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Li K, Zhu Q, Yang J, Zheng Y, Du S, Song M, Peng Q, Yang R, Liu Y, Qi L. Imaging and Liquid Biopsy for Distinguishing True Progression From Pseudoprogression in Gliomas, Current Advances and Challenges. Acad Radiol 2024:S1076-6332(24)00162-4. [PMID: 38614827 DOI: 10.1016/j.acra.2024.03.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Revised: 01/14/2024] [Accepted: 03/18/2024] [Indexed: 04/15/2024]
Abstract
RATIONALE AND OBJECTIVES Gliomas are aggressive brain tumors with a poor prognosis. Assessing treatment response is challenging because magnetic resonance imaging (MRI) may not distinguish true progression (TP) from pseudoprogression (PsP). This review aims to discuss imaging techniques and liquid biopsies used to distinguish TP from PsP. MATERIALS AND METHODS This review synthesizes existing literature to examine advances in imaging techniques, such as magnetic resonance diffusion imaging (MRDI), perfusion-weighted imaging (PWI) MRI, and liquid biopsies, for identifying TP or PsP through tumor markers and tissue characteristics. RESULTS Advanced imaging techniques, including MRDI and PWI MRI, have proven effective in delineating tumor tissue properties, offering valuable insights into glioma behavior. Similarly, liquid biopsy has emerged as a potent tool for identifying tumor-derived markers in biofluids, offering a non-invasive glimpse into tumor evolution. Despite their promise, these methodologies grapple with significant challenges. Their sensitivity remains inconsistent, complicating the accurate differentiation between TP and PSP. Furthermore, the absence of standardized protocols across platforms impedes the reliability of comparisons, while inherent biological variability adds complexity to data interpretation. CONCLUSION Their potential applications have been highlighted, but gaps remain before routine clinical use. Further research is needed to develop and validate these promising methods for distinguishing TP from PsP in gliomas.
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Affiliation(s)
- Kaishu Li
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China; Department of Neurosurgery & Medical Research Center, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), 1# Jiazi Road, Foshan, Guangdong 528300, China.; Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou 510515, China
| | - Qihui Zhu
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Junyi Yang
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Yin Zheng
- Department of Neurosurgery, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Siyuan Du
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Meihui Song
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Qian Peng
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China
| | - Runwei Yang
- Department of Neurosurgery & Medical Research Center, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), 1# Jiazi Road, Foshan, Guangdong 528300, China
| | - Yawei Liu
- Department of Neurosurgery & Medical Research Center, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), 1# Jiazi Road, Foshan, Guangdong 528300, China
| | - Ling Qi
- Institute of Digestive Disease of Guangzhou Medical University, Affiliated Qingyuan Hospital,Guangzhou Medical University,Qingyuan People's Hospital, Qingyuan 511518, China.
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Luan J, Zhang D, Liu B, Yang A, Lv K, Hu P, Yu H, Shmuel A, Zhang C, Ma G. Immune-related lncRNAs signature and radiomics signature predict the prognosis and immune microenvironment of glioblastoma multiforme. J Transl Med 2024; 22:107. [PMID: 38279111 PMCID: PMC10821572 DOI: 10.1186/s12967-023-04823-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Accepted: 12/22/2023] [Indexed: 01/28/2024] Open
Abstract
BACKGROUND Glioblastoma multiforme (GBM) is the most common primary malignant brain tumor in adults. This study aimed to construct immune-related long non-coding RNAs (lncRNAs) signature and radiomics signature to probe the prognosis and immune infiltration of GBM patients. METHODS We downloaded GBM RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) project database, and MRI data were obtained from The Cancer Imaging Archive (TCIA). Then, we conducted a cox regression analysis to establish the immune-related lncRNAs signature and radiomics signature. Afterward, we employed a gene set enrichment analysis (GSEA) to explore the biological processes and pathways. Besides, we used CIBERSORT to estimate the abundance of tumor-infiltrating immune cells (TIICs). Furthermore, we investigated the relationship between the immune-related lncRNAs signature, radiomics signature and immune checkpoint genes. Finally, we constructed a multifactors prognostic model and compared it with the clinical prognostic model. RESULTS We identified four immune-related lncRNAs and two radiomics features, which show the ability to stratify patients into high-risk and low-risk groups with significantly different survival rates. The risk score curves and Kaplan-Meier curves confirmed that the immune-related lncRNAs signature and radiomics signature were a novel independent prognostic factor in GBM patients. The GSEA suggested that the immune-related lncRNAs signature were involved in L1 cell adhesion molecular (L1CAM) interactions and the radiomics signature were involved signaling by Robo receptors. Besides, the two signatures was associated with the infiltration of immune cells. Furthermore, they were linked with the expression of critical immune genes and could predict immunotherapy's clinical response. Finally, the area under the curve (AUC) (0.890,0.887) and C-index (0.737,0.817) of the multifactors prognostic model were greater than those of the clinical prognostic model in both the training and validation sets, indicated significantly improved discrimination. CONCLUSIONS We identified the immune-related lncRNAs signature and tradiomics signature that can predict the outcomes, immune cell infiltration, and immunotherapy response in patients with GBM.
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Affiliation(s)
- Jixin Luan
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
- China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Di Zhang
- Department of Radiology, Liaocheng People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Liaocheng, Shandong, China
| | - Bing Liu
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
- China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Aocai Yang
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
- China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Kuan Lv
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
| | - Pianpian Hu
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
| | - Hongwei Yu
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China
- China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Amir Shmuel
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, QC, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Chuanchen Zhang
- Department of Radiology, Liaocheng People's Hospital, Shandong First Medical University & Shandong Academy of Medical Sciences, Liaocheng, Shandong, China.
| | - Guolin Ma
- Department of Radiology, China-Japan Friendship Hospital, Beijing, China.
