163:173-183. [PMID: 37129737 DOI: 10.1007/s11060-023-04324-4] [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: 02/15/2023] [Accepted: 04/24/2023] [Indexed: 05/03/2023]
Abstract
PURPOSE Autologous tumor lysate-loaded dendritic cell vaccine (DCVax-L) is a promising treatment modality for glioblastomas. The purpose of this study was to investigate the potential utility of multiparametric MRI-based prediction model in evaluating treatment response in glioblastoma patients treated with DCVax-L. METHODS Seventeen glioblastoma patients treated with standard-of-care therapy + DCVax-L were included. When tumor progression (TP) was suspected and repeat surgery was being contemplated, we sought to ascertain the number of cases correctly classified as TP + mixed response or pseudoprogression (PsP) from multiparametric MRI-based prediction model using histopathology/mRANO criteria as ground truth. Multiparametric MRI model consisted of predictive probabilities (PP) of tumor progression computed from diffusion and perfusion MRI-derived parameters. A comparison of overall survival (OS) was performed between patients treated with standard-of-care therapy + DCVax-L and standard-of-care therapy alone (external controls). Additionally, Kaplan-Meier analyses were performed to compare OS between two groups of patients using PsP, Ki-67, and MGMT promoter methylation status as stratification variables. RESULTS Multiparametric MRI model correctly predicted TP + mixed response in 72.7% of cases (8/11) and PsP in 83.3% (5/6) with an overall concordance rate of 76.5% with final diagnosis as determined by histopathology/mRANO criteria. There was a significant concordant correlation coefficient between PP values and histopathology/mRANO criteria (r = 0.54; p = 0.026). DCVax-L-treated patients had significantly prolonged OS than those treated with standard-of-care therapy (22.38 ± 12.8 vs. 13.8 ± 9.5 months, p = 0.040). Additionally, glioblastomas with PsP, MGMT promoter methylation status, and Ki-67 values below median had longer OS than their counterparts. CONCLUSION Multiparametric MRI-based prediction model can assess treatment response to DCVax-L in patients with glioblastoma.
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Affiliation(s)
- Laiz Laura de Godoy
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sanjeev Chawla
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA.
| | - Steven Brem
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Sumei Wang
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Donald M O'Rourke
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - MacLean P Nasrallah
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Clinical Pathology and Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Arati Desai
- Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
- Glioblastoma Translational Center of Excellence, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Laurie A Loevner
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Linda M Liau
- Department of Neurosurgery, University of California Los Angeles David Geffen School of Medicine & Jonsson Comprehensive Cancer Center, Los Angeles, CA, USA
| | - Suyash Mohan
- Department of Radiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
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Molecular MRI-Based Monitoring of Cancer Immunotherapy Treatment Response. Int J Mol Sci 2023; 24:ijms24043151. [PMID: 36834563 PMCID: PMC9959624 DOI: 10.3390/ijms24043151] [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: 01/07/2023] [Revised: 01/29/2023] [Accepted: 02/02/2023] [Indexed: 02/09/2023] Open
Abstract
Immunotherapy constitutes a paradigm shift in cancer treatment. Its FDA approval for several indications has yielded improved prognosis for cases where traditional therapy has shown limited efficiency. However, many patients still fail to benefit from this treatment modality, and the exact mechanisms responsible for tumor response are unknown. Noninvasive treatment monitoring is crucial for longitudinal tumor characterization and the early detection of non-responders. While various medical imaging techniques can provide a morphological picture of the lesion and its surrounding tissue, a molecular-oriented imaging approach holds the key to unraveling biological effects that occur much earlier in the immunotherapy timeline. Magnetic resonance imaging (MRI) is a highly versatile imaging modality, where the image contrast can be tailored to emphasize a particular biophysical property of interest using advanced engineering of the imaging pipeline. In this review, recent advances in molecular-MRI based cancer immunotherapy monitoring are described. Next, the presentation of the underlying physics, computational, and biological features are complemented by a critical analysis of the results obtained in preclinical and clinical studies. Finally, emerging artificial intelligence (AI)-based strategies to further distill, quantify, and interpret the image-based molecular MRI information are discussed in terms of perspectives for the future.
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Li AY, Iv M. Conventional and Advanced Imaging Techniques in Post-treatment Glioma Imaging. FRONTIERS IN RADIOLOGY 2022; 2:883293. [PMID: 37492665 PMCID: PMC10365131 DOI: 10.3389/fradi.2022.883293] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 06/06/2022] [Indexed: 07/27/2023]
Abstract
Despite decades of advancement in the diagnosis and therapy of gliomas, the most malignant primary brain tumors, the overall survival rate is still dismal, and their post-treatment imaging appearance remains very challenging to interpret. Since the limitations of conventional magnetic resonance imaging (MRI) in the distinction between recurrence and treatment effect have been recognized, a variety of advanced MR and functional imaging techniques including diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI), perfusion-weighted imaging (PWI), MR spectroscopy (MRS), as well as a variety of radiotracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) have been investigated for this indication along with voxel-based and more quantitative analytical methods in recent years. Machine learning and radiomics approaches in recent years have shown promise in distinguishing between recurrence and treatment effect as well as improving prognostication in a malignancy with a very short life expectancy. This review provides a comprehensive overview of the conventional and advanced imaging techniques with the potential to differentiate recurrence from treatment effect and includes updates in the state-of-the-art in advanced imaging with a brief overview of emerging experimental techniques. A series of representative cases are provided to illustrate the synthesis of conventional and advanced imaging with the clinical context which informs the radiologic evaluation of gliomas in the post-treatment setting.
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Affiliation(s)
- Anna Y. Li
- Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
| | - Michael Iv
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University School of Medicine, Stanford, CA, United States
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Candiota AP, Arús C. Establishing Imaging Biomarkers of Host Immune System Efficacy during Glioblastoma Therapy Response: Challenges, Obstacles and Future Perspectives. Metabolites 2022; 12:metabo12030243. [PMID: 35323686 PMCID: PMC8950145 DOI: 10.3390/metabo12030243] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/04/2022] [Accepted: 03/10/2022] [Indexed: 11/16/2022] Open
Abstract
This hypothesis proposal addresses three major questions: (1) Why do we need imaging biomarkers for assessing the efficacy of immune system participation in glioblastoma therapy response? (2) Why are they not available yet? and (3) How can we produce them? We summarize the literature data supporting the claim that the immune system is behind the efficacy of most successful glioblastoma therapies but, unfortunately, there are no current short-term imaging biomarkers of its activity. We also discuss how using an immunocompetent murine model of glioblastoma, allowing the cure of mice and the generation of immune memory, provides a suitable framework for glioblastoma therapy response biomarker studies. Both magnetic resonance imaging and magnetic resonance-based metabolomic data (i.e., magnetic resonance spectroscopic imaging) can provide non-invasive assessments of such a system. A predictor based in nosological images, generated from magnetic resonance spectroscopic imaging analyses and their oscillatory patterns, should be translational to clinics. We also review hurdles that may explain why such an oscillatory biomarker was not reported in previous imaging glioblastoma work. Single shot explorations that neglect short-term oscillatory behavior derived from immune system attack on tumors may mislead actual response extent detection. Finally, we consider improvements required to properly predict immune system-mediated early response (1–2 weeks) to therapy. The sensible use of improved biomarkers may enable translatable evidence-based therapeutic protocols, with the possibility of extending preclinical results to human patients.
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Affiliation(s)
- Ana Paula Candiota
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, 08193 Barcelona, Spain;
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Edifici Cs, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
| | - Carles Arús
- Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Cerdanyola del Vallès, 08193 Barcelona, Spain;
- Departament de Bioquímica i Biologia Molecular, Unitat de Bioquímica de Biociències, Edifici Cs, Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Institut de Biotecnologia i de Biomedicina (IBB), Universitat Autònoma de Barcelona, Cerdanyola del Vallès, 08193 Barcelona, Spain
- Correspondence:
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Henriksen OM, del Mar Álvarez-Torres M, Figueiredo P, Hangel G, Keil VC, Nechifor RE, Riemer F, Schmainda KM, Warnert EAH, Wiegers EC, Booth TC. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques. Front Oncol 2022; 12:810263. [PMID: 35359414 PMCID: PMC8961422 DOI: 10.3389/fonc.2022.810263] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 01/05/2022] [Indexed: 01/16/2023] Open
Abstract
Objective Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). Results High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. Conclusion Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.
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Affiliation(s)
- Otto M. Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | | | - Patricia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics-Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Gilbert Hangel
- Department of Neurosurgery, Medical University, Vienna, Austria
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University, Vienna, Austria
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Ruben E. Nechifor
- International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Department of Clinical Psychology and Psychotherapy, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | | | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Thomas C. Booth
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School of Biomedical Engineering and Imaging Sciences, St. Thomas’ Hospital, King’s College London, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
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Li Y, Ma Y, Wu Z, Xie R, Zeng F, Cai H, Lui S, Song B, Chen L, Wu M. Advanced Imaging Techniques for Differentiating Pseudoprogression and Tumor Recurrence After Immunotherapy for Glioblastoma. Front Immunol 2021; 12:790674. [PMID: 34899760 PMCID: PMC8656432 DOI: 10.3389/fimmu.2021.790674] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Accepted: 11/08/2021] [Indexed: 02/05/2023] Open
Abstract
Glioblastoma (GBM) is the most common malignant tumor of the central nervous system with poor prognosis. Although the field of immunotherapy in glioma is developing rapidly, glioblastoma is still prone to recurrence under strong immune intervention. The major challenges in the process of immunotherapy are evaluating the curative effect, accurately distinguishing between treatment-related reactions and tumor recurrence, and providing guidance for clinical decision-making. Since the conventional magnetic resonance imaging (MRI) is usually difficult to distinguish between pseudoprogression and the true tumor progression, many studies have used various advanced imaging techniques to evaluate treatment-related responses. Meanwhile, criteria for efficacy evaluation of immunotherapy are constantly updated and improved. A standard imaging scheme to evaluate immunotherapeutic response will benefit patients finally. This review mainly summarizes the application status and future trend of several advanced imaging techniques in evaluating the efficacy of GBM immunotherapy.
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Affiliation(s)
- Yan Li
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Yiqi Ma
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Zijun Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Ruoxi Xie
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Fanxin Zeng
- Department of Clinic Medical Center, Dazhou Central Hospital, Dazhou, China
| | - Huawei Cai
- Laboratory of Clinical Nuclear Medicine, Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, China
| | - Su Lui
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Bin Song
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China
| | - Lei Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China.,Department of Clinical Research Management, West China Hospital, Sichuan University, Chengdu, China
| | - Min Wu
- Huaxi MR Research Center (HMRRC), Department of Radiology, Functional and Molecular Imaging Key Laboratory of Sichuan Province, West China Hospital, Sichuan University, Chengdu, China.,Department of Clinic Medical Center, Dazhou Central Hospital, Dazhou, China
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11
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Zakaria R, Radon M, Mills S, Mitchell D, Palmieri C, Chung C, Jenkinson MD. The Role of the Immune Response in Brain Metastases: Novel Imaging Biomarkers for Immunotherapy. Front Oncol 2021; 11:711405. [PMID: 34765539 PMCID: PMC8577813 DOI: 10.3389/fonc.2021.711405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 09/30/2021] [Indexed: 11/19/2022] Open
Abstract
Brain metastases are a major clinical problem, and immunotherapy offers a novel treatment paradigm with the potential to synergize with existing focal therapies like surgery and radiosurgery or even replace them in future. The brain is a unique microenvironment structurally and immunologically. The immune response is likely to be crucial to the adaptation of systemic immune modulating agents against this disease. Imaging is frequently employed in the clinical diagnosis and management of brain metastasis, so it is logical that brain imaging techniques are investigated as a source of biomarkers of the immune response in these tumors. Current imaging techniques in clinical use include structural MRI (post-contrast T1W sequences, T2, and FLAIR), physiological sequences (perfusion- and diffusion-weighted imaging), and molecular imaging (MR spectroscopy and PET). These are reviewed for their application to predicting and measuring the response to immunotherapy in brain metastases.
