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Śledzińska-Bebyn P, Furtak J, Bebyn M, Serafin Z. Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling. Magn Reson Imaging 2024; 112:63-81. [PMID: 38914147 DOI: 10.1016/j.mri.2024.06.004] [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: 04/04/2024] [Revised: 05/20/2024] [Accepted: 06/20/2024] [Indexed: 06/26/2024]
Abstract
This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.
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Affiliation(s)
- Paulina Śledzińska-Bebyn
- Department of Radiology, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland.
| | - Jacek Furtak
- Department of Clinical Medicine, Faculty of Medicine, University of Science and Technology, Bydgoszcz, Poland; Department of Neurosurgery, 10th Military Research Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Marek Bebyn
- Department of Internal Diseases, 10th Military Clinical Hospital and Polyclinic, 85-681 Bydgoszcz, Poland
| | - Zbigniew Serafin
- Department of Radiology and Diagnostic Imaging, Nicolaus Copernicus University, Collegium Medicum, Bydgoszcz, Poland
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Panholzer J, Malsiner-Walli G, Grün B, Kalev O, Sonnberger M, Pichler R. Multiparametric Analysis Combining DSC-MR Perfusion and [18F]FET-PET is Superior to a Single Parameter Approach for Differentiation of Progressive Glioma from Radiation Necrosis. Clin Neuroradiol 2024; 34:351-360. [PMID: 38157019 DOI: 10.1007/s00062-023-01372-1] [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: 06/16/2023] [Accepted: 11/29/2023] [Indexed: 01/03/2024]
Abstract
PURPOSE Perfusion-weighted (PWI) magnetic resonance imaging (MRI) and O‑(2-[18F]fluoroethyl-)-l-tyrosine ([18F]FET) positron emission tomography (PET) are both useful for discrimination of progressive disease (PD) from radiation necrosis (RN) in patients with gliomas. Previous literature showed that the combined use of FET-PET and MRI-PWI is advantageous; hhowever the increased diagnostic performances were only modest compared to the use of a single modality. Hence, the goal of this study was to further explore the benefit of combining MRI-PWI and [18F]FET-PET for differentiation of PD from RN. Secondarily, we evaluated the usefulness of cerebral blood flow (CBF), mean transit time (MTT) and time to peak (TTP) as previous studies mainly examined cerebral blood volume (CBV). METHODS In this single center study, we retrospectively identified patients with WHO grades II-IV gliomas with suspected tumor recurrence, presenting with ambiguous findings on structural MRI. For differentiation of PD from RN we used both MRI-PWI and [18F]FET-PET. Dynamic susceptibility contrast MRI-PWI provided normalized parameters derived from perfusion maps (r(relative)CBV, rCBF, rMTT, rTTP). Static [18F]FET-PET parameters including mean and maximum tumor to brain ratios (TBRmean, TBRmax) were calculated. Based on histopathology and radioclinical follow-up we diagnosed PD in 27 and RN in 10 cases. Using the receiver operating characteristic (ROC) analysis, area under the curve (AUC) values were calculated for single and multiparametric models. The performances of single and multiparametric approaches were assessed with analysis of variance and cross-validation. RESULTS After application of inclusion and exclusion criteria, we included 37 patients in this study. Regarding the in-sample based approach, in single parameter analysis rTBRmean (AUC = 0.91, p < 0.001), rTBRmax (AUC = 0.89, p < 0.001), rTTP (AUC = 0.87, p < 0.001) and rCBVmean (AUC = 0.84, p < 0.001) were efficacious for discrimination of PD from RN. The rCBFmean and rMTT did not reach statistical significance. A classification model consisting of TBRmean, rCBVmean and rTTP achieved an AUC of 0.98 (p < 0.001), outperforming the use of rTBRmean alone, which was the single parametric approach with the highest AUC. Analysis of variance confirmed the superiority of the multiparametric approach over the single parameter one (p = 0.002). While cross-validation attributed the highest AUC value to the model consisting of TBRmean and rCBVmean, it also suggested that the addition of rTTP resulted in the highest accuracy. Overall, multiparametric models performed better than single parameter ones. CONCLUSION A multiparametric MRI-PWI and [18F]FET-PET model consisting of TBRmean, rCBVmean and PWI rTTP significantly outperformed the use of rTBRmean alone, which was the best single parameter approach. Secondarily, we firstly report the potential usefulness of PWI rTTP for discrimination of PD from RN in patients with glioma; however, for validation of our findings the prospective studies with larger patient samples are necessary.
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Affiliation(s)
- Jürgen Panholzer
- Department of Neurology, Kepler University Hospital, Linz, Austria.
- Faculty of Medicine, Johannes Kepler University, Linz, Austria.
| | - Gertraud Malsiner-Walli
- Institute for Statistics and Mathematics, WU University of Economics and Business, Vienna, Austria
| | - Bettina Grün
- Institute for Statistics and Mathematics, WU University of Economics and Business, Vienna, Austria
| | - Ognian Kalev
- Department for Pathology and Molecular Pathology, Neuromed Campus, Kepler University Hospital, Linz, Austria
| | - Michael Sonnberger
- Department for Neuroradiology, Neuromed Campus, Kepler University Hospital, Linz, Austria
| | - Robert Pichler
- Department for Nuclear Medicine, Neuromed Campus, Kepler University Hospital, Linz, Austria
- Institute of Nuclear Medicine, Steyr Hospital, Steyr, Austria
- Department of Radiology, Clinic of Nuclear Medicine, Medical University Graz, Graz, Austria
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Schack A, Aunan-Diop JS, Gerhardt FA, Pedersen CB, Halle B, Kofoed MS, Markovic L, Wirenfeldt M, Poulsen FR. Evaluating the Efficacy of Perfusion MRI and Conventional MRI in Distinguishing Recurrent Cerebral Metastasis from Brain Radiation Necrosis. Brain Sci 2024; 14:321. [PMID: 38671973 PMCID: PMC11048647 DOI: 10.3390/brainsci14040321] [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: 02/28/2024] [Revised: 03/25/2024] [Accepted: 03/26/2024] [Indexed: 04/28/2024] Open
Abstract
Differentiating recurrent cerebral metastasis (CM) from brain radiation necrosis (BRN) is pivotal for guiding appropriate treatment and prognostication. Despite advances in imaging techniques, however, accurately distinguishing these conditions non-invasively is still challenging. This single-center retrospective study reviewed 32 cases (28 patients) with confirmed cerebral metastases who underwent surgical excision of lesions initially diagnosed by MRI and/or MR perfusion scans from 1 January 2015 to 30 September 2020. Diagnostic accuracy was assessed by comparing imaging findings with postoperative histopathology. Conventional MRI accurately identified recurrent CM in 75% of cases. MR perfusion scans showed significantly higher mean maximum relative cerebral blood volume (max. rCBV) in metastasis cases, indicating its potential as a discriminative biomarker. No single imaging modality could definitively distinguish CM from BRN. Survival analysis revealed gender as the only significant factor affecting overall survival, with no significant survival difference observed between patients with CM and BRN after controlling for confounding factors. This study underscores the limitations of both conventional MRI and MR perfusion scans in differentiating recurrent CM from BRN. Histopathological examination remains essential for accurate diagnosis. Further research is needed to improve the reliability of non-invasive imaging and to guide the management of patients with these post-radiation events.
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Affiliation(s)
- Anders Schack
- Department of Neurosurgery, Odense University Hospital, DK-5000 Odense, Denmark
- Department of Clinical Research, BRIDGE (Brain Research—Inter Disciplinary Guided Excellence), University of Southern Denmark, DK-5230 Odense, Denmark
| | - Jan Saip Aunan-Diop
- Department of Neurosurgery, Odense University Hospital, DK-5000 Odense, Denmark
- Department of Clinical Research, BRIDGE (Brain Research—Inter Disciplinary Guided Excellence), University of Southern Denmark, DK-5230 Odense, Denmark
| | - Frederik A. Gerhardt
- Department of Neurosurgery, Odense University Hospital, DK-5000 Odense, Denmark
- Department of Clinical Research, BRIDGE (Brain Research—Inter Disciplinary Guided Excellence), University of Southern Denmark, DK-5230 Odense, Denmark
| | - Christian Bonde Pedersen
- Department of Neurosurgery, Odense University Hospital, DK-5000 Odense, Denmark
- Department of Clinical Research, BRIDGE (Brain Research—Inter Disciplinary Guided Excellence), University of Southern Denmark, DK-5230 Odense, Denmark
| | - Bo Halle
- Department of Neurosurgery, Odense University Hospital, DK-5000 Odense, Denmark
- Department of Clinical Research, BRIDGE (Brain Research—Inter Disciplinary Guided Excellence), University of Southern Denmark, DK-5230 Odense, Denmark
| | - Mikkel S. Kofoed
- Department of Neurosurgery, Odense University Hospital, DK-5000 Odense, Denmark
- Department of Clinical Research, BRIDGE (Brain Research—Inter Disciplinary Guided Excellence), University of Southern Denmark, DK-5230 Odense, Denmark
| | - Ljubo Markovic
- Department of Radiology, Odense University Hospital, DK-5000 Odense, Denmark
| | - Martin Wirenfeldt
- Department of Pathology, University Hospital of Southern Denmark, DK-6000 Esbjerg, Denmark
- Department of Regional Health Research, BRIDGE (Brain Research—Inter Disciplinary Guided Excellence), University of Southern Denmark, DK-5230 Odense, Denmark
| | - Frantz Rom Poulsen
- Department of Neurosurgery, Odense University Hospital, DK-5000 Odense, Denmark
- Department of Clinical Research, BRIDGE (Brain Research—Inter Disciplinary Guided Excellence), University of Southern Denmark, DK-5230 Odense, Denmark
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Hilario A, Salvador E, Cardenas A, Romero J, Lechuga C, Chen Z, Martinez de Aragon A, Perez-Nuñez A, Hernandez-Lain A, Sepulveda J, Lagares A, Toldos O, Rodriguez-Gonzalez V, Ramos A. Low rCBV values in glioblastoma tumor progression under chemoradiotherapy. Neuroradiology 2024; 66:317-323. [PMID: 38183424 DOI: 10.1007/s00234-023-03279-7] [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: 08/05/2023] [Accepted: 12/26/2023] [Indexed: 01/08/2024]
Abstract
PURPOSE After standard treatment for glioblastoma, perfusion MRI remains challenging for differentiating tumor progression from post-treatment changes. Our objectives were (1) to correlate rCBV values at diagnosis and at first tumor progression and (2) to analyze the relationship of rCBV values at tumor recurrence with enhancing volume, localization of tumor progression, and time elapsed since the end of radiotherapy in tumor recurrence. METHODS Inclusion criteria were (1) age > 18 years, (2) histologically confirmed glioblastoma treated with STUPP regimen, and (3) tumor progression according to RANO criteria > 12 weeks after radiotherapy. Co-registration of segmented enhancing tumor VOIs with dynamic susceptibility contrast perfusion MRI was performed using Olea Sphere software. For tumor recurrence, we correlated rCBV values with enhancing tumor volume, with recurrence localization, and with time elapsed from the end of radiotherapy to progression. Analyses were performed with SPSS software. RESULTS Sixty-four patients with glioblastoma were included in the study. Changes in rCBV values between diagnosis and first tumor progression were significant (p < 0.001), with a mean and median decreases of 32% and 46%, respectively. Mean rCBV values were also different (p < 0.01) when tumors progressed distally (radiation field rCBV values of 1.679 versus 3.409 distally). However, changes and, therefore, low rCBV values after radiotherapy in tumor recurrence were independent of time. CONCLUSION Chemoradiation alters tumor perfusion and rCBV values may be decreased in the setting of tumor progression. Changes in rCBV values with respect to diagnosis, with low rCBV in tumor progression, are independent of time but related to the site of recurrence.
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Affiliation(s)
- A Hilario
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain.
| | - E Salvador
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Cardenas
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - J Romero
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - C Lechuga
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - Z Chen
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Martinez de Aragon
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Perez-Nuñez
- Department of Neurosurgery, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Hernandez-Lain
- Department of Neuropathology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - J Sepulveda
- Department of Medical Oncology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Lagares
- Department of Neurosurgery, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - O Toldos
- Department of Neuropathology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - V Rodriguez-Gonzalez
- Department of Radiation Oncology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
| | - A Ramos
- Department of Radiology, Hospital 12 de Octubre, Avenida de Cordoba s/n, 28041, Madrid, Spain
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Gu X, He X, Wang H, Li J, Chen R, Liu H. Dynamic Susceptibility Contrast-Enhanced Perfusion-Weighted Imaging in Differentiation Between Recurrence and Pseudoprogression in High-Grade Glioma: A Meta-analysis. J Comput Assist Tomogr 2024; 48:303-310. [PMID: 37654056 DOI: 10.1097/rct.0000000000001543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
INTRODUCTION In glioma patients that have undergone surgical tumor resection, the ability to reliably distinguish between pseudoprogression (PsP) and a recurrent tumor (RT) is of key clinical importance. Accordingly, this meta-analysis evaluated the utility of dynamic susceptibility contrast-enhanced perfusion-weighted imaging as a means of distinguishing between PsP and RT when analyzing patients with high-grade glioma. MATERIALS AND METHODS The PubMed, Web of Science, and Wanfang databases were searched for relevant studies. Pooled analyses of sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) values were conducted, after which the area under the curve (AUC) for summary receiver operating characteristic curves was computed. RESULTS This meta-analysis ultimately included 21 studies enrolling 879 patients with 888 lesions. Cerebral blood volume-associated diagnostic results were reported in 20 of the analyzed studies, and the respective pooled sensitivity, specificity, PLR, and NLR values were 86% (95% confidence interval [CI], 0.81-0.89), 83% (95% CI, 0.77-0.87), 4.94 (95% CI, 3.61-6.75), and 0.18 (95% CI, 0.13-0.23) for these 20 studies. The corresponding AUC value was 0.91 (95% CI, 0.88-0.93), and the publication bias risk was low ( P = 0.976). Cerebral blood flow-related diagnostic results were additionally reported in 6 of the analyzed studies, with respective pooled sensitivity, specificity, PLR, and NLR values of 85% (95% CI, 0.78-0.90), 85% (95% CI, 0.76-0.91), 5.54 (95% CI, 3.40-9.01), and 0.18 (95% CI, 0.12-0.26). The corresponding AUC value was 0.92 (95% CI, 0.89-0.94), and the publication bias risk was low ( P = 0.373). CONCLUSIONS The present meta-analysis results suggest that dynamic susceptibility contrast-enhanced perfusion-weighted imaging represents an effective diagnostic approach to distinguishing between PsP and RT in high-grade glioma patients.