- China-Japan Friendship Hospital (Institute of Clinical Medical Sciences), Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
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Zeyen T, Paech D, Weller J, Schäfer N, Tzaridis T, Duffy C, Nitsch L, Schneider M, Potthoff AL, Steinbach JP, Hau P, Schlegel U, Seidel C, Krex D, Grauer O, Goldbrunner R, Zeiner PS, Tabatabai G, Galldiks N, Stummer W, Hattingen E, Glas M, Radbruch A, Herrlinger U, Schaub C. Undetected pseudoprogressions in the CeTeG/NOA-09 trial: hints from postprogression survival and MRI analyses. J Neurooncol 2023; 164:607-616. [PMID: 37728779 PMCID: PMC10589172 DOI: 10.1007/s11060-023-04444-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2023] [Accepted: 09/02/2023] [Indexed: 09/21/2023]
Abstract
PURPOSE In the randomized CeTeG/NOA-09 trial, lomustine/temozolomide (CCNU/TMZ) was superior to TMZ therapy regarding overall survival (OS) in MGMT promotor-methylated glioblastoma. Progression-free survival (PFS) and pseudoprogression rates (about 10%) were similar in both arms. Further evaluating this discrepancy, we analyzed patterns of postprogression survival (PPS) and MRI features at first progression according to modified RANO criteria (mRANO). METHODS We classified the patients of the CeTeG/NOA-09 trial according to long vs. short PPS employing a cut-off of 18 months and compared baseline characteristics and survival times. In patients with available MRIs and confirmed progression, the increase in T1-enhancing, FLAIR hyperintense lesion volume and the change in ADC mean value of contrast-enhancing tumor upon progression were determined. RESULTS Patients with long PPS in the CCNU/TMZ arm had a particularly short PFS (5.6 months). PFS in this subgroup was shorter than in the long PPS subgroup of the TMZ arm (11.1 months, p = 0.01). At mRANO-defined progression, patients of the CCNU/TMZ long PPS subgroup had a significantly higher increase of mean ADC values (p = 0.015) and a tendency to a stronger volumetric increase in T1-enhancement (p = 0.22) as compared to long PPS patients of the TMZ arm. CONCLUSION The combination of survival and MRI analyses identified a subgroup of CCNU/TMZ-treated patients with features that sets them apart from other patients in the trial: short first PFS despite long PPS and significant increase in mean ADC values upon mRANO-defined progression. The observed pattern is compatible with the features commonly observed in pseudoprogression suggesting mRANO-undetected pseudoprogressions in the CCNU/TMZ arm of CeTeG/NOA-09.
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Affiliation(s)
- Thomas Zeyen
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Daniel Paech
- Department of Neuroradiology, University Hospital Bonn, Bonn, Germany
| | - Johannes Weller
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Niklas Schäfer
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Theophilos Tzaridis
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Cathrina Duffy
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Louisa Nitsch
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | | | | | | | - Peter Hau
- Department of Neurology and Wilhelm Sander NeuroOncology Unit, University Hospital Regensburg, Regensburg, Germany
| | - Uwe Schlegel
- Department of Neurology, Klinik Hirslanden, Zürich, Switzerland
| | - Clemens Seidel
- Department of Radiation Oncology, University of Leipzig, Leipzig, Germany
| | - Dietmar Krex
- Department of Neurosurgery, Technische Universität Dresden, Faculty of Medicine and University Hospital Carl Gustav Carus, Fetscherstrasse 74, 01307, Dresden, Germany
| | - Oliver Grauer
- Department of Neurology, University of Münster, Münster, Germany
| | - Roland Goldbrunner
- Center of Neurosurgery Department of General, Neurosurgery University of Cologne, Cologne, Germany
| | - Pia Susan Zeiner
- Dr. Senckenberg Institute of Neurooncology, University of Frankfurt, Frankfurt, Germany
| | - Ghazaleh Tabatabai
- Department of Neurology and Interdisciplinary Neuro-Oncology, Institute for Clinical Brain Research, University Hospital Tübingen, Eberhard Karls University Tübingen, HertieTübingen, Germany
- Center for Neuro-Oncology, Comprehensive Cancer Center Tübingen-Stuttgart, University Hospital Tübingen, Eberhard Karls University Tübingen, Tübingen, Germany
| | - Norbert Galldiks
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany and Research Center Juelich, Inst. of Neuroscience and Medicine (INM-3), Juelich, Germany
| | - Walter Stummer
- Department of Neurosurgery, University of Münster, Münster, Germany
| | - Elke Hattingen
- Department of Neuroradiology, University Hospital Frankfurt, 60590, Frankfurt Am Main, Germany
| | - Martin Glas
- Division of Clinical Neurooncology, Department of Neurology and Center for Translational Neuro- and Behavioral Sciences (C-TNBS), University Medicine Essen, University Duisburg-Essen, Essen, Germany
- German Cancer Consortium (DKTK), Partner Site University Medicine Essen, Hufelandstr. 55, 45147, Essen, Germany
| | | | - Ulrich Herrlinger
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany
| | - Christina Schaub
- Division of Clinical Neurooncology, Department of Neurology, University Hospital Bonn, Bonn, Germany.