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Affiliation(s)
- Rasheed Zakaria
- Department of Neurosurgery, University of Texas M.D.Anderson Cancer Center, Houston, TX, United States
- Faculty of Health and Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Mark Radon
- Department of Radiology, Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Samantha Mills
- Department of Radiology, Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
| | - Drew Mitchell
- Department of Imaging Physics, University of Texas M.D.Anderson Cancer Center, Houston, TX, United States
| | - Carlo Palmieri
- Faculty of Health and Life Sciences, University of Liverpool, Liverpool, United Kingdom
| | - Caroline Chung
- Department of Radiation Oncology, University of Texas M.D.Anderson Cancer Center, Houston, TX, United States
| | - Michael D. Jenkinson
- Faculty of Health and Life Sciences, University of Liverpool, Liverpool, United Kingdom
- Department of Neurosurgery, Walton Centre NHS Foundation Trust, Liverpool, United Kingdom
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12
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Ahn SS, Cha S. Pre- and Post-Treatment Imaging of Primary Central Nervous System Tumors in the Molecular and Genetic Era. Korean J Radiol 2021; 22:1858-1874. [PMID: 34402244 PMCID: PMC8546137 DOI: 10.3348/kjr.2020.1450] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 04/08/2021] [Accepted: 04/09/2021] [Indexed: 11/15/2022] Open
Abstract
Recent advances in the molecular and genetic characterization of central nervous system (CNS) tumors have ushered in a new era of tumor classification, diagnosis, and prognostic assessment. In this emerging and rapidly evolving molecular genetic era, imaging plays a critical role in the preoperative diagnosis and surgical planning, molecular marker prediction, targeted treatment planning, and post-therapy assessment of CNS tumors. This review provides an overview of the current imaging methods relevant to the molecular genetic classification of CNS tumors. Specifically, we focused on 1) the correlates between imaging features and specific molecular genetic markers and 2) the post-therapy imaging used for therapeutic assessment.
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Affiliation(s)
- Sung Soo Ahn
- Department of Radiology, Severance Hospital, Research Institute of Radiological Science and Center for Clinical Image Data Science, Yonsei University College of Medicine, Seoul, Korea.,Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Soonmee Cha
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA.
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13
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Nakata J, Isohashi K, Oka Y, Nakajima H, Morimoto S, Fujiki F, Oji Y, Tsuboi A, Kumanogoh A, Hashimoto N, Hatazawa J, Sugiyama H. Imaging Assessment of Tumor Response in the Era of Immunotherapy. Diagnostics (Basel) 2021; 11:diagnostics11061041. [PMID: 34198874 PMCID: PMC8226723 DOI: 10.3390/diagnostics11061041] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 05/29/2021] [Accepted: 06/03/2021] [Indexed: 02/07/2023] Open
Abstract
Assessment of tumor response during treatment is one of the most important purposes of imaging. Before the appearance of immunotherapy, response evaluation criteria in solid tumors (RECIST) and positron emission tomography response criteria in solid tumors (PERCIST) were, respectively, the established morphologic and metabolic response criteria, and cessation of treatment was recommended when progressive disease was detected according to these criteria. However, various types of immunotherapy have been developed over the past 20 years, which show novel false positive findings on images, as well as distinct response patterns from conventional therapies. Antitumor immune response itself causes 18F-fluorodeoxyglucose (FDG) uptake in tumor sites, known as "flare phenomenon", so that positron emission tomography using FDG can no longer accurately identify remaining tumors. Furthermore, tumors often initially increase, followed by stability or decrease resulting from immunotherapy, which is called "pseudoprogression", so that progressive disease cannot be confirmed by computed tomography or magnetic resonance imaging at a single time point. As a result, neither RECIST nor PERCIST can accurately predict the response to immunotherapy, and therefore several new response criteria fixed for immunotherapy have been proposed. However, these criteria are still controversial, and also require months for response confirmation. The establishment of optimal response criteria and the development of new imaging technologies other than FDG are therefore urgently needed. In this review, we summarize the false positive images and the revision of response criteria for each immunotherapy, in order to avoid discontinuation of a truly effective immunotherapy.
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Affiliation(s)
- Jun Nakata
- Department of Clinical Laboratory and Biomedical Sciences, Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan;
- Correspondence: ; Tel.: +81-6-6879-3676; Fax: +81-6-6879-3677
| | - Kayako Isohashi
- Department of Kansai BNCT Medical Center, Osaka Medical and Pharmaceutical University, Takatsuki City 596-8686, Osaka, Japan;
| | - Yoshihiro Oka
- Department of Cancer Stem Cell Biology, Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan;
- Department of Immunopathology, WP1 Immunology Frontier Research Center, Osaka University, Suita City 565-0871, Osaka, Japan;
| | - Hiroko Nakajima
- Department of Cancer Immunology, Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan; (H.N.); (F.F.); (H.S.)
| | - Soyoko Morimoto
- Department of Cancer Immunotherapy, Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan; (S.M.); (A.T.)
| | - Fumihiro Fujiki
- Department of Cancer Immunology, Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan; (H.N.); (F.F.); (H.S.)
| | - Yusuke Oji
- Department of Clinical Laboratory and Biomedical Sciences, Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan;
| | - Akihiro Tsuboi
- Department of Cancer Immunotherapy, Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan; (S.M.); (A.T.)
| | - Atsushi Kumanogoh
- Department of Immunopathology, WP1 Immunology Frontier Research Center, Osaka University, Suita City 565-0871, Osaka, Japan;
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives (OTRI), Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan
| | - Naoya Hashimoto
- Department of Neurosurgery, Kyoto Prefectural University of Medicine Graduate School of Medical Science, Kyoto City 602-8566, Kyoto, Japan;
| | - Jun Hatazawa
- Department of Research Center for Nuclear Physics, Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan;
| | - Haruo Sugiyama
- Department of Cancer Immunology, Osaka University Graduate School of Medicine, Suita City 565-0871, Osaka, Japan; (H.N.); (F.F.); (H.S.)
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14
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Coolens C, Gwilliam MN, Alcaide-Leon P, de Freitas Faria IM, Ynoe de Moraes F. Transformational Role of Medical Imaging in (Radiation) Oncology. Cancers (Basel) 2021; 13:cancers13112557. [PMID: 34070984 PMCID: PMC8197089 DOI: 10.3390/cancers13112557] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2021] [Revised: 05/18/2021] [Accepted: 05/19/2021] [Indexed: 12/30/2022] Open
Abstract
Simple Summary Onboard, imaging techniques have brought about a huge transformation in the ability to deliver targeted radiation therapies. Each generation of these technologies enables us to better visualize where to deliver lethal doses of radiation and thus allows the shrinking of necessary geometric margins leading to reduced toxicities. Alongside improvements in treatment delivery, advances in medical imaging have also allowed us to better define the volumes we wish to target. The development of imaging techniques that can capture aspects of the tumor’s biology before, during and after therapy is transforming how treatment can be delivered. Technological changes have further made these biological imaging techniques available in real-time providing the opportunity to monitor a patient’s response to treatment closely and often before any volume changes are visible on conventional radiological images. Here we discuss the development of robust quantitative imaging biomarkers and how they can personalize therapy towards meaningful clinical endpoints. Abstract Onboard, real-time, imaging techniques, from the original megavoltage planar imaging devices, to the emerging combined MRI-Linear Accelerators, have brought a huge transformation in the ability to deliver targeted radiation therapies. Each generation of these technologies enables lethal doses of radiation to be delivered to target volumes with progressively more accuracy and thus allows shrinking of necessary geometric margins, leading to reduced toxicities. Alongside these improvements in treatment delivery, advances in medical imaging, e.g., PET, and MRI, have also allowed target volumes themselves to be better defined. The development of functional and molecular imaging is now driving a conceptually larger step transformation to both better understand the cancer target and disease to be treated, as well as how tumors respond to treatment. A biological description of the tumor microenvironment is now accepted as an essential component of how to personalize and adapt treatment. This applies not only to radiation oncology but extends widely in cancer management from surgical oncology planning and interventional radiology, to evaluation of targeted drug delivery efficacy in medical oncology/immunotherapy. Here, we will discuss the role and requirements of functional and metabolic imaging techniques in the context of brain tumors and metastases to reliably provide multi-parametric imaging biomarkers of the tumor microenvironment.
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Affiliation(s)
- Catherine Coolens
- Department of Medical Physics, Princess Margaret Cancer Centre & University Health Network, Toronto, ON M5G 1Z5, Canada;
- Department of Radiation Oncology, University of Toronto, Toronto, ON M5T 1P5, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON M5G 1L7, Canada
- Department of Biomedical Engineering, University of Toronto, Toronto, ON M5S 3G9, Canada
- TECHNA Institute, University Health Network, Toronto, ON M5G 1Z5, Canada
- Correspondence:
| | - Matt N. Gwilliam
- Department of Medical Physics, Princess Margaret Cancer Centre & University Health Network, Toronto, ON M5G 1Z5, Canada;
| | - Paula Alcaide-Leon
- Joint Department of Medical Imaging, University Health Network, Toronto, ON M5G 1Z5, Canada;
| | | | - Fabio Ynoe de Moraes
- Department of Oncology, Division of Radiation Oncology, Queen’s University, Kingston, ON K7L 5P9, Canada;
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15
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Frederico SC, Hancock JC, Brettschneider EES, Ratnam NM, Gilbert MR, Terabe M. Making a Cold Tumor Hot: The Role of Vaccines in the Treatment of Glioblastoma. Front Oncol 2021; 11:672508. [PMID: 34041034 PMCID: PMC8141615 DOI: 10.3389/fonc.2021.672508] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Accepted: 04/19/2021] [Indexed: 12/28/2022] Open
Abstract
The use of immunotherapies for the treatment of brain tumors is a topic that has garnered considerable excitement in recent years. Discoveries such as the presence of a glymphatic system and immune surveillance in the central nervous system (CNS) have shattered the theory of immune privilege and opened up the possibility of treating CNS malignancies with immunotherapies. However, despite many immunotherapy clinical trials aimed at treating glioblastoma (GBM), very few have demonstrated a significant survival benefit. Several factors for this have been identified, one of which is that GBMs are immunologically "cold," implying that the cancer does not induce a strong T cell response. It is postulated that this is why clinical trials using an immune checkpoint inhibitor alone have not demonstrated efficacy. While it is well established that anti-cancer T cell responses can be facilitated by the presentation of tumor-specific antigens to the immune system, treatment-related death of GBM cells and subsequent release of molecules have not been shown to be sufficient to evoke an anti-tumor immune response effective enough to have a significant impact. To overcome this limitation, vaccines can be used to introduce exogenous antigens at higher concentrations to the immune system to induce strong tumor antigen-specific T cell responses. In this review, we will describe vaccination strategies that are under investigation to treat GBM; categorizing them based on their target antigens, form of antigens, vehicles used, and pairing with specific adjuvants. We will review the concept of vaccine therapy in combination with immune checkpoint inhibitors, as it is hypothesized that this approach may be more effective in overcoming the immunosuppressive milieu of GBM. Clinical trial design and the need for incorporating robust immune monitoring into future studies will also be discussed here. We believe that the integration of evolving technologies of vaccine development, delivery, and immune monitoring will further enhance the role of these therapies and will likely remain an important area of investigation for future treatment strategies for GBM patients.
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Affiliation(s)
- Stephen C. Frederico
- Neuro-Oncology Branch, CCR, NCI, National Institutes of Health, Bethesda, MD, United States
| | - John C. Hancock
- Neuro-Oncology Branch, CCR, NCI, National Institutes of Health, Bethesda, MD, United States
| | - Emily E. S. Brettschneider
- Neuro-Oncology Branch, CCR, NCI, National Institutes of Health, Bethesda, MD, United States
- Ludwig Institute for Cancer Research, University of Oxford, Oxford, United Kingdom
| | - Nivedita M. Ratnam
- Neuro-Oncology Branch, CCR, NCI, National Institutes of Health, Bethesda, MD, United States
| | - Mark R. Gilbert
- Neuro-Oncology Branch, CCR, NCI, National Institutes of Health, Bethesda, MD, United States
| | - Masaki Terabe
- Neuro-Oncology Branch, CCR, NCI, National Institutes of Health, Bethesda, MD, United States
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16
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Durgin JS, Henderson F, Nasrallah MP, Mohan S, Wang S, Lacey SF, Melenhorst JJ, Desai AS, Lee JYK, Maus MV, June CH, Brem S, O'Connor RS, Binder Z, O'Rourke DM. Case Report: Prolonged Survival Following EGFRvIII CAR T Cell Treatment for Recurrent Glioblastoma. Front Oncol 2021; 11:669071. [PMID: 34026647 PMCID: PMC8138201 DOI: 10.3389/fonc.2021.669071] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 04/07/2021] [Indexed: 12/01/2022] Open
Abstract
Autologous chimeric antigen receptor (CAR) T cells targeted to epidermal growth factor receptor variant III (CAR T-EGFRvIII) have been developed and administered experimentally to treat patients with IDH1 wildtype recurrent glioblastoma (rGBM) (NCT02209376). We report the case of a 59-year-old patient who received a single peripheral infusion of CAR T-EGFRvIII cells and survived 36 months after disease recurrence, exceeding expected survival for recurrent glioblastoma. Post-infusion histopathologic analysis of tissue obtained during a second stage surgical resection revealed immunosuppressive adaptive changes in the tumor tissue as well as reduced EGFRvIII expression. Serial brain imaging demonstrated a significant reduction in relative cerebral blood volume (rCBV), a measure strongly associated with tumor proliferative activity, at early time points following CAR T treatment. Notably, CAR T-EGFRvIII cells persisted in her peripheral circulation during 29 months of follow-up, the longest period of CAR T persistence reported in GBM trials to date. These findings in a long-term survivor show that peripherally administered CAR T-EGFRvIII cells can persist for years in the circulation and suggest that this cell therapy approach could be optimized to achieve broader efficacy in recurrent GBM patients.
