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Montosa-i-Micó V, Álvarez-Torres MDM, Burgos-Panadero R, Gil-Terrón FJ, Gómez Mahiques M, Lopez-Mateu C, García-Gómez JM, Fuster-Garcia E. The prognostic relevance of a gene expression signature in MRI-defined highly vascularized glioblastoma. Heliyon 2024; 10:e31175. [PMID: 38832259 PMCID: PMC11145239 DOI: 10.1016/j.heliyon.2024.e31175] [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: 05/09/2024] [Accepted: 05/12/2024] [Indexed: 06/05/2024] Open
Abstract
Background The vascular heterogeneity of glioblastomas (GB) remains an important area of research, since tumor progression and patient prognosis are closely tied to this feature. With this study, we aim to identify gene expression profiles associated with MRI-defined tumor vascularity and to investigate its relationship with patient prognosis. Methods The study employed MRI parameters calculated with DSC Perfusion Quantification of ONCOhabitats glioma analysis software and RNA-seq data from the TCGA-GBM project dataset. In our study, we had a total of 147 RNA-seq samples, which 15 of them also had MRI parameter information. We analyzed the gene expression profiles associated with MRI-defined tumor vascularity using differential gene expression analysis and performed Log-rank tests to assess the correlation between the identified genes and patient prognosis. Results The findings of our research reveal a set of 21 overexpressed genes associated with the high vascularity pattern. Notably, several of these overexpressed genes have been previously implicated in worse prognosis based on existing literature. Our log-rank test further validates that the collective upregulation of these genes is indeed correlated with an unfavorable prognosis. This set of genes includes a variety of molecules, such as cytokines, receptors, ligands, and other molecules with diverse functions. Conclusions Our findings suggest that the set of 21 overexpressed genes in the High Vascularity group could potentially serve as prognostic markers for GB patients. These results highlight the importance of further investigating the relationship between the molecules such as cytokines or receptors underlying the vascularity in GB and its observation through MRI and developing targeted therapies for this aggressive disease.
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Affiliation(s)
- Víctor Montosa-i-Micó
- Instituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain
| | - María del Mar Álvarez-Torres
- Instituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain
| | - Rebeca Burgos-Panadero
- Laboratory of Cellular and Molecular Biology, Clinical and Translational Research in Cancer Group, La Fe Health Research Institute, Valencia, Spain
| | - F. Javier Gil-Terrón
- Instituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain
| | - Maria Gómez Mahiques
- Instituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain
| | - Carles Lopez-Mateu
- Instituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain
| | - Juan M. García-Gómez
- Instituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain
| | - Elies Fuster-Garcia
- Instituto Universitario de Tecnologías de la Información y Comunicaciones (ITACA), BDSLab, Universitat Politècnica de València, Spain
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Fatania K, Frood R, Mistry H, Short SC, O’Connor J, Scarsbrook AF, Currie S. Tumour Size and Overall Survival in a Cohort of Patients with Unifocal Glioblastoma: A Uni- and Multivariable Prognostic Modelling and Resampling Study. Cancers (Basel) 2024; 16:1301. [PMID: 38610979 PMCID: PMC11011077 DOI: 10.3390/cancers16071301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 03/15/2024] [Accepted: 03/20/2024] [Indexed: 04/14/2024] Open
Abstract
Published models inconsistently associate glioblastoma size with overall survival (OS). This study aimed to investigate the prognostic effect of tumour size in a large cohort of patients diagnosed with GBM and interrogate how sample size and non-linear transformations may impact on the likelihood of finding a prognostic effect. In total, 279 patients with a IDH-wildtype unifocal WHO grade 4 GBM between 2014 and 2020 from a retrospective cohort were included. Uni-/multivariable association between core volume, whole volume (CV and WV), and diameter with OS was assessed with (1) Cox proportional hazard models +/- log transformation and (2) resampling with 1,000,000 repetitions and varying sample size to identify the percentage of models, which showed a significant effect of tumour size. Models adjusted for operation type and a diameter model adjusted for all clinical variables remained significant (p = 0.03). Multivariable resampling increased the significant effects (p < 0.05) of all size variables as sample size increased. Log transformation also had a large effect on the chances of a prognostic effect of WV. For models adjusted for operation type, 19.5% of WV vs. 26.3% log-WV (n = 50) and 69.9% WV and 89.9% log-WV (n = 279) were significant. In this large well-curated cohort, multivariable modelling and resampling suggest tumour volume is prognostic at larger sample sizes and with log transformation for WV.