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Qin D, Yang G, Jing H, Tan Y, Zhao B, Zhang H. Tumor Progression and Treatment-Related Changes: Radiological Diagnosis Challenges for the Evaluation of Post Treated Glioma. Cancers (Basel) 2022; 14:cancers14153771. [PMID: 35954435 PMCID: PMC9367286 DOI: 10.3390/cancers14153771] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Revised: 07/25/2022] [Accepted: 07/27/2022] [Indexed: 12/30/2022] Open
Abstract
Simple Summary Glioma is the most common primary malignant tumor of the adult central nervous system. Despite aggressive multimodal treatment, its prognosis remains poor. During follow-up, it remains challenging to distinguish treatment-related changes from tumor progression in treated patients with gliomas due to both share clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions). The early effective identification of tumor progression and treatment-related changes is of great significance for the prognosis and treatment of gliomas. We believe that advanced neuroimaging techniques can provide additional information for distinguishing both at an early stage. In this article, we focus on the research of magnetic resonance imaging technology and artificial intelligence in tumor progression and treatment-related changes. Finally, it provides new ideas and insights for clinical diagnosis. Abstract As the most common neuro-epithelial tumors of the central nervous system in adults, gliomas are highly malignant and easy to recurrence, with a dismal prognosis. Imaging studies are indispensable for tracking tumor progression (TP) or treatment-related changes (TRCs). During follow-up, distinguishing TRCs from TP in treated patients with gliomas remains challenging as both share similar clinical symptoms and morphological imaging characteristics (with new and/or increasing enhancing mass lesions) and fulfill criteria for progression. Thus, the early identification of TP and TRCs is of great significance for determining the prognosis and treatment. Histopathological biopsy is currently the gold standard for TP and TRC diagnosis. However, the invasive nature of this technique limits its clinical application. Advanced imaging methods (e.g., diffusion magnetic resonance imaging (MRI), perfusion MRI, magnetic resonance spectroscopy (MRS), positron emission tomography (PET), amide proton transfer (APT) and artificial intelligence (AI)) provide a non-invasive and feasible technical means for identifying of TP and TRCs at an early stage, which have recently become research hotspots. This paper reviews the current research on using the abovementioned advanced imaging methods to identify TP and TRCs of gliomas. First, the review focuses on the pathological changes of the two entities to establish a theoretical basis for imaging identification. Then, it elaborates on the application of different imaging techniques and AI in identifying the two entities. Finally, the current challenges and future prospects of these techniques and methods are discussed.
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Affiliation(s)
- Danlei Qin
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China;
- Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, Shanxi Medical University School, Hospital of Stomatology, Taiyuan 030001, China
| | - Guoqiang Yang
- Department of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, China; (G.Y.); (Y.T.)
| | - Hui Jing
- Department of MRI, The Six Hospital, Shanxi Medical University, Taiyuan 030008, China;
| | - Yan Tan
- Department of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, China; (G.Y.); (Y.T.)
| | - Bin Zhao
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China;
- Shanxi Province Key Laboratory of Oral Diseases Prevention and New Materials, Shanxi Medical University School, Hospital of Stomatology, Taiyuan 030001, China
- Correspondence: (B.Z.); (H.Z.)
| | - Hui Zhang
- College of Medical Imaging, Shanxi Medical University, Taiyuan 030001, China;
- Department of Radiology, First Clinical Medical College, Shanxi Medical University, Taiyuan 030001, China; (G.Y.); (Y.T.)
- Intelligent Imaging Big Data and Functional Nano-imaging Engineering Research Center of Shanxi Province, Taiyuan 030001, China
- Correspondence: (B.Z.); (H.Z.)
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Taylor C, Ekert JO, Sefcikova V, Fersht N, Samandouras G. Discriminators of pseudoprogression and true progression in high-grade gliomas: A systematic review and meta-analysis. Sci Rep 2022; 12:13258. [PMID: 35918373 PMCID: PMC9345984 DOI: 10.1038/s41598-022-16726-x] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Accepted: 07/14/2022] [Indexed: 11/09/2022] Open
Abstract
High-grade gliomas remain the most common primary brain tumour with limited treatments options and early recurrence rates following adjuvant treatments. However, differentiating true tumour progression (TTP) from treatment-related effects or pseudoprogression (PsP), may critically influence subsequent management options. Structural MRI is routinely employed to evaluate treatment responses, but misdiagnosis of TTP or PsP may lead to continuation of ineffective or premature cessation of effective treatments, respectively. A systematic review and meta-analysis were conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-analyses method. Embase, MEDLINE, Web of Science and Google Scholar were searched for methods applied to differentiate PsP and TTP, and studies were selected using pre-specified eligibility criteria. The sensitivity and specificity of included studies were summarised. Three of the identified methods were compared in a separate subgroup meta-analysis. Thirty studies assessing seven distinct neuroimaging methods in 1372 patients were included in the systematic review. The highest performing methods in the subgroup analysis were DWI (AUC = 0.93 [0.91-0.95]) and DSC-MRI (AUC = 0.93 [0.90-0.95]), compared to DCE-MRI (AUC = 0.90 [0.87-0.93]). 18F-fluoroethyltyrosine PET (18F-FET PET) and amide proton transfer-weighted MRI (APTw-MRI) also showed high diagnostic accuracy, but results were based on few low-powered studies. Both DWI and DSC-MRI performed with high sensitivity and specificity for differentiating PsP from TTP. Considering the technical parameters and feasibility of each identified method, the authors suggested that, at present, DSC-MRI technique holds the most clinical potential.