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Affiliation(s)
- Joseph S Durgin
- Glioblastoma Translational Center of Excellence, The Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.,Center for Cellular Immunotherapies, University of Pennsylvania, Philadelphia, PA, United States.,Department of Pathology & Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Fraser Henderson
- Department of Neurosurgery, Medical University of South Carolina, Charleston, SC, United States
| | - MacLean P Nasrallah
- Glioblastoma Translational Center of Excellence, The Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.,Department of Pathology & Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Suyash Mohan
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Sumei Wang
- Department of Radiology, Division of Neuroradiology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Simon F Lacey
- Center for Cellular Immunotherapies, University of Pennsylvania, Philadelphia, PA, United States
| | - Jan Joseph Melenhorst
- Glioblastoma Translational Center of Excellence, The Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.,Center for Cellular Immunotherapies, University of Pennsylvania, Philadelphia, PA, United States.,Department of Pathology & Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Arati S Desai
- Glioblastoma Translational Center of Excellence, The Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.,Division of Hematology/Oncology, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - John Y K Lee
- Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Marcela V Maus
- Cellular Immunotherapy Program, Massachusetts General Hospital Cancer Center and Harvard Medical School, Boston, MA, United States
| | - Carl H June
- Center for Cellular Immunotherapies, University of Pennsylvania, Philadelphia, PA, United States.,Department of Pathology & Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Steven Brem
- Glioblastoma Translational Center of Excellence, The Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.,Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Roddy S O'Connor
- Center for Cellular Immunotherapies, University of Pennsylvania, Philadelphia, PA, United States.,Department of Pathology & Laboratory Medicine, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Zev Binder
- Glioblastoma Translational Center of Excellence, The Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.,Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
| | - Donald M O'Rourke
- Glioblastoma Translational Center of Excellence, The Abramson Cancer Center, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States.,Department of Neurosurgery, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, United States
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17
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Bapuraj JR, Perni K, Gomez-Hassan D, Srinivasan A. Imaging Surveillance of Gliomas: Role of Basic and Advanced Imaging Techniques. Radiol Clin North Am 2021; 59:395-407. [PMID: 33926685 DOI: 10.1016/j.rcl.2021.01.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
Abstract
It is essential to be aware of widely accepted criteria for grading of treatment response in both high-grade and low-grade gliomas. These criteria primarily take into account responses of measurable and nonmeasurable lesions on T2-weighted, fluid-attenuated inversion recovery, and postcontrast images to determine a final category of response for the patient. The additional role that other advanced imaging techniques, such as diffusion and perfusion imaging, can play in the surveillance of these tumors is discussed in this article.
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Affiliation(s)
- Jayapalli Rajiv Bapuraj
- Division of Neuroradiology, Department of Radiology, University of Michigan Medical School, Michigan Medicine, 1500 East Medical Center Drive, UMHS, B2-A209, Ann Arbor, MI 48109, USA
| | - Krishna Perni
- Division of Neuroradiology, Department of Radiology, University of Michigan Medical School, Michigan Medicine, 1500 East Medical Center Drive, UMHS, B2-A209, Ann Arbor, MI 48109, USA
| | - Diana Gomez-Hassan
- Division of Neuroradiology, Department of Radiology, University of Michigan Medical School, Michigan Medicine, 4260 Plymouth Road, Ann Arbor, MI 48105, USA
| | - Ashok Srinivasan
- Division of Neuroradiology, Department of Radiology, University of Michigan Medical School, Michigan Medicine, 1500 East Medical Center Drive, UMHS, B2-A209, Ann Arbor, MI 48109, USA.
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18
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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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19
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Song J, Kadaba P, Kravitz A, Hormigo A, Friedman J, Belani P, Hadjipanayis C, Ellingson BM, Nael K. Multiparametric MRI for early identification of therapeutic response in recurrent glioblastoma treated with immune checkpoint inhibitors. Neuro Oncol 2021; 22:1658-1666. [PMID: 32193547 DOI: 10.1093/neuonc/noaa066] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND Physiologic changes quantified by diffusion and perfusion MRI have shown utility in predicting treatment response in glioblastoma (GBM) patients treated with cytotoxic therapies. We aimed to investigate whether quantitative changes in diffusion and perfusion after treatment by immune checkpoint inhibitors (ICIs) would determine 6-month progression-free survival (PFS6) in patients with recurrent GBM. METHODS Inclusion criteria for this retrospective study were: (i) diagnosis of recurrent GBM treated with ICIs and (ii) availability of diffusion and perfusion in pre and post ICI MRI (iii) at ≥6 months follow-up from treatment. After co-registration, mean values of the relative apparent diffusion coefficient (rADC), Ktrans (volume transfer constant), Ve (extravascular extracellular space volume) and Vp (plasma volume), and relative cerebral blood volume (rCBV) were calculated from a volume-of-interest of the enhancing tumor. Final assignment of stable/improved versus progressive disease was determined on 6-month follow-up using modified Response Assessment in Neuro-Oncology criteria. RESULTS Out of 19 patients who met inclusion criteria and follow-up (mean ± SD: 7.8 ± 1.4 mo), 12 were determined to have tumor progression, while 7 had treatment response after 6 months of ICI treatment. Only interval change of rADC was suggestive of treatment response. Patients with treatment response (6/7: 86%) had interval increased rADC, while 11/12 (92%) with tumor progression had decreased rADC (P = 0.001). Interval change in rCBV, Ktrans, Vp, and Ve were not indicative of treatment response within 6 months. CONCLUSIONS In patients with recurrent GBM, interval change in rADC is promising in assessing treatment response versus progression within the first 6 months following ICI treatment. KEY POINTS • In recurrent GBM treated with ICIs, interval change in rADC suggests early treatment response.• Interval change in rADC can be used as an imaging biomarker to determine PFS6.• Interval change in MR perfusion and permeability measures do not suggest ICI treatment response.
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Affiliation(s)
- Joseph Song
- Icahn School of Medicine at Mount Sinai, Department of Radiology (Neuroimaging Advanced and Exploratory Lab), New York, New York
| | - Priyanka Kadaba
- Icahn School of Medicine at Mount Sinai, Department of Radiology (Neuroimaging Advanced and Exploratory Lab), New York, New York
| | - Amanda Kravitz
- Icahn School of Medicine at Mount Sinai, Department of Radiology (Neuroimaging Advanced and Exploratory Lab), New York, New York
| | - Adilia Hormigo
- Department of Neurology, Medicine (Div Hem Onc), The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Joshua Friedman
- Department of Neurology, Medicine (Div Hem Onc), The Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Puneet Belani
- Icahn School of Medicine at Mount Sinai, Department of Radiology (Neuroimaging Advanced and Exploratory Lab), New York, New York
| | | | - Benjamin M Ellingson
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
| | - Kambiz Nael
- UCLA Brain Tumor Imaging Laboratory, Center for Computer Vision and Imaging Biomarkers, Department of Radiological Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California
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20
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Crotty EE, Downey KM, Ferrerosa LM, Flores CT, Hegde B, Raskin S, Hwang EI, Vitanza NA, Okada H. Considerations when treating high-grade pediatric glioma patients with immunotherapy. Expert Rev Neurother 2021; 21:205-219. [PMID: 33225764 PMCID: PMC7880880 DOI: 10.1080/14737175.2020.1855144] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2020] [Accepted: 11/20/2020] [Indexed: 12/21/2022]
Abstract
INTRODUCTION Children with high-grade gliomas (pHGGs) represent a clinical population in substantial need of new therapeutic options given the inefficacy and toxicity of current standard-of-care modalities. Although immunotherapy has emerged as a promising modality, it has yet to elicit a significant survival benefit for pHGG patients. While preclinical studies address a variety of underlying challenges, translational clinical trial design and management also need to reflect the most updated progress and lessons from the field. AREAS COVERED The authors will focus our discussion on the design of clinical trials, the management of potential toxicities, immune monitoring, and novel biomarkers. Clinical trial design should integrate appropriate patient populations, novel, and preclinically optimized trial design, and logical treatment combinations, particularly those which synergize with standard of care modalities. However, there are caveats due to the nature of immunotherapy trials, such as patient selection bias, evidenced by the frequent exclusion of patients on high-dose corticosteroids. Robust immune-modulating effects of modern immunotherapy can have toxicities. As such, it is important to understand and manage these, especially in pHGG patients. EXPERT OPINION Adequate integration of these considerations should allow us to effectively gain insights on biological activity, safety, and biomarkers associated with benefits for patients.
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Affiliation(s)
- Erin E. Crotty
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, Seattle Children’s Hospital, University of Washington, Seattle, WA, USA
| | - Kira M. Downey
- Department of Neurological Surgery, Helen Diller Family Comprehensive Cancer Research Center, University of California San Francisco, San Francisco, CA, USA
| | - Lauren M. Ferrerosa
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, UCSF Benioff Children’s Hospital, Oakland, 747 52nd Street, Oakland, CA, USA
| | | | - Bindu Hegde
- Department of Neurological Surgery, Helen Diller Family Comprehensive Cancer Research Center, University of California San Francisco, San Francisco, CA, USA
| | - Scott Raskin
- Children’s National Hospital, Washington, DC, USA
| | | | - Nicholas A. Vitanza
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Division of Pediatric Hematology/Oncology, Department of Pediatrics, Seattle Children’s Hospital, University of Washington, Seattle, WA, USA
- Ben Towne Center for Childhood Cancer Research, Seattle Children’s Research Institute, Seattle, WA, USA
| | - Hideho Okada
- Department of Neurological Surgery, Helen Diller Family Comprehensive Cancer Research Center, University of California San Francisco, San Francisco, CA, USA
- The Parker Institute for Cancer Immunotherapy, University of California, San Francisco, San Francisco, CA, USA
- Cancer Immunotherapy Program, University of California, San Francisco, San Francisco, CA, USA
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21
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Strauss SB, Meng A, Ebani EJ, Chiang GC. Imaging Glioblastoma Posttreatment: Progression, Pseudoprogression, Pseudoresponse, Radiation Necrosis. Neuroimaging Clin N Am 2021; 31:103-120. [PMID: 33220823 DOI: 10.1016/j.nic.2020.09.010] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Radiographic monitoring of posttreatment glioblastoma is important for clinical trials and determining next steps in management. Evaluation for tumor progression is confounded by the presence of treatment-related radiographic changes, making a definitive determination less straight-forward. The purpose of this article was to describe imaging tools available for assessing treatment response in glioblastoma, as well as to highlight the definitions, pathophysiology, and imaging features typical of true progression, pseudoprogression, pseudoresponse, and radiation necrosis.
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Affiliation(s)
- Sara B Strauss
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Alicia Meng
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Edward J Ebani
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Gloria C Chiang
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA.
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22
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Ratnam NM, Frederico SC, Gonzalez JA, Gilbert MR. Clinical correlates for immune checkpoint therapy: significance for CNS malignancies. Neurooncol Adv 2021; 3:vdaa161. [PMID: 33506203 PMCID: PMC7813206 DOI: 10.1093/noajnl/vdaa161] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022] Open
Abstract
Immune checkpoint inhibitors (ICIs) have revolutionized the field of cancer immunotherapy. Most commonly, inhibitors of PD-1 and CTLA4 are used having received approval for the treatment of many cancers like melanoma, non-small-cell lung carcinoma, and leukemia. In contrast, to date, clinical studies conducted in patients with CNS malignancies have not demonstrated promising results. However, patients with CNS malignancies have several underlying factors such as treatment with supportive medications like corticosteroids and cancer therapies including radiation and chemotherapy that may negatively impact response to ICIs. Although many clinical trials have been conducted with ICIs, measures that reproducibly and reliably indicate that treatment has evoked an effective immune response have not been fully developed. In this article, we will review the history of ICI therapy and the correlative biology that has been performed in the clinical trials testing these therapies in different cancers. It is our aim to help provide an overview of the assays that may be used to gauge immunologic response. This may be particularly germane for CNS tumors, where there is currently a great need for predictive biomarkers that will allow for the selection of patients with the highest likelihood of responding.