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Affiliation(s)
- Kavi Fatania
- Department of Radiology, Leeds Teaching Hospitals NHS Trust, Leeds General Infirmary, Leeds LS1 3EX, UK (A.F.S.); (S.C.)
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK;
| | - Russell Frood
- Department of Radiology, Leeds Teaching Hospitals NHS Trust, Leeds General Infirmary, Leeds LS1 3EX, UK (A.F.S.); (S.C.)
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK;
| | - Hitesh Mistry
- Division of Cancer Sciences, The University of Manchester, Manchester M13 9PL, UK; (H.M.)
| | - Susan C. Short
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK;
- Department of Oncology, Leeds Teaching Hospitals NHS Trust, St James’s University Hospital, Leeds LS9 7TF, UK
| | - James O’Connor
- Division of Cancer Sciences, The University of Manchester, Manchester M13 9PL, UK; (H.M.)
- Department of Radiology, The Christie Hospital, Manchester M20 4BX, UK
- Division of Radiotherapy and Imaging, Institute of Cancer Research, London SM2 5NG, UK
| | - Andrew F. Scarsbrook
- Department of Radiology, Leeds Teaching Hospitals NHS Trust, Leeds General Infirmary, Leeds LS1 3EX, UK (A.F.S.); (S.C.)
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK;
| | - Stuart Currie
- Department of Radiology, Leeds Teaching Hospitals NHS Trust, Leeds General Infirmary, Leeds LS1 3EX, UK (A.F.S.); (S.C.)
- Leeds Institute of Medical Research, University of Leeds, Leeds LS2 9TJ, UK;
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Qiao J, Wu H, Liu J, Kang H, Wang S, Fang J, Zhang J, Zhang W. Spectral Analysis Based on Hemodynamic Habitat Imaging Predicts Isocitrate Dehydrogenase Status and Prognosis in High-Grade Glioma. World Neurosurg 2023; 175:e520-e530. [PMID: 37028478 DOI: 10.1016/j.wneu.2023.03.136] [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: 03/21/2023] [Accepted: 03/30/2023] [Indexed: 04/08/2023]
Abstract
BACKGROUND The intratumoral heterogeneity of high-grade gliomas (HGGs) is associated with isocitrate dehydrogenase (IDH) status and prognosis, which can be established by quantitative radioanalysis of spatial tumor habitats. Therefore, we designed a framework for tackling tumors based on spatial metabolism using the hemodynamic tissue signature (HTS), focusing on metabolic changes in tumor habitat to predict IDH status and assess prognosis in patients with HGG. METHODS Preoperative data for 121 patients with HGG with subsequent histologic confirmation of HGG were prospectively collected (January 2016 to December 2020). The HTS was mapped from the image data, chemical shift imaging voxels were selected from the HTS habitat as the region of interest, and the metabolic ratio of the HTS was calculated using weighted least square method fitting. The metabolic rate of the tumor enhancement area was used as a control to analyze the efficacy of each HTS metabolic rate in predicting the IDH status and prognosis of HGG. RESULTS Total choline (Cho)/total creatine and Cho/N-acetyl-aspartate showed significant differences between IDH-wildtype and IDH-mutant in high- and low-angiogenic enhanced tumor sites (P < 0.05); Cho/total creatine was an independent risk factor for prognosis of HGG patients in high-angiogenic enhanced tumor habitats, with significant differences in survival time between groups (P < 0.05). The metabolic ratio in the tumor enhanced area could not predict IDH status or evaluate prognosis. CONCLUSIONS Spectral analysis based on hemodynamic habitat imaging can clearly distinguish IDH mutations and the prognosis assessment is more accurate, rendering it superior to traditional spectral analysis in tumor enhancement areas.