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Affiliation(s)
- Chris Taylor
- UCL Queen Square Institute of Neurology, University College London, Gower St., Bloomsbury, Queen Square, London, WC1E 6BT, UK.
| | - Justyna O Ekert
- Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, UK
| | - Viktoria Sefcikova
- UCL Queen Square Institute of Neurology, University College London, Gower St., Bloomsbury, Queen Square, London, WC1E 6BT, UK
| | - Naomi Fersht
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, UK
| | - George Samandouras
- Wellcome Centre for Human Neuroimaging, University College London, 12 Queen Square, London, UK
- Victor Horsley Department of Neurosurgery, The National Hospital for Neurology and Neurosurgery, Queen Square, London, UK
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Flies CM, van Leuken KH, Voorde MT, Verhoeff JJC, De Vos FYF, Seute T, Robe PA, Witkamp TD, Hendrikse J, Dankbaar JW, Snijders TJ. Conventional MRI Criteria to Differentiate Progressive Disease from Treatment-Induced Effects in High-Grade (WHO Grade 3-4) Gliomas. Neurology 2022; 99:e77-e88. [PMID: 35437259 PMCID: PMC9259090 DOI: 10.1212/wnl.0000000000200359] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 02/22/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Post-treatment radiological deterioration of patients with an irradiated high-grade (WHO grade 3-4) glioma (HGG) may be the result of true progressive disease (PD) or treatment-induced effects (TIE). Differentiation between these entities is of great importance, but remains a diagnostic challenge. This study assesses the diagnostic value of conventional MRI characteristics to differentiate PD from TIE in HGGs. MATERIAL AND METHODS In this single-centre, retrospective, consecutive cohort study, we included adults with a HGG, who were treated with (chemo-)radiotherapy and subsequently developed a new or increasing contrast-enhancing lesion on conventional follow-up MRI. TIE and PD were defined radiologically as stable/decreased for ≥6 weeks or RANO-progression, and histologically as TIE without viable tumour or PD. Two neuroradiologists assessed twenty-one preselected MRI characteristics of the progressive lesions. The statistical analysis included logistic regression to develop a) a full multivariable model b) a diagnostic model with model reduction, and a Cohen's Kappa interrater reliability (IRR) coefficient. RESULTS 210 patients (median age=61, IQR=54-68, 189 males) with 284 lesions were included, of which 141 (50%) had PD. Median time to PD was 2 (0.7-6.1) and to TIE 0.9 (0.7-3.5) months after radiotherapy. After multivariable modelling and model reduction, the following determinants prevailed: Radiation dose (Odds ratio (OR)=0.68, 95%-CI=0.49-0.93), longer time to progression (TTP, OR=3.56, 95%-CI=1.84-6.88), marginal enhancement (OR=2.04, 95%-CI=1.09-3.83), soap bubble enhancement (OR=2.63, 95%-CI=1.39-4.98) and isointense apparent diffusion coefficient (ADC)-signal (OR=2.11, 95%-CI=1.05-4.24). ORs>1 indicate higher odds of PD. The Hosmer&Lemeshow test showed good calibration (p=0.947) and the area under the ROC-curve was 0.722 (95%-CI=0.66-0.78). In the glioblastoma subgroup, TTP, marginal enhancement and ADC-signal were significant. IRR analysis between neuroradiologists revealed moderate to near-perfect agreement for the predictive items, but poor agreement for others. DISCUSSION Several characteristics from conventional MRI are significant predictors for the discrimination between PD and TIE. However, IRR was variable. Conventional MRI characteristics from this study should be incorporated into a multimodal diagnostic model with advanced imaging techniques. CLASSIFICATION OF EVIDENCE This study provides Class II evidence that in patients with irradiated HGGs, radiation dose, longer time to progression, marginal enhancement, soap bubble enhancement and isointense apparent ADC-signal distinguish PD from TIE.
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Affiliation(s)
- Christina M Flies
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Karlijn H van Leuken
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.,Stichting Beroepsopleiding Huisarts, the Netherlands
| | - Marlies Ten Voorde
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands.,Mission of the Netherlands Reformed Congregations, in Guinea (Conakry)
| | - Joost J C Verhoeff
- Department of Radiation Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Filip Y F De Vos
- Department of Medical Oncology, University Medical Center Utrecht, Utrecht, the Netherlands
| | - Tatjana Seute
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Pierre A Robe
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
| | - Theodoor D Witkamp
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jeroen Hendrikse
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jan Willem Dankbaar
- Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Tom J Snijders
- Department of Neurology & Neurosurgery, UMC Utrecht Brain Center, University Medical Center Utrecht, the Netherlands
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Shim KY, Chung SW, Jeong JH, Hwang I, Park CK, Kim TM, Park SH, Won JK, Lee JH, Lee ST, Yoo RE, Kang KM, Yun TJ, Kim JH, Sohn CH, Choi KS, Choi SH. Radiomics-based neural network predicts recurrence patterns in glioblastoma using dynamic susceptibility contrast-enhanced MRI. Sci Rep 2021; 11:9974. [PMID: 33976264 DOI: 10.1038/s41598-021-89218-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2020] [Accepted: 04/22/2021] [Indexed: 02/03/2023] Open
Abstract
Glioblastoma remains the most devastating brain tumor despite optimal treatment, because of the high rate of recurrence. Distant recurrence has distinct genomic alterations compared to local recurrence, which requires different treatment planning both in clinical practice and trials. To date, perfusion-weighted MRI has revealed that perfusional characteristics of tumor are associated with prognosis. However, not much research has focused on recurrence patterns in glioblastoma: namely, local and distant recurrence. Here, we propose two different neural network models to predict the recurrence patterns in glioblastoma that utilizes high-dimensional radiomic profiles based on perfusion MRI: area under the curve (AUC) (95% confidence interval), 0.969 (0.903-1.000) for local recurrence; 0.864 (0.726-0.976) for distant recurrence for each patient in the validation set. This creates an opportunity to provide personalized medicine in contrast to studies investigating only group differences. Moreover, interpretable deep learning identified that salient radiomic features for each recurrence pattern are related to perfusional intratumoral heterogeneity. We also demonstrated that the combined salient radiomic features, or "radiomic risk score", increased risk of recurrence/progression (hazard ratio, 1.61; p = 0.03) in multivariate Cox regression on progression-free survival.