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Affiliation(s)
- Nivedita M Ratnam
- Neuro-Oncology Branch, CCR, NCI, National Institutes of Health, Bethesda, Maryland, USA
| | - Stephen C Frederico
- Neuro-Oncology Branch, CCR, NCI, National Institutes of Health, Bethesda, Maryland, USA
| | - Javier A Gonzalez
- Neuro-Oncology Branch, CCR, NCI, National Institutes of Health, Bethesda, Maryland, USA
| | - Mark R Gilbert
- Neuro-Oncology Branch, CCR, NCI, National Institutes of Health, Bethesda, Maryland, USA
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23
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Xie T, Chen X, Fang J, Xue W, Zhang J, Tong H, Liu H, Guo Y, Yang Y, Zhang W. Non-invasive monitoring of the kinetic infiltration and therapeutic efficacy of nanoparticle-labeled chimeric antigen receptor T cells in glioblastoma via 7.0-Tesla magnetic resonance imaging. Cytotherapy 2020; 23:211-222. [PMID: 33334686 DOI: 10.1016/j.jcyt.2020.10.006] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 10/28/2020] [Accepted: 10/30/2020] [Indexed: 01/15/2023]
Abstract
BACKGROUND AIMS Chimeric antigen receptor (CAR) T-cell therapy is a promising treatment strategy in solid tumors. In vivo cell tracking techniques can help us better understand the infiltration, persistence and therapeutic efficacy of CAR T cells. In this field, magnetic resonance imaging (MRI) can achieve high-resolution images of cells by using cellular imaging probes. MRI can also provide various biological information on solid tumors. METHODS The authors adopted the amino alcohol derivatives of glucose-coated nanoparticles, ultra-small superparamagnetic particles of iron oxide (USPIOs), to label CAR T cells for non-invasive monitoring of kinetic infiltration and persistence in glioblastoma (GBM). The specific targeting CARs included anti-human epidermal growth factor receptor variant III and IL13 receptor subunit alpha 2 CARs. RESULTS When using an appropriate concentration, USPIO labeling exerted no negative effects on the biological characteristics and killing efficiency of CAR T cells. Increasing hypointensity signals could be detected in GBM models by susceptibility-weighted imaging MRI ranging from 3 days to 14 days following the injection of USPIO-labeled CAR T cells. In addition, nanoparticles and CAR T cells were found on consecutive histopathological sections. Moreover, diffusion and perfusion MRI revealed significantly increased water diffusion and decreased vascular permeability on day 3 after treatment, which was simultaneously accompanied by a significant decrease in tumor cell proliferation and increase in intercellular tight junction on immunostaining sections. CONCLUSION These results establish an effective imaging technique that can track CAR T cells in GBM models and validate their early therapeutic effects, which may guide the evaluation of CAR T-cell therapies in solid tumors.
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Affiliation(s)
- Tian Xie
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Center for Imaging and Nuclear Medicine, Chongqing, China
| | - Xiao Chen
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Center for Imaging and Nuclear Medicine, Chongqing, China
| | - Jingqin Fang
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Center for Imaging and Nuclear Medicine, Chongqing, China
| | - Wei Xue
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Center for Imaging and Nuclear Medicine, Chongqing, China
| | - Junfeng Zhang
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Center for Imaging and Nuclear Medicine, Chongqing, China
| | - Haipeng Tong
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Center for Imaging and Nuclear Medicine, Chongqing, China
| | - Heng Liu
- Department of Radiology, PLA Rocket Force Characteristic Medical Center, Beijing, China
| | - Yu Guo
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Center for Imaging and Nuclear Medicine, Chongqing, China
| | - Yizeng Yang
- Department of Medicine, Division of Gastroenterology, University of Pennsylvania School of Medicine, Philadelphia, Pennsylvania, USA.
| | - Weiguo Zhang
- Department of Radiology, Institute of Surgery Research, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Center for Imaging and Nuclear Medicine, Chongqing, China.
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24
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García-Figueiras R, Baleato-González S, Luna A, Muñoz-Iglesias J, Oleaga L, Vallejo Casas JA, Martín-Noguerol T, Broncano J, Areses MC, Vilanova JC. Assessing Immunotherapy with Functional and Molecular Imaging and Radiomics. Radiographics 2020; 40:1987-2010. [PMID: 33035135 DOI: 10.1148/rg.2020200070] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Immunotherapy is changing the treatment paradigm for cancer and has introduced new challenges in medical imaging. Because not all patients benefit from immunotherapy, pretreatment imaging should be performed to identify not only prognostic factors but also factors that allow prediction of response to immunotherapy. Follow-up studies must allow detection of nonresponders, without confusion of pseudoprogression with real progression to prevent premature discontinuation of treatment that can benefit the patient. Conventional imaging techniques and classic tumor response criteria are limited for the evaluation of the unusual patterns of response that arise from the specific mechanisms of action of immunotherapy, so advanced imaging methods must be developed to overcome these shortcomings. The authors present the fundamentals of the tumor immune microenvironment and immunotherapy and how they influence imaging findings. They also discuss advances in functional and molecular imaging techniques for the assessment of immunotherapy in clinical practice, including their use to characterize immune phenotypes, assess patient prognosis and response to therapy, and evaluate immune-related adverse events. Finally, the development of radiomics and radiogenomics in these therapies and the future role of imaging biomarkers for immunotherapy are discussed. Online supplemental material is available for this article. ©RSNA, 2020.
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Affiliation(s)
- Roberto García-Figueiras
- From the Department of Radiology, Oncologic Imaging, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706, Santiago de Compostela, Spain (R.G.F., S.B.G.); Department of Radiology, HT Medica, Jaén, Spain (A.L, J.B.); Department of Nuclear Medicine, Complexo Hospitalario Universitario de Vigo, Vigo, Spain (J.M.I.); Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain (L.O.); Unidad de Gestión Clínica de Medicina Nuclear, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain (J.A.V.C.); MRI Unit, HT Medica, Jaén, Spain (T.M.N.); Department of Medical Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Spain (M.C.A.); and Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging, Girona, Spain (J.C.V.)
| | - Sandra Baleato-González
- From the Department of Radiology, Oncologic Imaging, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706, Santiago de Compostela, Spain (R.G.F., S.B.G.); Department of Radiology, HT Medica, Jaén, Spain (A.L, J.B.); Department of Nuclear Medicine, Complexo Hospitalario Universitario de Vigo, Vigo, Spain (J.M.I.); Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain (L.O.); Unidad de Gestión Clínica de Medicina Nuclear, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain (J.A.V.C.); MRI Unit, HT Medica, Jaén, Spain (T.M.N.); Department of Medical Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Spain (M.C.A.); and Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging, Girona, Spain (J.C.V.)
| | - Antonio Luna
- From the Department of Radiology, Oncologic Imaging, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706, Santiago de Compostela, Spain (R.G.F., S.B.G.); Department of Radiology, HT Medica, Jaén, Spain (A.L, J.B.); Department of Nuclear Medicine, Complexo Hospitalario Universitario de Vigo, Vigo, Spain (J.M.I.); Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain (L.O.); Unidad de Gestión Clínica de Medicina Nuclear, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain (J.A.V.C.); MRI Unit, HT Medica, Jaén, Spain (T.M.N.); Department of Medical Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Spain (M.C.A.); and Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging, Girona, Spain (J.C.V.)
| | - José Muñoz-Iglesias
- From the Department of Radiology, Oncologic Imaging, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706, Santiago de Compostela, Spain (R.G.F., S.B.G.); Department of Radiology, HT Medica, Jaén, Spain (A.L, J.B.); Department of Nuclear Medicine, Complexo Hospitalario Universitario de Vigo, Vigo, Spain (J.M.I.); Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain (L.O.); Unidad de Gestión Clínica de Medicina Nuclear, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain (J.A.V.C.); MRI Unit, HT Medica, Jaén, Spain (T.M.N.); Department of Medical Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Spain (M.C.A.); and Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging, Girona, Spain (J.C.V.)
| | - Laura Oleaga
- From the Department of Radiology, Oncologic Imaging, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706, Santiago de Compostela, Spain (R.G.F., S.B.G.); Department of Radiology, HT Medica, Jaén, Spain (A.L, J.B.); Department of Nuclear Medicine, Complexo Hospitalario Universitario de Vigo, Vigo, Spain (J.M.I.); Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain (L.O.); Unidad de Gestión Clínica de Medicina Nuclear, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain (J.A.V.C.); MRI Unit, HT Medica, Jaén, Spain (T.M.N.); Department of Medical Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Spain (M.C.A.); and Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging, Girona, Spain (J.C.V.)
| | - Juan Antonio Vallejo Casas
- From the Department of Radiology, Oncologic Imaging, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706, Santiago de Compostela, Spain (R.G.F., S.B.G.); Department of Radiology, HT Medica, Jaén, Spain (A.L, J.B.); Department of Nuclear Medicine, Complexo Hospitalario Universitario de Vigo, Vigo, Spain (J.M.I.); Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain (L.O.); Unidad de Gestión Clínica de Medicina Nuclear, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain (J.A.V.C.); MRI Unit, HT Medica, Jaén, Spain (T.M.N.); Department of Medical Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Spain (M.C.A.); and Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging, Girona, Spain (J.C.V.)
| | - Teodoro Martín-Noguerol
- From the Department of Radiology, Oncologic Imaging, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706, Santiago de Compostela, Spain (R.G.F., S.B.G.); Department of Radiology, HT Medica, Jaén, Spain (A.L, J.B.); Department of Nuclear Medicine, Complexo Hospitalario Universitario de Vigo, Vigo, Spain (J.M.I.); Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain (L.O.); Unidad de Gestión Clínica de Medicina Nuclear, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain (J.A.V.C.); MRI Unit, HT Medica, Jaén, Spain (T.M.N.); Department of Medical Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Spain (M.C.A.); and Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging, Girona, Spain (J.C.V.)
| | - Jordi Broncano
- From the Department of Radiology, Oncologic Imaging, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706, Santiago de Compostela, Spain (R.G.F., S.B.G.); Department of Radiology, HT Medica, Jaén, Spain (A.L, J.B.); Department of Nuclear Medicine, Complexo Hospitalario Universitario de Vigo, Vigo, Spain (J.M.I.); Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain (L.O.); Unidad de Gestión Clínica de Medicina Nuclear, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain (J.A.V.C.); MRI Unit, HT Medica, Jaén, Spain (T.M.N.); Department of Medical Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Spain (M.C.A.); and Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging, Girona, Spain (J.C.V.)
| | - María Carmen Areses
- From the Department of Radiology, Oncologic Imaging, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706, Santiago de Compostela, Spain (R.G.F., S.B.G.); Department of Radiology, HT Medica, Jaén, Spain (A.L, J.B.); Department of Nuclear Medicine, Complexo Hospitalario Universitario de Vigo, Vigo, Spain (J.M.I.); Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain (L.O.); Unidad de Gestión Clínica de Medicina Nuclear, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain (J.A.V.C.); MRI Unit, HT Medica, Jaén, Spain (T.M.N.); Department of Medical Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Spain (M.C.A.); and Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging, Girona, Spain (J.C.V.)
| | - Joan C Vilanova
- From the Department of Radiology, Oncologic Imaging, Hospital Clínico Universitario de Santiago de Compostela, Choupana s/n, 15706, Santiago de Compostela, Spain (R.G.F., S.B.G.); Department of Radiology, HT Medica, Jaén, Spain (A.L, J.B.); Department of Nuclear Medicine, Complexo Hospitalario Universitario de Vigo, Vigo, Spain (J.M.I.); Department of Radiology, Hospital Clínic Barcelona, Barcelona, Spain (L.O.); Unidad de Gestión Clínica de Medicina Nuclear, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain (J.A.V.C.); MRI Unit, HT Medica, Jaén, Spain (T.M.N.); Department of Medical Oncology, Complexo Hospitalario Universitario de Ourense, Ourense, Spain (M.C.A.); and Department of Radiology, Clínica Girona, Institute of Diagnostic Imaging, Girona, Spain (J.C.V.)
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25
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A multidisciplinary consensus on the morphological and functional responses to immunotherapy treatment. Clin Transl Oncol 2020; 23:434-449. [PMID: 32623581 PMCID: PMC7936941 DOI: 10.1007/s12094-020-02442-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2020] [Accepted: 06/22/2020] [Indexed: 02/08/2023]
Abstract
The implementation of immunotherapy has radically changed the treatment of oncological patients. Currently, immunotherapy is indicated in the treatment of patients with head and neck tumors, melanoma, lung cancer, bladder tumors, colon cancer, cervical cancer, breast cancer, Merkel cell carcinoma, liver cancer, leukemia and lymphomas. However, its efficacy is restricted to a limited number of cases. The challenge is, therefore, to identify which subset of patients would benefit from immunotherapy. To this end, the establishment of immunotherapy response criteria and predictive and prognostic biomarkers is of paramount interest. In this report, a group of experts of the Spanish Society of Medical Oncology (SEOM), the Spanish Society of Medical Radiology (SERAM), and Spanish Society of Nuclear Medicine and Molecular Imaging (SEMNIM) provide an up-to-date review and a consensus guide on these issues.