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Affiliation(s)
- Jinguo Qiao
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Centre of Imaging and Nuclear Medicine, Chongqing, China
| | - Hao Wu
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jiachen Liu
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Centre of Imaging and Nuclear Medicine, Chongqing, China
| | - Houyi Kang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Centre of Imaging and Nuclear Medicine, Chongqing, China
| | - Shunan Wang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Centre of Imaging and Nuclear Medicine, Chongqing, China
| | - Jingqin Fang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Centre of Imaging and Nuclear Medicine, Chongqing, China
| | - Junfeng Zhang
- Department of Radiology, General Hospital of Western Theater Command of PLA, Chengdu, Sichuan Province, China
| | - Weiguo Zhang
- Department of Radiology, Daping Hospital, Army Medical University, Chongqing, China; Chongqing Clinical Research Centre of Imaging and Nuclear Medicine, Chongqing, China.
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Bailo M, Pecco N, Callea M, Scifo P, Gagliardi F, Presotto L, Bettinardi V, Fallanca F, Mapelli P, Gianolli L, Doglioni C, Anzalone N, Picchio M, Mortini P, Falini A, Castellano A. Decoding the Heterogeneity of Malignant Gliomas by PET and MRI for Spatial Habitat Analysis of Hypoxia, Perfusion, and Diffusion Imaging: A Preliminary Study. Front Neurosci 2022; 16:885291. [PMID: 35911979 PMCID: PMC9326318 DOI: 10.3389/fnins.2022.885291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Accepted: 06/14/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundTumor heterogeneity poses major clinical challenges in high-grade gliomas (HGGs). Quantitative radiomic analysis with spatial tumor habitat clustering represents an innovative, non-invasive approach to represent and quantify tumor microenvironment heterogeneity. To date, habitat imaging has been applied mainly on conventional magnetic resonance imaging (MRI), although virtually extendible to any imaging modality, including advanced MRI techniques such as perfusion and diffusion MRI as well as positron emission tomography (PET) imaging.ObjectivesThis study aims to evaluate an innovative PET and MRI approach for assessing hypoxia, perfusion, and tissue diffusion in HGGs and derive a combined map for clustering of intra-tumor heterogeneity.Materials and MethodsSeventeen patients harboring HGGs underwent a pre-operative acquisition of MR perfusion (PWI), Diffusion (dMRI) and 18F-labeled fluoroazomycinarabinoside (18F-FAZA) PET imaging to evaluate tumor vascularization, cellularity, and hypoxia, respectively. Tumor volumes were segmented on fluid-attenuated inversion recovery (FLAIR) and T1 post-contrast images, and voxel-wise clustering of each quantitative imaging map identified eight combined PET and physiologic MRI habitats. Habitats’ spatial distribution, quantitative features and histopathological characteristics were analyzed.ResultsA highly reproducible distribution pattern of the clusters was observed among different cases, particularly with respect to morphological landmarks as the necrotic core, contrast-enhancing vital tumor, and peritumoral infiltration and edema, providing valuable supplementary information to conventional imaging. A preliminary analysis, performed on stereotactic bioptic samples where exact intracranial coordinates were available, identified a reliable correlation between the expected microenvironment of the different spatial habitats and the actual histopathological features. A trend toward a higher representation of the most aggressive clusters in WHO (World Health Organization) grade IV compared to WHO III was observed.ConclusionPreliminary findings demonstrated high reproducibility of the PET and MRI hypoxia, perfusion, and tissue diffusion spatial habitat maps and correlation with disease-specific histopathological features.