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Tsakiris C, Siempis T, Alexiou GA, Zikou A, Sioka C, Voulgaris S, Argyropoulou MI. Differentiation Between True Tumor Progression of Glioblastoma and Pseudoprogression Using Diffusion-Weighted Imaging and Perfusion-Weighted Imaging: Systematic Review and Meta-analysis. World Neurosurg 2020; 144:e100-e109. [DOI: 10.1016/j.wneu.2020.07.218] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 07/28/2020] [Accepted: 07/30/2020] [Indexed: 01/08/2023]
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10
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Kassubek R, Müller HP, Thiele A, Kassubek J, Niessen HG. Advanced magnetic resonance imaging to support clinical drug development for malignant glioma. Drug Discov Today 2021; 26:429-41. [PMID: 33249294 DOI: 10.1016/j.drudis.2020.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/23/2020] [Accepted: 11/18/2020] [Indexed: 11/22/2022]
Abstract
Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.
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Bani-sadr A, Berner L, Barritault M, Chamard L, Bidet C, Eker O, Hermier M, Guyotat J, Jouanneau E, Meyronet D, Gouttard S, D’hombres A, Iziquierdo C, Honnorat J, Berthezène Y, Ducray F. Combined analysis of MGMT methylation and dynamic-susceptibility-contrast MRI for the distinction between early and pseudo-progression in glioblastoma patients. Rev Neurol (Paris) 2019; 175:534-43. [DOI: 10.1016/j.neurol.2019.01.400] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Revised: 12/05/2018] [Accepted: 01/21/2019] [Indexed: 01/13/2023]
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13
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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] [What about the content of this article? (0)] [Affiliation(s)] [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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Werner JM, Stoffels G, Lichtenstein T, Borggrefe J, Lohmann P, Ceccon G, Shah NJ, Fink GR, Langen KJ, Kabbasch C, Galldiks N. Differentiation of treatment-related changes from tumour progression: a direct comparison between dynamic FET PET and ADC values obtained from DWI MRI. Eur J Nucl Med Mol Imaging 2019; 46:1889-1901. [PMID: 31203420 DOI: 10.1007/s00259-019-04384-7] [Citation(s) in RCA: 41] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 05/30/2019] [Indexed: 12/18/2022]
Abstract
BACKGROUND Following brain cancer treatment, the capacity of anatomical MRI to differentiate neoplastic tissue from treatment-related changes (e.g., pseudoprogression) is limited. This study compared apparent diffusion coefficients (ADC) obtained by diffusion-weighted MRI (DWI) with static and dynamic parameters of O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET for the differentiation of treatment-related changes from tumour progression. PATIENTS AND METHODS Forty-eight pretreated high-grade glioma patients with anatomical MRI findings suspicious for progression (median time elapsed since last treatment was 16 weeks) were investigated using DWI and dynamic FET PET. Maximum and mean tumour-to-brain ratios (TBRmax, TBRmean) as well as dynamic parameters (time-to-peak and slope values) of FET uptake were calculated. For mean ADC calculation, regions-of-interest analyses were performed on ADC maps calculated from DWI coregistered with the contrast-enhanced MR image. Diagnoses were confirmed neuropathologically (21%) or clinicoradiologically. Diagnostic performance was evaluated using receiver-operating-characteristic analyses or Fisher's exact test for a combinational approach. RESULTS Ten of 48 patients had treatment-related changes (21%). The diagnostic performance of FET PET was significantly higher (threshold for both TBRmax and TBRmean, 1.95; accuracy, 83%; AUC, 0.89 ± 0.05; P < 0.001) than that of ADC values (threshold ADC, 1.09 × 10-3 mm2/s; accuracy, 69%; AUC, 0.73 ± 0.09; P = 0.13). The addition of static FET PET parameters to ADC values increased the latter's accuracy to 89%. The highest accuracy was achieved by combining static and dynamic FET PET parameters (93%). Moreover, in contrast to ADC values, TBRs <1.95 at suspected progression predicted a significantly longer survival (P = 0.01). CONCLUSIONS Data suggest that static and dynamic FET PET provide valuable information concerning the differentiation of early treatment-related changes from tumour progression and outperform ADC measurement for this highly relevant clinical question.
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Affiliation(s)
- Jan-Michael Werner
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Gabriele Stoffels
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany
| | - Thorsten Lichtenstein
- Department of Neuroradiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Jan Borggrefe
- Department of Neuroradiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Philipp Lohmann
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany
| | - Garry Ceccon
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Nadim J Shah
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany
- Department of Neurology, University Hospital Aachen, Aachen, 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, Juelich, Germany
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany
- Department of Nuclear Medicine, University Hospital Aachen, Aachen, Germany
| | - Christoph Kabbasch
- Department of Neuroradiology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Norbert Galldiks
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany.
- Institute of Neuroscience and Medicine (INM-3, -4), Research Center Juelich, Juelich, Germany.
- Center of Integrated Oncology (CIO), Universities of Aachen, Bonn, Cologne, and Düsseldorf, Cologne, Germany.
- Institute of Neuroscience and Medicine (INM-3), Research Center Juelich, Leo-Brandt-St. 5, 52425, Juelich, Germany.
- Department of Neurology, University Hospital Cologne, Kerpener St. 62, 50937, Cologne, Germany.