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26
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Daghighi S, Bahrami N, Tom WJ, Coley N, Seibert TM, Hattangadi-Gluth JA, Piccioni DE, Dale AM, Farid N, McDonald CR. Restriction Spectrum Imaging Differentiates True Tumor Progression From Immune-Mediated Pseudoprogression: Case Report of a Patient With Glioblastoma. Front Oncol 2020; 10:24. [PMID: 32047723 PMCID: PMC6997150 DOI: 10.3389/fonc.2020.00024] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2019] [Accepted: 01/08/2020] [Indexed: 11/13/2022] Open
Abstract
Immunotherapy is increasingly used in the treatment of glioblastoma (GBM), with immune checkpoint therapy gaining in popularity given favorable outcomes achieved for other tumors. However, immune-mediated (IM)-pseudoprogression is common, remains poorly characterized, and renders conventional imaging of little utility when evaluating for treatment response. We present the case of a 64-year-old man with GBM who developed pathologically proven IM-pseudoprogression after initiation of a checkpoint inhibitor, and who subsequently developed true tumor progression at a distant location. Based on both qualitative and quantitative analysis, we demonstrate that an advanced diffusion-weighted imaging (DWI) technique called restriction spectrum imaging (RSI) can differentiate IM-pseudoprogression from true progression even when conventional imaging, including standard DWI/apparent diffusion coefficient (ADC), is not informative. These data complement existing literature supporting the ability of RSI to estimate tumor cellularity, which may help to resolve complex diagnostic challenges such as the identification of IM-pseudoprogression.
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Affiliation(s)
- Shadi Daghighi
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Naeim Bahrami
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States
| | - William J. Tom
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Nicholas Coley
- Department of Pathology, University of California, San Diego, La Jolla, CA, United States
| | - Tyler M. Seibert
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States
- Department of Radiation Medicine, University of California, San Diego, La Jolla, CA, United States
| | - Jona A. Hattangadi-Gluth
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States
- Department of Radiation Medicine, University of California, San Diego, La Jolla, CA, United States
| | - David E. Piccioni
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Anders M. Dale
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, United States
| | - Nikdokht Farid
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States
- Department of Radiology, University of California, San Diego, La Jolla, CA, United States
| | - Carrie R. McDonald
- Center for Multimodal Imaging and Genetics, University of California, San Diego, La Jolla, CA, United States
- Department of Radiation Medicine, University of California, San Diego, La Jolla, CA, United States
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, United States
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27
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Galldiks N, Lohmann P, Werner JM, Ceccon G, Fink GR, Langen KJ. Molecular imaging and advanced MRI findings following immunotherapy in patients with brain tumors. Expert Rev Anticancer Ther 2019; 20:9-15. [PMID: 31842635 DOI: 10.1080/14737140.2020.1705788] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Introduction: Currently, immunotherapy using vaccination strategies or oncolytic virus approaches, cell-based immunotherapy, and the blockade of immune checkpoints are under evaluation in patients with brain cancer. Here we summarize clinically significant imaging findings such as treatment-related changes detected by advanced neuroimaging techniques following the most suitable immunotherapy options currently used in neuro-oncology. We, furthermore, provide an overview of how these advanced imaging techniques may help to overcome shortcomings of standard MRI in the assessment and follow-up of patients with brain cancer.Areas covered: The current literature on neuroimaging for immunotherapy in the field of brain tumors, with a focus on gliomas and brain metastases is summarized.Expert commentary: Data suggest that imaging parameters primarily derived from amino acid PET, diffusion- and perfusion-weighted MRI, or MR spectroscopy are particularly helpful for the evaluation of treatment response and provide valuable information for the differentiation of treatment-induced changes from actual brain tumor progression following various immunotherapy approaches.
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Affiliation(s)
- Norbert Galldiks
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Jülich, Germany.,Center of Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Jülich, Germany
| | - Jan-Michael Werner
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Garry Ceccon
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Gereon R Fink
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.,Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Jülich, Germany
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Jülich, Germany.,Center of Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Duesseldorf, Germany.,Department of Nuclear Medicine, University Hospital RWTH Aachen, Aachen, Germany
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28
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Wu M, Zhang Y, Zhang Y, Liu Y, Wu M, Ye Z. Imaging-based Biomarkers for Predicting and Evaluating Cancer Immunotherapy Response. Radiol Imaging Cancer 2019; 1:e190031. [PMID: 33778682 DOI: 10.1148/rycan.2019190031] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2019] [Revised: 08/24/2019] [Accepted: 08/26/2019] [Indexed: 12/31/2022]
Abstract
Proper patient selection for immunotherapy is critical, as certain tumor microenvironments are more permissible to therapy than others. Currently, the use of programmed cell death ligand-1 (PD-L1) and microsatellite instability high and/or mismatch repair deficiency are used as biomarkers for immunotherapy response. To improve tumor characterization, methodologies are being developed to combine imaging with tumor immune environment characterization. Imaging of tumors from immunotherapy responders and nonresponders with various imaging modalities has led to the development of criteria that could predict patient response to immunotherapy. Additionally, radiomics-based artificial intelligence methods are being used to characterize tumor microenvironments to predict and evaluate immunotherapy responses, as well as to predict risk of immune-related adverse events. Molecular imaging techniques are also being developed for various modalities to observe tumor expression of immunotherapy targets, such as PD-L1 and, to confirm the target is being expressed on resident tumors. In all, the advancements of imaging techniques to define tumor immunologic characteristics will help to stratify patients who are more likely to respond to immunotherapies. Keywords: Computer Aided Diagnosis (CAD), Computer Applications-Virtual Imaging, Efficacy Studies, MR-Imaging, Molecular Imaging-Cancer, Molecular Imaging-Immunotherapy, Molecular Imaging-Nanoparticles, Molecular Imaging-Probe Development, Molecular Imaging-Target Development, SPECT/CT © RSNA, 2019.
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Affiliation(s)
- Minghao Wu
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin 300060, PR China (M.W., Y.Z., Y. Z., Y.L., Z.Y.); and Institut National de la Recherche Scientifique-Énergie Matériaux et Télécommunications, Varennes, Quebec, Canada (Mingjie Wu)
| | - Yanyan Zhang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin 300060, PR China (M.W., Y.Z., Y. Z., Y.L., Z.Y.); and Institut National de la Recherche Scientifique-Énergie Matériaux et Télécommunications, Varennes, Quebec, Canada (Mingjie Wu)
| | - Yuwei Zhang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin 300060, PR China (M.W., Y.Z., Y. Z., Y.L., Z.Y.); and Institut National de la Recherche Scientifique-Énergie Matériaux et Télécommunications, Varennes, Quebec, Canada (Mingjie Wu)
| | - Ying Liu
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin 300060, PR China (M.W., Y.Z., Y. Z., Y.L., Z.Y.); and Institut National de la Recherche Scientifique-Énergie Matériaux et Télécommunications, Varennes, Quebec, Canada (Mingjie Wu)
| | - Mingjie Wu
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin 300060, PR China (M.W., Y.Z., Y. Z., Y.L., Z.Y.); and Institut National de la Recherche Scientifique-Énergie Matériaux et Télécommunications, Varennes, Quebec, Canada (Mingjie Wu)
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer Key Laboratory of Cancer Prevention and Therapy, Huanhuxi Road, Hexi District, Tianjin 300060, PR China (M.W., Y.Z., Y. Z., Y.L., Z.Y.); and Institut National de la Recherche Scientifique-Énergie Matériaux et Télécommunications, Varennes, Quebec, Canada (Mingjie Wu)
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29
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Cuccarini V, Aquino D, Gioppo A, Anghileri E, Pellegatta S, Schettino C, Mazzi F, Finocchiaro G, Bruzzone MG, Eoli M. Advanced MRI Assessment during Dendritic Cell Immunotherapy Added to Standard Treatment Against Glioblastoma. J Clin Med 2019; 8:jcm8112007. [PMID: 31744235 PMCID: PMC6912338 DOI: 10.3390/jcm8112007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2019] [Revised: 11/12/2019] [Accepted: 11/13/2019] [Indexed: 01/18/2023] Open
Abstract
Evaluating changes induced by immunotherapies (IT) on conventional magnetic resonance imaging (MRI) is difficult because those treatments may produce inflammatory responses. To explore the potential contribution of advanced MRI to distinguish pseudoprogression (PsP) and true tumor progression (TTP), and to identify patients obtaining therapeutic benefit from IT, we examined aMRI findings in newly diagnosed glioblastoma treated with dendritic cell IT added to standard treatment. We analyzed longitudinal MRIs obtained in 22 patients enrolled in the EUDRACT N° 2008-005035-15 trial. According to RANO criteria, we observed 18 TTP and 8 PsP. Comparing MRI performed at the time of TTP/PsP with the previous exam performed two months before, a difference in cerebral blood volume ΔrCBVmax ≥ 0.47 distinguished TTP from PsP with a sensitivity of 67% and specificity of 75% (p = 0.004). A decrease in minimal apparent diffusion coefficient rADCmin (1.15 vs. 1.01, p = 0.003) was observed after four vaccinations only in patients with a persistent increase of natural killer cells (response effectors during IT) in peripheral blood. Basal rADCmin > 1 was independent predictor of longer progression free (16.1 vs. 9 months, p = 0.0001) and overall survival (32.8 vs. 17.5 months, p = 0.0005). In conclusion, rADC predicted response to immunotherapy and survival; Apparent Diffusion Coefficient (ADC) and Cerebral Blood Volume (CBV) modifications over time help differentiating PsP from TTP at onset.
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Affiliation(s)
- Valeria Cuccarini
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (V.C.); (D.A.); (A.G.); (F.M.)
| | - Domenico Aquino
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (V.C.); (D.A.); (A.G.); (F.M.)
| | - Andrea Gioppo
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (V.C.); (D.A.); (A.G.); (F.M.)
| | - Elena Anghileri
- Neuro-oncology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (E.A.); (S.P.); (C.S.); (G.F.); (M.E.)
| | - Serena Pellegatta
- Neuro-oncology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (E.A.); (S.P.); (C.S.); (G.F.); (M.E.)
| | - Carla Schettino
- Neuro-oncology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (E.A.); (S.P.); (C.S.); (G.F.); (M.E.)
| | - Federica Mazzi
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (V.C.); (D.A.); (A.G.); (F.M.)
| | - Gaetano Finocchiaro
- Neuro-oncology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (E.A.); (S.P.); (C.S.); (G.F.); (M.E.)
| | - Maria Grazia Bruzzone
- Neuroradiology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (V.C.); (D.A.); (A.G.); (F.M.)
- Correspondence: ; Tel.: +39-0223942775
| | - Marica Eoli
- Neuro-oncology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, 20133 Milan, Italy; (E.A.); (S.P.); (C.S.); (G.F.); (M.E.)
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30
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Sinigaglia M, Assi T, Besson FL, Ammari S, Edjlali M, Feltus W, Rozenblum-Beddok L, Zhao B, Schwartz LH, Mokrane FZ, Dercle L. Imaging-guided precision medicine in glioblastoma patients treated with immune checkpoint modulators: research trend and future directions in the field of imaging biomarkers and artificial intelligence. EJNMMI Res 2019; 9:78. [PMID: 31432278 PMCID: PMC6702257 DOI: 10.1186/s13550-019-0542-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/21/2019] [Accepted: 07/19/2019] [Indexed: 12/14/2022] Open
Abstract
Immunotherapies that employ immune checkpoint modulators (ICMs) have emerged as an effective treatment for a variety of solid cancers, as well as a paradigm shift in the treatment of cancers. Despite this breakthrough, the median survival time of glioblastoma patients has remained at about 2 years. Therefore, the safety and anti-cancer efficacy of combination therapies that include ICMs are being actively investigated. Because of the distinct mechanisms of ICMs, which restore the immune system’s anti-tumor capacity, unconventional immune-related phenomena are increasingly being reported in terms of tumor response and progression, as well as adverse events. Indeed, immunotherapy response assessments for neuro-oncology (iRANO) play a central role in guiding cancer patient management and define a “wait and see strategy” for patients treated with ICMs in monotherapy with progressive disease on MRI. This article deciphers emerging research trends to ameliorate four challenges unaddressed by the iRANO criteria: (1) patient selection, (2) identification of immune-related phenomena other than pseudoprogression (i.e., hyperprogression, the abscopal effect, immune-related adverse events), (3) response assessment in combination therapies including ICM, and (4) alternatives to MRI. To this end, our article provides a structured approach for standardized selection and reporting of imaging modalities to enable the use of precision medicine by deciphering the characteristics of the tumor and its immune environment. Emerging preclinical or clinical innovations are also discussed as future directions such as immune-specific targeting and implementation of artificial intelligence algorithms.
