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Foltyn-Dumitru M, Kessler T, Sahm F, Wick W, Heiland S, Bendszus M, Vollmuth P, Schell M. Cluster-based prognostication in glioblastoma: Unveiling heterogeneity based on diffusion and perfusion similarities. Neuro Oncol 2024; 26:1099-1108. [PMID: 38153923 PMCID: PMC11145444 DOI: 10.1093/neuonc/noad259] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Indexed: 12/30/2023] Open
Abstract
BACKGROUND While the association between diffusion and perfusion magnetic resonance imaging (MRI) and survival in glioblastoma is established, prognostic models for patients are lacking. This study employed clustering of functional imaging to identify distinct functional phenotypes in untreated glioblastomas, assessing their prognostic significance for overall survival. METHODS A total of 289 patients with glioblastoma who underwent preoperative multimodal MR imaging were included. Mean values of apparent diffusion coefficient normalized relative cerebral blood volume and relative cerebral blood flow were calculated for different tumor compartments and the entire tumor. Distinct imaging patterns were identified using partition around medoids (PAM) clustering on the training dataset, and their ability to predict overall survival was assessed. Additionally, tree-based machine-learning models were trained to ascertain the significance of features pertaining to cluster membership. RESULTS Using the training dataset (231/289) we identified 2 stable imaging phenotypes through PAM clustering with significantly different overall survival (OS). Validation in an independent test set revealed a high-risk group with a median OS of 10.2 months and a low-risk group with a median OS of 26.6 months (P = 0.012). Patients in the low-risk cluster had high diffusion and low perfusion values throughout, while the high-risk cluster displayed the reverse pattern. Including cluster membership in all multivariate Cox regression analyses improved performance (P ≤ 0.004 each). CONCLUSIONS Our research demonstrates that data-driven clustering can identify clinically relevant, distinct imaging phenotypes, highlighting the potential role of diffusion, and perfusion MRI in predicting survival rates of glioblastoma patients.
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Affiliation(s)
- Martha Foltyn-Dumitru
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Section for Computational Neuroimaging, Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Tobias Kessler
- Department of Neurology and Neurooncology Program, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
- Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Felix Sahm
- Department of Neuropathology, Heidelberg University Hospital, Heidelberg, Germany
| | - Wolfgang Wick
- Department of Neurology and Neurooncology Program, Heidelberg University Hospital, Heidelberg University, Heidelberg, Germany
- Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Philipp Vollmuth
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Section for Computational Neuroimaging, Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Marianne Schell
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
- Section for Computational Neuroimaging, Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
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Qian X, Tan H, Liu X, Zhao W, Chan MD, Kim P, Zhou X. Radiogenomics-Based Risk Prediction of Glioblastoma Multiforme with Clinical Relevance. Genes (Basel) 2024; 15:718. [PMID: 38927654 PMCID: PMC11202835 DOI: 10.3390/genes15060718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2024] [Revised: 05/20/2024] [Accepted: 05/24/2024] [Indexed: 06/28/2024] Open
Abstract
Glioblastoma multiforme (GBM)is the most common and aggressive primary brain tumor. Although temozolomide (TMZ)-based radiochemotherapy improves overall GBM patients' survival, it also increases the frequency of false positive post-treatment magnetic resonance imaging (MRI) assessments for tumor progression. Pseudo-progression (PsP) is a treatment-related reaction with an increased contrast-enhancing lesion size at the tumor site or resection margins miming tumor recurrence on MRI. The accurate and reliable prognostication of GBM progression is urgently needed in the clinical management of GBM patients. Clinical data analysis indicates that the patients with PsP had superior overall and progression-free survival rates. In this study, we aimed to develop a prognostic model to evaluate the tumor progression potential of GBM patients following standard therapies. We applied a dictionary learning scheme to obtain imaging features of GBM patients with PsP or true tumor progression (TTP) from the Wake dataset. Based on these radiographic features, we conducted a radiogenomics analysis to identify the significantly associated genes. These significantly associated genes were used as features to construct a 2YS (2-year survival rate) logistic regression model. GBM patients were classified into low- and high-survival risk groups based on the individual 2YS scores derived from this model. We tested our model using an independent The Cancer Genome Atlas Program (TCGA) dataset and found that 2YS scores were significantly associated with the patient's overall survival. We used two cohorts of the TCGA data to train and test our model. Our results show that the 2YS scores-based classification results from the training and testing TCGA datasets were significantly associated with the overall survival of patients. We also analyzed the survival prediction ability of other clinical factors (gender, age, KPS (Karnofsky performance status), normal cell ratio) and found that these factors were unrelated or weakly correlated with patients' survival. Overall, our studies have demonstrated the effectiveness and robustness of the 2YS model in predicting the clinical outcomes of GBM patients after standard therapies.
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Affiliation(s)
- Xiaohua Qian
- Department of Radiology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
| | - Hua Tan
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
| | - Xiaona Liu
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
| | - Weiling Zhao
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
| | - Michael D. Chan
- Department of Radiation Oncology, Wake Forest School of Medicine, Winston-Salem, NC 27157, USA
| | - Pora Kim
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
| | - Xiaobo Zhou
- Department of Bioinformatics and Systems Medicine, McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA (X.L.); (P.K.)
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Zhang Y, Wang F, Huang Y. PDZK1 is correlated with DCE-MRI perfusion parameters in high-grade glioma. Clinics (Sao Paulo) 2024; 79:100367. [PMID: 38692010 PMCID: PMC11070665 DOI: 10.1016/j.clinsp.2024.100367] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2023] [Revised: 03/11/2024] [Accepted: 04/11/2024] [Indexed: 05/03/2024] Open
Abstract
OBJECTIVE This study investigated the relationship between PDZK1 expression and Dynamic Contrast-Enhanced MRI (DCE-MRI) perfusion parameters in High-Grade Glioma (HGG). METHODS Preoperative DCE-MRI scanning was performed on 80 patients with HGG to obtain DCE perfusion transfer coefficient (Ktrans), vascular plasma volume fraction (vp), extracellular volume fraction (ve), and reverse transfer constant (kep). PDZK1 in HGG patients was detected, and its correlation with DCE-MRI perfusion parameters was assessed by the Pearson method. An analysis of Cox regression was performed to determine the risk factors affecting survival, while Kaplan-Meier and log-rank tests to evaluate PDZK1's prognostic significance, and ROC curve analysis to assess its diagnostic value. RESULTS PDZK1 was upregulated in HGG patients and predicted poor overall survival and progression-free survival. Moreover, PDZK1 expression distinguished grade III from grade IV HGG. PDZK1 expression was positively correlated with Ktrans 90, and ve_90, and negatively correlated with kep_max, and kep_90. CONCLUSION PDZK1 is upregulated in HGG, predicts poor survival, and differentiates tumor grading in HGG patients. PDZK1 expression is correlated with DCE-MRI perfusion parameters.
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Affiliation(s)
- Yi Zhang
- Department of Radiology, The First People's Hospital of Shuangliu District, (West China Airport Hospital of Sichuan University), Chengdu City, Sichuan Province, China.
| | - Feng Wang
- Department of Radiology, The First People's Hospital of Shuangliu District, (West China Airport Hospital of Sichuan University), Chengdu City, Sichuan Province, China
| | - YongLi Huang
- Department of Radiology, The First People's Hospital of Shuangliu District, (West China Airport Hospital of Sichuan University), Chengdu City, Sichuan Province, China
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Gupta M, Anjari M, Brandner S, Fersht N, Wilson E, Thust S, Kosmin M. Isocitrate Dehydrogenase 1/2 Wildtype Adult Astrocytoma with WHO Grade 2/3 Histological Features: Molecular Re-Classification, Prognostic Factors, Clinical Outcomes. Biomedicines 2024; 12:901. [PMID: 38672254 PMCID: PMC11048525 DOI: 10.3390/biomedicines12040901] [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: 01/24/2024] [Revised: 03/27/2024] [Accepted: 03/31/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND Isocitrate Dehydrogenase 1/2 (IDH 1/2)-wildtype (WT) astrocytomas constitute a heterogeneous group of tumors and have undergone a series of diagnostic reclassifications over time. This study aimed to investigate molecular markers, clinical, imaging, and treatment factors predictive of outcomes in WHO grade 2/3 IDH-WT astrocytomas ('early glioblastoma'). METHODOLOGY Patients with WHO grade 2/3 IDH-WT astrocytomas were identified from the hospital archives. They were cross-referenced with the electronic medical records systems, including neuroimaging. The expert neuro-pathology team retrieved data on molecular markers-MGMT, TERT, IDH, and EGFR. Tumors with a TERT mutation and/or EGFR amplification were reclassified as glioblastoma. RESULTS Fifty-four patients were identified. Sixty-three percent of the patients could be conclusively reclassified as glioblastoma based on either TERT mutation, EGFR amplification, or both. On imaging, 65% showed gadolinium enhancement on MRI. Thirty-nine patients (72%) received long-course radiotherapy, of whom 64% received concurrent chemotherapy. The median follow-up of the group was 16 months (range: 2-90), and the median overall survival (OS) was 17.3 months. The 2-year OS of the whole cohort was 31%. On univariate analysis, older age, worse performance status (PS), and presence versus absence of contrast enhancement on diagnostic MRI were statistically significant for poorer OS. CONCLUSION IDH-WT WHO grade 2/3 astrocytomas are a heterogeneous group of tumors with poor clinical outcomes. The majority can be reclassified as glioblastoma, based on current WHO classification criteria, but further understanding of the underlying biology of these tumors and the discovery of novel targeted agents are needed for better outcomes.