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Chen J, Hua H, Pang J, Shi X, Bi W, Li Y, Xu W. The Value of Diffusion-Weighted Magnetic Resonance Imaging in Predicting the Efficacy of Radiation and Chemotherapy in Cervical Cancer. Open Life Sci 2018; 13:305-311. [PMID: 33817097 PMCID: PMC7874687 DOI: 10.1515/biol-2018-0037] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2017] [Accepted: 05/08/2018] [Indexed: 01/22/2023] Open
Abstract
Background To analyze the application value of apparent diffusion coefficient (ADC) and exponent apparent diffusion coefficient (EADC) in evaluating the efficacy of radiation and chemotherapy in cervical cancer using pre- and posttreatment diffusion-weighted magnetic resonance imaging (DW-MRI) scans. Methods 52 patients with cervical cancer were administered radiation and chemotherapy. Both MRI and DW-MRI were obtained at different stages. The ADC and EADC values, as well as the maximum tumor diameter, were measured and analyzed. Results We found that the ADC value increased after treatment, and the EADC value decreased. Changes in the calculated ADC occurred earlier than the morphologic changes of the tumors. A negative correlation was detected between reduced rates in the maximum tumor diameter two months after treatment and pretreatment ADC value (r = –0.658, P < 0.05). An ROC curve and nonlinear regression analysis showed that the formula, y = (1525500.122x2 – 4689.962x + 3.482) × 100%, can be used to calculate the percentage of complete remission after treatment according to the pretreatment ADC value. Conclusion Our data suggest that pretreatment ADC and EADC values are predictive of the efficacy of radiation and chemotherapy. Both ADC and EADC values during treatment were instrumental in early monitoring and dynamic observation.
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Affiliation(s)
- Jingjing Chen
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Hui Hua
- Department of Thyroid Surgery, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Jing Pang
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Xianglong Shi
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Weiqun Bi
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Yingduan Li
- Department of Radiology, The Affiliated Hospital of Qingdao University, Qingdao 266000, Shandong Province, China
| | - Wenjian Xu
- Department of Radiology, The Affiliated Hospital of Qingdao University, 16 Jiangsu Road, Qingdao 266000, Shandong Province, China
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16
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Piper RJ, Senthil KK, Yan JL, Price SJ. Neuroimaging classification of progression patterns in glioblastoma: a systematic review. J Neurooncol 2018; 139:77-88. [PMID: 29603080 DOI: 10.1007/s11060-018-2843-3] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2017] [Accepted: 03/21/2018] [Indexed: 01/05/2023]
Abstract
BACKGROUND Our primary objective was to report the current neuroimaging classification systems of spatial patterns of progression in glioblastoma. In addition, we aimed to report the terminology used to describe 'progression' and to assess the compliance with the Response Assessment in Neuro-Oncology (RANO) Criteria. METHODS We conducted a systematic review to identify all neuroimaging studies of glioblastoma that have employed a categorical classification system of spatial progression patterns. Our review was registered with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) registry. RESULTS From the included 157 results, we identified 129 studies that used labels of spatial progression patterns that were not based on radiation volumes (Group 1) and 50 studies that used labels that were based on radiation volumes (Group 2). In Group 1, we found 113 individual labels and the most frequent were: local/localised (58%), distant/distal (51%), diffuse (20%), multifocal (15%) and subependymal/subventricular zone (15%). We identified 13 different labels used to refer to 'progression', of which the most frequent were 'recurrence' (99%) and 'progression' (92%). We identified that 37% (n = 33/90) of the studies published following the release of the RANO classification were adherent compliant with the RANO criteria. CONCLUSIONS Our review reports significant heterogeneity in the published systems used to classify glioblastoma spatial progression patterns. Standardization of terminology and classification systems used in studying progression would increase the efficiency of our research in our attempts to more successfully treat glioblastoma.
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Affiliation(s)
- Rory J Piper
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Hill's Road, Cambridge, CB2 0QQ, UK.
| | - Keerthi K Senthil
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Hill's Road, Cambridge, CB2 0QQ, UK
| | - Jiun-Lin Yan
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Hill's Road, Cambridge, CB2 0QQ, UK
| | - Stephen J Price
- Cambridge Brain Tumour Imaging Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Hill's Road, Cambridge, CB2 0QQ, UK
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Abstract
This review describes the definition, incidence, clinical implications, and magnetic resonance imaging (MRI) findings of pseudoprogression of brain tumors, in particular, but not limited to, high-grade glioma. Pseudoprogression is an important clinical problem after brain tumor treatment, interfering not only with day-to-day patient care but also the execution and interpretation of clinical trials. Radiologically, pseudoprogression is defined as a new or enlarging area(s) of contrast agent enhancement, in the absence of true tumor growth, which subsides or stabilizes without a change in therapy. The clinical definitions of pseudoprogression have been quite variable, which may explain some of the differences in reported incidences, which range from 9-30%. Conventional structural MRI is insufficient for distinguishing pseudoprogression from true progressive disease, and advanced imaging is needed to obtain higher levels of diagnostic certainty. Perfusion MRI is the most widely used imaging technique to diagnose pseudoprogression and has high reported diagnostic accuracy. Diagnostic performance of MR spectroscopy (MRS) appears to be somewhat higher, but MRS is less suitable for the routine and universal application in brain tumor follow-up. The combination of MRS and diffusion-weighted imaging and/or perfusion MRI seems to be particularly powerful, with diagnostic accuracy reaching up to or even greater than 90%. While diagnostic performance can be high with appropriate implementation and interpretation, even a combination of techniques, however, does not provide 100% accuracy. It should also be noted that most studies to date are small, heterogeneous, and retrospective in nature. Future improvements in diagnostic accuracy can be expected with harmonization of acquisition and postprocessing, quantitative MRI and computer-aided diagnostic technology, and meticulous evaluation with clinical and pathological data. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018.
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Affiliation(s)
- Stefanie C. Thust
- Lysholm Neuroradiology DepartmentNational Hospital for Neurology and NeurosurgeryLondonUK
- Department of Brain Rehabilitation and RepairUCL Institute of NeurologyLondonUK
- Imaging DepartmentUniversity College London HospitalLondonUK
| | - Martin J. van den Bent
- Department of NeurologyThe Brain Tumor Centre at Erasmus MC Cancer InstituteRotterdamThe Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MCUniversity Medical Centre RotterdamRotterdamThe Netherlands
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18
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Abstract
Imaging plays several key roles in managing brain tumors, including diagnosis, prognosis, and treatment response assessment. Ongoing challenges remain as new therapies emerge and there are urgent needs to find accurate and clinically feasible methods to noninvasively evaluate brain tumors before and after treatment. This review aims to provide an overview of several advanced imaging modalities including magnetic resonance imaging and positron emission tomography (PET), including advances in new PET agents, and summarize several key areas of their applications, including improving the accuracy of diagnosis and addressing the challenging clinical problems such as evaluation of pseudoprogression and anti-angiogenic therapy, and rising challenges of imaging with immunotherapy.