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Affiliation(s)
| | - Xining He
- From the Departments of Neurosurgery
| | - Hualong Wang
- Radiology, Binzhou People's Hospital, Binzhou, China
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Sabeghi P, Zarand P, Zargham S, Golestany B, Shariat A, Chang M, Yang E, Rajagopalan P, Phung DC, Gholamrezanezhad A. Advances in Neuro-Oncological Imaging: An Update on Diagnostic Approach to Brain Tumors. Cancers (Basel) 2024; 16:576. [PMID: 38339327 PMCID: PMC10854543 DOI: 10.3390/cancers16030576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 01/22/2024] [Accepted: 01/24/2024] [Indexed: 02/12/2024] Open
Abstract
This study delineates the pivotal role of imaging within the field of neurology, emphasizing its significance in the diagnosis, prognostication, and evaluation of treatment responses for central nervous system (CNS) tumors. A comprehensive understanding of both the capabilities and limitations inherent in emerging imaging technologies is imperative for delivering a heightened level of personalized care to individuals with neuro-oncological conditions. Ongoing research in neuro-oncological imaging endeavors to rectify some limitations of radiological modalities, aiming to augment accuracy and efficacy in the management of brain tumors. This review is dedicated to the comparison and critical examination of the latest advancements in diverse imaging modalities employed in neuro-oncology. The objective is to investigate their respective impacts on diagnosis, cancer staging, prognosis, and post-treatment monitoring. By providing a comprehensive analysis of these modalities, this review aims to contribute to the collective knowledge in the field, fostering an informed approach to neuro-oncological care. In conclusion, the outlook for neuro-oncological imaging appears promising, and sustained exploration in this domain is anticipated to yield further breakthroughs, ultimately enhancing outcomes for individuals grappling with CNS tumors.
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Affiliation(s)
- Paniz Sabeghi
- Department of Radiology, Keck School of Medicine, University of Southern California, 1500 San Pablo St., Los Angeles, CA 90033, USA; (P.S.); (E.Y.); (P.R.); (D.C.P.)
| | - Paniz Zarand
- School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran 1985717411, Iran;
| | - Sina Zargham
- Department of Basic Science, California Northstate University College of Medicine, 9700 West Taron Drive, Elk Grove, CA 95757, USA;
| | - Batis Golestany
- Division of Biomedical Sciences, Riverside School of Medicine, University of California, 900 University Ave., Riverside, CA 92521, USA;
| | - Arya Shariat
- Kaiser Permanente Los Angeles Medical Center, 4867 W Sunset Blvd, Los Angeles, CA 90027, USA;
| | - Myles Chang
- Keck School of Medicine, University of Southern California, 1975 Zonal Avenue, Los Angeles, CA 90089, USA;
| | - Evan Yang
- Department of Radiology, Keck School of Medicine, University of Southern California, 1500 San Pablo St., Los Angeles, CA 90033, USA; (P.S.); (E.Y.); (P.R.); (D.C.P.)
| | - Priya Rajagopalan
- Department of Radiology, Keck School of Medicine, University of Southern California, 1500 San Pablo St., Los Angeles, CA 90033, USA; (P.S.); (E.Y.); (P.R.); (D.C.P.)
| | - Daniel Chang Phung
- Department of Radiology, Keck School of Medicine, University of Southern California, 1500 San Pablo St., Los Angeles, CA 90033, USA; (P.S.); (E.Y.); (P.R.); (D.C.P.)
| | - Ali Gholamrezanezhad
- Department of Radiology, Keck School of Medicine, University of Southern California, 1500 San Pablo St., Los Angeles, CA 90033, USA; (P.S.); (E.Y.); (P.R.); (D.C.P.)
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Cruz N, Herculano-Carvalho M, Roque D, Faria CC, Cascão R, Ferreira HA, Reis CP, Matela N. Highlighted Advances in Therapies for Difficult-To-Treat Brain Tumours Such as Glioblastoma. Pharmaceutics 2023; 15:pharmaceutics15030928. [PMID: 36986790 PMCID: PMC10054750 DOI: 10.3390/pharmaceutics15030928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2023] [Revised: 02/25/2023] [Accepted: 03/10/2023] [Indexed: 03/15/2023] Open
Abstract
Glioblastoma multiforme (GBM) remains a challenging disease, as it is the most common and deadly brain tumour in adults and has no curative solution and an overall short survival time. This incurability and short survival time means that, despite its rarity (average incidence of 3.2 per 100,000 persons), there has been an increased effort to try to treat this disease. Standard of care in newly diagnosed glioblastoma is maximal tumour resection followed by initial concomitant radiotherapy and temozolomide (TMZ) and then further chemotherapy with TMZ. Imaging techniques are key not only to diagnose the extent of the affected tissue but also for surgery planning and even for intraoperative use. Eligible patients may combine TMZ with tumour treating fields (TTF) therapy, which delivers low-intensity and intermediate-frequency electric fields to arrest tumour growth. Nonetheless, the blood–brain barrier (BBB) and systemic side effects are obstacles to successful chemotherapy in GBM; thus, more targeted, custom therapies such as immunotherapy and nanotechnological drug delivery systems have been undergoing research with varying degrees of success. This review proposes an overview of the pathophysiology, possible treatments, and the most (not all) representative examples of the latest advancements.
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Affiliation(s)
- Nuno Cruz
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
- iMED.ULisboa, Research Institute for Medicines, Faculdade de Farmácia, Universidade de Lisboa, Av. Prof. Gama Pinto, 1649-003 Lisboa, Portugal
| | - Manuel Herculano-Carvalho
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal
- Department of Neurosurgery, Hospital de Santa Maria, Centro Hospitalar Universitário Lisboa Norte (CHULN), 1649-028 Lisboa, Portugal
| | - Diogo Roque
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal
- Department of Neurosurgery, Hospital de Santa Maria, Centro Hospitalar Universitário Lisboa Norte (CHULN), 1649-028 Lisboa, Portugal
| | - Cláudia C. Faria
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal
- Department of Neurosurgery, Hospital de Santa Maria, Centro Hospitalar Universitário Lisboa Norte (CHULN), 1649-028 Lisboa, Portugal
| | - Rita Cascão
- Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, 1649-028 Lisboa, Portugal
| | - Hugo Alexandre Ferreira
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
| | - Catarina Pinto Reis
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
- iMED.ULisboa, Research Institute for Medicines, Faculdade de Farmácia, Universidade de Lisboa, Av. Prof. Gama Pinto, 1649-003 Lisboa, Portugal
- Correspondence: (C.P.R.); (N.M.); Tel.: +351-217-946-400 (ext. 14244) (C.P.R.); Fax: +351-217-946-470 (C.P.R.)
| | - Nuno Matela
- Instituto de Biofísica e Engenharia Biomédica, Faculdade de Ciências, Universidade de Lisboa, 1749-016 Lisboa, Portugal
- Correspondence: (C.P.R.); (N.M.); Tel.: +351-217-946-400 (ext. 14244) (C.P.R.); Fax: +351-217-946-470 (C.P.R.)
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Shen F, Li J, Liu F, Sun N, Qiu X, Ding W, Sun X. The efficacy and adverse effects of anlotinib in the treatment of high-grade glioma: A retrospective analysis. Front Oncol 2023; 13:1095362. [PMID: 36874124 PMCID: PMC9982121 DOI: 10.3389/fonc.2023.1095362] [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: 11/11/2022] [Accepted: 01/19/2023] [Indexed: 02/19/2023] Open
Abstract
Introduction Anlotinib, a novel multi-kinase inhibitor, was found to improve progression-free survival (PFS) in brain metastases. Methods This paper retrospectively analyzed 26 newly diagnosed or recurrent high-grade gliomas from 2017 to 2022, and the patients received oral anlotinib during concurrent postoperative chemoradiotherapy or after recurrence. Efficacy was evaluated according to the Response Assessment in Neuro-Oncology (RANO) criteria, and the main study endpoints were PFS at 6 months and overall survival (OS) at 1 year. Results After the follow-up, until May 2022, 13 patients survived and 13 patients died, with a median follow-up time of 25.6 months. The disease control rate (DCR) was 96.2% (25/26), and the overall response rate (ORR) rate was 73.1% (19/26). The median PFS after oral anlotinib was 8.9 months (0.8-15.1), and the PFS at 6 months was 72.5%. The median OS after oral anlotinib was 12 months (1.6-24.4), and the OS at 12 months was 42.6%. Anlotinib-related toxicities were observed in 11 patients, mostly grades 1-2. In the multivariate analysis, patients with Karnofsky Performance Scale (KPS) above 80 had a highermedian PFS of 9.9months (p = 0.02), and their sex, age, IDH mutation, MGMTmethylation, and whether anlotinib was combined with chemoradiotherapy or maintenance treatment had no effect on PFS. Conclusion We found that anlotinib combined with chemoradiotherapy in treating high-grade central nervous system (CNS) tumors can prolong PFS and OS and that it was safe.
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Affiliation(s)
| | | | | | | | | | - Wei Ding
- *Correspondence: Wei Ding, ; XiangDong Sun,
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Henssen D, Meijer F, Verburg FA, Smits M. Challenges and opportunities for advanced neuroimaging of glioblastoma. Br J Radiol 2023; 96:20211232. [PMID: 36062962 PMCID: PMC10997013 DOI: 10.1259/bjr.20211232] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2021] [Revised: 08/10/2022] [Accepted: 08/25/2022] [Indexed: 11/05/2022] Open
Abstract
Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.
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Affiliation(s)
- Dylan Henssen
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Frederick Meijer
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Frederik A. Verburg
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
| | - Marion Smits
- Department of Medical Imaging, Radboud university medical
center, Nijmegen, The Netherlands
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10
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Diagnostic Performance of Dynamic Susceptibility Contrast-Enhanced Perfusion-Weighted Imaging in Differentiating Recurrence From Radiation Injury in Postoperative Glioma: A Meta-analysis. J Comput Assist Tomogr 2022; 46:938-944. [PMID: 35969866 DOI: 10.1097/rct.0000000000001356] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
PURPOSE It is important to differentiate between radiation injury (RI) and tumor recurrence (TR) in patients with glioma after surgery and radiotherapy. Our objective was to evaluate the use of dynamic susceptibility contrast-enhanced perfusion-weighted imaging to distinguish between TR and RI in patients with glioma. METHODS Relevant studies published until October 2021 were identified in the PubMed, Embase, and Cochrane Library databases. Stata v12.0 and RevMan 5.3 were used for meta-analysis. RESULTS In total, the meta-analysis incorporated 13 retrospective studies that included 513 patients with 522 lesions. Among the 522 lesions, 329 lesions were TRs and 193 lesions were RIs. The pooled relative cerebral blood volume value was significantly greater in the TR group (P < 0.00001) with significant heterogeneity (I2 = 88%). The pooled sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were 83% (95 confidence interval [CI], 77%-88%), 85% (95 CI, 77%-91%), 5.60 (95 CI, 3.61-8.70), and 0.20 (95% CI, 0.14-0.27), respectively. The heterogeneity of sensitivity (I2 = 33.18%), specificity (I2 = 24.01%), PLR (I2 = 0.00%), and NLR (I2 = 6.68%) is not significant. The area under the receiver operating characteristic curve was 0.91 (95% CI, 0.88-0.93). The 3.0 T magnetic resonance imaging, high-grade glioma, and Europe/America patient subgroups showed PLR greater than 5 and NLR less than 0.2. There was no significant indication of publication bias in the analysis (P = 0.496). CONCLUSIONS It is concluded that dynamic susceptibility contrast-enhanced perfusion-weighted imaging is effective for the diagnostic differentiation between TR and RI in patients with glioma.
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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: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [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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12
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Kouwenberg V, van Santwijk L, Meijer FJA, Henssen D. Reliability of dynamic susceptibility contrast perfusion metrics in pre- and post-treatment glioma. Cancer Imaging 2022; 22:28. [PMID: 35715866 PMCID: PMC9205029 DOI: 10.1186/s40644-022-00466-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Accepted: 05/26/2022] [Indexed: 11/26/2022] Open
Abstract
Background In neuro-oncology, dynamic susceptibility contrast magnetic resonance (DSC-MR) perfusion imaging emerged as a tool to aid in the diagnostic work-up and to surveil effectiveness of treatment. However, it is believed that a significant variability exists with regard to the measured in DSC-MR perfusion parameters. The aim of this study was to assess the observer variability in measured DSC-MR perfusion parameters in patients before and after treatment. In addition, we investigated whether region-of-interest (ROI) shape impacted the observer variability. Materials and methods Twenty non-treated patients and a matched group of twenty patients post-treatment (neurosurgical resection and post-chemoradiotherapy) were included. Six ROIs were independently placed by three readers: circular ROIs and polygonal ROIs covering 1) the tumor hotspot; 2) the peritumoral region (T2/FLAIR-hyperintense region) and 3) the whole tumor region. A two-way random Intra-class coefficient (ICC) model was used to assess variability in measured DSC-MRI perfusion parameters. The perfusion metrics as assessed by the circular and the polygonal ROI were compared by use of the dependent T-test. Results In the non-treated group, circular ROIs showed good–excellent overlap (ICC-values ranging from 0.741–0.963) with the exception of those representing the tumor hotspot. Polygonal ROIs showed lower ICC-values, ranging from 0.113 till 0.856. ROI-placement in the posttreatment group showed to be highly variable with a significant deterioration of ICC-values. Furthermore, perfusion metric assessment in similar tumor regions was not impacted by ROI shape. Discussion This study shows that posttreatment quantitative interpretation of DSC-MR perfusion imaging is highly variable and should be carried out with precaution. Pretreatment assessment of DSC-MR images, however, could be carried out be a single reader in order to provide valid data for further analyses. • DSC-MR perfusion imaging measurements in non-treated glioma is highly reliable between readers, even readers with little experience. • DSC-MR perfusion imaging measurements in treated glioma is show to be inconsistent between readers. • When using DSC-MR perfusion imaging as a quantitative surveillance tool for the recurrence of glioma after treatment, double-reading should be preferred.
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Affiliation(s)
- Valentina Kouwenberg
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Lusien van Santwijk
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Frederick J A Meijer
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands
| | - Dylan Henssen
- Department of Medical Imaging, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 EZ, Nijmegen, The Netherlands.