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Affiliation(s)
- Meetakshi Gupta
- Department of Radiotherapy, Guy’s and St Thomas’ NHS Foundation Trust, Great Maze Pond, London SE1 9RT, UK;
| | - Mustafa Anjari
- Department of Radiology, Royal Free Hospital, Royal Free London NHS Foundation Trust, Pond Street, London NW3 2QG, UK;
- Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
- Department of Brain Rehabilitation and Repair, Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK;
| | - Sebastian Brandner
- Division of Neuropathology, University College London Hospitals NHS Foundation Trust, Queen Square, London WC1N 3BG, UK
- Department of Neurodegenerative Diseases, Queen Square Institute of Neurology, University College London, London WC1N 3BG, UK
| | - Naomi Fersht
- Department of Radiotherapy, University College London NHS Foundation Trust, 250 Euston Rd, London NW1 2PG, UK
| | - Elena Wilson
- Department of Radiotherapy, University College London NHS Foundation Trust, 250 Euston Rd, London NW1 2PG, UK
| | - Steffi Thust
- Department of Brain Rehabilitation and Repair, Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK;
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham NG7 2RD, UK
- Queens Medical Centre, Nottingham University NHS Trust, Nottingham NG7 2UH, UK
| | - Michael Kosmin
- Department of Radiotherapy, University College London NHS Foundation Trust, 250 Euston Rd, London NW1 2PG, UK
- NIHR Biomedical Research Centre, University College London Hospitals NHS Foundation Trust, London W1T 7DN, UK
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Heidari M, Shokrani P. Imaging Role in Diagnosis, Prognosis, and Treatment Response Prediction Associated with High-grade Glioma. JOURNAL OF MEDICAL SIGNALS & SENSORS 2024; 14:7. [PMID: 38993200 PMCID: PMC11111132 DOI: 10.4103/jmss.jmss_30_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2022] [Revised: 07/31/2022] [Accepted: 03/14/2023] [Indexed: 07/13/2024]
Abstract
Background Glioma is one of the most drug and radiation-resistant tumors. Gliomas suffer from inter- and intratumor heterogeneity which makes the outcome of similar treatment protocols vary from patient to patient. This article is aimed to overview the potential imaging markers for individual diagnosis, prognosis, and treatment response prediction in malignant glioma. Furthermore, the correlation between imaging findings and biological and clinical information of glioma patients is reviewed. Materials and Methods The search strategy in this study is to select related studies from scientific websites such as PubMed, Scopus, Google Scholar, and Web of Science published until 2022. It comprised a combination of keywords such as Biomarkers, Diagnosis, Prognosis, Imaging techniques, and malignant glioma, according to Medical Subject Headings. Results Some imaging parameters that are effective in glioma management include: ADC, FA, Ktrans, regional cerebral blood volume (rCBV), cerebral blood flow (CBF), ve, Cho/NAA and lactate/lipid ratios, intratumoral uptake of 18F-FET (for diagnostic application), RD, ADC, ve, vp, Ktrans, CBFT1, rCBV, tumor blood flow, Cho/NAA, lactate/lipid, MI/Cho, uptakes of 18F-FET, 11C-MET, and 18F-FLT (for prognostic and predictive application). Cerebral blood volume and Ktrans are related to molecular markers such as vascular endothelial growth factor (VEGF). Preoperative ADCmin value of GBM tumors is associated with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. 2-hydroxyglutarate metabolite and dynamic 18F-FDOPA positron emission tomography uptake are related to isocitrate dehydrogenase (IDH) mutations. Conclusion Parameters including ADC, RD, FA, rCBV, Ktrans, vp, and uptake of 18F-FET are useful for diagnosis, prognosis, and treatment response prediction in glioma. A significant correlation between molecular markers such as VEGF, MGMT, and IDH mutations with some diffusion and perfusion imaging parameters has been identified.
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Affiliation(s)
- Maryam Heidari
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Parvaneh Shokrani
- Department of Medical Physics, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran
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Fernández-Valverde F, Bautista-Bárcena MP, Roldán-Romero E, Solivera-Vela J, Bravo-Rodríguez F, Ramos-Gómez MJ. Prognostic value of brain perfusion by MRI in the initial study of high grade gliomas. RADIOLOGIA 2024; 66:114-120. [PMID: 38614528 DOI: 10.1016/j.rxeng.2022.12.010] [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: 10/04/2022] [Accepted: 12/05/2022] [Indexed: 04/15/2024]
Abstract
OBJECTIVES To evaluate if the tumour perfusion at the initial MRI scan is a marker of prognosis for survival in patients diagnosed with High Grade Gliomas (HGG). To analyse the risk factors which influence on the mortality from HGG to quantify the overall survival to be expected in patients. PATIENTS AND METHODS The patients diagnosed with HGG through a MRI scan in a third-level hospital between 2017 and 2019 were selected. Clinical and tumour variables were collected. The survival analysis was used to determine the association between the tumour perfusion and the survival time. The relation between the collected variables and the survival period was assessed through Wald's statistical method, measuring the relationship via Cox's regression model. Finally, the type of relationship that exists between the tumour perfusion and the survival was analysed through the Lineal Regression method.Those statistical analysis were carried out using the software SPSS v.17. RESULTS 38 patients were included (average age: 61.1 years old). The general average survival period was 20.6 months. A relationship between the tumour perfusion at the MRI scan and the overall survival has been identified, in detail, a group with intratumor values of relative cerebral blood volume (rCBV)>3.0 has shown a significant decline in the average survival period with regard to the average survival period of the group with values <3.0 (14.6 months vs. 22.8 months, p = 0.046). It has also been proved that variables like Karnofsky's scale and the response time since the intervention significantly influence on the survival period. CONCLUSIONS It has become evident that the tumour perfusion via MRI scan has a prognostic value in the initial analysis of HGG. The average survival period of patients with rCBV less than or equal to 3.0 is significantly higher than those patients whose values are higher, which allows to be more precise with the prognosis of each patient.
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Affiliation(s)
- F Fernández-Valverde
- Servicio de Radiodiagnóstico y Cáncer de Mama, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain.
| | | | - E Roldán-Romero
- Servicio de Radiodiagnóstico y Cáncer de Mama, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain
| | - J Solivera-Vela
- Servicio de Neurocirugía, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain
| | - F Bravo-Rodríguez
- Servicio de Radiodiagnóstico y Cáncer de Mama, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain
| | - M J Ramos-Gómez
- Servicio de Radiodiagnóstico y Cáncer de Mama, Hospital Universitario Reina Sofía de Córdoba, Córdoba, Spain
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Campion A, Iv M. Brain Tumor Imaging: Review of Conventional and Advanced Techniques. Semin Neurol 2023; 43:867-888. [PMID: 37963581 DOI: 10.1055/s-0043-1776765] [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: 11/16/2023]
Abstract
Approaches to central nervous system (CNS) tumor classification and evaluation have undergone multiple iterations over the past few decades, in large part due to our growing understanding of the influence of genetics on tumor behavior and our refinement of brain tumor imaging techniques. Computed tomography and magnetic resonance imaging (MRI) both play a critical role in the diagnosis and monitoring of brain tumors, although MRI has become especially important due to its superior soft tissue resolution. The purpose of this article will be to briefly review the fundamentals of conventional and advanced techniques used in brain tumor imaging. We will also highlight the applications of these imaging tools in the context of commonly encountered tumors based on the most recently updated 2021 World Health Organization (WHO) classification of CNS tumors framework.
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Affiliation(s)
- Andrew Campion
- Department of Radiology (Neuroradiology), Stanford University, Stanford, California
| | - Michael Iv
- Department of Radiology (Neuroradiology), Stanford University, Stanford, California
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Young JR, Ressler JA, Shiroishi MS, Mortimer JE, Schmolze D, Fitzgibbons M, Chen BT. Association of Relative Cerebral Blood Volume from Dynamic Susceptibility Contrast-Enhanced Perfusion MR with HER2 Status in Breast Cancer Brain Metastases. Acad Radiol 2023; 30:1816-1822. [PMID: 36549990 DOI: 10.1016/j.acra.2022.12.008] [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: 10/23/2022] [Revised: 11/28/2022] [Accepted: 12/03/2022] [Indexed: 12/24/2022]
Abstract
RATIONALE AND OBJECTIVES With the development of HER2-directed therapies, identifying non-invasive imaging biomarkers of HER2 expression in breast cancer brain metastases has become increasingly important. The purpose of this study was to investigate whether relative cerebral blood volume (rCBV) from dynamic susceptibility contrast-enhanced (DSC) perfusion MR could help identify the HER2 status of breast cancer brain metastases. MATERIALS AND METHODS With IRB approval for this HIPAA-compliant cross-sectional study and a waiver of informed consent, we queried our institution's electronic medical record to derive a cohort of 14 histologically proven breast cancer brain metastases with preoperative DSC perfusion MR and HER2 analyses of the resected/biopsied brain specimens from 2011-2021. The rCBV of the lesions was measured and compared using Mann-Whitney tests. Receiver operating characteristic analyses were performed to evaluate the performance of rCBV in identifying HER2 status. RESULTS The study cohort was comprised of 14 women with a mean age of 56 years (range: 32-81 years) with a total of 14 distinct lesions. The rCBV of HER2-positive breast cancer brain metastases was significantly greater than the rCBV of HER2-negative lesions (8.02 vs 3.97, U=48.00, p=0.001). rCBV differentiated HER2-positive lesions from HER2-negative lesions with an area under the curve of 0.98 (standard error=0.032, p<0.001). The accuracy-maximizing rCBV threshold (4.8) was associated with an accuracy of 93% (13/14), a sensitivity of 100% (7/7), and a specificity of 86% (6/7). CONCLUSION rCBV may assist in identifying the HER2 status of breast cancer brain metastases, if validated in a large prospective trial.