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Affiliation(s)
- Hari Nandu
- Department of Radiology, Brigham and Women's Hospital, Boston, MA, USA
| | | | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, 75 Francis Street, Boston, MA 02445, USA
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Suh CH, Kim HS, Jung SC, Choi CG, Kim SJ. Multiparametric MRI as a potential surrogate endpoint for decision-making in early treatment response following concurrent chemoradiotherapy in patients with newly diagnosed glioblastoma: a systematic review and meta-analysis. Eur Radiol 2018; 28:2628-2638. [PMID: 29374321 DOI: 10.1007/s00330-017-5262-5] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2017] [Revised: 12/09/2017] [Accepted: 12/20/2017] [Indexed: 11/28/2022]
Abstract
OBJECTIVE To evaluate the value of multiparametric MRI for determination of early treatment response following concurrent chemoradiotherapy in patients with newly diagnosed glioblastoma. METHODS A computerized search of Ovid-MEDLINE and EMBASE up to 1 October 2017 was performed to find studies on the diagnostic performance of multiparametric MRI for differentiating true progression from pseudoprogression. The beginning search date was not specified. Pooled estimates of sensitivity and specificity were obtained using hierarchical logistic regression modeling. We performed meta-regression and sensitivity analyses to explain the effects of the study heterogeneity. RESULTS Nine studies including 456 patients were included. Pooled sensitivity and specificity were 84 % (95 % CI 74-91) and 95 % (95 % CI 83-99), respectively. Area under the hierarchical summary receiver operating characteristic curve was 0.95 (95 % CI 0.92-0.96). Meta-regression showed true progression in the study population, the mean age and the reference standard were significant factors affecting heterogeneity. CONCLUSION Multiparametric MRI may be used as a potential surrogate endpoint for assessment of early treatment response, especially in the differentiation of true progression from pseudoprogression. However, based on the current evidence, monoparametric and multiparametric MRI perform equally in the clinical context. Further evaluation will be needed. KEY POINTS • Multiparametric MRI shows high diagnostic performance for early treatment response in glioblastoma. • Multiparametric MRI could differentiate true progression from pseudoprogression in newly diagnosed glioblastoma. • The normalized rCBV derived from DSC was the most commonly used parameter.
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Affiliation(s)
- Chong Hyun Suh
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 138-736, Republic of Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 138-736, Republic of Korea.
| | - Seung Chai Jung
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 138-736, Republic of Korea
| | - Choong Gon Choi
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 138-736, Republic of Korea
| | - Sang Joon Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 86 Asanbyeongwon-Gil, Songpa-Gu, Seoul, 138-736, Republic of Korea
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Abstract
PURPOSE OF REVIEW Neuroimaging plays a critical role in diagnosis of brain tumors and in assessment of response to therapy. However, challenges remain, including accurately and reproducibly assessing response to therapy, defining endpoints for neuro-oncology trials, providing prognostic information, and differentiating progressive disease from post-therapeutic changes particularly in the setting of antiangiogenic and other novel therapies. RECENT FINDINGS Recent advances in the imaging of brain tumors include application of advanced MRI imaging techniques to assess tumor response to therapy and analysis of imaging features correlating to molecular markers, grade, and prognosis. This review aims to summarize recent advances in imaging as applied to current diagnostic and therapeutic neuro-oncologic challenges.
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Affiliation(s)
- Katherine M Mullen
- Department of Radiology, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, USA
| | - Raymond Y Huang
- Department of Radiology, Brigham and Women's Hospital, 75 Francis St, Boston, MA, 02115, USA.
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Yao ZG, Li WH, Hua F, Cheng HX, Zhao MQ, Sun XC, Qin YJ, Li JM. LBH589 Inhibits Glioblastoma Growth and Angiogenesis Through Suppression of HIF-1α Expression. J Neuropathol Exp Neurol 2017; 76:1000-1007. [PMID: 29136455 DOI: 10.1093/jnen/nlx088] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2017] [Indexed: 02/05/2023] Open
Abstract
Glioblastoma (GBM) is an angiogenic malignancy with a highly unfavorable prognosis. Angiogenesis in GBM represents an adaptation to a hypoxic microenvironment and is correlated with tumor growth, invasion, clinical recurrence, and lethality. LBH589 (also called panobinostat) is a histone deacetylase (HDAC) inhibitor with potent antitumor activity. In the current study, we investigated the mechanism and effects of LBH589 on GBM growth and hypoxia-induced angiogenesis in vitro and in vivo. To determine the antitumor and angiogenesis activity and mechanism of LBH589, we used cell proliferations in vitro and GBM xenografts in vivo. To clarify mechanisms of LBH589 on angiogenesis, HDAC assay, RT-PCR, Western blot, and co-immunoprecipitation assays were performed. We found LBH589 displayed significant antitumor effects on GBM as demonstrated by inhibited cell proliferation, slower tumor growth, and decreased microvessel density of subcutaneous xenografts. These actions of LBH589 resulted from the disruption of heat shock protein 90/HDAC6 complex, increased HIF-1α instability and degradation, and decreased VEGF expression. Our results indicate the potential antiangiogenic activity of LBH589 in human GBM and provide some preclinical data to warrant further exploration of HDAC inhibitors for the treatment of advanced glioma. Moreover, our study supports the role of HDAC inhibitors as a therapeutic strategy to target tumor angiogenesis.