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13
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Seo M, Ahn KJ, Choi Y, Shin NY, Jang J, Kim BS. Volumetric Measurement of Relative CBV Using T1-Perfusion-Weighted MRI with High Temporal Resolution Compared with Traditional T2*-Perfusion-Weighted MRI in Postoperative Patients with High-Grade Gliomas. AJNR Am J Neuroradiol 2022; 43:864-871. [PMID: 35618428 DOI: 10.3174/ajnr.a7527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 04/08/2022] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE T1-PWI with high temporal resolution may provide a reliable relative CBV value as a valid alternative to T2*-PWI under increased susceptibility. The purpose of this study was to assess the technical and clinical performance of T1-relative CBV in patients with postoperative high-grade gliomas. MATERIALS AND METHODS Forty-five MRIs of 34 patients with proved high-grade gliomas were included. In all MRIs, T1- and T2*-PWIs were both acquired and processed semiautomatically to generate relative CBV maps using a released commercial software. Lesion masks were overlaid on the relative CBV maps, followed by a histogram of the whole VOI. The intraclass correlation coefficient and Bland-Altman plots were used for quantitative and qualitative comparisons. Signal loss from both methods was compared using the Wilcoxon signed-rank test of zero voxel percentage. The MRIs were divided into a progression group (n = 20) and a nonprogression group (n = 14) for receiver operating characteristic curve analysis. RESULTS Fair intertechnique consistency was observed between the 90th percentiles of the T1- and T2*-relative CBV values (intraclass correlation coefficient = 0.558, P < .001). T2*-PWI revealed a significantly higher percentage of near-zero voxels than T1-PWI (17.7% versus 3.1%, P < .001). There was no statistically significant difference between the area under the curve of T1- and T2*-relative CBV (0.811 versus 0.793, P = .835). T1-relative CBV showed 100% sensitivity and 57.1% specificity for the detection of progressive lesions. CONCLUSIONS T1-relative CBV demonstrated exquisite diagnostic performance for detecting progressive lesions in postoperative patients with high-grade gliomas, suggesting the potential role of T1-PWI as a valid alternative to the traditional T2*-PWI.
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Affiliation(s)
- M Seo
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, Republic of Korea
| | - K-J Ahn
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, Republic of Korea
| | - Y Choi
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, Republic of Korea
| | - N-Y Shin
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, Republic of Korea
| | - J Jang
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, Republic of Korea
| | - B-S Kim
- From the Department of Radiology, Seoul St. Mary's Hospital, College of Medicine, the Catholic University of Korea, Seoul, Republic of Korea
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14
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Starck L, Skeie BS, Moen G, Grüner R. Dynamic Susceptibility Contrast MRI May Contribute in Prediction of Stereotactic Radiosurgery Outcome in Brain Metastases. Neurooncol Adv 2022; 4:vdac070. [PMID: 35673606 PMCID: PMC9167634 DOI: 10.1093/noajnl/vdac070] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background Following stereotactic radiosurgery (SRS), predicting treatment response is not possible at an early stage using structural imaging alone. Hence, the current study aims at investigating whether dynamic susceptibility contrast (DSC)-MRI estimated prior to SRS can provide predictive biomarkers in response to SRS treatment and characterize vascular characteristics of pseudo-progression. Methods In this retrospective study, perfusion-weighted DSC-MRI image data acquired with a temporal resolution of 1.45 seconds were collected from 41 patients suffering from brain metastases. Outcome was defined based on lesion volume changes in time (determined on structural images) or death. Motion correction and manual lesion delineation were performed prior to semi-automated, voxel-wise perfusion analysis. Statistical testing was performed using linear regression and a significance threshold at P = .05. Age, sex, primary cancers (pulmonary cancer and melanoma), lesion volume, and dichotomized survival time were added as covariates in the linear regression models (ANOVA). Results Relative cerebral blood volume (rCBV) and relative cerebral blood flow (rCBF) were found to be significantly lower prior to SRS treatment in patients with increasing lesion volume or early death post-SRS (P ≤ .01). Conclusion Unfavorable treatment outcome may be linked to low perfusion prior to SRS. Pseudo-progression may be preceded by a transient rCBF increase post-SRS. However, results should be verified in different or larger patient material.
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Affiliation(s)
- Lea Starck
- Department of Physics and Technology, University of Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | | | - Gunnar Moen
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Renate Grüner
- Department of Physics and Technology, University of Bergen, Norway
- Mohn Medical Imaging and Visualization Centre, Department of Radiology, Haukeland University Hospital, Bergen, Norway
- Department of Radiology, Haukeland University Hospital, Bergen, Norway
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15
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Maiter A, Butteriss D, English P, Lewis J, Hassani A, Bhatnagar P. Assessing the diagnostic accuracy and interobserver agreement of MRI perfusion in differentiating disease progression and pseudoprogression following treatment for glioblastoma in a tertiary UK centre. Clin Radiol 2022; 77:e568-e575. [DOI: 10.1016/j.crad.2022.04.011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 04/12/2022] [Indexed: 11/03/2022]
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16
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Malik DG, Rath TJ, Urcuyo Acevedo JC, Canoll PD, Swanson KR, Boxerman JL, Quarles CC, Schmainda KM, Burns TC, Hu LS. Advanced MRI Protocols to Discriminate Glioma From Treatment Effects: State of the Art and Future Directions. FRONTIERS IN RADIOLOGY 2022; 2:809373. [PMID: 37492687 PMCID: PMC10365126 DOI: 10.3389/fradi.2022.809373] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/04/2021] [Accepted: 03/01/2022] [Indexed: 07/27/2023]
Abstract
In the follow-up treatment of high-grade gliomas (HGGs), differentiating true tumor progression from treatment-related effects, such as pseudoprogression and radiation necrosis, presents an ongoing clinical challenge. Conventional MRI with and without intravenous contrast serves as the clinical benchmark for the posttreatment surveillance imaging of HGG. However, many advanced imaging techniques have shown promise in helping better delineate the findings in indeterminate scenarios, as posttreatment effects can often mimic true tumor progression on conventional imaging. These challenges are further confounded by the histologic admixture that can commonly occur between tumor growth and treatment-related effects within the posttreatment bed. This review discusses the current practices in the surveillance imaging of HGG and the role of advanced imaging techniques, including perfusion MRI and metabolic MRI.
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Affiliation(s)
- Dania G. Malik
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Tanya J. Rath
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
| | - Javier C. Urcuyo Acevedo
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Peter D. Canoll
- Departments of Pathology and Cell Biology, Columbia University, New York, NY, United States
| | - Kristin R. Swanson
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
| | - Jerrold L. Boxerman
- Department of Diagnostic Imaging, Brown University, Providence, RI, United States
| | - C. Chad Quarles
- Department of Neuroimaging Research & Barrow Neuroimaging Innovation Center, Barrow Neurologic Institute, Phoenix, AZ, United States
| | - Kathleen M. Schmainda
- Department of Biophysics & Radiology, Medical College of Wisconsin, Milwaukee, WI, United States
| | - Terry C. Burns
- Departments of Neurologic Surgery and Neuroscience, Mayo Clinic, Rochester, MN, United States
| | - Leland S. Hu
- Department of Radiology, Mayo Clinic, Phoenix, AZ, United States
- Mathematical Neurooncology Lab, Precision Neurotherapeutics Innovation Program, Mayo Clinic, Phoenix, AZ, United States
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Lao Y, Ruan D, Vassantachart A, Fan Z, Ye JC, Chang EL, Chin R, Kaprealian T, Zada G, Shiroishi MS, Sheng K, Yang W. Voxelwise Prediction of Recurrent High-Grade Glioma via Proximity Estimation-Coupled Multidimensional Support Vector Machine. Int J Radiat Oncol Biol Phys 2022; 112:1279-1287. [PMID: 34963559 PMCID: PMC8923952 DOI: 10.1016/j.ijrobp.2021.12.153] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2021] [Revised: 12/09/2021] [Accepted: 12/16/2021] [Indexed: 01/28/2023]
Abstract
PURPOSE To provide early and localized glioblastoma (GBM) recurrence prediction, we introduce a novel postsurgery multiparametric magnetic resonance-based support vector machine (SVM) method coupling with stem cell niche (SCN) proximity estimation. METHODS AND MATERIALS This study used postsurgery magnetic resonance imaging (MRI) scans from 50 patients with recurrent GBM, obtained approximately 2 months before clinically diagnosed recurrence. The main prediction pipeline consisted of a proximity-based estimator to identify regions with high risk of recurrence (HRRs) and an SVM classifier to provide voxelwise prediction in HRRs. The HRRs were estimated using the weighted sum of inverse distances to 2 possible origins of recurrence-the SCN and the tumor cavity. Subsequently, multiparametric voxels (from T1, T1 contrast-enhanced, fluid-attenuated inversion recovery, T2, and apparent diffusion coefficient) within the HRR were grouped into recurrent (warped from the clinical diagnosis) and nonrecurrent subregions and fed into the proximity estimation-coupled SVM classifier (SVMPE). The cohort was randomly divided into 40% and 60% for training and testing, respectively. The trained SVMPE was then extrapolated to an earlier time point for earlier recurrence prediction. As an exploratory analysis, the SVMPE predictive cluster sizes and the image intensities from the 5 magnetic resonance sequences were compared across time to assess the progressive subclinical traces. RESULTS On 2-month prerecurrence MRI scans from 30 test cohort patients, the SVMPE classifier achieved a recall of 0.80, a precision of 0.69, an F1-score of 0.73, and a mean boundary distance of 7.49 mm. Exploratory analysis at early time points showed spatially consistent but significantly smaller subclinical clusters and significantly increased T1 contrast-enhanced and apparent diffusion coefficient values over time. CONCLUSIONS We demonstrated a novel voxelwise early prediction method, SVMPE, for GBM recurrence based on clinical follow-up MR scans. The SVMPE is promising in localizing subclinical traces of recurrence 2 months ahead of clinical diagnosis and may be used to guide more effective personalized early salvage therapy.
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Affiliation(s)
- Yi Lao
- Department of Radiation Oncology, University of California - Los Angeles, USA
| | - Dan Ruan
- Department of Radiation Oncology, University of California - Los Angeles, USA
| | - April Vassantachart
- Department of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, USA
| | - Zhaoyang Fan
- Department of Radiology, Keck School of Medicine of USC, Los Angeles, USA
| | - Jason C. Ye
- Department of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, USA
| | - Eric L. Chang
- Department of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, USA
| | - Robert Chin
- Department of Radiation Oncology, University of California - Los Angeles, USA
| | - Tania Kaprealian
- Department of Radiation Oncology, University of California - Los Angeles, USA
| | - Gabriel Zada
- Department of Neurosurgery, Keck School of Medicine of USC, Los Angeles, USA
| | - Mark S Shiroishi
- Department of Radiology, Keck School of Medicine of USC, Los Angeles, USA
| | - Ke Sheng
- Department of Radiation Oncology, University of California - Los Angeles, USA
| | - Wensha Yang
- Department of Radiation Oncology, Keck School of Medicine of USC, Los Angeles, USA
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Jajodia A, Goel V, Goyal J, Patnaik N, Khoda J, Pasricha S, Gairola M. Combined Diagnostic Accuracy of Diffusion and Perfusion MR Imaging to Differentiate Radiation-Induced Necrosis from Recurrence in Glioblastoma. Diagnostics (Basel) 2022; 12:diagnostics12030718. [PMID: 35328270 PMCID: PMC8947286 DOI: 10.3390/diagnostics12030718] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 02/12/2022] [Accepted: 03/11/2022] [Indexed: 11/26/2022] Open
Abstract
We aimed to use quantitative values derived from perfusion and diffusion-weighted MR imaging (PWI and DWI) to differentiate radiation-induced necrosis (RIN) from tumor recurrence in Glioblastoma (GBM) and investigate the best parameters for improved diagnostic accuracy and clinical decision-making. Methods: A retrospective analysis of follow-up MRI with new enhancing observations was performed in histopathologically confirmed subjects of post-treated GBM, who underwent re-surgical exploration. Quantitative estimation of rCBV (relative cerebral blood volume) from PWI and three methods of apparent diffusion coefficient (ADC) estimation were performed, namely ADC R1 (whole cross-sectional area of tumor), ADC R2 (only solid enhancing lesion), and ADC R3 (central necrosis). ROC curve and logistic regression analysis was completed. A confusion matrix table created using Excel provided the best combination parameters to ameliorate false-positive and false-negative results. Results: Forty-four subjects with a mean age of 46 years (range, 19−70 years) underwent re-surgical exploration with RIN in 28 (67%) and recurrent tumor in 16 (33%) on histopathology. rCBV threshold of >3.4 had the best diagnostic accuracy (AUC = 0.93, 81% sensitivity and 89% specificity). A multiple logistic regression model showed significant contributions from rCBV (p < 0.001) and ADC R3 (p = 0.001). After analysis of confusion matrix ADC R3 > 2032 × 10−6 mm2 achieved 100% specificity with gain in sensitivity (94% vs. 56%). Conclusions: A combination of parameters had better diagnostic performance, and a stepwise combination of rCBV and ADC R3 obviated unnecessary biopsies in 10% (3/28), leading to improved clinical decision-making.
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Affiliation(s)
- Ankush Jajodia
- Department of Radiology, McMaster University, Hamilton Health Sciences, Hamilton, ON L8V 5C2, Canada
- Correspondence: (A.J.); (V.G.); Tel.: +91-97-6510-7872 (V.G.)
| | - Varun Goel
- Department of Medical Oncology, Rajiv Gandhi Cancer Institute and Research Centre, Delhi 110085, India
- Correspondence: (A.J.); (V.G.); Tel.: +91-97-6510-7872 (V.G.)
| | - Jitin Goyal
- Department of Radiology, Rajiv Gandhi Cancer Institute and Research Centre, Delhi 110085, India; (J.G.); (J.K.)
| | - Nivedita Patnaik
- Department of Laboratory & Histopathology, Rajiv Gandhi Cancer Institute, Delhi 110085, India; (N.P.); (S.P.)
| | - Jeevitesh Khoda
- Department of Radiology, Rajiv Gandhi Cancer Institute and Research Centre, Delhi 110085, India; (J.G.); (J.K.)
| | - Sunil Pasricha
- Department of Laboratory & Histopathology, Rajiv Gandhi Cancer Institute, Delhi 110085, India; (N.P.); (S.P.)
| | - Munish Gairola
- Department of Radiation Oncology, Rajiv Gandhi Cancer Institute, Delhi 110085, India;
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19
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Diao W, Su D, Cao Y, Jia Z. The diagnostic accuracy of O-(2-18F-fluoroethyl)-L-tyrosine parameters for the differentiation of brain tumour progression from treatment-related changes. Nucl Med Commun 2022; 43:350-358. [PMID: 35102078 DOI: 10.1097/mnm.0000000000001524] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
BACKGROUND 18F-fluoro-ethyl-tyrosine (18F-FET) is recommended to distinguish brain tumours post-therapeutic true progression (including recurrent and metastatic brain tumours) and treatment-related change (TRC). However, many parameters of 18F-FET can be used for this differential diagnosis. Our purpose was to investigate the diagnostic accuracy of various 18F-FET parameters to differentiate true progression from TRC. METHODS We performed a literature search using the following databases: the PubMed, Embase and Web of Science databases up to 29 November 2020. We included studies that reported the diagnostic test results of 18F-FET to distinguish true progression from TRC. The Quality Assessment of Diagnostic Accuracy Studies-2 tool was used to evaluate the quality of the included studies. The diagnostic accuracy of various parameters was pooled using a random-effects model. RESULTS We included 17 eligible studies (nine parameters). For static parameters of 18F-FET, the maximum and mean tumour-to-brain ratios (TBRmax and TBRmean) showed similar pooled sensitivities of 82% [95% confidence interval (CI), 80-85%) and 82% (95% CI, 78-85%), respectively. Among the three kinetic parameters (slope, time to peak and kinetic pattern), the kinetic pattern presented the optimal diagnostic value with a pooled sensitivity of 81% (95% CI, 75-86%). When combining the static and kinetic parameters, the diagnostic performance of 18F-FET was significantly improved, with a pooled sensitivity of 90% (95% CI, 84-94%) in the combination of TBR and kinetic patterns. CONCLUSIONS 18F-FET static parameters alone showed a comparably high sensitivity in the differentiation between brain tumour true progression and TRC. Combining static and kinetic parameters provided improved diagnostic performance.