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Affiliation(s)
- Jonathan R Young
- Division of Neuroradiology, Department of Radiology, City of Hope Comprehensive Cancer Center, 1500 E. Duarte Rd, Duarte, California, 91010.
| | - Julie A Ressler
- Division of Neuroradiology, Department of Radiology, City of Hope Comprehensive Cancer Center, 1500 E. Duarte Rd, Duarte, California, 91010
| | - Mark S Shiroishi
- Division of Neuroradiology, Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Joanne E Mortimer
- Department of Medical Oncology and Therapeutics Research, City of Hope Comprehensive Cancer Center, Duarte, California
| | - Daniel Schmolze
- Department of Pathology, City of Hope Comprehensive Cancer Center, Duarte, California
| | - Mariko Fitzgibbons
- Division of Neuroradiology, Department of Radiology, City of Hope Comprehensive Cancer Center, 1500 E. Duarte Rd, Duarte, California, 91010
| | - Bihong T Chen
- Division of Neuroradiology, Department of Radiology, City of Hope Comprehensive Cancer Center, 1500 E. Duarte Rd, Duarte, California, 91010
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Picca A, Bruno F, Nichelli L, Sanson M, Rudà R. Advances in molecular and imaging biomarkers in lower-grade gliomas. Expert Rev Neurother 2023; 23:1217-1231. [PMID: 37982735 DOI: 10.1080/14737175.2023.2285472] [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: 08/07/2023] [Accepted: 11/15/2023] [Indexed: 11/21/2023]
Abstract
INTRODUCTION Lower-grade (grade 2-3) gliomas (LGGs) constitutes a group of primary brain tumors with variable clinical behaviors and treatment responses. Recent advancements in molecular biology have redefined their classification, and novel imaging modalities emerged for the noninvasive diagnosis and follow-up. AREAS COVERED This review comprehensively analyses the current knowledge on molecular and imaging biomarkers in LGGs. Key molecular alterations, such as IDH mutations and 1p/19q codeletion, are discussed for their prognostic and predictive implications in guiding treatment decisions. Moreover, the authors explore theranostic biomarkers for the potential of tailored therapies. Additionally, they also describe the utility of advanced imaging modalities, including widely available techniques, as dynamic susceptibility contrast perfusion-weighted imaging and less validated, emerging approaches, for the noninvasive LGGs characterization and follow-up. EXPERT OPINION The integration of molecular markers enhanced the stratification of LGGs, leading to the new concept of integrated histomolecular classification. While the IDH mutation is an established key prognostic and predictive marker, recent results from IDH inhibitors trials showed its potential value as a theranostic marker. In this setting, advanced MRI techniques such as 2-D-hydroxyglutarate spectroscopy are very promising for the noninvasive diagnosis and monitoring of LGGs. This progress offers exciting prospects for personalized medicine and improved treatment outcomes in LGGs.
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Affiliation(s)
- Alberto Picca
- Service de Neurologie 2 Mazarin, Hôpital Universitaire Pitié-Salpêtrière, AP-HP, Paris, France
- Sorbonne Université, Inserm, CNRS, UMRS1127, Institut du Cerveau-Paris Brain Institute-ICM, AP-HP, Paris, France
| | - Francesco Bruno
- Division of Neuro-Oncology, Department of Neuroscience "Rita Levi Montalcini", University and City of Health and Science University Hospital, Turin, Italy
| | - Lucia Nichelli
- Service de Neuroradiologie, Hôpital Universitaire Pitié-Salpêtrière, AP-HP, Paris, France
| | - Marc Sanson
- Service de Neurologie 2 Mazarin, Hôpital Universitaire Pitié-Salpêtrière, AP-HP, Paris, France
- Sorbonne Université, Inserm, CNRS, UMRS1127, Institut du Cerveau-Paris Brain Institute-ICM, AP-HP, Paris, France
| | - Roberta Rudà
- Division of Neuro-Oncology, Department of Neuroscience "Rita Levi Montalcini", University and City of Health and Science University Hospital, Turin, Italy
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Steidl E, Filipski K, Hattingen E, Steinbach JP, Maurer GD. Longitudinal study on MRI and neuropathological findings: Neither DSC-perfusion derived rCBVmax nor vessel densities correlate between newly diagnosed and progressive glioblastoma. PLoS One 2023; 18:e0274400. [PMID: 36724187 PMCID: PMC9891512 DOI: 10.1371/journal.pone.0274400] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 08/26/2022] [Indexed: 02/02/2023] Open
Abstract
INTRODUCTION When evaluating MRIs for glioblastoma progression, previous scans are usually included into the review. Nowadays dynamic susceptibility contrast (DSC)-perfusion is an essential component in MR-diagnostics of gliomas, since the extent of hyperperfusion upon first diagnosis correlates with gene expression and survival. We aimed to investigate if this initial perfusion signature also characterizes the glioblastoma at time of progression. If so, DSC-perfusion data from the initial diagnosis could be of diagnostic benefit in follow-up assessments. METHODS We retrospectively identified 65 patients with isocitrate dehydrogenase wildtype glioblastoma who had received technically identical DSC-perfusion measurements at initial diagnosis and at time of first progression. We determined maximum relative cerebral blood volume values (rCBVmax) by standardized re-evaluation of the data including leakage correction. In addition, the corresponding tissue samples from 24 patients were examined histologically for the maximum vessel density within the tumor. Differences (paired t-test/ Wilcoxon matched pairs test) and correlations (Spearman) between the measurements at both timepoints were calculated. RESULTS The rCBVmax was consistently lower at time of progression compared to rCBVmax at time of first diagnosis (p < .001). There was no correlation between the rCBVmax values at both timepoints (r = .12). These findings were reflected in the histological examination, with a lower vessel density in progressive glioblastoma (p = .01) and no correlation between the two timepoints (r = -.07). CONCLUSION Our results suggest that the extent of hyperperfusion in glioblastoma at first diagnosis is not a sustaining tumor characteristic. Hence, the rCBVmax at initial diagnosis should be disregarded when reviewing MRIs for glioblastoma progression.
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Affiliation(s)
- Eike Steidl
- Institute of Neuroradiology, Goethe University Hospital, Frankfurt am Main, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- * E-mail:
| | - Katharina Filipski
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Institute of Neurology (Edinger Institute), Goethe University Hospital, Frankfurt am Main, Germany
- Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany
| | - Elke Hattingen
- Institute of Neuroradiology, Goethe University Hospital, Frankfurt am Main, Germany
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany
| | - Joachim P. Steinbach
- German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ), Heidelberg, Germany
- Frankfurt Cancer Institute (FCI), Frankfurt am Main, Germany
- Dr. Senckenberg Institute of Neurooncology, Goethe University Hospital, Frankfurt am Main, Germany
| | - Gabriele D. Maurer
- Dr. Senckenberg Institute of Neurooncology, Goethe University Hospital, Frankfurt am Main, Germany
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11
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Fernández-Valverde F, Bautista-Bárcena M, Roldán-Romero E, Solivera-Vela J, Bravo-Rodríguez F, Ramos-Gómez M. Valor pronóstico de la perfusión cerebral por RM en el estudio inicial de los gliomas de alto grado. RADIOLOGIA 2023. [DOI: 10.1016/j.rx.2022.12.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
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12
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Qiu X, Gao J, Yang J, Hu J, Hu W, Zhang X, Lu JJ, Kong L. Perfusion MR prior to radiotherapy is a strong predictor of survival in high-grade gliomas after proton and carbon ion radiotherapy. ANNALS OF TRANSLATIONAL MEDICINE 2022; 10:1199. [PMID: 36544672 PMCID: PMC9761124 DOI: 10.21037/atm-20-1646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 04/27/2020] [Indexed: 12/24/2022]
Abstract
Background To assess the survival predictability of perfusion magnetic resonance imaging (MRI) by the normalized cerebral blood volume (nCBV) prior to particle beam radiotherapy (PBRT) in high-grade glioma (HGG) patients underwent particle therapy. Methods The study retrieved dynamic susceptibility contrast MRI acquired prior to PBRT between 6/2015 and 3/2019 in 45 patients with HGG. Maximum nCBV (nCBVmax) within or adjacent to surgical/tumor bed was measured using 'hot-spot' method. The predictive values of nCBVmax for progression-free survival (PFS) and overall survival (OS) were assessed in univariate Kaplan-Meier curve and multivariate Cox proportional hazards (CPH) models. Nomograms based on CPH results were constructed to individualize the predicted probability of OS and PFS. Results The Kaplan-Meier curves and all CPH models based on nCBVmax as continuous variable (nCBVmax-C), group by cut-off derived from median value and Youden-index method showed that nCBVmax prior to radiotherapy was a strong predictor for both PFS and OS in HGG patients who underwent PBRT. Nomograms built on CPH models showed similar excellent performance in both discrimination and calibration. Conclusions Perfusion imaging prior to PBRT is a strong predictor of survival in HGG. Novel perfusion MR-based nomogram with prospective validation could potentially be formally used in future clinical practice to individualize survival probability.
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Affiliation(s)
- Xianxin Qiu
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Jing Gao
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Jing Yang
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Jiyi Hu
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Weixu Hu
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Xiaoyong Zhang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China;,Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Jiade J. Lu
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Shanghai, China
| | - Lin Kong
- Shanghai Engineering Research Center of Proton and Heavy Ion Radiation Therapy, Shanghai, China;,Department of Radiation Oncology, Shanghai Proton and Heavy Ion Center, Fudan University Cancer Center, Shanghai, China
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13
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Pang Y, Wang H, Li H. Medical Imaging Biomarker Discovery and Integration Towards AI-Based Personalized Radiotherapy. Front Oncol 2022; 11:764665. [PMID: 35111666 PMCID: PMC8801459 DOI: 10.3389/fonc.2021.764665] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Accepted: 11/29/2021] [Indexed: 12/22/2022] Open
Abstract
Intensity-modulated radiation therapy (IMRT) has been used for high-accurate physical dose distribution sculpture and employed to modulate different dose levels into Gross Tumor Volume (GTV), Clinical Target Volume (CTV) and Planning Target Volume (PTV). GTV, CTV and PTV can be prescribed at different dose levels, however, there is an emphasis that their dose distributions need to be uniform, despite the fact that most types of tumour are heterogeneous. With traditional radiomics and artificial intelligence (AI) techniques, we can identify biological target volume from functional images against conventional GTV derived from anatomical imaging. Functional imaging, such as multi parameter MRI and PET can be used to implement dose painting, which allows us to achieve dose escalation by increasing doses in certain areas that are therapy-resistant in the GTV and reducing doses in less aggressive areas. In this review, we firstly discuss several quantitative functional imaging techniques including PET-CT and multi-parameter MRI. Furthermore, theoretical and experimental comparisons for dose painting by contours (DPBC) and dose painting by numbers (DPBN), along with outcome analysis after dose painting are provided. The state-of-the-art AI-based biomarker diagnosis techniques is reviewed. Finally, we conclude major challenges and future directions in AI-based biomarkers to improve cancer diagnosis and radiotherapy treatment.