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Affiliation(s)
- Michele Bailo
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Nicolò Pecco
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Paola Scifo
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Filippo Gagliardi
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Luca Presotto
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Federico Fallanca
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Paola Mapelli
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Luigi Gianolli
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Nicoletta Anzalone
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Maria Picchio
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Pietro Mortini
- Vita-Salute San Raffaele University, Milan, Italy
- Department of Neurosurgery and Gamma Knife Radiosurgery, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Andrea Falini
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Antonella Castellano
- Vita-Salute San Raffaele University, Milan, Italy
- Neuroradiology Unit and CERMAC, IRCCS Ospedale San Raffaele, Milan, Italy
- *Correspondence: Antonella Castellano,
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Hemodynamic Imaging in Cerebral Diffuse Glioma-Part A: Concept, Differential Diagnosis and Tumor Grading. Cancers (Basel) 2022; 14:cancers14061432. [PMID: 35326580 PMCID: PMC8946242 DOI: 10.3390/cancers14061432] [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] [Received: 02/01/2022] [Revised: 03/01/2022] [Accepted: 03/08/2022] [Indexed: 11/17/2022] Open
Abstract
Diffuse gliomas are the most common primary malignant intracranial neoplasms. Aside from the challenges pertaining to their treatment-glioblastomas, in particular, have a dismal prognosis and are currently incurable-their pre-operative assessment using standard neuroimaging has several drawbacks, including broad differentials diagnosis, imprecise characterization of tumor subtype and definition of its infiltration in the surrounding brain parenchyma for accurate resection planning. As the pathophysiological alterations of tumor tissue are tightly linked to an aberrant vascularization, advanced hemodynamic imaging, in addition to other innovative approaches, has attracted considerable interest as a means to improve diffuse glioma characterization. In the present part A of our two-review series, the fundamental concepts, techniques and parameters of hemodynamic imaging are discussed in conjunction with their potential role in the differential diagnosis and grading of diffuse gliomas. In particular, recent evidence on dynamic susceptibility contrast, dynamic contrast-enhanced and arterial spin labeling magnetic resonance imaging are reviewed together with perfusion-computed tomography. While these techniques have provided encouraging results in terms of their sensitivity and specificity, the limitations deriving from a lack of standardized acquisition and processing have prevented their widespread clinical adoption, with current efforts aimed at overcoming the existing barriers.
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Stumpo V, Guida L, Bellomo J, Van Niftrik CHB, Sebök M, Berhouma M, Bink A, Weller M, Kulcsar Z, Regli L, Fierstra J. Hemodynamic Imaging in Cerebral Diffuse Glioma—Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions. Cancers (Basel) 2022; 14:cancers14051342. [PMID: 35267650 PMCID: PMC8909110 DOI: 10.3390/cancers14051342] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 02/05/2023] Open
Abstract
Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.
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Affiliation(s)
- Vittorio Stumpo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Correspondence:
| | - Lelio Guida
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jacopo Bellomo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Christiaan Hendrik Bas Van Niftrik
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Martina Sebök
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Moncef Berhouma
- Department of Neurosurgical Oncology and Vascular Neurosurgery, Pierre Wertheimer Neurological and Neurosurgical Hospital, Hospices Civils de Lyon, 69500 Lyon, France;
| | - Andrea Bink
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Michael Weller
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neurology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Zsolt Kulcsar
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
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Álvarez-Torres MDM, Fuster-García E, Balaña C, Puig J, García-Gómez JM. Lack of Benefit of Extending Temozolomide Treatment in Patients with High Vascular Glioblastoma with Methylated MGMT. Cancers (Basel) 2021; 13:5420. [PMID: 34771583 PMCID: PMC8582449 DOI: 10.3390/cancers13215420] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 10/25/2021] [Accepted: 10/25/2021] [Indexed: 11/25/2022] Open
Abstract
In this study, we evaluated the benefit on survival of the combination of methylation of O6-methylguanine-DNA methyltransferase (MGMT) promotor gene and moderate vascularity in glioblastoma using a retrospective dataset of 123 patients from a multicenter cohort. MRI processing and calculation of relative cerebral blood volume (rCBV), used to define moderate- and high-vascular groups, were performed with the automatic ONCOhabitats method. We assessed the previously proposed rCBV threshold (10.7) and the new calculated ones (9.1 and 9.8) to analyze the association with survival for different populations according to vascularity and MGMT methylation status. We found that patients included in the moderate-vascular group had longer survival when MGMT is methylated (significant median survival difference of 174 days, p = 0.0129*). However, we did not find significant differences depending on the MGMT methylation status for the high-vascular group (p = 0.9119). In addition, we investigated the combined correlation of MGMT methylation status and rCBV with the prognostic effect of the number of temozolomide cycles, and only significant results were found for the moderate-vascular group. In conclusion, there is a lack of benefit of extending temozolomide treatment for patients with high vascular glioblastomas, even presenting MGMT methylation. Preliminary results suggest that patients with moderate vascularity and methylated MGMT glioblastomas would benefit more from prolonged adjuvant chemotherapy.