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Affiliation(s)
- Wei Diao
- Department of Nuclear Medicine, West China Hospital of Sichuan University, Chengdu, Peoples Republic of China
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20
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Sidibe I, Tensaouti F, Roques M, Cohen-Jonathan-Moyal E, Laprie A. Pseudoprogression in Glioblastoma: Role of Metabolic and Functional MRI-Systematic Review. Biomedicines 2022; 10:biomedicines10020285. [PMID: 35203493 PMCID: PMC8869397 DOI: 10.3390/biomedicines10020285] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2021] [Revised: 01/20/2022] [Accepted: 01/22/2022] [Indexed: 12/16/2022] Open
Abstract
Background: Glioblastoma is the most frequent malignant primitive brain tumor in adults. The treatment includes surgery, radiotherapy, and chemotherapy. During follow-up, combined chemoradiotherapy can induce treatment-related changes mimicking tumor progression on medical imaging, such as pseudoprogression (PsP). Differentiating PsP from true progression (TP) remains a challenge for radiologists and oncologists, who need to promptly start a second-line treatment in the case of TP. Advanced magnetic resonance imaging (MRI) techniques such as diffusion-weighted imaging, perfusion MRI, and proton magnetic resonance spectroscopic imaging are more efficient than conventional MRI in differentiating PsP from TP. None of these techniques are fully effective, but current advances in computer science and the advent of artificial intelligence are opening up new possibilities in the imaging field with radiomics (i.e., extraction of a large number of quantitative MRI features describing tumor density, texture, and geometry). These features are used to build predictive models for diagnosis, prognosis, and therapeutic response. Method: Out of 7350 records for MR spectroscopy, GBM, glioma, recurrence, diffusion, perfusion, pseudoprogression, radiomics, and advanced imaging, we screened 574 papers. A total of 228 were eligible, and we analyzed 72 of them, in order to establish the role of each imaging modality and the usefulness and limitations of radiomics analysis.
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Affiliation(s)
- Ingrid Sidibe
- Radiation Oncology Department, Claudius Regaud Institute, Toulouse University Cancer Institute Oncopole, 31100 Toulouse, France; (I.S.); (F.T.); (E.C.-J.-M.)
- Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier INSERM, 31100 Toulouse, France;
| | - Fatima Tensaouti
- Radiation Oncology Department, Claudius Regaud Institute, Toulouse University Cancer Institute Oncopole, 31100 Toulouse, France; (I.S.); (F.T.); (E.C.-J.-M.)
- Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier INSERM, 31100 Toulouse, France;
| | - Margaux Roques
- Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier INSERM, 31100 Toulouse, France;
- Radiology Department, Purpan University Hospital, 31300 Toulouse, France
| | - Elizabeth Cohen-Jonathan-Moyal
- Radiation Oncology Department, Claudius Regaud Institute, Toulouse University Cancer Institute Oncopole, 31100 Toulouse, France; (I.S.); (F.T.); (E.C.-J.-M.)
- INSERM UMR.1037-Cancer Research Center of Toulouse (CRCT)/University Paul Sabatier Toulouse III, 31100 Toulouse, France
| | - Anne Laprie
- Radiation Oncology Department, Claudius Regaud Institute, Toulouse University Cancer Institute Oncopole, 31100 Toulouse, France; (I.S.); (F.T.); (E.C.-J.-M.)
- Toulouse NeuroImaging Center (ToNIC), University of Toulouse Paul Sabatier INSERM, 31100 Toulouse, France;
- Correspondence:
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21
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El-Abtah ME, Talati P, Fu M, Chun B, Clark P, Peters A, Ranasinghe A, He J, Rapalino O, Batchelor TT, Gilberto Gonzalez R, Curry WT, Dietrich J, Gerstner ER, Ratai EM. Magnetic resonance spectroscopy outperforms perfusion in distinguishing between pseudoprogression and disease progression in patients with glioblastoma. Neurooncol Adv 2022; 4:vdac128. [PMID: 36071927 PMCID: PMC9446677 DOI: 10.1093/noajnl/vdac128] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Background
There is a need to establish biomarkers that distinguish between pseudoprogression (PsP) and true tumor progression in patients with glioblastoma (GBM) treated with chemoradiation.
Methods
We analyzed magnetic resonance spectroscopic imaging (MRSI) and dynamic susceptibility contrast (DSC) MR perfusion data in patients with GBM with PsP or disease progression after chemoradiation. MRSI metabolites of interest included intratumoral choline (Cho), myo-inositol (mI), glutamate + glutamine (Glx), lactate (Lac), and creatine on the contralateral hemisphere (c-Cr). Student T-tests and area under the ROC curve analyses were used to detect group differences in metabolic ratios and their ability to predict clinical status, respectively.
Results
28 subjects (63 ± 9 years, 19 men) were evaluated. Subjects with true progression (n = 20) had decreased enhancing region mI/c-Cr (P = .011), a marker for more aggressive tumors, compared to those with PsP, which predicted tumor progression (AUC: 0.84 [0.76, 0.92]). Those with true progression had elevated Lac/Glx (P = .0009), a proxy of the Warburg effect, compared to those with PsP which predicted tumor progression (AUC: 0.84 [0.75, 0.92]). Cho/c-Cr did not distinguish between PsP and true tumor progression. Despite rCBV (AUC: 0.70 [0.60, 0.80]) and rCBF (AUC: 0.75 [0.65, 0.84]) being individually predictive of tumor response, they added no additional predictive value when combined with MRSI metabolic markers.
Conclusions
Incorporating enhancing lesion MRSI measures of mI/c-Cr and Lac/Glx into brain tumor imaging protocols can distinguish between PsP and true progression and inform patient management decisions.
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Affiliation(s)
- Mohamed E El-Abtah
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Pratik Talati
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Neurosurgery, Massachusetts General Hospital , Boston, Massachusetts , USA
| | - Melanie Fu
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Benjamin Chun
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Patrick Clark
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Anna Peters
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Anthony Ranasinghe
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Julian He
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
| | - Otto Rapalino
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
| | - Tracy T Batchelor
- Harvard Medical School , Boston, Massachusetts , USA
- Brigham and Women’s Hospital, Neurosciences Center , Boston, Massachusetts , USA
| | - R Gilberto Gonzalez
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
| | - William T Curry
- Department of Neurosurgery, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Jorg Dietrich
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Elizabeth R Gerstner
- Harvard Medical School , Boston, Massachusetts , USA
- Massachusetts General Hospital Cancer Center , Boston, Massachusetts , USA
| | - Eva-Maria Ratai
- Athinoula A. Martinos Center for Biomedical Imaging , Charlestown, Massachusetts , USA
- Department of Radiology, Massachusetts General Hospital , Boston, Massachusetts , USA
- Harvard Medical School , Boston, Massachusetts , USA
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22
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Fu R, Szidonya L, Barajas RF, Ambady P, Varallyay C, Neuwelt EA. Diagnostic performance of DSC perfusion MRI to distinguish tumor progression and treatment-related changes: a systematic review and meta-analysis. Neurooncol Adv 2022; 4:vdac027. [PMID: 35386567 PMCID: PMC8982196 DOI: 10.1093/noajnl/vdac027] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background In patients with high-grade glioma (HGG), true disease progression and treatment-related changes often appear similar on magnetic resonance imaging (MRI), making it challenging to evaluate therapeutic response. Dynamic susceptibility contrast (DSC) MRI has been extensively studied to differentiate between disease progression and treatment-related changes. This systematic review evaluated and synthesized the evidence for using DSC MRI to distinguish true progression from treatment-related changes. Methods We searched Ovid MEDLINE and the Ovid MEDLINE in-process file (January 2005-October 2019) and the reference lists. Studies on test performance of DSC MRI using relative cerebral blood volume in HGG patients were included. One investigator abstracted data, and a second investigator confirmed them; two investigators independently assessed study quality. Meta-analyses were conducted to quantitatively synthesize area under the receiver operating curve (AUROC), sensitivity, and specificity. Results We screened 1177 citations and included 28 studies with 638 patients with true tumor progression, and 430 patients with treatment-related changes. Nineteen studies reported AUROC and the combined AUROC is 0.85 (95% CI, 0.81-0.90). All studies contributed data for sensitivity and specificity, and the pooled sensitivity and specificity are 0.84 (95% CI, 0.80-0.88), and 0.78 (95% CI, 0.72-0.83). Extensive subgroup analyses based on study, treatment, and imaging characteristics generally showed similar results. Conclusions There is moderate strength of evidence that relative cerebral blood volume obtained from DSC imaging demonstrated "excellent" ability to discriminate true tumor progression from treatment-related changes, with robust sensitivity and specificity.
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Affiliation(s)
- Rongwei Fu
- Oregon Health & Science University-Portland State University, School of Public Health, Portland, Oregon, USA.,Department of Medical Informatics & Clinical Epidemiology, Oregon Health & Science University, Portland, Oregon, USA
| | - Laszlo Szidonya
- Department of Radiology, Oregon Health & Science University, Portland, Oregon, USA.,Neuro-Oncology Program, Oregon Health & Science University, Portland, Oregon, USA.,Heart and Vascular Center, Diagnostic Radiology, Semmelweis University, Budapest, Hungary
| | - Ramon F Barajas
- Department of Radiology, Oregon Health & Science University, Portland, Oregon, USA.,Advanced Imaging Research Center, Oregon Health & Science University, Portland, Oregon, USA.,Knight Cancer Institute Translational Oncology Program, Oregon Health & Science University, Portland, Oregon, USA
| | - Prakash Ambady
- Neuro-Oncology Program, Oregon Health & Science University, Portland, Oregon, USA
| | | | - Edward A Neuwelt
- Neuro-Oncology Program, Oregon Health & Science University, Portland, Oregon, USA.,Department of Neurosurgery, Oregon Health and Sciences University, Portland, Oregon, USA.,Office of Research and Development, Department of Veterans Affairs Medical Center, Portland, Oregon, USA
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23
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Roesler R, Dini SA, Isolan GR. Neuroinflammation and immunoregulation in glioblastoma and brain metastases: Recent developments in imaging approaches. Clin Exp Immunol 2021; 206:314-324. [PMID: 34591980 DOI: 10.1111/cei.13668] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Revised: 09/23/2021] [Accepted: 09/24/2021] [Indexed: 01/12/2023] Open
Abstract
Brain tumors and brain metastases induce changes in brain tissue remodeling that lead to immunosuppression and trigger an inflammatory response within the tumor microenvironment. These immune and inflammatory changes can influence invasion and metastasis. Other neuroinflammatory and necrotic lesions may occur in patients with brain cancer or brain metastases as sequelae from treatment with radiotherapy. Glioblastoma (GBM) is the most aggressive primary malignant brain cancer in adults. Imaging methods such as positron emission tomography (PET) and different magnetic resonance imaging (MRI) techniques are highly valuable for the diagnosis and therapeutic evaluation of GBM and other malignant brain tumors. However, differentiating between tumor tissue and inflamed brain tissue with imaging protocols remains a challenge. Here, we review recent advances in imaging methods that have helped to improve the specificity of primary tumor diagnosis versus evaluation of inflamed and necrotic brain lesions. We also comment on advances in differentiating metastasis from neuroinflammation processes. Recent advances include the radiosynthesis of 18 F-FIMP, an L-type amino acid transporter 1 (LAT1)-specific PET probe that allows clearer differentiation between tumor tissue and inflammation compared to previous probes, and the combination of different advanced imaging protocols with the inclusion of radiomics and machine learning algorithms.
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Affiliation(s)
- Rafael Roesler
- Department of Pharmacology, Institute for Basic Health Sciences, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil.,Cancer and Neurobiology Laboratory, Experimental Research Center, Clinical Hospital (CPE-HCPA), Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Simone Afonso Dini
- The Center for Advanced Neurology and Neurosurgery (CEANNE)-Brazil, Porto Alegre, RS, Brazil
| | - Gustavo R Isolan
- The Center for Advanced Neurology and Neurosurgery (CEANNE)-Brazil, Porto Alegre, RS, Brazil.,Mackenzie Evangelical University of Paraná (FEMPAR), Curitiba, PR, Brazil
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24
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Advanced Imaging and Computational Techniques for the Diagnostic and Prognostic Assessment of Malignant Gliomas. Cancer J 2021; 27:344-352. [PMID: 34570448 DOI: 10.1097/ppo.0000000000000545] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
ABSTRACT Advanced imaging techniques provide a powerful tool to assess the intratumoral and intertumoral heterogeneity of gliomas. Advances in the molecular understanding of glioma subgroups may allow improved diagnostic assessment combining imaging and molecular tumor features, with enhanced prognostic utility and implications for patient treatment. In this article, a comprehensive overview of the physiologic basis for conventional and advanced imaging techniques is presented, and clinical applications before and after treatment are discussed. An introduction to the principles of radiomics and the advanced integration of imaging, clinical outcomes, and genomic data highlights the future potential for this field of research to better stratify and select patients for standard as well as investigational therapies.