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Affiliation(s)
- Yaru Pang
- Department of Medical Physics and Biomedical Engineering, University College London, London, United Kingdom
| | - Hui Wang
- Department of Chemical Engineering, University College London, London, United Kingdom
| | - He Li
- Department of Engineering, University of Cambridge, Cambridge, United Kingdom
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14
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Preliminary study of multiple b-value diffusion-weighted images and T1 post enhancement magnetic resonance imaging images fusion with Laplacian Re-decomposition (LRD) medical fusion algorithm for glioma grading. Eur J Radiol Open 2021; 8:100378. [PMID: 34632000 PMCID: PMC8487979 DOI: 10.1016/j.ejro.2021.100378] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2021] [Revised: 09/20/2021] [Accepted: 09/26/2021] [Indexed: 12/21/2022] Open
Abstract
LRD medical image fusion algorithm can be used for glioma grading. We can use the LRD fusion algorithm with MRI image for glioma grading. Fusing of DWI (b50) and T1 enhancement (T1Gd) by LRD, have highest diagnostic value for glioma grading.
Background Grade of brain tumor is thought to be the most significant and crucial component in treatment management. Recent development in medical imaging techniques have led to the introduce non-invasive methods for brain tumor grading such as different magnetic resonance imaging (MRI) protocols. Combination of different MRI protocols with fusion algorithms for tumor grading is used to increase diagnostic improvement. This paper investigated the efficiency of the Laplacian Re-decomposition (LRD) fusion algorithms for glioma grading. Procedures In this study, 69 patients were examined with MRI. The T1 post enhancement (T1Gd) and diffusion-weighted images (DWI) were obtained. To evaluated LRD performance for glioma grading, we compared the parameters of the receiver operating characteristic (ROC) curves. Findings We found that the average Relative Signal Contrast (RSC) for high-grade gliomas is greater than RSCs for low-grade gliomas in T1Gd images and all fused images. No significant difference in RSCs of DWI images was observed between low-grade and high-grade gliomas. However, a significant RSCs difference was detected between grade III and IV in the T1Gd, b50, and all fussed images. Conclusions This research suggests that T1Gd images are an appropriate imaging protocol for separating low-grade and high-grade gliomas. According to the findings of this study, we may use the LRD fusion algorithm to increase the diagnostic value of T1Gd and DWI picture for grades III and IV glioma distinction. In conclusion, this article has emphasized the significance of the LRD fusion algorithm as a tool for differentiating grade III and IV gliomas.
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Key Words
- ADC, apparent diffusion coefficient
- AUC, Aera Under Curve
- BOLD, blood oxygen level dependent imaging
- CBV, Cerebral Blood Volume
- DCE, Dynamic contrast enhancement
- DGR, Decision Graph Re-decomposition
- DWI, Diffusion-weighted imaging
- Diffusion-weighted images
- FA, flip angle
- Fusion algorithm
- GBM, glioblastomas
- GDIE, Gradient Domain Image Enhancement
- Glioma
- Grade
- IRS, Inverse Re-decomposition Scheme
- LEM, Local Energy Maximum
- LP, Laplacian Pyramid
- LRD, Laplacian Re-decomposition
- Laplacian Re-decomposition
- MLD, Maximum Local Difference
- MRI, magnetic resonance imaging
- MRS, Magnetic resonance spectroscopy
- MST, Multi-scale transform
- Magnetic resonance imaging
- NOD, Non-overlapping domain
- OD, overlapping domain
- PACS, PACS picture archiving and communication system
- ROC, receiver operating characteristic curve
- ROI, regions of interest
- RSC, Relative Signal Contrast
- SCE, Susceptibility contrast enhancement
- T1Gd, T1 post enhancement
- TE, time of echo
- TI, time of inversion
- TR, repetition time
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Connor M, Kim MM, Cao Y, Hattangadi-Gluth J. Precision Radiotherapy for Gliomas: Implementing Novel Imaging Biomarkers to Improve Outcomes With Patient-Specific Therapy. Cancer J 2021; 27:353-363. [PMID: 34570449 PMCID: PMC8480523 DOI: 10.1097/ppo.0000000000000546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/27/2022]
Abstract
ABSTRACT Gliomas are the most common primary brain cancer, yet are extraordinarily challenging to treat because they can be aggressive and infiltrative, locally recurrent, and resistant to standard treatments. Furthermore, the treatments themselves, including radiation therapy, can affect patients' neurocognitive function and quality of life. Noninvasive imaging is the standard of care for primary brain tumors, including diagnosis, treatment planning, and monitoring for treatment response. This article explores the ways in which advanced imaging has and will continue to transform radiation treatment for patients with gliomas, with a focus on cognitive preservation and novel biomarkers, as well as precision radiotherapy and treatment adaptation. Advances in novel imaging techniques continue to push the field forward, to more precisely guided treatment planning, radiation dose escalation, measurement of therapeutic response, and understanding of radiation-associated injury.
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Affiliation(s)
- Michael Connor
- From the Department of Radiation Medicine and Applied Sciences, UC San Diego, Moores Cancer Center, La Jolla, CA
| | - Michelle M Kim
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, MI
| | - Jona Hattangadi-Gluth
- From the Department of Radiation Medicine and Applied Sciences, UC San Diego, Moores Cancer Center, La Jolla, CA
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16
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Kim MM, Sun Y, Aryal MP, Parmar HA, Piert M, Rosen B, Mayo CS, Balter JM, Schipper M, Gabel N, Briceño EM, You D, Heth J, Al-Holou W, Umemura Y, Leung D, Junck L, Wahl DR, Lawrence TS, Cao Y. A Phase 2 Study of Dose-intensified Chemoradiation Using Biologically Based Target Volume Definition in Patients With Newly Diagnosed Glioblastoma. Int J Radiat Oncol Biol Phys 2021; 110:792-803. [PMID: 33524546 PMCID: PMC8920120 DOI: 10.1016/j.ijrobp.2021.01.033] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 01/14/2021] [Accepted: 01/21/2021] [Indexed: 12/15/2022]
Abstract
PURPOSE We hypothesized that dose-intensified chemoradiation therapy targeting adversely prognostic hypercellular (TVHCV) and hyperperfused (TVCBV) tumor volumes would improve outcomes in patients with glioblastoma. METHODS AND MATERIALS This single-arm, phase 2 trial enrolled adult patients with newly diagnosed glioblastoma. Patients with a TVHCV/TVCBV >1 cm3, identified using high b-value diffusion-weighted magnetic resonance imaging (MRI) and dynamic contrast-enhanced perfusion MRI, were treated over 30 fractions to 75 Gy to the TVHCV/TVCBV with temozolomide. The primary objective was to estimate improvement in 12-month overall survival (OS) versus historical control. Secondary objectives included evaluating the effect of 3-month TVHCV/TVCBV reduction on OS using Cox proportional-hazard regression and characterizing coverage (95% isodose line) of metabolic tumor volumes identified using correlative 11C-methionine positron emission tomography. Clinically meaningful change was assessed for quality of life by the European Organisation for the Research and Treatment of Cancer Quality of Life Questionnaire C30, for symptom burden by the MD Anderson Symptom Inventory for brain tumor, and for neurocognitive function (NCF) by the Controlled Oral Word Association Test, the Trail Making Test, parts A and B, and the Hopkins Verbal Learning Test-Revised. RESULTS Between 2016 and 2018, 26 patients were enrolled. Initial patients were boosted to TVHCV alone, and 13 patients were boosted to both TVHCV/TVCBV. Gross or subtotal resection was performed in 87% of patients; 22% were O6-methylguanine-DNA methyltransferase (MGMT) methylated. With 26-month follow-up (95% CI, 19-not reached), the 12-month OS rate among patients boosted to the combined TVHCV/TVCBV was 92% (95% CI, 78%-100%; P = .03) and the median OS was 20 months (95% CI, 18-not reached); the median OS for the whole study cohort was 20 months (95% CI, 14-29 months). Patients whose 3-month TVHCV/TVCBV decreased to less than the median volume (3 cm3) had superior OS (29 vs 12 months; P = .02). Only 5 patients had central or in-field failures, and 93% (interquartile range, 59%-100%) of the 11C-methionine metabolic tumor volumes received high-dose coverage. Late grade 3 neurologic toxicity occurred in 2 patients. Among non-progressing patients, 1-month and 7-month deterioration in quality of life, symptoms, and NCF were similar in incidence to standard therapy. CONCLUSIONS Dose intensification against hypercellular/hyperperfused tumor regions in glioblastoma yields promising OS with favorable outcomes for NCF, symptom burden, and quality of life, particularly among patients with greater tumor reduction 3 months after radiation therapy.