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Affiliation(s)
- Mathieu Sinigaglia
- Department of Imaging Nuclear Medicine, Institut Claudius Regaud-Institut Universitaire du Cancer de Toulouse-Oncopole, Toulouse, France
| | - Tarek Assi
- Département de médecine oncologique, Gustave Roussy, Université Paris-Saclay, 94805, Villejuif, France
| | - Florent L Besson
- Department of Biophysics and Nuclear Medicine, Bicêtre University Hospital, Assistance Publique-Hôpitaux de Paris, 78 rue du Général Leclerc, 94275, Le Kremlin-Bicêtre, France.,IR4M-UMR 8081, CNRS, Université Paris Sud, Université Paris Saclay, Orsay, France
| | - Samy Ammari
- Département d'imagerie médicale, Gustave Roussy, Université Paris-Saclay, 94805, Villejuif, France
| | - Myriam Edjlali
- INSERM U894, Service d'imagerie morphologique et fonctionnelle, Hôpital Sainte-Anne, Université Paris Descartes, 1, rue Cabanis, 75014, Paris, France
| | - Whitney Feltus
- Department of Radiology, New York Presbyterian Hospital-Columbia University Medical Center, New York, NY, 10039, USA
| | - Laura Rozenblum-Beddok
- Service de Médecine Nucléaire, AP-HP, Hôpital La Pitié-Salpêtrière, Sorbonne Université, 75013, Paris, France
| | - Binsheng Zhao
- Department of Radiology, New York Presbyterian Hospital-Columbia University Medical Center, New York, NY, 10039, USA
| | - Lawrence H Schwartz
- Department of Radiology, New York Presbyterian Hospital-Columbia University Medical Center, New York, NY, 10039, USA
| | - Fatima-Zohra Mokrane
- Department of Radiology, New York Presbyterian Hospital-Columbia University Medical Center, New York, NY, 10039, USA.,Département d'imagerie médicale, CHU Rangueil, Université Toulouse Paul Sabatier, Toulouse, France
| | - Laurent Dercle
- Department of Radiology, New York Presbyterian Hospital-Columbia University Medical Center, New York, NY, 10039, USA. .,UMR1015, Institut Gustave Roussy, Université Paris Saclay, 94800, Villejuif, France.
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31
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Strauss SB, Meng A, Ebani EJ, Chiang GC. Imaging Glioblastoma Posttreatment: Progression, Pseudoprogression, Pseudoresponse, Radiation Necrosis. Radiol Clin North Am 2019; 57:1199-1216. [PMID: 31582045 DOI: 10.1016/j.rcl.2019.07.003] [Citation(s) in RCA: 45] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Radiographic monitoring of posttreatment glioblastoma is important for clinical trials and determining next steps in management. Evaluation for tumor progression is confounded by the presence of treatment-related radiographic changes, making a definitive determination less straight-forward. The purpose of this article was to describe imaging tools available for assessing treatment response in glioblastoma, as well as to highlight the definitions, pathophysiology, and imaging features typical of true progression, pseudoprogression, pseudoresponse, and radiation necrosis.
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Affiliation(s)
- Sara B Strauss
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Alicia Meng
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Edward J Ebani
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA
| | - Gloria C Chiang
- Department of Radiology, Weill Cornell Medical Center, 525 East 68th Street, Box 141, New York, NY 10065, USA.
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32
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Kasten BB, Udayakumar N, Leavenworth JW, Wu AM, Lapi SE, McConathy JE, Sorace AG, Bag AK, Markert JM, Warram JM. Current and Future Imaging Methods for Evaluating Response to Immunotherapy in Neuro-Oncology. Theranostics 2019; 9:5085-5104. [PMID: 31410203 PMCID: PMC6691392 DOI: 10.7150/thno.34415] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2019] [Accepted: 04/20/2019] [Indexed: 12/28/2022] Open
Abstract
Imaging plays a central role in evaluating responses to therapy in neuro-oncology patients. The advancing clinical use of immunotherapies has demonstrated that treatment-related inflammatory responses mimic tumor growth via conventional imaging, thus spurring the development of new imaging approaches to adequately distinguish between pseudoprogression and progressive disease. To this end, an increasing number of advanced imaging techniques are being evaluated in preclinical and clinical studies. These novel molecular imaging approaches will serve to complement conventional response assessments during immunotherapy. The goal of these techniques is to provide definitive metrics of tumor response at earlier time points to inform treatment decisions, which has the potential to improve patient outcomes. This review summarizes the available immunotherapy regimens, clinical response criteria, current state-of-the-art imaging approaches, and groundbreaking strategies for future implementation to evaluate the anti-tumor and immune responses to immunotherapy in neuro-oncology applications.
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Affiliation(s)
- Benjamin B. Kasten
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Neha Udayakumar
- School of Medicine, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Jianmei W. Leavenworth
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Anna M. Wu
- Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, United States
| | - Suzanne E. Lapi
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Jonathan E. McConathy
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Anna G. Sorace
- Department of Radiology, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Asim K. Bag
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - James M. Markert
- Department of Neurosurgery, University of Alabama at Birmingham, Birmingham, AL, United States
| | - Jason M. Warram
- Department of Otolaryngology, University of Alabama at Birmingham, Birmingham, AL, United States
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33
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Chuntova P, Downey KM, Hegde B, Almeida ND, Okada H. Genetically Engineered T-Cells for Malignant Glioma: Overcoming the Barriers to Effective Immunotherapy. Front Immunol 2019; 9:3062. [PMID: 30740109 PMCID: PMC6357938 DOI: 10.3389/fimmu.2018.03062] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 12/11/2018] [Indexed: 12/12/2022] Open
Abstract
Malignant gliomas carry a dismal prognosis. Conventional treatment using chemo- and radiotherapy has limited efficacy with adverse events. Therapy with genetically engineered T-cells, such as chimeric antigen receptor (CAR) T-cells, may represent a promising approach to improve patient outcomes owing to their potential ability to attack highly infiltrative tumors in a tumor-specific manner and possible persistence of the adaptive immune response. However, the unique anatomical features of the brain and susceptibility of this organ to irreversible tissue damage have made immunotherapy especially challenging in the setting of glioma. With safety concerns in mind, multiple teams have initiated clinical trials using CAR T-cells in glioma patients. The valuable lessons learnt from those trials highlight critical areas for further improvement: tackling the issues of the antigen presentation and T-cell homing in the brain, immunosuppression in the glioma microenvironment, antigen heterogeneity and off-tumor toxicity, and the adaptation of existing clinical therapies to reflect the intricacies of immune response in the brain. This review summarizes the up-to-date clinical outcomes of CAR T-cell clinical trials in glioma patients and examines the most pressing hurdles limiting the efficacy of these therapies. Furthermore, this review uses these hurdles as a framework upon which to evaluate cutting-edge pre-clinical strategies aiming to overcome those barriers.
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Affiliation(s)
- Pavlina Chuntova
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Kira M Downey
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Bindu Hegde
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States
| | - Neil D Almeida
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.,George Washington University School of Medicine and Health Sciences, Washington, DC, United States
| | - Hideho Okada
- Department of Neurological Surgery, University of California, San Francisco, San Francisco, CA, United States.,The Parker Institute for Cancer Immunotherapy, University of California, San Francisco, San Francisco, CA, United States.,Cancer Immunotherapy Program, University of California, San Francisco, San Francisco, CA, United States
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34
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Tamrazi B, Mankad K, Nelson M, D'Arco F. Current concepts and challenges in the radiologic assessment of brain tumors in children: part 2. Pediatr Radiol 2018; 48:1844-1860. [PMID: 30215111 DOI: 10.1007/s00247-018-4232-7] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2018] [Revised: 07/06/2018] [Accepted: 08/08/2018] [Indexed: 12/16/2022]
Abstract
Assessing tumor response is a large part of everyday clinical work in neuroradiology. However in the setting of tumor treatment, distinguishing tumor progression from treatment-related changes is difficult on conventional MRI sequences. This is made even more challenging in children where mainstay advanced imaging techniques that are often used to decipher progression versus treatment-related changes have technical limitations. In this review, we highlight the challenges in pediatric neuro-oncologic tumor assessment with discussion of pseudophenomenon including pseudoresponse and pseudoprogression. Additionally, we discuss the advanced imaging techniques often employed in neuroradiology to distinguish between pseudophenomenon and true progressive disease.
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Affiliation(s)
- Benita Tamrazi
- Department of Radiology, Children's Hospital Los Angeles, 4650 Sunset Blvd., MS #81, Los Angeles, CA, 90027, USA.
| | - Kshitij Mankad
- Department of Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Marvin Nelson
- Department of Radiology, Children's Hospital Los Angeles, 4650 Sunset Blvd., MS #81, Los Angeles, CA, 90027, USA
| | - Felice D'Arco
- Department of Radiology, Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
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35
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Ly KI, Gerstner ER. The Role of Advanced Brain Tumor Imaging in the Care of Patients with Central Nervous System Malignancies. Curr Treat Options Oncol 2018; 19:40. [PMID: 29931476 DOI: 10.1007/s11864-018-0558-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OPINION STATEMENT T1-weighted post-contrast and T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) constitute the gold standard for diagnosis and response assessment in neuro-oncologic patients but are limited in their ability to accurately reflect tumor biology and metabolism, particularly over the course of a patient's treatment. Advanced MR imaging methods are sensitized to different biophysical processes in tissue, including blood perfusion, tumor metabolism, and chemical composition of tissue, and provide more specific information on tissue physiology than standard MRI. This review provides an overview of the most common and emerging advanced imaging modalities in the field of brain tumor imaging and their applications in the care of neuro-oncologic patients.
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Affiliation(s)
- K Ina Ly
- Stephen E. and Catherine Pappas Center for Neuro-Oncology, Massachusetts General Hospital, 55 Fruit Street, Yawkey 9E, Boston, MA, 02114, USA
| | - Elizabeth R Gerstner
- Stephen E. and Catherine Pappas Center for Neuro-Oncology, Massachusetts General Hospital, 55 Fruit Street, Yawkey 9E, Boston, MA, 02114, USA.
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36
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Ranjan S, Quezado M, Garren N, Boris L, Siegel C, Lopes Abath Neto O, Theeler BJ, Park DM, Nduom E, Zaghloul KA, Gilbert MR, Wu J. Clinical decision making in the era of immunotherapy for high grade-glioma: report of four cases. BMC Cancer 2018; 18:239. [PMID: 29490632 PMCID: PMC5831705 DOI: 10.1186/s12885-018-4131-1] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2017] [Accepted: 02/14/2018] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND Immune checkpoint inhibitors (ICPIs) are being investigated in clinical trials for patients with glioblastoma. While these therapies hold great promise, management of the patients receiving such treatment can be complicated due to the challenges in recognizing immune-related adverse events caused by checkpoint inhibitor treatment. Brain imaging changes that are the consequence of an inflammatory response may be misinterpreted as disease progression leading to inappropriate premature cessation of treatment. The aim of this study was to, by way of a series of cases, underscore the challenges in determining the nature of contrast-enhancing masses that develop during the treatment of patients with glioblastoma treated with ICPIs. CASE PRESENTATION We reviewed the clinical course and management of 4 patients on ICPIs who developed signs of tumor progression on imaging. These findings were examined in the context of Immunotherapy Response Assessment in Neuro-Oncology (iRANO) guidelines. Although all 4 patients had very similar imaging findings, 2 of the 4 patients were later found to have intense inflammatory changes (pseudoprogression) by pathologic examination. CONCLUSIONS A high index of suspicion for pseudoprogression needs to be maintained when a patient with brain tumor on immunotherapy presents with worsening in an area of a pre-existing tumor or a new lesion in brain. Our findings strongly suggest that pathological diagnosis remains the gold standard for distinguishing tumor progression from pseudoprogression in patients receiving immunotherapy. There is a large unmet need to develop reliable non-invasive imaging diagnostic techniques. TRIAL REGISTRATION ClinicalTrials.gov NCT02311920. Registered 8 December 2014.