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25
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Li C, Yi C, Chen Y, Xi S, Guo C, Yang Q, Wang J, Sai K, Zhang J, Ke C, Chen F, Lv Y, Zhang X, Chen Z. Identify glioma recurrence and treatment effects with triple-tracer PET/CT. BMC Med Imaging 2021; 21:92. [PMID: 34059015 PMCID: PMC8165792 DOI: 10.1186/s12880-021-00624-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Accepted: 05/24/2021] [Indexed: 02/16/2023] Open
Abstract
Background Differential diagnosis of tumour recurrence (TuR) from treatment effects (TrE), mostly induced by radiotherapy and chemotherapy, is still difficult by using conventional computed tomography (CT) or magnetic resonance (MR) imaging. We have investigated the diagnostic performance of PET/CT with 3 tracers, 13N-NH3, 18F-FDOPA, and 18F-FDG, to identify TuR and TrE in glioma patients following treatment. Methods Forty-three patients with MR-suspected recurrent glioma were included. The maximum and mean standardized uptake values (SUVmax and SUVmean) of the lesion and the lesion-to-normal grey-matter cortex uptake (L/G) ratio were obtained from each tracer PET/CT. TuR or TrE was determined by histopathology or clinical MR follow-up for at least 6 months. Results In this cohort, 34 patients were confirmed to have TuR, and 9 patients met the diagnostic standard of TrE. The SUVmax and SUVmean of 13N-NH3 and 18F-FDOPA PET/CT at TuR lesions were significantly higher compared with normal brain tissue (13N-NH3 0.696 ± 0.558, 0.625 ± 0.507 vs 0.486 ± 0.413; 18F-FDOPA 0.455 ± 0.518, 0.415 ± 0.477 vs 0.194 ± 0.203; both P < 0.01), but there was no significant difference in 18F-FDG (6.918 ± 3.190, 6.016 ± 2.807 vs 6.356 ± 3.104, P = 0.290 and 0.493). L/G ratios of 13N-NH3 and 18F-FDOPA were significantly higher in TuR than in TrE group (13N-NH3, 1.573 ± 0.099 vs 1.025 ± 0.128, P = 0.008; 18F-FDOPA, 2.729 ± 0.131 vs 1.514 ± 0.141, P < 0.001). The sensitivity, specificity and AUC (area under the curve) by ROC (receiver operating characteristic) analysis were 57.7%, 100% and 0.803, for 13N-NH3; 84.6%, 100% and 0.938, for 18F-FDOPA; and 80.8%, 100%, and 0.952, for the combination, respectively. Conclusion Our results suggest that although multiple tracer PET/CT may improve differential diagnosis efficacy, for glioma TuR from TrE, 18F-FDOPA PET-CT is the most reliable. The combination of 18F-FDOPA and 13N-NH3 does not increase the diagnostic efficiency, while 18F-FDG is not worthy for differential diagnosis of glioma TuR and TrE.
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Affiliation(s)
- Cong Li
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China
| | - Chang Yi
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China
| | - Yingshen Chen
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China
| | - Shaoyan Xi
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China
| | - Chengcheng Guo
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China
| | - Qunying Yang
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China
| | - Jian Wang
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China
| | - Ke Sai
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China
| | - Ji Zhang
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China
| | - Chao Ke
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China
| | - Fanfan Chen
- Department of Neurosurgery, The First Affiliated Hospital of Shenzhen University/Shenzhen Second People's Hospital, Shenzhen, 518035, China
| | - Yanchun Lv
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China
| | - Xiangsong Zhang
- Department of Nuclear Medicine, The First Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510080, China.
| | - Zhongping Chen
- Sun Yat-Sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, 510060, China.
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26
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Siakallis L, Sudre CH, Mulholland P, Fersht N, Rees J, Topff L, Thust S, Jager R, Cardoso MJ, Panovska-Griffiths J, Bisdas S. Longitudinal structural and perfusion MRI enhanced by machine learning outperforms standalone modalities and radiological expertise in high-grade glioma surveillance. Neuroradiology 2021; 63:2047-2056. [PMID: 34047805 PMCID: PMC8589799 DOI: 10.1007/s00234-021-02719-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 04/12/2021] [Indexed: 11/30/2022]
Abstract
PURPOSE Surveillance of patients with high-grade glioma (HGG) and identification of disease progression remain a major challenge in neurooncology. This study aimed to develop a support vector machine (SVM) classifier, employing combined longitudinal structural and perfusion MRI studies, to classify between stable disease, pseudoprogression and progressive disease (3-class problem). METHODS Study participants were separated into two groups: group I (total cohort: 64 patients) with a single DSC time point and group II (19 patients) with longitudinal DSC time points (2-3). We retrospectively analysed 269 structural MRI and 92 dynamic susceptibility contrast perfusion (DSC) MRI scans. The SVM classifier was trained using all available MRI studies for each group. Classification accuracy was assessed for different feature dataset and time point combinations and compared to radiologists' classifications. RESULTS SVM classification based on combined perfusion and structural features outperformed radiologists' classification across all groups. For the identification of progressive disease, use of combined features and longitudinal DSC time points improved classification performance (lowest error rate 1.6%). Optimal performance was observed in group II (multiple time points) with SVM sensitivity/specificity/accuracy of 100/91.67/94.7% (first time point analysis) and 85.71/100/94.7% (longitudinal analysis), compared to 60/78/68% and 70/90/84.2% for the respective radiologist classifications. In group I (single time point), the SVM classifier also outperformed radiologists' classifications with sensitivity/specificity/accuracy of 86.49/75.00/81.53% (SVM) compared to 75.7/68.9/73.84% (radiologists). CONCLUSION Our results indicate that utilisation of a machine learning (SVM) classifier based on analysis of longitudinal perfusion time points and combined structural and perfusion features significantly enhances classification outcome (p value= 0.0001).
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Affiliation(s)
- Loizos Siakallis
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, Queen Square, London, WC1N 3BG, UK.
| | - Carole H Sudre
- Translational Imaging Group, Centre for Medical Image Computing, University College London , London, UK.,Department of Medical Physics, University College London, London, UK
| | - Paul Mulholland
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Naomi Fersht
- Department of Oncology, University College London Hospitals NHS Foundation Trust, London, UK
| | - Jeremy Rees
- Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK.,Department of Neurooncology, National Hospital for Neurology and Neurosurgery, London, UK
| | - Laurens Topff
- Department of Radiology, The Netherlands Cancer Institute, Amsterdam, Netherlands
| | - Steffi Thust
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, Queen Square, London, WC1N 3BG, UK
| | - Rolf Jager
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, Queen Square, London, WC1N 3BG, UK.,Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK
| | - M Jorge Cardoso
- Translational Imaging Group, Centre for Medical Image Computing, University College London , London, UK
| | - Jasmina Panovska-Griffiths
- Institute for Global Health, University College London, London, UK.,The Queen's College, University of Oxford, Oxford, UK
| | - Sotirios Bisdas
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, Queen Square, London, WC1N 3BG, UK.,Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK
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27
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Trinh A, Wintermark M, Iv M. Clinical Review of Computed Tomography and MR Perfusion Imaging in Neuro-Oncology. Radiol Clin North Am 2021; 59:323-334. [PMID: 33926680 DOI: 10.1016/j.rcl.2021.01.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Neuroimaging plays an essential role in the initial diagnosis and continued surveillance of intracranial neoplasms. The advent of perfusion techniques with computed tomography and MR imaging have proven useful in neuro-oncology, offering enhanced approaches for tumor grading, guiding stereotactic biopsies, and monitoring treatment efficacy. Perfusion imaging can help to identify treatment-related processes, such as radiation necrosis, pseudoprogression, and pseudoregression, and can help to inform treatment-related decision making. Perfusion imaging is useful to differentiate between tumor types and between tumor and nonneoplastic conditions. This article reviews the clinical relevance and implications of perfusion imaging in neuro-oncology and highlights promising perfusion biomarkers.
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Affiliation(s)
- Austin Trinh
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University, 300 Pasteur Drive, Grant Building, Room S031, Stanford, CA 94305-5105, USA
| | - Max Wintermark
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University, 300 Pasteur Drive, Grant Building, Room S047, Stanford, CA 94305-5105, USA. https://twitter.com/mwNRAD
| | - Michael Iv
- Division of Neuroimaging and Neurointervention, Department of Radiology, Stanford University, 300 Pasteur Drive, Grant Building, Room S031E, Stanford, CA 94305-5105, USA.
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28
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Le Fèvre C, Constans JM, Chambrelant I, Antoni D, Bund C, Leroy-Freschini B, Schott R, Cebula H, Noël G. Pseudoprogression versus true progression in glioblastoma patients: A multiapproach literature review. Part 2 - Radiological features and metric markers. Crit Rev Oncol Hematol 2021; 159:103230. [PMID: 33515701 DOI: 10.1016/j.critrevonc.2021.103230] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 01/10/2021] [Accepted: 01/16/2021] [Indexed: 12/28/2022] Open
Abstract
After chemoradiotherapy for glioblastoma, pseudoprogression can occur and must be distinguished from true progression to correctly manage glioblastoma treatment and follow-up. Conventional treatment response assessment is evaluated via conventional MRI (contrast-enhanced T1-weighted and T2/FLAIR), which is unreliable. The emergence of advanced MRI techniques, MR spectroscopy, and PET tracers has improved pseudoprogression diagnostic accuracy. This review presents a literature review of the different imaging techniques and potential imaging biomarkers to differentiate pseudoprogression from true progression.
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Affiliation(s)
- Clara Le Fèvre
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Jean-Marc Constans
- Department of Radiology, Amiens-Picardie University Hospital, 1 rond-point du Professeur Christian Cabrol, 80054, Amiens Cedex 1, France.
| | - Isabelle Chambrelant
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Delphine Antoni
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Caroline Bund
- Department of Nuclear Medicine, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Benjamin Leroy-Freschini
- Department of Nuclear Medicine, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Roland Schott
- Departement of Medical Oncology, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
| | - Hélène Cebula
- Departement of Neurosurgery, Hautepierre University Hospital, 1, avenue Molière, 67200, Strasbourg, France.
| | - Georges Noël
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France.
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29
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Le Fèvre C, Lhermitte B, Ahle G, Chambrelant I, Cebula H, Antoni D, Keller A, Schott R, Thiery A, Constans JM, Noël G. Pseudoprogression versus true progression in glioblastoma patients: A multiapproach literature review: Part 1 - Molecular, morphological and clinical features. Crit Rev Oncol Hematol 2020; 157:103188. [PMID: 33307200 DOI: 10.1016/j.critrevonc.2020.103188] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2020] [Revised: 11/12/2020] [Accepted: 11/23/2020] [Indexed: 01/04/2023] Open
Abstract
With new therapeutic protocols, more patients treated for glioblastoma have experienced a suspicious radiologic image of progression (pseudoprogression) during follow-up. Pseudoprogression should be differentiated from true progression because the disease management is completely different. In the case of pseudoprogression, the follow-up continues, and the patient is considered stable. In the case of true progression, a treatment adjustment is necessary. Presently, a pseudoprogression diagnosis certainly needs to be pathologically confirmed. Some important efforts in the radiological, histopathological, and genomic fields have been made to differentiate pseudoprogression from true progression, and the assessment of response criteria exists but remains limited. The aim of this paper is to highlight clinical and pathological markers to differentiate pseudoprogression from true progression through a literature review.
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Affiliation(s)
- Clara Le Fèvre
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Benoît Lhermitte
- Département of Pathology, Hautepierre University Hospital, 1, Avenue Molière, 67200, Strasbourg, France
| | - Guido Ahle
- Departement of Neurology, Hôpitaux Civils de Colmar, 39 Avenue de la Liberté, 68024, Colmar, France
| | - Isabelle Chambrelant
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Hélène Cebula
- Departement of Neurosurgery, Hautepierre University Hospital, 1, Avenue Molière, 67200, Strasbourg, France
| | - Delphine Antoni
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Audrey Keller
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Roland Schott
- Departement of Medical Oncology, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Alicia Thiery
- Department of Public Health, ICANS, Institut Cancérologie Strasbourg Europe, 17 rue Albert Calmette, 67200, Strasbourg Cedex, France
| | - Jean-Marc Constans
- Department of Radiology, Amiens-Pïcardie University Hospital, 1 rond point du Professeur Christian Cabrol, 80054 Amiens Cedex 1, France
| | - Georges Noël
- Department of Radiotherapy, ICANS, Institut Cancérologie Strasbourg Europe, 17 Rue Albert Calmette, 67200, Strasbourg Cedex, France.
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Tsakiris C, Siempis T, Alexiou GA, Zikou A, Sioka C, Voulgaris S, Argyropoulou MI. Differentiation Between True Tumor Progression of Glioblastoma and Pseudoprogression Using Diffusion-Weighted Imaging and Perfusion-Weighted Imaging: Systematic Review and Meta-analysis. World Neurosurg 2020; 144:e100-e109. [DOI: 10.1016/j.wneu.2020.07.218] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2020] [Revised: 07/28/2020] [Accepted: 07/30/2020] [Indexed: 01/08/2023]
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Boxerman JL, Quarles CC, Hu LS, Erickson BJ, Gerstner ER, Smits M, Kaufmann TJ, Barboriak DP, Huang RH, Wick W, Weller M, Galanis E, Kalpathy-Cramer J, Shankar L, Jacobs P, Chung C, van den Bent MJ, Chang S, Al Yung WK, Cloughesy TF, Wen PY, Gilbert MR, Rosen BR, Ellingson BM, Schmainda KM. Consensus recommendations for a dynamic susceptibility contrast MRI protocol for use in high-grade gliomas. Neuro Oncol 2020; 22:1262-1275. [PMID: 32516388 PMCID: PMC7523451 DOI: 10.1093/neuonc/noaa141] [Citation(s) in RCA: 112] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Despite the widespread clinical use of dynamic susceptibility contrast (DSC) MRI, DSC-MRI methodology has not been standardized, hindering its utilization for response assessment in multicenter trials. Recently, the DSC-MRI Standardization Subcommittee of the Jumpstarting Brain Tumor Drug Development Coalition issued an updated consensus DSC-MRI protocol compatible with the standardized brain tumor imaging protocol (BTIP) for high-grade gliomas that is increasingly used in the clinical setting and is the default MRI protocol for the National Clinical Trials Network. After reviewing the basis for controversy over DSC-MRI protocols, this paper provides evidence-based best practices for clinical DSC-MRI as determined by the Committee, including pulse sequence (gradient echo vs spin echo), BTIP-compliant contrast agent dosing (preload and bolus), flip angle (FA), echo time (TE), and post-processing leakage correction. In summary, full-dose preload, full-dose bolus dosing using intermediate (60°) FA and field strength-dependent TE (40-50 ms at 1.5 T, 20-35 ms at 3 T) provides overall best accuracy and precision for cerebral blood volume estimates. When single-dose contrast agent usage is desired, no-preload, full-dose bolus dosing using low FA (30°) and field strength-dependent TE provides excellent performance, with reduced contrast agent usage and elimination of potential systematic errors introduced by variations in preload dose and incubation time.