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Affiliation(s)
- Michelle M Kim
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan.
| | - Yilun Sun
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Madhava P Aryal
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Hemant A Parmar
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Morand Piert
- Department of Radiology, University of Michigan, Ann Arbor, Michigan
| | - Benjamin Rosen
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Charles S Mayo
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - James M Balter
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Matthew Schipper
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Biostatistics, University of Michigan, Ann Arbor, Michigan
| | - Nicolette Gabel
- Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor, Michigan
| | - Emily M Briceño
- Department of Physical Medicine and Rehabilitation, University of Michigan, Ann Arbor, Michigan
| | - Daekeun You
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Jason Heth
- Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan
| | - Wajd Al-Holou
- Department of Neurosurgery, University of Michigan, Ann Arbor, Michigan
| | - Yoshie Umemura
- Department of Neurology, University of Michigan, Ann Arbor, Michigan
| | - Denise Leung
- Department of Neurology, University of Michigan, Ann Arbor, Michigan
| | - Larry Junck
- Department of Neurology, University of Michigan, Ann Arbor, Michigan
| | - Daniel R Wahl
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Theodore S Lawrence
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan
| | - Yue Cao
- Department of Radiation Oncology, University of Michigan, Ann Arbor, Michigan; Department of Radiology, University of Michigan, Ann Arbor, Michigan; Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan
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Cao H, Xiao X, Hua J, Huang G, He W, Qin J, Wu Y, Li X. The Added Value of Inflow-Based Vascular-Space-Occupancy and Diffusion-Weighted Imaging in Preoperative Grading of Gliomas. NEURODEGENER DIS 2021; 20:123-130. [PMID: 33735873 DOI: 10.1159/000512545] [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] [Received: 09/20/2020] [Accepted: 10/26/2020] [Indexed: 11/19/2022] Open
Abstract
OBJECTIVES The present study aimed to study whether combined inflow-based vascular-space-occupancy (iVASO) MR imaging (MRI) and diffusion-weighted imaging (DWI) improve the diagnostic accuracy in the preoperative grading of gliomas. METHODS Fifty-one patients with histopathologically confirmed diffuse gliomas underwent preoperative structural MRI, iVASO, and DWI. We performed 2 qualitative consensus reviews: (1) structural MR images alone and (2) structural MR images with iVASO and DWI. Relative arteriolar cerebral blood volume (rCBVa) and minimum apparent diffusion coefficient (mADC) were compared between low-grade and high-grade gliomas. Receiver operating characteristic (ROC) curve analysis was performed to compare the tumor grading efficiency of rCBVa, mADC, and the combination of the two parameters. RESULTS Two observers diagnosed accurate tumor grade in 40 of 51 (78.4%) patients in the first review and in 46 of 51 (90.2%) in the second review. Both rCBVa and mADC showed significant differences between low-grade and high-grade gliomas. ROC analysis gave a threshold value of 1.52 for rCBVa and 0.85 × 10-3 mm2/s for mADC to provide a sensitivity and specificity of 88.0 and 81.2% and 100.0 and 68.7%, respectively. The area under the ROC curve (AUC) was 0.87 and 0.85 for rCBVa and mADC, respectively. The combination of rCBVa and mADC values increased the AUC to 0.92. CONCLUSION The combined application of iVASO and DWI may improve the diagnostic accuracy of glioma grading.
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Affiliation(s)
- Haimei Cao
- Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Xiang Xiao
- Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jun Hua
- Neurosection, Division of MRI Research, Department of Radiology, Johns Hopkins University School of Medicine, Baltimore, Meghalaya, USA.,Department of Radiology, F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Johns Hopkins University School of Medicine, Baltimore, Meghalaya, USA
| | - Guanglong Huang
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Wenle He
- Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Jie Qin
- Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, China
| | - Yuankui Wu
- Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, China,
| | - Xiaodan Li
- Department of Medical Imaging, Nanfang Hospital, Southern Medical University, Guangzhou, China
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18
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Fudaba H, Momii Y, Matsuta H, Onishi K, Kawasaki Y, Sugita K, Shimomura T, Fujiki M. Perfusion Parameter Obtained on 3-Tesla Magnetic Resonance Imaging and the Ki-67 Labeling Index Predict the Overall Survival of Glioblastoma. World Neurosurg 2021; 149:e469-e480. [PMID: 33567368 DOI: 10.1016/j.wneu.2021.02.002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2020] [Revised: 01/31/2021] [Accepted: 02/01/2021] [Indexed: 11/30/2022]
Abstract
BACKGROUND Pulsed arterial spin-labeling, diffusion tensor imaging (DTI), and magnetic resonance spectroscopy (MRS) are useful for predicting glioma survival. We performed a comparative review of multiple parameters obtained using these pulse sequences on 3-Tesla magnetic resonance imaging (MRI) including the molecular status and Ki-67 labeling index in newly diagnosed supratentorial glioblastomas. METHODS A total of 35 patients with glioblastomas underwent pulsed arterial spin-labeling, DTI, and MRS studies using 3-Tesla MRI preoperatively. The isocitrate dehydrogenase (IDH) mutation status, methylguanine-DNA methyltransferase methylation status, and Ki-67 labeling index were calculated from the tumor specimen. Cutoff values were identified by analyzing a receiver operating characteristic curve, and the multivariate survival statistical technique was performed to determine the significant and independent parameters for predicting overall survival. RESULTS The multivariate Cox analysis showed that the maximum/mean relative cerebral blood flow (rCBF) ratio and the Ki-67 labeling index were significant and independent predictive parameters with a cutoff value of 1.589 for the maximum rCBF ratio, 1.286 for the mean rCBF ratio, and 19% for the Ki-67 labeling index and hazard ratios of 6.132 and 5.119, respectively. The Kaplan-Meier survival curves showed that patients with higher rCBF ratios and Ki-67 labeling indices had a shorter overall survival than others, with median overall survival durations of 479 (95% CI, 370-559) and 1243 (95% CI, 666-NA) days, respectively (P = 0.000167). CONCLUSIONS Our findings indicate that the preoperative rCBF ratio and Ki-67 labeling index are useful parameters for predicting the overall survival of cerebral glioblastomas.
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Affiliation(s)
- Hirotaka Fudaba
- Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan.
| | - Yasutomo Momii
- Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - Hiroyuki Matsuta
- Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - Kouhei Onishi
- Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - Yukari Kawasaki
- Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - Kenji Sugita
- Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
| | - Tsuyoshi Shimomura
- Department of Medical Informatics, Oita University Faculty of Medicine, Oita, Japan
| | - Minoru Fujiki
- Department of Neurosurgery, Oita University Faculty of Medicine, Oita, Japan
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Evaluating survival in subjects with astrocytic brain tumors by dynamic susceptibility-weighted perfusion MR imaging. PLoS One 2021; 16:e0244275. [PMID: 33406116 PMCID: PMC7787526 DOI: 10.1371/journal.pone.0244275] [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] [Received: 02/18/2020] [Accepted: 12/07/2020] [Indexed: 12/02/2022] Open
Abstract
Purpose Studies have evaluated the application of perfusion MR for predicting survival in patients with astrocytic brain tumors, but few of them statistically adjust their results to reflect the impact of the variability of treatment administered in the patients. Our aim was to analyze the association between the perfusion values and overall survival time, with adjustment for various clinical factors, including initial treatments and follow-up treatments. Materials and methods This study consisted of 51 patients with astrocytic brain tumors who underwent perfusion-weighted MRI with MultiHance® at a dose of 0.1 mmol/kg prior to initial surgery. We measured the mean rCBV, the 5% & 10% maximum rCBV, and the variation of rCBV in the tumors. Comparisons were made between patients with and without 2-year survival using two-sample t-test or Wilcoxon rank-sum test for the continuous data, or chi-square and Fisher exact tests for categorical data. The multivariate cox-proportional hazard regression was fit to evaluate the association between rCBV and overall survival time, with adjustment for clinical factors. Results Patients who survived less than 2 years after diagnosis had a higher mean and maximum rCBV and a larger variation of rCBV. After adjusting for clinical factors including therapeutic measures, we found no significant association of overall survival time within 2 years with any of these rCBV values. Conclusions Although patients who survived less than 2 years had a higher mean and maximum rCBV and a larger variation of rCBV, rCBV itself may not be used independently for predicting 2-year survival of patients with astrocytic brain tumors.
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20
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Lundy P, Domino J, Ryken T, Fouke S, McCracken DJ, Ormond DR, Olson JJ. The role of imaging for the management of newly diagnosed glioblastoma in adults: a systematic review and evidence-based clinical practice guideline update. J Neurooncol 2020; 150:95-120. [DOI: 10.1007/s11060-020-03597-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Accepted: 08/08/2020] [Indexed: 12/11/2022]
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21
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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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22
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Schiff D, Van den Bent M, Vogelbaum MA, Wick W, Miller CR, Taphoorn M, Pope W, Brown PD, Platten M, Jalali R, Armstrong T, Wen PY. Recent developments and future directions in adult lower-grade gliomas: Society for Neuro-Oncology (SNO) and European Association of Neuro-Oncology (EANO) consensus. Neuro Oncol 2020; 21:837-853. [PMID: 30753579 DOI: 10.1093/neuonc/noz033] [Citation(s) in RCA: 70] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/01/2023] Open
Abstract
The finding that most grades II and III gliomas harbor isocitrate dehydrogenase (IDH) mutations conveying a relatively favorable and fairly similar prognosis in both tumor grades highlights that these tumors represent a fundamentally different entity from IDH wild-type gliomas exemplified in most glioblastoma. Herein we review the most recent developments in molecular neuropathology leading to reclassification of these tumors based upon IDH and 1p/19q status, as well as the potential roles of methylation profiling and deletional analysis of cyclin-dependent kinase inhibitor 2A and 2B. We discuss the epidemiology, clinical manifestations, benefit of surgical resection, and neuroimaging features of lower-grade gliomas as they relate to molecular subtype, including advanced imaging techniques such as 2-hydroxyglutarate magnetic resonance spectroscopy and amino acid PET scanning. Recent, ongoing, and planned studies of radiation therapy and both cytotoxic and targeted chemotherapies are summarized, including both small molecule and immunotherapy approaches specifically targeting the mutant IDH protein.