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Affiliation(s)
- María del Mar Álvarez-Torres
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
| | - Elies Fuster-García
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
- Department of Diagnostic Physics, Oslo University Hospital, 0450 Oslo, Norway
| | - Carmen Balaña
- Institut Catala d’Oncologia (ICO), Applied Research Group in Oncology (B-ARGO Group), Institut Investigació Germans Trias i Pujol (IGTP), 08916 Badalona, Spain;
| | - Josep Puig
- Institut de Diagnostic per la Image (IDI), Hospital Dr. Josep Trueta, 17007 Girona, Spain;
| | - Juan M. García-Gómez
- Biomedical Data Science Laboratory, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, 46022 Valencia, Spain; (E.F.-G.); (J.M.G.-G.)
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8
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Tewarie IA, Senders JT, Kremer S, Devi S, Gormley WB, Arnaout O, Smith TR, Broekman MLD. Survival prediction of glioblastoma patients-are we there yet? A systematic review of prognostic modeling for glioblastoma and its clinical potential. Neurosurg Rev 2020; 44:2047-2057. [PMID: 33156423 PMCID: PMC8338817 DOI: 10.1007/s10143-020-01430-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2020] [Revised: 09/28/2020] [Accepted: 10/27/2020] [Indexed: 02/07/2023]
Abstract
Glioblastoma is associated with a poor prognosis. Even though survival statistics are well-described at the population level, it remains challenging to predict the prognosis of an individual patient despite the increasing number of prognostic models. The aim of this study is to systematically review the literature on prognostic modeling in glioblastoma patients. A systematic literature search was performed to identify all relevant studies that developed a prognostic model for predicting overall survival in glioblastoma patients following the PRISMA guidelines. Participants, type of input, algorithm type, validation, and testing procedures were reviewed per prognostic model. Among 595 citations, 27 studies were included for qualitative review. The included studies developed and evaluated a total of 59 models, of which only seven were externally validated in a different patient cohort. The predictive performance among these studies varied widely according to the AUC (0.58-0.98), accuracy (0.69-0.98), and C-index (0.66-0.70). Three studies deployed their model as an online prediction tool, all of which were based on a statistical algorithm. The increasing performance of survival prediction models will aid personalized clinical decision-making in glioblastoma patients. The scientific realm is gravitating towards the use of machine learning models developed on high-dimensional data, often with promising results. However, none of these models has been implemented into clinical care. To facilitate the clinical implementation of high-performing survival prediction models, future efforts should focus on harmonizing data acquisition methods, improving model interpretability, and externally validating these models in multicentered, prospective fashion.