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Affiliation(s)
- Jerrold L Boxerman
- Department of Diagnostic Imaging, Warren Alpert Medical School, Brown University, Providence, Rhode Island, USA
- Representative of the Eastern Cooperative Oncology Group–American College of Radiology Imaging Network (ECOG-ACRIN) Cancer Research Group
- Representative of the American Society of Neuroradiology (ASNR)
- Representative of the American Society of Functional Neuroradiology (ASFNR)
| | - Chad C Quarles
- Department of Neuroimaging Research and Barrow Neuroimaging Innovation Center, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Leland S Hu
- Department of Radiology, Mayo Clinic, Phoenix, Arizona, USA
- Representative of the Alliance for Clinical Trials in Oncology
- Representative of the American Society of Neuroradiology (ASNR)
| | - Bradley J Erickson
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Representative of the Alliance for Clinical Trials in Oncology
- Representative of the RSNA Quantitative Imaging Biomarker Alliance (QIBA)
- Representative of the American Society of Neuroradiology (ASNR)
| | - Elizabeth R Gerstner
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA
- Representative of the Adult Brain Tumor Consortium (ABTC)
| | - Marion Smits
- Department of Radiology and Nuclear Medicine, Erasmus MC–University Medical Center Rotterdam, Rotterdam, Netherlands
- Representative of the European Organisation for Research and Treatment of Cancer (EORTC)
| | - Timothy J Kaufmann
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Representative of the Alliance for Clinical Trials in Oncology
| | - Daniel P Barboriak
- Department of Radiology, Duke University School of Medicine, Durham, North Carolina, USA
- Representative of the Eastern Cooperative Oncology Group–American College of Radiology Imaging Network (ECOG-ACRIN) Cancer Research Group
- Representative of the RSNA Quantitative Imaging Biomarker Alliance (QIBA)
- Representative of the American Society of Neuroradiology (ASNR)
| | - Raymond H Huang
- Department of Radiology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, Massachusetts, USA
| | - Wolfgang Wick
- Department of Neurooncology, National Center of Tumor Disease, University Clinic Heidelberg, Heidelberg, Germany
- Representative of the European Organisation for Research and Treatment of Cancer (EORTC)
| | - Michael Weller
- Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland
- Representative of the European Organisation for Research and Treatment of Cancer (EORTC)
| | - Evanthia Galanis
- Division of Medical Oncology, Department of Oncology, Mayo Clinic, Rochester, Minnesota, USA
- Representative of the Alliance for Clinical Trials in Oncology
| | - Jayashree Kalpathy-Cramer
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Lalitha Shankar
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland, USA
| | - Paula Jacobs
- Division of Cancer Treatment and Diagnosis, National Cancer Institute (NCI), Bethesda, Maryland, USA
| | - Caroline Chung
- Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
- Representative of the Alliance for Clinical Trials in Oncology
| | - Martin J van den Bent
- Department of Neuro-Oncology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
- Representative of the European Organisation for Research and Treatment of Cancer (EORTC)
| | - Susan Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California, USA
| | - W K Al Yung
- Department of Neuro-Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, USA
| | - Timothy F Cloughesy
- UCLA Neuro-Oncology Program and UCLA Brain Tumor Imaging Laboratory (BTIL), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Neurology, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber/Brigham and Women’s Cancer Center, Harvard Medical School, Boston, Massachusetts, USA
- Representative of the Adult Brain Tumor Consortium (ABTC)
| | - Mark R Gilbert
- Neuro-Oncology Branch, National Cancer Institute (NCI), Bethesda, Maryland, USA
- Representative of the Radiation Therapy Oncology Group (RTOG)
| | - Bruce R Rosen
- Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Benjamin M Ellingson
- UCLA Neuro-Oncology Program and UCLA Brain Tumor Imaging Laboratory (BTIL), David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Departments of Radiological Sciences, Psychiatry, and Biobehavioral Sciences, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Representative of the Adult Brain Tumor Consortium (ABTC)
- Representative of the Ivy Consortium for Early Phase Clinical Trials
- Representative of the Eastern Cooperative Oncology Group–American College of Radiology Imaging Network (ECOG-ACRIN) Cancer Research Group
- Representative of the RSNA Quantitative Imaging Biomarker Alliance (QIBA)
- Representative of the American Society of Neuroradiology (ASNR)
| | - Kathleen M Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, Wisconsin, USA
- Representative of the Eastern Cooperative Oncology Group–American College of Radiology Imaging Network (ECOG-ACRIN) Cancer Research Group
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Soni N, Ora M, Mohindra N, Menda Y, Bathla G. Diagnostic Performance of PET and Perfusion-Weighted Imaging in Differentiating Tumor Recurrence or Progression from Radiation Necrosis in Posttreatment Gliomas: A Review of Literature. AJNR Am J Neuroradiol 2020; 41:1550-1557. [PMID: 32855194 DOI: 10.3174/ajnr.a6685] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2020] [Accepted: 05/29/2020] [Indexed: 01/22/2023]
Abstract
Tumor resection followed by chemoradiation remains the current criterion standard treatment for high-grade gliomas. Regardless of aggressive treatment, tumor recurrence and radiation necrosis are 2 different outcomes. Differentiation of tumor recurrence from radiation necrosis remains a critical problem in these patients because of considerable overlap in clinical and imaging presentations. Contrast-enhanced MR imaging is the universal imaging technique for diagnosis, treatment evaluation, and detection of recurrence of high-grade gliomas. PWI and PET with novel radiotracers have an evolving role for monitoring treatment response in high-grade gliomas. In the literature, there is no clear consensus on the superiority of either technique or their complementary information. This review aims to elucidate the diagnostic performance of individual and combined use of functional (PWI) and metabolic (PET) imaging modalities to distinguish recurrence from posttreatment changes in gliomas.
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Affiliation(s)
- N Soni
- Department of Radiology (N.S., Y.M., G.B.), University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - M Ora
- Department of Radiodiagnosis (M.O., N.M.), Sanjay Gandhi Post Graduate Institute of Medical Sciences, Institute of Nuclear Medicine, Lucknow, India
| | - N Mohindra
- Department of Radiodiagnosis (M.O., N.M.), Sanjay Gandhi Post Graduate Institute of Medical Sciences, Institute of Nuclear Medicine, Lucknow, India
| | - Y Menda
- Department of Radiology (N.S., Y.M., G.B.), University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - G Bathla
- Department of Radiology (N.S., Y.M., G.B.), University of Iowa Hospitals and Clinics, Iowa City, Iowa
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Himes BT, Arnett A, Merrell KW, Gates M, Bhargav A, Raghunathan A, Brown DA, Burns TC, Parney IF. Glioblastoma Recurrence Versus Treatment Effect in a Pathology-Documented Series. Can J Neurol Sci 2020; 47:525-530. [PMID: 32077389 PMCID: PMC10807241 DOI: 10.1017/cjn.2020.36] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022]
Abstract
OBJECTIVE Patients diagnosed with glioblastoma (GBM) are treated with surgery followed by fractionated radiotherapy with concurrent and adjuvant temozolomide. Patients are monitored with serial magnetic resonance imaging (MRI). However, treatment-related changes frequently mimic disease progression. We reviewed a series of patients undergoing surgery for presumed first-recurrence GBM, where pathology reports were available for tissue diagnosis, in order to better understand factors associated with a diagnosis of treatment-related changes on final pathology. METHODS Patient records at a single institution between 2005 and 2015 were retrospectively reviewed. Pathology reports were reviewed to determine diagnosis of recurrent GBM or treatment effect. Survival analysis was performed interrogating overall survival (OS) and progression-free survival (PFS). Correlation with radiation treatment plans was also examined. RESULTS One-hundred-twenty-three patients were identified. One-hundred-sixteen patients (94%) underwent resection and seven underwent biopsy. Treatment-related changes were reported in 20 cases (16%). These patients had longer median OS and PFS from the time of recurrence than patients with true disease progression. However, there was no significant difference in OS from the time of initial diagnosis. Treatment effect was associated with surgery within 90 days of completing radiation. In patients receiving radiation at our institution (n = 53), larger radiation target volume and a higher maximum dose were associated with treatment effect. CONCLUSION Treatment effect was associated with surgery nearer to completion of radiation, a larger radiation target volume, and a higher maximum point dose. Treatment effect was associated with longer PFS and OS from the time of recurrence, but not from the time of initial diagnosis.
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Affiliation(s)
| | - Andrea Arnett
- Department of Radiation Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, OH
| | | | - Marcus Gates
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN
| | - Adip Bhargav
- Alix School of Medicine, Mayo Clinic, Rochester, MN
| | | | | | - Terry C. Burns
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN
| | - Ian F. Parney
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN
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Advanced multimodal imaging in differentiating glioma recurrence from post-radiotherapy changes. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2020; 151:281-297. [PMID: 32448612 DOI: 10.1016/bs.irn.2020.03.009] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Gliomas are the most common malignant primary brain tumor, and their prognosis is extremely poor. Radiotherapy is an important treatment for glioma patients, but the changes caused by radiotherapy have brought difficulties in clinical image evaluation because differentiating glioma recurrence from post-radiotherapy changes including pseudo-progression (PD) and radiation necrosis (RN) remains a challenge. Therefore, accurate and reliable imaging evaluation is very important for making clinical decisions. In recent years, advanced multimodal imaging techniques have been applied to achieve the goal of better differentiating glioma recurrence from post-radiotherapy changes for minimizing errors associated with interpretation of treatment effects. In this review, we discuss the recent applications of advanced multimodal imaging such as diffusion MRI sequences, amide proton transfer MRI sequences, perfusion MRI sequences, MR spectroscopy and multinuclides PET/CT in the evaluation of post-radiotherapy treatment response in glioma patients and highlight their potential role in differentiating post-radiotherapy changes from glioma recurrence.
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Rotkopf LT, Wiestler B, Preibisch C, Liesche-Starnecker F, Pyka T, Nörenberg D, Bette S, Gempt J, Thierfelder KM, Zimmer C, Huber T. The wavelet power spectrum of perfusion weighted MRI correlates with tumor vascularity in biopsy-proven glioblastoma samples. PLoS One 2020; 15:e0228030. [PMID: 31971966 PMCID: PMC6977746 DOI: 10.1371/journal.pone.0228030] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2019] [Accepted: 01/06/2020] [Indexed: 01/16/2023] Open
Abstract
Background Wavelet transformed reconstructions of dynamic susceptibility contrast (DSC) MR perfusion (wavelet-MRP) are a new and elegant way of visualizing vascularization. Wavelet-MRP maps yield a clear depiction of hypervascular tumor regions, as recently shown. Objective The aim of this study was to elucidate a possible connection of the wavelet-MRP power spectrum in glioblastoma (GBM) with local vascularity and cell proliferation. Methods For this IRB-approved study 12 patients (63.0+/-14.9y; 7m) with histologically confirmed IDH-wildtype GBM were included. Target regions for biopsies were prospectively marked on tumor regions as seen on preoperative 3T MRI. During subsequent neurosurgical tumor resection 43 targeted biopsies were taken from these target regions, of which all 27 matching samples were analyzed. All specimens were immunohistochemically analyzed for endothelial cell marker CD31 and proliferation marker Ki67 and correlated to the wavelet-MRP power spectrum as derived from DSC perfusion weighted imaging. Results There was a strong correlation between wavelet-MRP power spectrum (median = 4.41) and conventional relative cerebral blood volume (median = 5.97 ml/100g) in Spearman's rank-order correlation (κ = .83, p < .05). In a logistic regression model, the wavelet-MRP power spectrum showed a significant correlation to CD31 dichotomized to no or present staining (p = .04), while rCBV did not show a significant correlation to CD31 (p = .30). No significant association between Ki67 and rCBV or wavelet-MRP was found (p = .62 and p = .70, respectively). Conclusion The wavelet-MRP power spectrum derived from existing DSC-MRI data might be a promising new surrogate for tumor vascularity in GBM.
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Affiliation(s)
- Lukas T. Rotkopf
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
- * E-mail:
| | - Benedikt Wiestler
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Christine Preibisch
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | | | - Thomas Pyka
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Dominik Nörenberg
- Institute of Clinical Radiology and Nuclear Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Stefanie Bette
- Department of Diagnostic and Interventional Radiology and Neuroradiology, Universitaetsklinikum Augsburg, Augsburg, Germany
| | - Jens Gempt
- Department of Neurosurgery, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Kolja M. Thierfelder
- Institute of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, University Medical Center Rostock, Rostock, Germany
| | - Claus Zimmer
- Department of Diagnostic and Interventional Neuroradiology, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Thomas Huber
- Institute of Clinical Radiology and Nuclear Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
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Yang Y, Yang Y, Wu X, Pan Y, Zhou D, Zhang H, Chen Y, Zhao J, Mo Z, Huang B. Adding DSC PWI and DWI to BT-RADS can help identify postoperative recurrence in patients with high-grade gliomas. J Neurooncol 2020; 146:363-371. [PMID: 31902040 DOI: 10.1007/s11060-019-03387-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2019] [Accepted: 12/27/2019] [Indexed: 12/22/2022]
Abstract
BACKGROUND The Brain Tumor Reporting and Data System (BT-RADS) category 3 is suitable for identifying cases with intermediate probability of tumor recurrence that do not meet the Response Assessment in Neuro-Oncology (RANO) criteria for progression. The aim of this study was to evaluate the added value of dynamic susceptibility contrast-enhanced perfusion-weighted imaging (DSC PWI) and diffusion-weighted imaging (DWI) to BT-RADS for differentiating tumor recurrence from non-recurrence in postoperative high-grade glioma (HGG) patients with category 3 lesions. METHODS Patients with BT-RADS category 3 lesions were included. The maximal relative cerebral blood volume (rCBVmax) and the mean apparent diffusion coefficient (ADCmean) values were measured. The added value of DSC PWI and DWI to BT-RADS was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS Fifty-one of 91 patients had tumor recurrence, and 40 patients did not. There were significant differences in rCBVmax and ADCmean between the tumor recurrence group and non-recurrence group. Compared to BT-RADS alone, the addition of DSC PWI to BT-RADS increased the area under curve (AUC) from 0.76 (95% confidence interval [CI] 0.66-0.84) to 0.90 (95% CI 0.81-0.95) for differentiating tumor recurrence from non-recurrence. The addition of DWI to BT-RADS increased the AUC from 0.76 (95% CI 0.66-0.84) to 0.88 (95% CI 0.80-0.94). The combination of BT-RADS, DSC PWI, and DWI exhibited the best diagnostic performance (AUC = 0.95; 95% CI 0.88-0.98) for differentiating tumor recurrence from non-recurrence. CONCLUSION Adding DSC PWI and DWI to BT-RADS can significantly improve the diagnostic performance for differentiating tumor recurrence from non-recurrence in BT-RADS category 3 lesions.
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Affiliation(s)
- Yuelong Yang
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Yunjun Yang
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Xiaoling Wu
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Yi Pan
- Department of Radiotherapy, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Dong Zhou
- Department of Neurosurgery, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Hongdan Zhang
- Department of Radiotherapy, Cancer Center, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Guangzhou, 510080, China
| | - Yonglu Chen
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Jiayun Zhao
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Zihua Mo
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China
| | - Biao Huang
- Department of Radiology, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, 106 Zhongshan 2nd Road, Guangzhou, 510080, China.