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Affiliation(s)
- David Schiff
- Department of Neurology, University of Virginia, Charlottesville, Virginia
| | - Martin Van den Bent
- Department of Neurology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
| | | | - Wolfgang Wick
- Divison of Neuro-Oncology, German Cancer Research Center, Heidelberg, Germany
| | - C Ryan Miller
- Pathology and Lab Medicine, University of North Carolina, Chapel Hill, North Carolina
| | - Martin Taphoorn
- Department of Neurology, Leiden University Medical Center, Leiden, The Netherlands
| | - Whitney Pope
- Section of Neuroradiology, UCLA, Los Angeles, California
| | - Paul D Brown
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | - Michael Platten
- Department of Neurology, Mannheim University Hospital, Mannheim, Germany
| | | | - Terri Armstrong
- Neuro-Oncology Branch, National Institute of Health, Bethesda, Maryland
| | - Patrick Y Wen
- Center for Neuro-Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
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Impact of Early Reoperation on the Prognosis of Patients Operated on for Glioblastoma. World Neurosurg 2020; 139:e592-e600. [PMID: 32330620 DOI: 10.1016/j.wneu.2020.04.072] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2020] [Revised: 04/07/2020] [Accepted: 04/09/2020] [Indexed: 11/23/2022]
Abstract
BACKGROUND The prognosis for patients with glioblastoma depends particularly on the degree of tumor resection. Patients with tumor remnants in postsurgical magnetic resonance imaging (<72 hours) may benefit from early reoperation. We present our results concerning the impact on overall survival (OS) and progression-free survival (PFS) of reoperation in patients who have already undergone surgery for glioblastoma. METHODS This study included all patients who had undergone surgery for glioblastoma with control magnetic resonance imaging, who received adjuvant therapy as per the Stupp protocol, with a minimum follow-up of 24 months. We recorded the number of complete resections, partial resections, and early reoperations. We determined the impact on OS and PFS of the early reoperations and the functional status. We considered complete resection when the volume of the residual tumor was 0 cm3. RESULTS A total of 112 patients were diagnosed with glioblastoma between March 2014 and March 2017. The study included 58 patients who fulfilled all the inclusion criteria. Complete resection was achieved in 24 patients (41.4%) and partial resection in 34 (58.6%). Of these 34 patients, 11 (32.35%) underwent early reoperation. The final result was complete resection in 58.62% of the patients. In the patients who underwent reoperation, OS and PFS were 30.3 months and 16.6 months compared with 12.7 months and 6.75 months in those without reoperation (P = 0.013 and P = 0.012). The functional prognosis was similar between the 2 groups. CONCLUSIONS Early reoperation in patients with residual tumor improved OS and PFS without increasing the number of complications compared with the patients who did not undergo reoperation.
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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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25
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Kim MM, Parmar HA, Aryal MP, Mayo CS, Balter JM, Lawrence TS, Cao Y. Developing a Pipeline for Multiparametric MRI-Guided Radiation Therapy: Initial Results from a Phase II Clinical Trial in Newly Diagnosed Glioblastoma. ACTA ACUST UNITED AC 2020; 5:118-126. [PMID: 30854449 PMCID: PMC6403045 DOI: 10.18383/j.tom.2018.00035] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Quantitative mapping of hyperperfused and hypercellular regions of glioblastoma has been proposed to improve definition of tumor regions at risk for local recurrence following conventional radiation therapy. As the processing of the multiparametric dynamic contrast-enhanced (DCE-) and diffusion-weighted (DW-) magnetic resonance imaging (MRI) data for delineation of these subvolumes requires additional steps that go beyond the standard practices of target definition, we sought to devise a workflow to support the timely planning and treatment of patients. A phase II study implementing a multiparametric imaging biomarker for tumor hyperperfusion and hypercellularity consisting of DCE-MRI and high b-value DW-MRI to guide intensified (75 Gy/30 fractions) radiation therapy (RT) in patients with newly diagnosed glioblastoma was launched. In this report, the workflow and the initial imaging outcomes of the first 12 patients are described. Among all the first 12 patients, treatment was initiated within 6 weeks of surgery and within 2 weeks of simulation. On average, the combined hypercellular volume and high cerebral blood volume/tumor perfusion volume were 1.8 times smaller than the T1 gadolinium abnormality and 10 times smaller than the FLAIR abnormality. Hypercellular volume and high cerebral blood volume/tumor perfusion volume each identified largely distinct regions and showed 57% overlap with the enhancing abnormality, and minimal-to-no extension outside of the FLAIR. These results show the feasibility of implementing a workflow for multiparametric magnetic resonance-guided radiation therapy into clinical trials with a coordinated multidisciplinary team, and the unique and complementary tumor subregions identified by the combination of high b-value DW-MRI and DCE-MRI.
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Affiliation(s)
| | | | | | | | | | | | - Yue Cao
- Departments of Radiation Oncology and
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26
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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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Qin J, Zhang H, Wang X, Tan Y, Wu X. Combination value of diffusion‑weighted imaging and dynamic susceptibility contrast‑enhanced MRI in astrocytoma grading and correlation with GFAP, Topoisomerase IIα and MGMT. Oncol Lett 2019; 18:2763-2770. [PMID: 31452754 PMCID: PMC6704283 DOI: 10.3892/ol.2019.10656] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2016] [Accepted: 01/19/2017] [Indexed: 11/06/2022] Open
Abstract
The present study aimed to investigate the value of diffusion-weighted imaging (DWI) combined with dynamic susceptibility contrast-enhanced (DSC) magnetic resonance imaging (MRI) scans in astrocytoma grading, and correlated MRI scan parameters of values of apparent diffusion coefficient (ADC) and relative cereberal blood volume (rCBV) with the immunohistochemical (IHC) indices of glial fibrillary acidic protein (GFAP), topoisomerase IIα (Topo IIα) and O 6-methylguanine-DNA methyltransferase (MGMT). A total of 123 patients with pathologically confirmed astrocytomas of differing grades underwent DWI and DSC scans. The values of the ADC and relative cerebral blood volume rCBV were compared with the grade II–IV astrocytomas. Receiver operating characteristic curves were used to compare astrocytoma grading efficiency of ADC, rCBV and the combination of the two values. The parameters of ADC and rCBV with GFAP, Topo IIα and MGMT indices were then correlated. The differences in ADC values were significant between the grades II, III and IV astrocytomas, and the rCBV values for grades II, III and IV were also significant. The combination of DWI and DSC demonstrated the highest values for area under curve in identifying grades II and III, and identifying grades III and IV, respectively. GFAP displayed a positive correlation with ADC and a negative correlation with rCBV. Topo IIα exhibited a negative correlation with ADC, and a positive correlation with rCBV. No correlation was observed between MGMT and ADC or rCBV. The combined application of DWI and DSC may increase astrocytoma grading accuracy. Values of ADC and rCBV exhibit certain correlations with IHC indices, and may predict degree of malignancy of astrocytoma.
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Affiliation(s)
- Jiang‑Bo Qin
- Department of Radiology, The First Clinical Medical College of Shanxi Medical University, Taiyuan, Shanxi 030001, P.R. China
| | - Hui Zhang
- Department of Radiology, The First Clinical Medical College of Shanxi Medical University, Taiyuan, Shanxi 030001, P.R. China
| | - Xiao‑Chun Wang
- Department of Medical Imaging, Shanxi Medical University, Taiyuan, Shanxi 030001, P.R. China
| | - Yan Tan
- Department of Radiology, The First Clinical Medical College of Shanxi Medical University, Taiyuan, Shanxi 030001, P.R. China
| | - Xiao‑Feng Wu
- Department of Radiology, The First Clinical Medical College of Shanxi Medical University, Taiyuan, Shanxi 030001, P.R. China
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Radiomics in peritumoral non-enhancing regions: fractional anisotropy and cerebral blood volume improve prediction of local progression and overall survival in patients with glioblastoma. Neuroradiology 2019; 61:1261-1272. [PMID: 31289886 DOI: 10.1007/s00234-019-02255-4] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2019] [Accepted: 06/27/2019] [Indexed: 12/13/2022]
Abstract
PURPOSE The peritumoral non-enhancing region (NER) is frequently not removed during the surgical resection of glioblastoma, with most recurrences occurring within the original treatment field. This study determined whether radiomics analysis of the NER can predict local recurrence and overall survival in patients with glioblastoma. METHODS Preoperative magnetic resonance imaging (MRI) scans from 83 consecutive patients with glioblastoma were retrospectively reviewed and grouped into training (n = 59) and test sets (n = 24). A total of 6472 radiomic features were extracted from contrast-enhanced T1-weighted and fluid-attenuated inversion recovery images and from fractional anisotropy (FA) and normalized cerebral blood volume (CBV) maps. A diagnostic model to predict 6-month progression was tested using the area under the receiver operating characteristics curve (AUC) and compared with the single parameters of FA and CBV. A survival model was tested using Harrell's C-index and compared with clinical models that included age, sex, Karnofsky performance score, and extent of surgical resection. RESULTS Four FA features and six CBV features were selected for the diagnostic model; no features were extracted from conventional MRI. Combined FA and CBV radiomics showed better predictive value for local progression (AUC, 0.79; 95% CI, 0.67-0.90) than single imaging radiomics (AUC, 0.70-0.76) or single imaging parameters (AUC, 0.51-0.54). The combined model (C-index, 0.87) improved prognostication when added to clinical models (C-index, 0.72). CONCLUSION Radiomics features using FA and CBV in the NER have the potential to improve prediction of local progression and overall survival in patients with glioblastoma.