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Affiliation(s)
- Ishaan Ashwini Tewarie
- Department of Neurosurgery, Haaglanden Medical Center, Lijnbaan 32, 2512 VA, The Hague, The Netherlands
- Faculty of Medicine, Erasmus University Rotterdam, Rotterdam, The Netherlands
- Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Joeky T Senders
- Department of Neurosurgery, Haaglanden Medical Center, Lijnbaan 32, 2512 VA, The Hague, The Netherlands
- Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Stijn Kremer
- Department of Neurosurgery, Haaglanden Medical Center, Lijnbaan 32, 2512 VA, The Hague, The Netherlands
| | - Sharmila Devi
- Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- King's College, London, UK
| | - William B Gormley
- Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Omar Arnaout
- Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Timothy R Smith
- Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Marike L D Broekman
- Department of Neurosurgery, Haaglanden Medical Center, Lijnbaan 32, 2512 VA, The Hague, The Netherlands.
- Computational Neurosciences Outcomes Center, Department of Neurosurgery, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA.
- Department of Neurosurgery, Leiden University Medical Center, Leiden, The Netherlands.
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9
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Chelebian E, Fuster-Garcia E, Álvarez-Torres MDM, Juan-Albarracín J, García-Gómez JM. Higher vascularity at infiltrated peripheral edema differentiates proneural glioblastoma subtype. PLoS One 2020; 15:e0232500. [PMID: 33052913 PMCID: PMC7556526 DOI: 10.1371/journal.pone.0232500] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2020] [Accepted: 09/29/2020] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND AND PURPOSE Genetic classifications are crucial for understanding the heterogeneity of glioblastoma. Recently, perfusion MRI techniques have demonstrated associations molecular alterations. In this work, we investigated whether perfusion markers within infiltrated peripheral edema were associated with proneural, mesenchymal, classical and neural subtypes. MATERIALS AND METHODS ONCOhabitats open web services were used to obtain the cerebral blood volume at the infiltrated peripheral edema for MRI studies of 50 glioblastoma patients from The Cancer Imaging Archive: TCGA-GBM. ANOVA and Kruskal-Wallis tests were carried out in order to assess the association between vascular features and the Verhaak subtypes. For assessing specific differences, Mann-Whitney U-test was conducted. Finally, the association of overall survival with molecular and vascular features was assessed using univariate and multivariate Cox models. RESULTS ANOVA and Kruskal-Wallis tests for the maximum cerebral blood volume at the infiltrated peripheral edema between the four subclasses yielded false discovery rate corrected p-values of <0.001 and 0.02, respectively. This vascular feature was significantly higher (p = 0.0043) in proneural patients compared to the rest of the subtypes while conducting Mann-Whitney U-test. The multivariate Cox model pointed to redundant information provided by vascular features at the peripheral edema and proneural subtype when analyzing overall survival. CONCLUSIONS Higher relative cerebral blood volume at infiltrated peripheral edema is associated with proneural glioblastoma subtype suggesting underlying vascular behavior related to molecular composition in that area.
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Affiliation(s)
- Eduard Chelebian
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain.,Department of Information Technology, Uppsala University, Uppsala, Sweden
| | | | - María Del Mar Álvarez-Torres
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Javier Juan-Albarracín
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Juan M García-Gómez
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
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10
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Fuster-Garcia E, Lorente Estellés D, Álvarez-Torres MDM, Juan-Albarracín J, Chelebian E, Rovira A, Acosta CA, Pineda J, Oleaga L, Mollá-Olmos E, Filice S, Due-Tønnessen P, Meling TR, Emblem KE, García-Gómez JM. MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas. Eur Radiol 2020; 31:1738-1747. [PMID: 33001310 PMCID: PMC7880975 DOI: 10.1007/s00330-020-07297-4] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2020] [Revised: 08/05/2020] [Accepted: 09/15/2020] [Indexed: 11/29/2022]
Abstract