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Leao DJ, Craig PG, Godoy LF, Leite CC, Policeni B. Response Assessment in Neuro-Oncology Criteria for Gliomas: Practical Approach Using Conventional and Advanced Techniques. AJNR Am J Neuroradiol 2020; 41:10-20. [PMID: 31857322 PMCID: PMC6975322 DOI: 10.3174/ajnr.a6358] [Citation(s) in RCA: 86] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 10/29/2019] [Indexed: 01/08/2023]
Abstract
The Response Assessment in Neuro-Oncology criteria were developed as an objective tool for radiologic assessment of treatment response in high-grade gliomas. Imaging plays a critical role in the management of the patient with glioma, from initial diagnosis to posttreatment follow-up, which can be particularly challenging for radiologists. Interpreting findings after surgery, radiation, and chemotherapy requires profound knowledge about the tumor biology, as well as the peculiar changes expected to ensue as a consequence of each treatment technique. In this article, we discuss the imaging findings associated with tumor progression, tumor response, pseudoprogression, and pseudoresponse according to the Response Assessment in Neuro-Oncology criteria for high-grade and lower-grade gliomas. We describe relevant practical issues when evaluating patients with glioma, such as the need for imaging in the first 48 hours, the radiation therapy planning and isodose curves, the significance of T2/FLAIR hyperintense lesions, the impact of the timing for the evaluation after radiation therapy, and the definition of progressive disease on the histologic specimen. We also illustrate the correlation among the findings on conventional MR imaging with advanced techniques, such as perfusion, diffusion-weighted imaging, spectroscopy, and amino acid PET. Because many of the new lesions represent a mixture of tumor cells and tissue with radiation injury, the radiologist aims to identify the predominant component of the lesion and categorize the findings according to Response Assessment in Neuro-Oncology criteria so that the patient can receive the best treatment.
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Affiliation(s)
- D J Leao
- From the Cancer Hospital of Federal University of Uberlandia (D.J.L.), Uberlandia, Brazil
| | - P G Craig
- Department of Radiology, (P.G.C., B.P.), University of Iowa Hospitals and Clinics, Iowa City, Iowa
| | - L F Godoy
- Department of Diagnostic Radiology (L.F.G.), Hospital Sirio-Libanes, Sao Paulo, Brazil
- Department of Neuroradiology (L.F.G., C.C.L.), Faculdade de Medicina Instituto de Radiologia, Universidade de Sao Paulo Neuroradiology, Sao Paulo, Brazil
| | - C C Leite
- Department of Neuroradiology (L.F.G., C.C.L.), Faculdade de Medicina Instituto de Radiologia, Universidade de Sao Paulo Neuroradiology, Sao Paulo, Brazil
| | - B Policeni
- Department of Radiology, (P.G.C., B.P.), University of Iowa Hospitals and Clinics, Iowa City, Iowa
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Umemura Y, Wang D, Peck KK, Flynn J, Zhang Z, Fatovic R, Anderson ES, Beal K, Shoushtari AN, Kaley T, Young RJ. DCE-MRI perfusion predicts pseudoprogression in metastatic melanoma treated with immunotherapy. J Neurooncol 2019; 146:339-346. [PMID: 31873875 DOI: 10.1007/s11060-019-03379-6] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2019] [Accepted: 12/20/2019] [Indexed: 10/25/2022]
Abstract
PURPOSE It can be challenging to differentiate pseudoprogression from progression. We assessed the ability of dynamic contrast enhanced T1 MRI (DCE-MRI) perfusion to identify pseudoprogression in melanoma brain metastases. METHODS Patients with melanoma brain metastases who underwent immunotherapy and DCE-MRI were identified. Enhancing lesions ≥ 5mm in diameter on DCE-MRI and that were new or increased in size between a week from beginning the treatment, and a month after completing the treatment were included in the analysis. The 90th percentiles of rVp and rKtrans and the presence or absence of hemorrhage were recorded. Histopathology served as the reference standard for pseudoprogression. If not available, pseudoprogression was defined as neurological and radiographic stability or improvement without any new treatment for ≥ 2 months. RESULTS Forty-four patients were identified; 64% received ipilimumab monotherapy for a median duration of 9 weeks (range, 1-138). Sixty-four lesions in 44 patients were included in the study. Of these, nine lesions in eight patients were determined to be pseudoprogression and seven lesions were previously irradiated. Forty-four progression lesions and eight pseudoprogression lesions were hemorrhagic. Median lesion volume for pseudoprogression and progression were not significantly different, at 2.3 cm3 and 3.2 cm3, respectively (p = 0.82). The rVp90 was smaller in pseudoprogression versus progression, at 2.2 and 5.3, respectively (p = 0.02), and remained significant after false discovery rate adjustment (p = 0.04). CONCLUSIONS Pseudoprogression exhibited significantly lower rVp90 on DCE-MRI compared with progression. This knowledge can be useful for managing growing lesions in patients with melanoma brain metastases who are receiving immunotherapy.
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Affiliation(s)
- Yoshie Umemura
- Department of Neurology, University of Michigan, 1914 Taubman Center, 1500 E. Medical Center Dr., SPC 5316, Ann Arbor, MI, 48109 5316, USA.
| | - Diane Wang
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Kyung K Peck
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jessica Flynn
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Zhigang Zhang
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Robin Fatovic
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Erik S Anderson
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Kathryn Beal
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Thomas Kaley
- Department of Neurology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Robert J Young
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.,Brain Tumor Center, Memorial Sloan Kettering Cancer Center, New York, NY, USA
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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; 175:534-543. [DOI: 10.1016/j.neurol.2019.01.400] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [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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40
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Multicenter study demonstrates radiomic features derived from magnetic resonance perfusion images identify pseudoprogression in glioblastoma. Nat Commun 2019; 10:3170. [PMID: 31320621 PMCID: PMC6639324 DOI: 10.1038/s41467-019-11007-0] [Citation(s) in RCA: 104] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2019] [Accepted: 06/07/2019] [Indexed: 01/04/2023] Open
Abstract
Pseudoprogression (PsP) is a diagnostic clinical dilemma in cancer. In this study, we retrospectively analyse glioblastoma patients, and using their dynamic susceptibility contrast and dynamic contrast-enhanced perfusion MRI images we build a classifier using radiomic features obtained from both Ktrans and rCBV maps coupled with support vector machines. We achieve an accuracy of 90.82% (area under the curve (AUC) = 89.10%, sensitivity = 91.36%, 67 specificity = 88.24%, p = 0.017) in differentiating between pseudoprogression (PsP) and progressive disease (PD). The diagnostic performances of the models built using radiomic features from Ktrans and rCBV separately were equally high (Ktrans: AUC = 94%, 69 p = 0.012; rCBV: AUC = 89.8%, p = 0.004). Thus, this MR perfusion-based radiomic model demonstrates high accuracy, sensitivity and specificity in discriminating PsP from PD, thus provides a reliable alternative for noninvasive identification of PsP versus PD at the time of clinical/radiologic question. This study also illustrates the successful application of radiomic analysis as an advanced processing step on different MR perfusion maps. MRI scans of glioblastoma patients can be misleading and some patients appear to show features of progressive disease although they respond to treatment. Here, the authors use MRI images of progressive disease or pseudoprogression and build a classifier using machine learning to distinguish the two.
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Qiao Z, Zhao X, Wang K, Zhang Y, Fan D, Yu T, Shen H, Chen Q, Ai L. Utility of Dynamic Susceptibility Contrast Perfusion-Weighted MR Imaging and 11C-Methionine PET/CT for Differentiation of Tumor Recurrence from Radiation Injury in Patients with High-Grade Gliomas. AJNR Am J Neuroradiol 2019; 40:253-259. [PMID: 30655259 DOI: 10.3174/ajnr.a5952] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Accepted: 11/24/2018] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Both 11C-methionine PET/CT and DSC-PWI could be used to differentiate radiation injury from recurrent brain tumors. Our aim was to assess the performance of MET PET/CT and DSC-PWI for differentiation of recurrence and radiation injury in patients with high-grade gliomas and to quantitatively analyze the diagnostic values of PET and PWI parameters. MATERIALS AND METHODS Forty-two patients with high-grade gliomas were enrolled in this study. The final diagnosis was determined by histopathologic analysis or clinical follow-up. PWI and PET parameters were recorded and compared between patients with recurrence and those with radiation injury using Student t tests. Receiver operating characteristic and logistic regression analyses were used to determine the diagnostic performance of each parameter. RESULTS The final diagnosis was recurrence in 33 patients and radiation injury in 9. PET/CT showed a patient-based sensitivity and specificity of 0.909 and 0.556, respectively, while PWI showed values of 0.667 and 0.778, respectively. The maximum standardized uptake value, mean standardized uptake value, tumor-to-background maximum standardized uptake value, and mean relative CBV were significantly higher for patients with recurrence than for patients with radiation injury. All these parameters showed a high discriminative power in receiver operating characteristic analysis. The optimal cutoff values for the tumor-to-background maximum standardized uptake value and mean relative CBV were 1.85 and 1.83, respectively, and corresponding sensitivities and specificities for the diagnosis of recurrence were 0.97 and 0.667 and 0.788 and 0.88, respectively. Areas under the curve for the tumor-to-background maximum standardized uptake value and mean relative CBV were 0.847 ± 0.077 and 0.845 ± 0.078, respectively. Combined assessment of the tumor-to-background maximum standardized uptake value and mean relative CBV showed the largest area under the curve (0.953 ± 0.031), with corresponding sensitivity and specificity of 0.848 and 1.0, respectively. CONCLUSIONS Both 11C-methionine PET/CT and PWI are equally accurate in the differentiation of recurrence from radiation injury in patients with high-grade gliomas, and a combination of the 2 modalities could result in increased diagnostic accuracy.
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Affiliation(s)
- Z Qiao
- From the Departments of Nuclear Medicine (Z.Q., X.Z., K.W., Y.Z., D.F., Q.C., L.A.)
| | - X Zhao
- From the Departments of Nuclear Medicine (Z.Q., X.Z., K.W., Y.Z., D.F., Q.C., L.A.)
| | - K Wang
- From the Departments of Nuclear Medicine (Z.Q., X.Z., K.W., Y.Z., D.F., Q.C., L.A.)
| | - Y Zhang
- From the Departments of Nuclear Medicine (Z.Q., X.Z., K.W., Y.Z., D.F., Q.C., L.A.)
| | - D Fan
- From the Departments of Nuclear Medicine (Z.Q., X.Z., K.W., Y.Z., D.F., Q.C., L.A.)
| | - T Yu
- Department of Medical Imaging (T.Y.), Cancer Hospital of China Medical University, Shenyang, China.,Department of Medical Imaging (T.Y.), Liaoning Cancer Hospital and Institute, Shenyang, China
| | - H Shen
- Radiology (H.S.), Beijing Tian Tan Hospital, Capital Medical University, Beijing, China
| | - Q Chen
- From the Departments of Nuclear Medicine (Z.Q., X.Z., K.W., Y.Z., D.F., Q.C., L.A.)
| | - L Ai
- From the Departments of Nuclear Medicine (Z.Q., X.Z., K.W., Y.Z., D.F., Q.C., L.A.)
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van Dijken BR, van Laar PJ, Smits M, Dankbaar JW, Enting RH, van der Hoorn A. Perfusion MRI in treatment evaluation of glioblastomas: Clinical relevance of current and future techniques. J Magn Reson Imaging 2019; 49:11-22. [PMID: 30561164 PMCID: PMC6590309 DOI: 10.1002/jmri.26306] [Citation(s) in RCA: 62] [Impact Index Per Article: 12.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 07/30/2018] [Indexed: 12/22/2022] Open
Abstract
Treatment evaluation of patients with glioblastomas is important to aid in clinical decisions. Conventional MRI with contrast is currently the standard method, but unable to differentiate tumor progression from treatment-related effects. Pseudoprogression appears as new enhancement, and thus mimics tumor progression on conventional MRI. Contrarily, a decrease in enhancement or edema on conventional MRI during antiangiogenic treatment can be due to pseudoresponse and is not necessarily reflective of a favorable outcome. Neovascularization is a hallmark of tumor progression but not for posttherapeutic effects. Perfusion-weighted MRI provides a plethora of additional parameters that can help to identify this neovascularization. This review shows that perfusion MRI aids to identify tumor progression, pseudoprogression, and pseudoresponse. The review provides an overview of the most applicable perfusion MRI methods and their limitations. Finally, future developments and remaining challenges of perfusion MRI in treatment evaluation in neuro-oncology are discussed. Level of Evidence: 3 Technical Efficacy: Stage 4 J. Magn. Reson. Imaging 2019;49:11-22.
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Affiliation(s)
- Bart R.J. van Dijken
- Department of Radiology, Medical Imaging Center (MIC)University Medical Center GroningenGroningenthe Netherlands
| | - Peter Jan van Laar
- Department of Radiology, Medical Imaging Center (MIC)University Medical Center GroningenGroningenthe Netherlands
| | - Marion Smits
- Department of Radiology and Nuclear MedicineErasmus Medical CenterRotterdamthe Netherlands
| | - Jan Willem Dankbaar
- Department of RadiologyUniversity Medical Center UtrechtUtrechtthe Netherlands
| | - Roelien H. Enting
- Department of NeurologyUniversity Medical Center GroningenGroningenthe Netherlands
| | - Anouk van der Hoorn
- Department of Radiology, Medical Imaging Center (MIC)University Medical Center GroningenGroningenthe Netherlands
- Brain Tumour Imaging Group, Division of Neurosurgery, Department of Clinical NeurosciencesUniversity of Cambridge and Addenbrooke's HospitalCambridgeUK
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Hou BL, Wen S, Katsevman GA, Liu H, Urhie O, Turner RC, Carpenter J, Bhatia S. Magnetic Resonance Imaging Parameters and Their Impact on Survival of Patients with Glioblastoma: Tumor Perfusion Predicts Survival. World Neurosurg 2018; 124:S1878-8750(18)32908-5. [PMID: 30593971 PMCID: PMC6597330 DOI: 10.1016/j.wneu.2018.12.085] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2018] [Revised: 12/07/2018] [Accepted: 12/10/2018] [Indexed: 02/06/2023]
Abstract
BACKGROUND Many prognostic factors influence overall survival (OS) of patients with glioblastoma. Despite gross total resection and Stupp protocol adherence, many patients have poor survival. Perfusion magnetic resonance imaging may assist in diagnosis, treatment monitoring, and prognostication. METHODS This retrospective study of 36 patients with glioblastoma assessed influence of preoperative magnetic resonance imaging parameters reflecting tumor cell density and vascularity and patient age on OS. RESULTS The area under curve based on optimal receiver operating characteristic curves for the perfusion parameters normalized relative tumor blood volume (n_rTBV) and normalized relative tumor blood flow (n_rTBF) were 0.92 and 0.89, respectively, and the highest among all imaging parameters and age. OS showed strongly negative correlations with corrected n_rTBV (R = -0.70; P < 0.001) and n_rTBF (R = -0.67; P < 0.001). The Cox model, which included age and imaging parameters, demonstrated that n_rTBV and n_rTBF were most predictive of OS, with hazard ratios of 5.97 (P = 0.0001) and 8.76 (P = 0.0001), respectively, compared with 1.63 (P = 0.19) for age. Eighteen patients with corrected n_rTBV ≤2.5 (best cutoff value) had a median OS of 15.1 months (95% confidence interval (CI), 11.34-21.25) compared with 2.8 months (95% CI, 1.48-4.03; P < 0.001) for 18 patients with corrected n_rTBV >2.5. Twenty-four patients with n_rTBF ≤2.79 had a median OS of 12 months (95% CI, 10.46-17.9) compared with 2.8 months for 12 patients with n_rTBF >2.79 (95% CI, 1.31-4.2; P < 0.001). CONCLUSIONS The dominant predictors of OS are normalized perfusion parameters n_rTBV and n_rTBF. Preoperative perfusion imaging may be used as a surrogate to predict glioblastoma aggressiveness and survival independent of treatment.