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Amide proton transfer imaging might predict survival and IDH mutation status in high-grade glioma. Eur Radiol 2019; 29:6643-6652. [PMID: 31175415 DOI: 10.1007/s00330-019-06203-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2018] [Revised: 03/14/2019] [Accepted: 03/26/2019] [Indexed: 01/27/2023]
Abstract
OBJECTIVES To assess the utility of amide proton transfer (APT) imaging as an imaging biomarker to predict prognosis and molecular marker status in high-grade glioma (HGG, WHO grade III/IV). METHODS We included 71 patients with pathologically diagnosed HGG who underwent preoperative MRI with APT imaging. Overall survival (OS) and progression-free survival (PFS) according to APT signal, clinical factors, MGMT methylation status, and IDH mutation status were analyzed. Multivariate Cox regression models with and without APT signal data were constructed. Model performance was compared using the integrated AUC (iAUC). Associations between APT signals and molecular markers were assessed using the Mann-Whitney test. RESULTS High APT signal was a significant predictor for poor OS (HR = 3.21, 95% CI = 1.62-6.34) and PFS (HR = 2.22, 95% CI = 1.33-3.72) on univariate analysis. On multivariate analysis, high APT signals were an independent predictor of poor OS and PFS when clinical factors alone (OS: HR = 2.89; PFS: HR = 2.13), or in combination with molecular markers (OS: HR = 2.85; PFS: HR = 2.00), were included as covariates. The incremental prognostic value of APT signals was significant for OS and PFS. IDH-wild type was significantly associated with high APT signals (p = 0.001) when compared to IDH-mutant; however, there was no difference based on MGMT methylation status (p = 0.208). CONCLUSION High APT signal was a significant predictor of poor prognosis in HGG. APT data showed significant incremental prognostic value over clinical prognostic factors and molecular markers and may also predict IDH mutation status. KEY POINTS • Amide proton transfer (APT) imaging is a promising prognostic marker of high-grade glioma. • APT signals were significantly higher in IDH-wild type compared to IDH-mutant high-grade glioma. • APT imaging may be valuable for preoperative screening and treatment guidance.
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30
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Navone SE, Doniselli FM, Summers P, Guarnaccia L, Rampini P, Locatelli M, Campanella R, Marfia G, Costa A. Correlation of Preoperative Von Willebrand Factor with Magnetic Resonance Imaging Perfusion and Permeability Parameters as Predictors of Prognosis in Glioblastoma. World Neurosurg 2019; 122:e226-e234. [DOI: 10.1016/j.wneu.2018.09.216] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Revised: 09/26/2018] [Accepted: 09/28/2018] [Indexed: 10/28/2022]
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Macrovascular Networks on Contrast-Enhanced Magnetic Resonance Imaging Improves Survival Prediction in Newly Diagnosed Glioblastoma. Cancers (Basel) 2019; 11:cancers11010084. [PMID: 30646519 PMCID: PMC6356693 DOI: 10.3390/cancers11010084] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2018] [Revised: 12/17/2018] [Accepted: 12/20/2018] [Indexed: 12/30/2022] Open
Abstract
A higher degree of angiogenesis is associated with shortened survival in glioblastoma. Feasible morphometric parameters for analyzing vascular networks in brain tumors in clinical practice are lacking. We investigated whether the macrovascular network classified by the number of vessel-like structures (nVS) visible on three-dimensional T1-weighted contrast–enhanced (3D-T1CE) magnetic resonance imaging (MRI) could improve survival prediction models for newly diagnosed glioblastoma based on clinical and other imaging features. Ninety-seven consecutive patients (62 men; mean age, 58 ± 15 years) with histologically proven glioblastoma underwent 1.5T-MRI, including anatomical, diffusion-weighted, dynamic susceptibility contrast perfusion, and 3D-T1CE sequences after 0.1 mmol/kg gadobutrol. We assessed nVS related to the tumor on 1-mm isovoxel 3D-T1CE images, and relative cerebral blood volume, relative cerebral flow volume (rCBF), delay mean time, and apparent diffusion coefficient in volumes of interest for contrast-enhancing lesion (CEL), non-CEL, and contralateral normal-appearing white matter. We also assessed Visually Accessible Rembrandt Images scoring system features. We used ROC curves to determine the cutoff for nVS and univariate and multivariate cox proportional hazards regression for overall survival. Prognostic factors were evaluated by Kaplan-Meier survival and ROC analyses. Lesions with nVS > 5 were classified as having highly developed macrovascular network; 58 (60.4%) tumors had highly developed macrovascular network. Patients with highly developed macrovascular network were older, had higher volumeCEL, increased rCBFCEL, and poor survival; nVS correlated negatively with survival (r = −0.286; p = 0.008). On multivariate analysis, standard treatment, age at diagnosis, and macrovascular network best predicted survival at 1 year (AUC 0.901, 83.3% sensitivity, 93.3% specificity, 96.2% PPV, 73.7% NPV). Contrast-enhanced MRI macrovascular network improves survival prediction in newly diagnosed glioblastoma.
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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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Fuster-Garcia E, Juan-Albarracín J, García-Ferrando GA, Martí-Bonmatí L, Aparici-Robles F, García-Gómez JM. Improving the estimation of prognosis for glioblastoma patients by MR based hemodynamic tissue signatures. NMR IN BIOMEDICINE 2018; 31:e4006. [PMID: 30239058 DOI: 10.1002/nbm.4006] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Revised: 07/20/2018] [Accepted: 07/23/2018] [Indexed: 06/08/2023]
Abstract
Advanced MRI and molecular markers have been raised as crucial to improve prognostic models for patients having glioblastoma (GBM) lesions. In particular, different MR perfusion based markers describing vascular intrapatient heterogeneity have been correlated with tumor aggressiveness, and represent key information to understand tumor resistance against effective therapies of these neoplasms. Recently, hemodynamic tissue signature (HTS) markers based on MR perfusion images have been demonstrated to be useful for describing the heterogeneity of GBM at the voxel level, as well as demonstrating significant correlations with the patient's overall survival. In this work, we analyze the abilities of these markers to improve the conventional prognostic models based on clinical, morphological, and demographic features. Our results, in both the regression and classification tests, show that inclusion of the HTS markers improves the reliability of prognostic models. The HTS method is fully automatic and it is available for research use at http://www.oncohabitats.upv.es.
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Affiliation(s)
- Elies Fuster-Garcia
- 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
| | - Germán A García-Ferrando
- Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de València, València, Spain
| | - Luis Martí-Bonmatí
- Medical Imaging Department, La Fe Polytechnics and University Hospital, València, Spain
- Imaging Research Group (GIBI230), La Fe Health Research Institute, València, Spain
| | - Fernando Aparici-Robles
- Medical Imaging Department, La Fe Polytechnics and University Hospital, València, Spain
- Imaging Research Group (GIBI230), La Fe Health Research Institute, 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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Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI. Sci Rep 2018; 8:17062. [PMID: 30459364 PMCID: PMC6244161 DOI: 10.1038/s41598-018-34820-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2018] [Accepted: 10/24/2018] [Indexed: 12/18/2022] Open
Abstract
Functional MRI may identify critical windows of opportunity for drug delivery and distinguish between early treatment responders and non-responders. Using diffusion-weighted, dynamic contrast-enhanced, and dynamic susceptibility contrast MRI, as well as pro-angiogenic and pro-inflammatory blood markers, we prospectively studied the physiologic tumor-related changes in fourteen newly diagnosed glioblastoma patients during standard therapy. 153 MRI scans and blood collection were performed before chemoradiation (baseline), weekly during chemoradiation (week 1–6), monthly before each cycle of adjuvant temozolomide (pre-C1-C6), and after cycle 6. The apparent diffusion coefficient, volume transfer coefficient (Ktrans), and relative cerebral blood volume (rCBV) and flow (rCBF) were calculated within the tumor and edema regions and compared to baseline. Cox regression analysis was used to assess the effect of clinical variables, imaging, and blood markers on progression-free (PFS) and overall survival (OS). After controlling for additional covariates, high baseline rCBV and rCBF within the edema region were associated with worse PFS (microvessel rCBF: HR = 7.849, p = 0.044; panvessel rCBV: HR = 3.763, p = 0.032; panvessel rCBF: HR = 3.984; p = 0.049). The same applied to high week 5 and pre-C1 Ktrans within the tumor region (week 5 Ktrans: HR = 1.038, p = 0.003; pre-C1 Ktrans: HR = 1.029, p = 0.004). Elevated week 6 VEGF levels were associated with worse OS (HR = 1.034; p = 0.004). Our findings suggest a role for rCBV and rCBF at baseline and Ktrans and VEGF levels during treatment as markers of response. Functional imaging changes can differ substantially between tumor and edema regions, highlighting the variable biologic and vascular state of tumor microenvironment during therapy.
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Hilario A, Hernandez-Lain A, Sepulveda JM, Lagares A, Perez-Nuñez A, Ramos A. Perfusion MRI grading diffuse gliomas: Impact of permeability parameters on molecular biomarkers and survival. Neurocirugia (Astur) 2018; 30:11-18. [PMID: 30143443 DOI: 10.1016/j.neucir.2018.06.004] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2017] [Revised: 05/04/2018] [Accepted: 06/01/2018] [Indexed: 10/28/2022]
Abstract
BACKGROUND AND PURPOSE Our objectives were: (1) compare dynamic susceptibility-weighted (DSC) and dynamic contrast-enhanced (DCE) permeability parameters, (2) evaluate diagnostic accuracy of DSC and DCE discriminating high- and low-grade tumors, (3) analyze relationship of permeability parameters with overall (OS) and progression-free survival (PFS) and (4) assess differences in high-grade tumors classified according to molecular biomarkers. MATERIALS AND METHODS 49 patients with histologically proved diffuse gliomas underwent DSC and DCE imaging. Parametric maps of cerebral blood volume (CBV), CBV-leakage corrected, volume transfer coefficient (Ktrans), fractional volume of the extravascular extracellular space (EES) (Ve), fractional blood plasma volume (Vp) and rate constant between EES and blood plasma (Kep) were calculated. High-grade gliomas were also classified according to isocitrate dehydrogenase (IDH), alpha-thalassemia/mental retardation syndrome X-linked (ATRX) and O6-methylguanine-dna-methyltransferase promoter methylation (MGMT) status. RESULTS There is correlation between parameters leakage, Ktrans and Vp. ROC curve analysis showed significance in both Ktrans and Ve for glioma grading. Threshold value of 0.075 for Ve generated the best combination of sensitivity (80%) and specificity (75%) in tumor gradation. Leakage was the only permeability parameter related to OS (P=0.006) and PFS (0.012); with prolonged survival for leakage values lower than 1.2. IDH-mutated high-grade tumors showed lower leakage and Ktrans values. High-grade tumors with loss of ATRX presented lower leakage and Vp values. CONCLUSIONS Both DSC and DCE permeability parameters serve as non-invasive method for glioma grading. Leakage was the unique permeability parameter related to survival and the best discriminating high-grade gliomas classified according to IDH and ATRX status.