Objectives To assess the combined role of tumor vascularity, estimated from perfusion MRI, and MGMT methylation status on overall survival (OS) in patients with glioblastoma. Methods A multicentric international dataset including 96 patients from NCT03439332 clinical study were used to study the prognostic relationships between MGMT and perfusion markers. Relative cerebral blood volume (rCBV) in the most vascularized tumor regions was automatically obtained from preoperative MRIs using ONCOhabitats online analysis service. Cox survival regression models and stratification strategies were conducted to define a subpopulation that is particularly favored by MGMT methylation in terms of OS. Results rCBV distributions did not differ significantly (p > 0.05) in the methylated and the non-methylated subpopulations. In patients with moderately vascularized tumors (rCBV < 10.73), MGMT methylation was a positive predictive factor for OS (HR = 2.73, p = 0.003, AUC = 0.70). In patients with highly vascularized tumors (rCBV > 10.73), however, there was no significant effect of MGMT methylation (HR = 1.72, p = 0.10, AUC = 0.56). Conclusions Our results indicate the existence of complementary prognostic information provided by MGMT methylation and rCBV. Perfusion markers could identify a subpopulation of patients who will benefit the most from MGMT methylation. Not considering this information may lead to bias in the interpretation of clinical studies. Key Points • MRI perfusion provides complementary prognostic information to MGMT methylation. • MGMT methylation improves prognosis in glioblastoma patients with moderate vascular profile. • Failure to consider these relations may lead to bias in the interpretation of clinical studies. Electronic supplementary material The online version of this article (10.1007/s00330-020-07297-4) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Elies Fuster-Garcia
- Department of Diagnostic Physics, Oslo University Hospital, Sognsvannsveien 20, 0372, Oslo, Norway.
| | - David Lorente Estellés
- Medical Oncology Service, Hospital Provinicial de Castellón, Castellón de La Plana, Castellón, Spain
| | - María Del Mar Álvarez-Torres
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Javier Juan-Albarracín
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Eduard Chelebian
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Alex Rovira
- Section of Neuroradiology, Hospital Universitari Vall d'Hebron, Barcelona, Spain
| | | | | | | | | | - Silvano Filice
- Department of Medical Physics, University Hospital of Parma, Parma, Italy
| | | | - Torstein R Meling
- Department of Neurosurgery, Oslo University Hospital, Oslo, Norway.,Department of Neurosurgery, Geneva University Hospitals, Geneva, Switzerland
| | - Kyrre E Emblem
- Department of Diagnostic Physics, Oslo University Hospital, Sognsvannsveien 20, 0372, Oslo, Norway
| | - Juan M García-Gómez
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
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11
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Vascular habitat analysis based on dynamic susceptibility contrast perfusion MRI predicts IDH mutation status and prognosis in high-grade gliomas. Eur Radiol 2020; 30:3254-3265. [PMID: 32078014 DOI: 10.1007/s00330-020-06702-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 12/29/2019] [Accepted: 02/03/2020] [Indexed: 12/31/2022]
Abstract
OBJECTIVE The current study aimed to evaluate the clinical practice for hemodynamic tissue signature (HTS) method in IDH genotype prediction in three groups derived from high-grade gliomas. METHODS Preoperative MRI examinations of 44 patients with known grade and IDH genotype were assigned into three study groups: glioblastoma multiforme, grade III, and high-grade gliomas. Perfusion parameters were analyzed and were used to automatically draw the four reproducible habitats (high-angiogenic enhancing tumor habitats, low-angiogenic enhancing tumor habitats, infiltrated peripheral edema habitats, vasogenic peripheral edema habitats) related to vascular heterogeneity. These four habitats were then compared between inter-patient with IDH mutation and their wild-type counterparts at these three groups, respectively. The discriminating potential for HTS in assessing IDH mutation status prediction was assessed by ROC curves. RESULTS Compared with IDH wild type, IDH mutation had significantly decreased relative cerebral blood volume (rCBV) at the high-angiogenic enhancing tumor habitats and low-angiogenic enhancing tumor habitats. ROC analysis revealed that the rCBVs in habitats had great ability to discriminate IDH mutation from their wild type in all groups. In addition, the Kaplan-Meier survival analysis yielded significant differences for the survival times observed from the populations dichotomized by low (< 4.31) and high (> 4.31) rCBV in the low-angiogenic enhancing tumor habitat. CONCLUSIONS The HTS method has been proven to have high prediction capabilities for IDH mutation status in high-grade glioma patients, providing a set of quantifiable habitats associated with tumor vascular heterogeneity. KEY POINTS • The HTS method has a high accuracy for molecular stratification prediction for all subsets of HGG. • The HTS method can give IDH mutation-related hemodynamic information of tumor-infiltrated and vasogenic edema. • IDH-relevant rCBV difference in habitats will be a great prognosis factor in HGG.