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Affiliation(s)
- Zhi-Gang Yao
- Department of Pathology and Department of Chemotherapy, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; and Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Wen-Huan Li
- Department of Pathology and Department of Chemotherapy, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; and Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Fang Hua
- Department of Pathology and Department of Chemotherapy, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; and Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hong-Xia Cheng
- Department of Pathology and Department of Chemotherapy, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; and Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Miao-Qing Zhao
- Department of Pathology and Department of Chemotherapy, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; and Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xi-Chao Sun
- Department of Pathology and Department of Chemotherapy, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; and Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ye-Jun Qin
- Department of Pathology and Department of Chemotherapy, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; and Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jia-Mei Li
- Department of Pathology and Department of Chemotherapy, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; and Department of Rheumatology and Clinical Immunology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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22
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Zhou Q, Zeng F, Ding Y, Fuller CD, Wang J. Meta-analysis of diffusion-weighted imaging for predicting locoregional failure of chemoradiotherapy in patients with head and neck squamous cell carcinoma. Mol Clin Oncol 2017; 8:197-203. [PMID: 29423223 DOI: 10.3892/mco.2017.1504] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Accepted: 10/24/2017] [Indexed: 02/06/2023] Open
Abstract
The purpose of this study was to evaluate the accuracy of diffusion-weighted imaging (DWI) for predicting locoregional failure of chemoradiotherapy in patients with head and neck squamous cell carcinoma (HNSCC). A comprehensive search was conducted through the EMBASE, PubMed and Cochrane Library databases for relevant publications. Stata software was used to calculate the pooled sensitivity, specificity, likelihood ratios and diagnostic odds ratios, and to construct a summary receiver operating characteristics (sROC) curve for DWI. A total of 9 studies comprising 421 patients were included. The pooled sensitivity, specificity, positive likelihood ratio, negative likelihood ratio and diagnostic odds ratio were 0.82 [95% confidence interval (CI): 0.72-0.88], 0.70 (95% CI: 0.62-0.77), 2.7 (95% CI: 2.1-3.6), 0.26 (95% CI: 0.17-0.41), and 10.48 (95% CI: 5.35-20.53), respectively. The area under the sROC curve was 0.84 (95% CI: 0.81-0.87). Therefore, DWI appears to be a promising imaging modality for predicting local failure of chemoradiotherapy in patients with HNSCC.
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Affiliation(s)
- Qiming Zhou
- Department of Oncology, The Sixth People's Hospital, Shenzhen, Guangdong 518052, P.R. China.,Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Fangfang Zeng
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong 510080, P.R. China
| | - Yao Ding
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Clifton D Fuller
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Jihong Wang
- Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
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23
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Abstract
Background Management of glioblastoma is complicated by pseudoprogression, a radiological phenomenon mimicking progression. This retrospective cohort study investigated the incidence, prognostic implications, and most clinically appropriate definition of pseudoprogression. Methods Consecutive glioblastoma patients treated at the Juravinski Hospital and Cancer Centre, Hamilton, Ontario between 2004 and 2012 with temozolomide chemoradiotherapy and with contrast-enhanced MRI at standard imaging intervals were included. At each imaging interval, patient responses as per the RECIST (Response Evaluation Criteria in Solid Tumors), MacDonald, and RANO (Response Assessment in Neuro-Oncology) criteria were reported. Based on each set of criteria, subjects were classified as having disease response, stable disease, pseudoprogression, or true progression. The primary outcome was overall survival. Results The incidence of pseudoprogression among 130 glioblastoma patients treated with chemoradiotherapy was 15%, 19%, and 23% as defined by RANO, MacDonald, and RECIST criteria, respectively. Using the RANO definition, median survival for patients with pseudoprogression was 13.0 months compared with 12.5 months for patients with stable disease (hazard ratio [HR]=0.70; 95% confidence interval [CI], 0.35-1.42). Similarly, using the MacDonald definition, median survival for the pseudoprogression group was 11.8 months compared with 12.0 months for the stable disease group (HR=0.86; 95% CI, 0.47-1.58). Furthermore, disease response compared with stable disease was also similar using the RANO (HR=0.52; 95% CI, 0.20-1.35) and MacDonald (HR=0.51: 95% CI, 0.20-1.31) definitions. Conclusions Of all conventional glioblastoma response criteria, the RANO criteria gave the lowest incidence of pseudoprogression. Regardless of criteria, patients with pseudoprogression did not have statistically significant difference in survival compared with patients with stable disease.
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Affiliation(s)
- Michael Jonathan Kucharczyk
- Juravinski Cancer Centre, 699 Concession Street, Hamilton, Ontario, Canada (M.J.K.; A.W.; J.N.G.), Ontario Clinical Oncology Group, McMaster University, 771 Concession Street, Hamilton, Ontario, Canada (S.P.)
| | - Sameer Parpia
- Juravinski Cancer Centre, 699 Concession Street, Hamilton, Ontario, Canada (M.J.K.; A.W.; J.N.G.), Ontario Clinical Oncology Group, McMaster University, 771 Concession Street, Hamilton, Ontario, Canada (S.P.)
| | - Anthony Whitton
- Juravinski Cancer Centre, 699 Concession Street, Hamilton, Ontario, Canada (M.J.K.; A.W.; J.N.G.), Ontario Clinical Oncology Group, McMaster University, 771 Concession Street, Hamilton, Ontario, Canada (S.P.)
| | - Jeffrey Noah Greenspoon
- Juravinski Cancer Centre, 699 Concession Street, Hamilton, Ontario, Canada (M.J.K.; A.W.; J.N.G.), Ontario Clinical Oncology Group, McMaster University, 771 Concession Street, Hamilton, Ontario, Canada (S.P.)
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