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Affiliation(s)
- Surabhi Ranjan
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20892 USA
| | - Martha Quezado
- Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892 USA
| | - Nancy Garren
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20892 USA
| | - Lisa Boris
- Clinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research, Inc., NCI Campus at Frederick, Frederick, MD 21702 USA
| | - Christine Siegel
- Clinical Research Directorate/Clinical Monitoring Research Program, Leidos Biomedical Research, Inc., NCI Campus at Frederick, Frederick, MD 21702 USA
| | - Osorio Lopes Abath Neto
- Laboratory of Pathology, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892 USA
| | - Brett J. Theeler
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20892 USA
- Department of Neurology and John P. Murtha Cancer Center, Walter Reed National Military Medical Center, Bethesda, MD 20889 USA
| | - Deric M. Park
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20892 USA
| | - Edjah Nduom
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892 USA
| | - Kareem A. Zaghloul
- Surgical Neurology Branch, National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20892 USA
| | - Mark R. Gilbert
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20892 USA
| | - Jing Wu
- Neuro-Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institute of Health, Bethesda, MD 20892 USA
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37
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Skolnik AD, Wang S, Gopal PP, Mohan S. Commentary: Pitfalls in the Neuroimaging of Glioblastoma in the Era of Antiangiogenic and Immuno/Targeted Therapy. Front Neurol 2018; 9:51. [PMID: 29459848 PMCID: PMC5807681 DOI: 10.3389/fneur.2018.00051] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2017] [Accepted: 01/18/2018] [Indexed: 12/22/2022] Open
Affiliation(s)
- Aaron D Skolnik
- Radiology, Penn Medicine Princeton Health, Plainsboro, NJ, United States
| | - Sumei Wang
- Neuroradiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States
| | - Pallavi P Gopal
- Pathology, Yale School of Medicine, New Haven, CT, United States
| | - Suyash Mohan
- Neuroradiology, Hospital of the University of Pennsylvania, Philadelphia, PA, United States
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38
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Margiewicz S, Cordova C, Chi AS, Jain R. State of the Art Treatment and Surveillance Imaging of Glioblastomas. Semin Roentgenol 2017; 53:23-36. [PMID: 29405952 DOI: 10.1053/j.ro.2017.11.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Affiliation(s)
| | - Christine Cordova
- Laura and Isaac Perlmutter Cancer Center, NYU School of Medicine, New York, NY
| | - Andrew S Chi
- Laura and Isaac Perlmutter Cancer Center, NYU School of Medicine, New York, NY
| | - Rajan Jain
- Department of Radiology, NYU School of Medicine, New York, NY; Department of Neurosurgery, NYU School of Medicine, New York, NY.
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MRI in Glioma Immunotherapy: Evidence, Pitfalls, and Perspectives. J Immunol Res 2017; 2017:5813951. [PMID: 28512646 PMCID: PMC5415864 DOI: 10.1155/2017/5813951] [Citation(s) in RCA: 47] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 02/06/2017] [Accepted: 03/02/2017] [Indexed: 01/14/2023] Open
Abstract
Pseudophenomena, that is, imaging alterations due to therapy rather than tumor evolution, have an important impact on the management of glioma patients and the results of clinical trials. RANO (response assessment in neurooncology) criteria, including conventional MRI (cMRI), addressed the issues of pseudoprogression after radiotherapy and concomitant chemotherapy and pseudoresponse during antiangiogenic therapy of glioblastomas (GBM) and other gliomas. The development of cancer immunotherapy forced the identification of further relevant response criteria, summarized by the iRANO working group in 2015. In spite of this, the unequivocal definition of glioma progression by cMRI remains difficult particularly in the setting of immunotherapy approaches provided by checkpoint inhibitors and dendritic cells. Advanced MRI (aMRI) may in principle address this unmet clinical need. Here, we discuss the potential contribution of different aMRI techniques and their indications and pitfalls in relation to biological and imaging features of glioma and immune system interactions.
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Lucas JT, Knapp BJ, Uh J, Hua CH, Merchant TE, Hwang SN, Patay Z, Broniscer A. Posttreatment DSC-MRI is Predictive of Early Treatment Failure in Children with Supratentorial High-Grade Glioma Treated with Erlotinib. Clin Neuroradiol 2017; 28:393-400. [PMID: 28382379 DOI: 10.1007/s00062-017-0580-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Accepted: 03/15/2017] [Indexed: 02/01/2023]
Abstract
BACKGROUND AND PURPOSE The role of perfusion imaging in the management of pediatric high grade glioma is unclear. We evaluated the ability of dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) to determine grade, evaluate post-treatment response and predict treatment failure. MATERIAL AND METHODS In this study 22 patients with high-grade glioma underwent biopsy and were treated with concurrent and sequential radiotherapy and erlotinib as part of a phase I/II clinical trial (NCT00124657). Preradiotherapy, immediate postradiotherapy, 6‑month and treatment failure DSC MR images were reviewed, registered, and processed for the ratio of cerebral blood flow (CBF) and cerebral blood volume (CBV). Processed, derived perfusion, and T1-weighted images (T1WI), T2WI, and fluid attenuation inversion recovery (FLAIR) MRI sequences were used for segmentation and extraction of tumor perfusion parameters at all time points. Patient, tumor, treatment, and outcome data were summarized and related to perfusion data. RESULTS Regional CBF in tumors increased from diagnosis to postradiotherapy, while they decreased to levels below those at diagnosis from postradiotherapy to 6‑month follow-up. At 6 months, the median regional CBF was higher in tumors that progressed (median 1.16) than in those that did not (median, 0.95; P < 0.05). Patients with regional CBF ratios above 1.4 at diagnosis had shorter survival times than did those with regional CBF ratios below 1.4 (P = 0.77). Tumors with a regional CBV above 1.15 at the postradiotherapy (1-3 months) follow-up scan were associated with an earlier time to death than that of tumors with a regional CBV below 1.15 (P < 0.05). CONCLUSION Posttreatment perfusion characteristics are prognostic and may help predict survival. Overall, perfusion MRI is useful for managing pediatric high-grade glioma and should be incorporated into future clinical trials.
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Affiliation(s)
- John T Lucas
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, MS 210, 38105-3678, Memphis, TN, USA.
| | - Brendan J Knapp
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jinsoo Uh
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, MS 210, 38105-3678, Memphis, TN, USA
| | - Chia-Ho Hua
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, MS 210, 38105-3678, Memphis, TN, USA
| | - Thomas E Merchant
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, MS 210, 38105-3678, Memphis, TN, USA
| | - Scott N Hwang
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Zoltan Patay
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Alberto Broniscer
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA.,Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, USA
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Pseudoprogression, radionecrosis, inflammation or true tumor progression? challenges associated with glioblastoma response assessment in an evolving therapeutic landscape. J Neurooncol 2017; 134:495-504. [PMID: 28382534 DOI: 10.1007/s11060-017-2375-2] [Citation(s) in RCA: 139] [Impact Index Per Article: 19.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2016] [Accepted: 01/13/2017] [Indexed: 01/24/2023]
Abstract
The wide variety of treatment options that exist for glioblastoma, including surgery, ionizing radiation, anti-neoplastic chemotherapies, anti-angiogenic therapies, and active or passive immunotherapies, all may alter aspects of vascular permeability within the tumor and/or normal parenchyma. These alterations manifest as changes in the degree of contrast enhancement or T2-weighted signal hyperintensity on standard anatomic MRI scans, posing a potential challenge for accurate radiographic response assessment for identifying anti-tumor effects. The current review highlights the challenges that remain in differentiating true disease progression from changes due to radiation therapy, including pseudoprogression and radionecrosis, as well as immune or inflammatory changes that may occur as either an undesired result of cytotoxic therapy or as a desired consequence of immunotherapies.
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Galbán CJ, Hoff BA, Chenevert TL, Ross BD. Diffusion MRI in early cancer therapeutic response assessment. NMR IN BIOMEDICINE 2017; 30:10.1002/nbm.3458. [PMID: 26773848 PMCID: PMC4947029 DOI: 10.1002/nbm.3458] [Citation(s) in RCA: 59] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2015] [Revised: 11/09/2015] [Accepted: 11/12/2015] [Indexed: 05/05/2023]
Abstract
Imaging biomarkers for the predictive assessment of treatment response in patients with cancer earlier than standard tumor volumetric metrics would provide new opportunities to individualize therapy. Diffusion-weighted MRI (DW-MRI), highly sensitive to microenvironmental alterations at the cellular level, has been evaluated extensively as a technique for the generation of quantitative and early imaging biomarkers of therapeutic response and clinical outcome. First demonstrated in a rodent tumor model, subsequent studies have shown that DW-MRI can be applied to many different solid tumors for the detection of changes in cellularity as measured indirectly by an increase in the apparent diffusion coefficient (ADC) of water molecules within the lesion. The introduction of quantitative DW-MRI into the treatment management of patients with cancer may aid physicians to individualize therapy, thereby minimizing unnecessary systemic toxicity associated with ineffective therapies, saving valuable time, reducing patient care costs and ultimately improving clinical outcome. This review covers the theoretical basis behind the application of DW-MRI to monitor therapeutic response in cancer, the analytical techniques used and the results obtained from various clinical studies that have demonstrated the efficacy of DW-MRI for the prediction of cancer treatment response. Copyright © 2016 John Wiley & Sons, Ltd.
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Affiliation(s)
| | | | | | - B. D. Ross
- Correspondence to: B. D. Ross, University of Michigan School of Medicine, Center for Molecular Imaging and Department of Radiology, Biomedical Sciences Research Building, 109 Zina Pitcher Place, Ann Arbor, MI 48109, USA.
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Li A, Wu Y, Tang F, Li W, Feng X, Yao Z. In Vivo Magnetic Resonance Imaging of CD8+ T Lymphocytes Recruiting to Glioblastoma in Mice. Cancer Biother Radiopharm 2017; 31:317-323. [PMID: 27831762 DOI: 10.1089/cbr.2016.2061] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Noninvasive in vivo tracking of adopted immune cells would help improve immunotherapy on glioblastoma. In this study, the authors tried to track adoptive CD8+ T lymphocytes in an in situ GL261 glioblastoma mouse model with magnetic resonance imaging (MRI). CD8+ T lymphocytes from spleen of preimmunized GL261 glioblastoma mice were labeled with superparamagnetic iron oxide, with polylysine as transfection agent. From Prussian blue staining, the labeling efficiency was 0.77% ± 0.06%, without altering cell viability and function. From anti-CD8, and anti-dextran staining, superparamagnetic iron oxide could be seen in the cytoplasm. In vitro imaging of agar gel mixtures with different concentrations of labeled CD8+ T lymphocytes was done with a 3.0T MR T2*WI sequence. Higher cell concentrations showed lower signal values. Twenty-four hours after tail vein injection of labeled and unlabeled CD8+ T lymphocytes, imaging of GL261 mice brain showed black spots at the periphery of the tumor in the labeled group only. Brain tumor pathology further verified infiltration of labeled CD8+ T lymphocytes in the tumor. Thus, preimmunized CD8+ T lymphocytes could be efficiently labeled with superparamagnetic iron oxide and tracked both in vitro and in vivo with 3.0T MRI.