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12
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Álvarez‐Torres M, Juan‐Albarracín J, Fuster‐Garcia E, Bellvís‐Bataller F, Lorente D, Reynés G, Font de Mora J, Aparici‐Robles F, Botella C, Muñoz‐Langa J, Faubel R, Asensio‐Cuesta S, García‐Ferrando GA, Chelebian E, Auger C, Pineda J, Rovira A, Oleaga L, Mollà‐Olmos E, Revert AJ, Tshibanda L, Crisi G, Emblem KE, Martin D, Due‐Tønnessen P, Meling TR, Filice S, Sáez C, García‐Gómez JM. Robust association between vascular habitats and patient prognosis in glioblastoma: An international multicenter study. J Magn Reson Imaging 2019; 51:1478-1486. [DOI: 10.1002/jmri.26958] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 09/19/2019] [Indexed: 02/03/2023] Open
Affiliation(s)
- María Álvarez‐Torres
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - Javier Juan‐Albarracín
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | | | - Fuensanta Bellvís‐Bataller
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - David Lorente
- Hospital Provincial de Castellón, Department of Medical Oncology Castellón de la Plana Castellón de la Plana Spain
| | - Gaspar Reynés
- Health Research Institute Hospital La FeCancer Research Group Valencia Spain
| | - Jaime Font de Mora
- Instituto de Investigación Sanitaria La Fe, Laboratory of Cellular and Molecular Biology Valencia Spain
| | | | - Carlos Botella
- Hospital Universitari i Politècnic La Fe, Área Clínica de Neurociencias Valencia Spain
| | - Jose Muñoz‐Langa
- Health Research Institute Hospital La FeCancer Research Group Valencia Spain
| | - Raquel Faubel
- Universitat de València, Departament de Fisioteràpia Valencia Spain
| | - Sabina Asensio‐Cuesta
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - Germán A. García‐Ferrando
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - Eduard Chelebian
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - Cristina Auger
- Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Magnetic Resonance Unit, Department of Radiology Barcelona Spain
| | - Jose Pineda
- Hospital Clinic de Barcelona Barcelona Spain
| | - Alex Rovira
- Hospital Vall d'Hebron, Universitat Autònoma de Barcelona, Magnetic Resonance Unit, Department of Radiology Barcelona Spain
| | | | - Enrique Mollà‐Olmos
- Hospital Universitario de la Ribera, Departamento de Radiodiagnóstico Alzira Valencia Spain
| | | | - Luaba Tshibanda
- Centre Hospitalier Universitaire de Liège, Service médical de Radiodiagnostic Liège Belgium
| | - Girolamo Crisi
- Azienda Ospedaliero‐Universitaria di Parma, Neuroradiology Parma Italy
| | - Kyrre E. Emblem
- Oslo University Hospital, Department of Diagnostic Physics Oslo Norway
| | - Didier Martin
- Centre Hospitalier Universitaire de Liege, Service de Neurochirurugie Liège Belgium
| | | | - Torstein R. Meling
- Oslo University Hospital, Department of Neurosurgery Oslo Norway
- Geneva University Hospital, Department of Neurosurgery Geneva Switzerland
| | - Silvano Filice
- Azienda Ospedaliero‐Universitaria di Parma, Medical Physics Parma Italy
| | - Carlos Sáez
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
| | - Juan M. García‐Gómez
- Universitat Politècnica de València, BDSLab, Instituto Universitarios de Tecnologías de la Información y Comunicaciones (ITACA) Valencia, Spain
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