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Affiliation(s)
- Bob L Hou
- Department of Radiology, West Virginia University, Morgantown, West Virginia, USA
| | - Sijin Wen
- Department of Biostatistics, West Virginia University, Morgantown, West Virginia, USA
| | - Gennadiy A Katsevman
- Department of Neurosurgery, West Virginia University, Morgantown, West Virginia, USA.
| | - Hui Liu
- Department of Biostatistics, West Virginia University, Morgantown, West Virginia, USA
| | - Ogaga Urhie
- West Virginia University School of Medicine, Morgantown, West Virginia, USA
| | - Ryan C Turner
- Department of Neurosurgery, West Virginia University, Morgantown, West Virginia, USA
| | - Jeffrey Carpenter
- Department of Radiology, West Virginia University, Morgantown, West Virginia, USA
| | - Sanjay Bhatia
- Department of Neurosurgery, West Virginia University, Morgantown, West Virginia, USA
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Marra JS, Mendes GP, Yoshinari GH, da Silva Guimarães F, Mazin SC, de Oliveira HF. Survival after radiation therapy for high-grade glioma. Rep Pract Oncol Radiother 2018; 24:35-40. [PMID: 30337846 DOI: 10.1016/j.rpor.2018.09.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 01/28/2018] [Accepted: 09/12/2018] [Indexed: 10/28/2022] Open
Abstract
Background High-grade gliomas (HGGs) are a heterogeneous disease group, with variable prognosis, inevitably causing deterioration of the quality of life. The estimated 2-year overall survival is 20%, despite the best trimodality treatment consisting of surgery, chemotherapy, and radiotherapy. Aim To evaluate long-term survival outcomes and factors influencing the survival of patients with high-grade gliomas treated with radiotherapy. Materials and methods Data from 47 patients diagnosed with high-grade gliomas between 2009 and 2014 and treated with three-dimensional radiotherapy (3DRT) or intensity-modulated radiotherapy (IMRT) were analyzed retrospectively. Results Median survival was 16.6 months; 29 patients (62%) died before the time of analysis. IMRT was employed in 68% of cases. The mean duration of radiotherapy was 56 days, and the mean delay to the start of radiotherapy was 61.7 days (range, 27-123 days). There were no statistically significant effects of duration of radiotherapy or delay to the start of radiotherapy on patient outcomes. Conclusions Age, total amount of gross resection, histological type, and use of adjuvant temozolomide influenced survival rate (p < 0.05). The estimated overall survival was 18 months (Kaplan-Meier estimator). Our results corroborated those reported in the literature.
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Affiliation(s)
- Joana Spaggiari Marra
- Department of Radiation Oncology, Hospital das Clínicas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil.,Department of Radiation Oncology, Hospital Regional do Cancer de Passos, Passos, MG, Brazil
| | - Guilherme Paulão Mendes
- Department of Radiation Oncology, Centro de Radioterapia de São Carlos, São Carlos, SP, Brazil.,Department of Radiation Oncology, Serviço de Radioterapia da Santa Casa de Araraquara, Araraquara, SP, Brazil
| | - Gerson Hiroshi Yoshinari
- Department of Radiation Oncology, Hospital Márcio Cunha, Fundação São Francisco Xavier, Ipatinga, MG, Brazil
| | - Flávio da Silva Guimarães
- Department of Radiation Oncology, Centro de Radioterapia de São Carlos, São Carlos, SP, Brazil.,Department of Radiation Oncology, Hospital das Clínicas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil
| | - Suleimy Cristina Mazin
- Department of Gynaecology and Obstetrics, Hospital das Clínicas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto - SP, Brazil
| | - Harley Francisco de Oliveira
- Department of Radiation Oncology, Hospital Márcio Cunha, Fundação São Francisco Xavier, Ipatinga, MG, Brazil.,Department of Gynaecology and Obstetrics, Hospital das Clínicas de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto - SP, Brazil.,Department of Radiation Oncology, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, Ribeirão Preto, SP, Brazil.,Department of Radiation Oncology, Centro de Tratamento em Radio-oncologia, Ribeirão Preto, SP, Brazil
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Soliman HM, ElBeheiry AA, Abdel-Kerim AA, Farhoud AH, Reda MI. Recurrent brain tumor versus radiation necrosis; can dynamic susceptibility contrast (DSC) perfusion magnetic resonance imaging differentiate? THE EGYPTIAN JOURNAL OF RADIOLOGY AND NUCLEAR MEDICINE 2018. [DOI: 10.1016/j.ejrnm.2018.03.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
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Rowe LS, Butman JA, Mackey M, Shih JH, Cooley-Zgela T, Ning H, Gilbert MR, Smart DK, Camphausen K, Krauze AV. Differentiating pseudoprogression from true progression: analysis of radiographic, biologic, and clinical clues in GBM. J Neurooncol 2018; 139:145-152. [PMID: 29767308 PMCID: PMC7983158 DOI: 10.1007/s11060-018-2855-z] [Citation(s) in RCA: 28] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Accepted: 03/31/2018] [Indexed: 01/15/2023]
Abstract
INTRODUCTION Pseudoprogression (PsP) is a diagnostic dilemma in glioblastoma (GBM) after chemoradiotherapy (CRT). Magnetic resonance imaging (MRI) features may fail to distinguish PsP from early true progression (eTP), however clinical findings may aid in their distinction. METHODS Sixty-seven patients received CRT for GBM between 2003 and 2016, and had pre- and post-treatment imaging suitable for retrospective evaluation using RANO criteria. Patients with signs of progression within the first 12-weeks post-radiation (P-12) were selected. Lesions that improved or stabilized were defined as PsP, and lesions that progressed were defined as eTP. RESULTS The median follow up for all patients was 17.6 months. Signs of progression developed in 35/67 (52.2%) patients within P-12. Of these, 20/35 (57.1%) were subsequently defined as eTP and 15/35 (42.9%) as PsP. MRI demonstrated increased contrast enhancement in 84.2% of eTP and 100% of PsP, and elevated CBV in 73.7% for eTP and 93.3% for PsP. A decrease in FLAIR was not seen in eTP patients, but was seen in 26.7% PsP patients. Patients with eTP were significantly more likely to require increased steroid doses or suffer clinical decline than PsP patients (OR 4.89, 95% CI 1.003-19.27; p = 0.046). KPS declined in 25% with eTP and none of the PsP patients. CONCLUSIONS MRI imaging did not differentiate eTP from PsP, however, KPS decline or need for increased steroids was significantly more common in eTP versus PsP. Investigation and standardization of clinical assessments in response criteria may help address the diagnostic dilemma of pseudoprogression after frontline treatment for GBM.
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Affiliation(s)
- Lindsay S Rowe
- Radiation Oncology Branch, National Cancer Institute, 10 Center Drive Magnuson Clinical Center, Room B2-3500, Bethesda, MD, 20892, USA.
| | - John A Butman
- Radiology and Imaging Sciences, National Institutes of Health, 10 Center Drive Magnuson Clinical Center, MSC 1182, Bethesda, MD, 20892, USA
| | - Megan Mackey
- Radiation Oncology Branch, National Cancer Institute, 10 Center Drive Magnuson Clinical Center, Room B2-3500, Bethesda, MD, 20892, USA
| | - Joanna H Shih
- Clinical Research Center, National Institutes of Health, 10 Center Drive Magnuson Clinical Center, Bethesda, MD, 20892, USA
| | - Theresa Cooley-Zgela
- Radiation Oncology Branch, National Cancer Institute, 10 Center Drive Magnuson Clinical Center, Room B2-3500, Bethesda, MD, 20892, USA
| | - Holly Ning
- Radiation Oncology Branch, National Cancer Institute, 10 Center Drive Magnuson Clinical Center, Room B2-3500, Bethesda, MD, 20892, USA
| | - Mark R Gilbert
- Neuro-Oncology Branch, National Cancer Institute, Building 82, Room 235A, Bethesda, MD, 20892, USA
| | - DeeDee K Smart
- Radiation Oncology Branch, National Cancer Institute, 10 Center Drive Magnuson Clinical Center, Room B2-3500, Bethesda, MD, 20892, USA
| | - Kevin Camphausen
- Radiation Oncology Branch, National Cancer Institute, 10 Center Drive Magnuson Clinical Center, Room B2-3500, Bethesda, MD, 20892, USA
| | - Andra V Krauze
- Radiation Oncology Branch, National Cancer Institute, 10 Center Drive Magnuson Clinical Center, Room B2-3500, Bethesda, MD, 20892, USA
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van West SE, de Bruin HG, van de Langerijt B, Swaak-Kragten AT, van den Bent MJ, Taal W. Incidence of pseudoprogression in low-grade gliomas treated with radiotherapy. Neuro Oncol 2018; 19:719-725. [PMID: 28453748 DOI: 10.1093/neuonc/now194] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2016] [Accepted: 08/01/2016] [Indexed: 11/14/2022] Open
Abstract
Background As the incidence of pseudo-progressive disease (psPD), or pseudoprogression, in low-grade glioma (LGG) is unknown, we retrospectively investigated this phenomenon in a cohort of LGG patients given radiotherapy (RT). Methods All MRI scans and clinical data from patients with histologically proven LGG treated with radiation between 2000 and 2011 were reviewed. PsPD was scored when a new enhancing lesion occurred after RT and subsequently disappeared or remained stable for at least a year without therapy, including dexamethasone. Results Sixty-three out of 71 patients who received RT for LGG were deemed eligible for evaluation of psPD. The median follow-up was 5 years (range 1‒10 y). PsPD was seen in 13 patients (20.6%). PsPD occurred after a median of 12 months with a range of 3-78 months. The median duration of psPD was 6 months, with a range of 2-26 months and always occurred within the RT high dose fields of at least 45 Gy. The area of the enhancement at the time of psPD was significantly smaller compared with the area of enhancement during "true" progression (median size 54mm2 [range 12-340mm2] vs 270mm2 [range 30-3420mm2], respectively; P = .009). Conclusions PsPD occurs frequently in LGG patients receiving RT. This supports the policy to postpone a new line of treatment until progression is evident, especially when patients have small contrast enhancing lesions within the RT field.
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Affiliation(s)
- Sophie E van West
- Department of Neuro-oncology/Neurology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Hein G de Bruin
- Department of Radiology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Bart van de Langerijt
- Department of Neuro-oncology/Neurology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Annemarie T Swaak-Kragten
- Department of Radiation Oncology, Erasmus MC/Daniel den Hoed Cancer Centre, Rotterdam, The Netherlands
| | - Martin J van den Bent
- Department of Neuro-oncology/Neurology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
| | - Walter Taal
- Department of Neuro-oncology/Neurology, Erasmus MC Cancer Institute, Rotterdam, Netherlands
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Differentiation of Recurrent/Residual Glioma From Radiation Necrosis Using Semi Quantitative 99mTc MDM (Bis-Methionine-DTPA) Brain SPECT/CT and Dynamic Susceptibility Contrast-Enhanced MR Perfusion. Clin Nucl Med 2018; 43:e74-e81. [PMID: 29356734 DOI: 10.1097/rlu.0000000000001943] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
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Dongas J, Asahina AT, Bacchi S, Patel S. Magnetic Resonance Perfusion Imaging in the Diagnosis of High-Grade Glioma Progression and Treatment-Related Changes: A Systematic Review. ACTA ACUST UNITED AC 2018. [DOI: 10.4236/ojmn.2018.83024] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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50
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Belliveau JG, Bauman GS, Macdonald D, Macdonald M, Klassen LM, Menon RS. Apparent transverse relaxation (R2∗) on MRI as a method to differentiate treatment effect (pseudoprogression) versus progressive disease in chemoradiation for malignant glioma. J Med Imaging Radiat Oncol 2017; 62:224-231. [PMID: 29193849 DOI: 10.1111/1754-9485.12694] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Accepted: 10/23/2017] [Indexed: 12/12/2022]
Abstract
INTRODUCTION Pseudoprogression (psPD) is a transient post-treatment imaging change that is commonly seen when treating glioma with chemotherapy and radiation. The use of apparent transverse relaxation rate (R2∗), which is calculated from a contrast-free multi-echo gradient echo Magnetic Resonance Imaging (MRI) sequence, may allow for quantitative identification of patients with suspected psPD. METHODS We acquired a multi-echo gradient echo sequence using a 3T-Siemens Prisma MRI. The signal decay through the echoes was fitted to provide the R2∗ coefficient. We segmented the T1 -gadolinium enhancing the image to provide a contrast enhancing lesion (CEL) and the FLAIR hyperintensity to provide a non-enhancing lesion (NEL). These regions of interest were applied to the multi-echo gradient echo to acquire a mean R2∗ within the CEL and NEL. We additionally acquired ADC data to attempt to corroborate our findings. RESULTS We found that patients who later exhibited PD exhibited a higher R2∗ within the CEL as well as a higher ratio of CEL to NEL. Our data correctly distinguished pseudoprogression from treatment effect in 9/9 patients, while ADC corrected identified 7/9 patients using an absolute ADC of 1200 × 10-6 mm2 /s. CONCLUSIONS Our method seems promising for the accurate identification of psPD, and the technique is amenable to evaluation in larger, multi-centre patient cohorts.
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Affiliation(s)
- Jean-Guy Belliveau
- Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada.,Center for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
| | - Glenn S Bauman
- Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada.,Department of Oncology, University of Western Ontario, London, Ontario, Canada.,London Regional Cancer Program, London, Ontario, Canada
| | - David Macdonald
- Department of Oncology, University of Western Ontario, London, Ontario, Canada.,London Regional Cancer Program, London, Ontario, Canada
| | - Maria Macdonald
- Department of Oncology, University of Western Ontario, London, Ontario, Canada.,London Regional Cancer Program, London, Ontario, Canada
| | - L Martyn Klassen
- Center for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
| | - Ravi S Menon
- Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada.,Center for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
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