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Affiliation(s)
- Anning Li
- 1 Department of Radiology, Qilu Hospital of Shandong University , Jinan, People's Republic of China
| | - Yue Wu
- 2 Department of Radiology, Fudan University , Shanghai, People's Republic of China
| | - Feng Tang
- 3 Department of Radiology, Pathology, Huashan Hospital, Fudan University , Shanghai, People's Republic of China
| | - Wei Li
- 3 Department of Radiology, Pathology, Huashan Hospital, Fudan University , Shanghai, People's Republic of China
| | - Xiaoyuan Feng
- 2 Department of Radiology, Fudan University , Shanghai, People's Republic of China
| | - Zhenwei Yao
- 2 Department of Radiology, Fudan University , Shanghai, People's Republic of China
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Ion-Mărgineanu A, Van Cauter S, Sima DM, Maes F, Sunaert S, Himmelreich U, Van Huffel S. Classifying Glioblastoma Multiforme Follow-Up Progressive vs. Responsive Forms Using Multi-Parametric MRI Features. Front Neurosci 2017; 10:615. [PMID: 28123355 PMCID: PMC5225114 DOI: 10.3389/fnins.2016.00615] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2016] [Accepted: 12/26/2016] [Indexed: 11/30/2022] Open
Abstract
Purpose: The purpose of this paper is discriminating between tumor progression and response to treatment based on follow-up multi-parametric magnetic resonance imaging (MRI) data retrieved from glioblastoma multiforme (GBM) patients. Materials and Methods: Multi-parametric MRI data consisting of conventional MRI (cMRI) and advanced MRI [i.e., perfusion weighted MRI (PWI) and diffusion kurtosis MRI (DKI)] were acquired from 29 GBM patients treated with adjuvant therapy after surgery. We propose an automatic pipeline for processing advanced MRI data and extracting intensity-based histogram features and 3-D texture features using manually and semi-manually delineated regions of interest (ROIs). Classifiers are trained using a leave-one-patient-out cross validation scheme on complete MRI data. Balanced accuracy rate (BAR)–values are computed and compared between different ROIs, MR modalities, and classifiers, using non-parametric multiple comparison tests. Results: Maximum BAR–values using manual delineations are 0.956, 0.85, 0.879, and 0.932, for cMRI, PWI, DKI, and all three MRI modalities combined, respectively. Maximum BAR–values using semi-manual delineations are 0.932, 0.894, 0.885, and 0.947, for cMRI, PWI, DKI, and all three MR modalities combined, respectively. After statistical testing using Kruskal-Wallis and post-hoc Dunn-Šidák analysis we conclude that training a RUSBoost classifier on features extracted using semi-manual delineations on cMRI or on all MRI modalities combined performs best. Conclusions: We present two main conclusions: (1) using T1 post-contrast (T1pc) features extracted from manual total delineations, AdaBoost achieves the highest BAR–value, 0.956; (2) using T1pc-average, T1pc-90th percentile, and Cerebral Blood Volume (CBV) 90th percentile extracted from semi-manually delineated contrast enhancing ROIs, SVM-rbf, and RUSBoost achieve BAR–values of 0.947 and 0.932, respectively. Our findings show that AdaBoost, SVM-rbf, and RUSBoost trained on T1pc and CBV features can differentiate progressive from responsive GBM patients with very high accuracy.
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Affiliation(s)
- Adrian Ion-Mărgineanu
- Department of Electrical Engineering (ESAT), Signal Processing and Data Analytics, STADIUS Center for Dynamical Systems, KU LeuvenLeuven, Belgium; imecLeuven, Belgium
| | - Sofie Van Cauter
- Department of Radiology, University Hospitals of Leuven Leuven, Belgium
| | - Diana M Sima
- Department of Electrical Engineering (ESAT), Signal Processing and Data Analytics, STADIUS Center for Dynamical Systems, KU LeuvenLeuven, Belgium; imecLeuven, Belgium
| | - Frederik Maes
- Department of Electrical Engineering (ESAT), PSI Center for Processing Speech and Images, KU Leuven Leuven, Belgium
| | - Stefan Sunaert
- Department of Radiology, University Hospitals of Leuven Leuven, Belgium
| | - Uwe Himmelreich
- Department of Imaging and Pathology, Biomedical MRI/MoSAIC, KU Leuven Leuven, Belgium
| | - Sabine Van Huffel
- Department of Electrical Engineering (ESAT), Signal Processing and Data Analytics, STADIUS Center for Dynamical Systems, KU LeuvenLeuven, Belgium; imecLeuven, Belgium
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Advanced MRI assessment to predict benefit of anti-programmed cell death 1 protein immunotherapy response in patients with recurrent glioblastoma. Neuroradiology 2017; 59:135-145. [PMID: 28070598 DOI: 10.1007/s00234-016-1769-8] [Citation(s) in RCA: 52] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Accepted: 11/18/2016] [Indexed: 12/22/2022]
Abstract
INTRODUCTION We describe the imaging findings encountered in GBM patients receiving immune checkpoint blockade and assess the potential of quantitative MRI biomarkers to differentiate patients who derive therapeutic benefit from those who do not. METHODS A retrospective analysis was performed on longitudinal MRIs obtained on recurrent GBM patients enrolled on clinical trials. Among 10 patients with analyzable data, bidirectional diameters were measured on contrast enhanced T1 (pGd-T1WI) and volumes of interest (VOI) representing measurable abnormality suggestive of tumor were selected on pGdT1WI (pGdT1 VOI), FLAIR-T2WI (FLAIR VOI), and ADC maps. Intermediate ADC (IADC) VOI represented voxels within the FLAIR VOI having ADC in the range of highly cellular tumor (0.7-1.1 × 10-3 mm2/s) (IADC VOI). Therapeutic benefit was determined by tissue pathology and survival on trial. IADC VOI, pGdT1 VOI, FLAIR VOI, and RANO assessment results were correlated with patient benefit. RESULTS Five patients were deemed to have received therapeutic benefit and the other five patients did not. The average time on trial for the benefit group was 194 days, as compared to 81 days for the no benefit group. IADC VOI correlated well with the presence or absence of clinical benefit in 10 patients. Furthermore, pGd VOI, FLAIR VOI, and RANO assessment correlated less well with response. CONCLUSION MRI reveals an initial increase in volumes of abnormal tissue with contrast enhancement, edema, and intermediate ADC suggesting hypercellularity within the first 0-6 months of immunotherapy. Subsequent stabilization and improvement in IADC VOI appear to better predict ultimate therapeutic benefit from these agents than conventional imaging.
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Dynamic Susceptibility Contrast MR Imaging in Glioma: Review of Current Clinical Practice. Magn Reson Imaging Clin N Am 2016; 24:649-670. [PMID: 27742108 DOI: 10.1016/j.mric.2016.06.005] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Dynamic susceptibility contrast (DSC) MR imaging, a perfusion-weighted MR imaging technique typically used in neuro-oncologic applications for estimating the relative cerebral blood volume within brain tumors, has demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response of gliomas. This review highlights recent developments using DSC-MR imaging and emphasizes the need for technical standardization and validation in prospective studies in order for this technique to become incorporated into standard-of-care imaging for patients with brain tumors.
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Antigen-specific immunoreactivity and clinical outcome following vaccination with glioma-associated antigen peptides in children with recurrent high-grade gliomas: results of a pilot study. J Neurooncol 2016; 130:517-527. [PMID: 27624914 DOI: 10.1007/s11060-016-2245-3] [Citation(s) in RCA: 46] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2016] [Accepted: 08/21/2016] [Indexed: 12/29/2022]
Abstract
Recurrent high-grade gliomas (HGGs) of childhood have an exceedingly poor prognosis with current therapies. Accordingly, new treatment approaches are needed. We initiated a pilot trial of vaccinations with peptide epitopes derived from glioma-associated antigens (GAAs) overexpressed in these tumors in HLA-A2+ children with recurrent HGG that had progressed after prior treatments. Peptide epitopes for three GAAs (EphA2, IL13Rα2, survivin), emulsified in Montanide-ISA-51, were administered subcutaneously adjacent to intramuscular injections of poly-ICLC every 3 weeks for 8 courses, followed by booster vaccines every 6 weeks. Primary endpoints were safety and T-cell responses against the GAA epitopes, assessed by enzyme-linked immunosorbent spot (ELISPOT) analysis. Treatment response was evaluated clinically and by magnetic resonance imaging. Twelve children were enrolled, 6 with glioblastoma, 5 with anaplastic astrocytoma, and one with malignant gliomatosis cerebri. No dose-limiting non-CNS toxicity was encountered. ELISPOT analysis, in ten children, showed GAA responses in 9: to IL13Rα2 in 4, EphA2 in 9, and survivin in 3. One child had presumed symptomatic pseudoprogression, discontinued vaccine therapy, and responded to subsequent treatment. One other child had a partial response that persisted throughout 2 years of vaccine therapy, and continues at >39 months. Median progression-free survival (PFS) from the start of vaccination was 4.1 months and median overall survival (OS) was 12.9 months. 6-month PFS and OS were 33 and 73 %, respectively. GAA peptide vaccination in children with recurrent malignant gliomas is generally well tolerated, and has preliminary evidence of immunological and modest clinical activity.
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Integrative analysis of diffusion-weighted MRI and genomic data to inform treatment of glioblastoma. J Neurooncol 2016; 129:289-300. [PMID: 27393347 DOI: 10.1007/s11060-016-2174-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2015] [Accepted: 06/04/2016] [Indexed: 12/15/2022]
Abstract
Gene expression profiling from glioblastoma (GBM) patients enables characterization of cancer into subtypes that can be predictive of response to therapy. An integrative analysis of imaging and gene expression data can potentially be used to obtain novel biomarkers that are closely associated with the genetic subtype and gene signatures and thus provide a noninvasive approach to stratify GBM patients. In this retrospective study, we analyzed the expression of 12,042 genes for 558 patients from The Cancer Genome Atlas (TCGA). Among these patients, 50 patients had magnetic resonance imaging (MRI) studies including diffusion weighted (DW) MRI in The Cancer Imaging Archive (TCIA). We identified the contrast enhancing region of the tumors using the pre- and post-contrast T1-weighted MRI images and computed the apparent diffusion coefficient (ADC) histograms from the DW-MRI images. Using the gene expression data, we classified patients into four molecular subtypes, determined the number and composition of genes modules using the gap statistic, and computed gene signature scores. We used logistic regression to find significant predictors of GBM subtypes. We compared the predictors for different subtypes using Mann-Whitney U tests. We assessed detection power using area under the receiver operating characteristic (ROC) analysis. We computed Spearman correlations to determine the associations between ADC and each of the gene signatures. We performed gene enrichment analysis using Ingenuity Pathway Analysis (IPA). We adjusted all p values using the Benjamini and Hochberg method. The mean ADC was a significant predictor for the neural subtype. Neural tumors had a significantly lower mean ADC compared to non-neural tumors ([Formula: see text]), with mean ADC of [Formula: see text] and [Formula: see text] for neural and non-neural tumors, respectively. Mean ADC showed an area under the ROC of 0.75 for detecting neural tumors. We found eight gene modules in the GBM cohort. The mean ADC was significantly correlated with the gene signature related with dendritic cell maturation ([Formula: see text], [Formula: see text]). Mean ADC could be used as a biomarker of a gene signature associated with dendritic cell maturation and to assist in identifying patients with neural GBMs, known to be resistant to aggressive standard of care.
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Copen WA, Lev MH, Rapalino O. Brain perfusion: computed tomography and magnetic resonance techniques. HANDBOOK OF CLINICAL NEUROLOGY 2016; 135:117-135. [PMID: 27432662 DOI: 10.1016/b978-0-444-53485-9.00006-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Cerebral perfusion imaging provides assessment of regional microvascular hemodynamics in the living brain, enabling in vivo measurement of a variety of different hemodynamic parameters. Perfusion imaging techniques that are used in the clinical setting usually rely upon X-ray computed tomography (CT) or magnetic resonance imaging (MRI). This chapter reviews CT- and MRI-based perfusion imaging techniques, with attention to image acquisition, clinically relevant aspects of image postprocessing, and fundamental differences between CT- and MRI-based techniques. Correlations with cerebrovascular physiology and potential clinical applications of perfusion imaging are reviewed, focusing upon the two major classes of neurologic disease in which perfusion imaging is most often performed: primary perfusion disorders (including ischemic stroke, transient ischemic attack, and reperfusion syndrome), and brain tumors.
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Affiliation(s)
- William A Copen
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| | - Michael H Lev
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Otto Rapalino
- Division of Neuroradiology, Department of Radiology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
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Shiroishi MS, Boxerman JL, Pope WB. Physiologic MRI for assessment of response to therapy and prognosis in glioblastoma. Neuro Oncol 2015; 18:467-78. [PMID: 26364321 DOI: 10.1093/neuonc/nov179] [Citation(s) in RCA: 57] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2015] [Accepted: 08/01/2015] [Indexed: 02/06/2023] Open
Abstract
Aside from bidimensional measurements from conventional contrast-enhanced MRI, there are no validated or FDA-qualified imaging biomarkers for high-grade gliomas. However, advanced functional MRI techniques, including perfusion- and diffusion-weighted MRI, have demonstrated much potential for determining prognosis, predicting therapeutic response, and assessing early treatment response. They may also prove useful for differentiating pseudoprogression from true progression after temozolomide chemoradiation and pseudoresponse from true response after anti-angiogenic therapy. This review will highlight recent developments using these techniques and emphasize the need for technical standardization and validation in prospective studies in order for these methods to become incorporated into standard-of-care imaging for brain tumor patients.
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Affiliation(s)
- Mark S Shiroishi
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California (M.S.S.); Department of Diagnostic Imaging, Rhode Island Hospital and Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.); Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California (W.B.P.)
| | - Jerrold L Boxerman
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California (M.S.S.); Department of Diagnostic Imaging, Rhode Island Hospital and Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.); Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California (W.B.P.)
| | - Whitney B Pope
- Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California (M.S.S.); Department of Diagnostic Imaging, Rhode Island Hospital and Alpert Medical School of Brown University, Providence, Rhode Island (J.L.B.); Department of Radiological Sciences, David Geffen School of Medicine at UCLA, Los Angeles, California (W.B.P.)
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