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Affiliation(s)
- Amaya Hilario
- Department of Radiology, Neuroradiology Section, Universitary Hospital 12 de Octubre, Madrid, Spain.
| | | | | | - Alfonso Lagares
- Department of Neurosurgery, Universitary Hospital 12 de Octubre, Madrid, Spain
| | - Angel Perez-Nuñez
- Department of Neurosurgery, Universitary Hospital 12 de Octubre, Madrid, Spain
| | - Ana Ramos
- Department of Radiology, Neuroradiology Section, Universitary Hospital 12 de Octubre, Madrid, Spain
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Ly KI, Gerstner ER. The Role of Advanced Brain Tumor Imaging in the Care of Patients with Central Nervous System Malignancies. Curr Treat Options Oncol 2018; 19:40. [PMID: 29931476 DOI: 10.1007/s11864-018-0558-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OPINION STATEMENT T1-weighted post-contrast and T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) constitute the gold standard for diagnosis and response assessment in neuro-oncologic patients but are limited in their ability to accurately reflect tumor biology and metabolism, particularly over the course of a patient's treatment. Advanced MR imaging methods are sensitized to different biophysical processes in tissue, including blood perfusion, tumor metabolism, and chemical composition of tissue, and provide more specific information on tissue physiology than standard MRI. This review provides an overview of the most common and emerging advanced imaging modalities in the field of brain tumor imaging and their applications in the care of neuro-oncologic patients.
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Affiliation(s)
- K Ina Ly
- Stephen E. and Catherine Pappas Center for Neuro-Oncology, Massachusetts General Hospital, 55 Fruit Street, Yawkey 9E, Boston, MA, 02114, USA
| | - Elizabeth R Gerstner
- Stephen E. and Catherine Pappas Center for Neuro-Oncology, Massachusetts General Hospital, 55 Fruit Street, Yawkey 9E, Boston, MA, 02114, USA.
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Juan-Albarracín J, Fuster-Garcia E, Pérez-Girbés A, Aparici-Robles F, Alberich-Bayarri Á, Revert-Ventura A, Martí-Bonmatí L, García-Gómez JM. Glioblastoma: Vascular Habitats Detected at Preoperative Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging Predict Survival. Radiology 2018; 287:944-954. [DOI: 10.1148/radiol.2017170845] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Affiliation(s)
- Javier Juan-Albarracín
- From the Instituto Universitario de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
| | - Elies Fuster-Garcia
- From the Instituto Universitario de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
| | - Alexandre Pérez-Girbés
- From the Instituto Universitario de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
| | - Fernando Aparici-Robles
- From the Instituto Universitario de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
| | - Ángel Alberich-Bayarri
- From the Instituto Universitario de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
| | - Antonio Revert-Ventura
- From the Instituto Universitario de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
| | - Luis Martí-Bonmatí
- From the Instituto Universitario de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
| | - Juan M. García-Gómez
- From the Instituto Universitario de Aplicaciones de las Tecnologías de la Información y de las Comunicaciones Avanzadas, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain
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Schmainda KM, Prah MA, Rand SD, Liu Y, Logan B, Muzi M, Rane SD, Da X, Yen YF, Kalpathy-Cramer J, Chenevert TL, Hoff B, Ross B, Cao Y, Aryal MP, Erickson B, Korfiatis P, Dondlinger T, Bell L, Hu L, Kinahan PE, Quarles CC. Multisite Concordance of DSC-MRI Analysis for Brain Tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project. AJNR Am J Neuroradiol 2018; 39:1008-1016. [PMID: 29794239 DOI: 10.3174/ajnr.a5675] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2017] [Accepted: 02/07/2018] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Standard assessment criteria for brain tumors that only include anatomic imaging continue to be insufficient. While numerous studies have demonstrated the value of DSC-MR imaging perfusion metrics for this purpose, they have not been incorporated due to a lack of confidence in the consistency of DSC-MR imaging metrics across sites and platforms. This study addresses this limitation with a comparison of multisite/multiplatform analyses of shared DSC-MR imaging datasets of patients with brain tumors. MATERIALS AND METHODS DSC-MR imaging data were collected after a preload and during a bolus injection of gadolinium contrast agent using a gradient recalled-echo-EPI sequence (TE/TR = 30/1200 ms; flip angle = 72°). Forty-nine low-grade (n = 13) and high-grade (n = 36) glioma datasets were uploaded to The Cancer Imaging Archive. Datasets included a predetermined arterial input function, enhancing tumor ROIs, and ROIs necessary to create normalized relative CBV and CBF maps. Seven sites computed 20 different perfusion metrics. Pair-wise agreement among sites was assessed with the Lin concordance correlation coefficient. Distinction of low- from high-grade tumors was evaluated with the Wilcoxon rank sum test followed by receiver operating characteristic analysis to identify the optimal thresholds based on sensitivity and specificity. RESULTS For normalized relative CBV and normalized CBF, 93% and 94% of entries showed good or excellent cross-site agreement (0.8 ≤ Lin concordance correlation coefficient ≤ 1.0). All metrics could distinguish low- from high-grade tumors. Optimum thresholds were determined for pooled data (normalized relative CBV = 1.4, sensitivity/specificity = 90%:77%; normalized CBF = 1.58, sensitivity/specificity = 86%:77%). CONCLUSIONS By means of DSC-MR imaging data obtained after a preload of contrast agent, substantial consistency resulted across sites for brain tumor perfusion metrics with a common threshold discoverable for distinguishing low- from high-grade tumors.
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Affiliation(s)
- K M Schmainda
- From the Department of Radiology (K.M.S., M.A.P., S.D.R.)
| | - M A Prah
- From the Department of Radiology (K.M.S., M.A.P., S.D.R.)
| | - S D Rand
- From the Department of Radiology (K.M.S., M.A.P., S.D.R.).,Department of Radiology (M.M., S.D.R., P.E.K.), University of Washington, Seattle, Washington
| | - Y Liu
- Division of Biostatistics (Y.L., B.L.), Institute for Health and Society, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - B Logan
- Division of Biostatistics (Y.L., B.L.), Institute for Health and Society, Medical College of Wisconsin, Milwaukee, Wisconsin
| | - M Muzi
- Department of Radiology (M.M., S.D.R., P.E.K.), University of Washington, Seattle, Washington
| | - S D Rane
- From the Department of Radiology (K.M.S., M.A.P., S.D.R.)
| | - X Da
- Department of Radiology (X.D.), Harvard Medical School, Brigham and Women's Hospital, Boston, Massachusetts
| | - Y-F Yen
- Athinoula A. Martinos Center for Biomedical Imaging (Y.-F.Y., J.K.-C.), Department of Radiology, Harvard Medical School/Massachusetts General Hospital, Charlestown, Massachusetts
| | - J Kalpathy-Cramer
- Athinoula A. Martinos Center for Biomedical Imaging (Y.-F.Y., J.K.-C.), Department of Radiology, Harvard Medical School/Massachusetts General Hospital, Charlestown, Massachusetts
| | | | - B Hoff
- Department of Radiology (T.L.C., B.H., B.R.)
| | - B Ross
- Department of Radiology (T.L.C., B.H., B.R.)
| | - Y Cao
- Departments of Radiation Oncology, Radiology, and Biomedical Engineering (Y.C., M.P.A.), University of Michigan, Ann Arbor, Michigan
| | - M P Aryal
- Departments of Radiation Oncology, Radiology, and Biomedical Engineering (Y.C., M.P.A.), University of Michigan, Ann Arbor, Michigan
| | - B Erickson
- Department of Radiology (B.E., P.K.), Mayo Clinic, Rochester, Minnesota
| | - P Korfiatis
- Department of Radiology (B.E., P.K.), Mayo Clinic, Rochester, Minnesota
| | - T Dondlinger
- Imaging Biometrics LLC (T.D.), Elm Grove, Wisconsin
| | - L Bell
- Division of Imaging Research (L.B., C.C.Q.), Barrow Neurological Institute, Phoenix, Arizona
| | - L Hu
- Department of Radiology (L.H.), Mayo Clinic, Scottsdale, Arizona
| | - P E Kinahan
- Department of Radiology (M.M., S.D.R., P.E.K.), University of Washington, Seattle, Washington
| | - C C Quarles
- Division of Imaging Research (L.B., C.C.Q.), Barrow Neurological Institute, Phoenix, Arizona
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Yang J, Hou Z, Wang C, Wang H, Zhang H. Gene expression microarray analysis reveals prognostic markers of survival in high grade astrocytomas. Neurol Res 2018; 40:744-751. [PMID: 29781781 DOI: 10.1080/01616412.2018.1475126] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
Abstract
OBJECTIVE High grade astrocytoma (HGA) as an aggressive brain tumor, is always correlated with poor prognosis. In this paper, we aimed to explore the genetic prognostic biomarkers for HGA. METHODS The genome-wide expression profile of 26 brain tumor samples obtained from 26 patients with HGA was downloaded from Gene Expression Omnibus. The risk genes for prognosis of HGA were identified and verified by the data in TCGA database. Protein-protein interaction (PPI) network of risk factor genes was constructed and significant module was screened. Function and pathway annotations were performed for risk genes and drug target genes were further analyzed. RESULTS A total of 598 genes were identified as significant risk genes for prognosis, such as checkpoint kinase 1, potassium inwardly-rectifying channel, subfamily J, member 6, leukocyte receptor tyrosine kinase and uncharacterized LOC283887. All risk genes for prognosis of HGA were significantly enriched in cell cycle, mitotic as well as mitotic anaphase. While the genes in the network module mainly participated in functions such as cell cycle, mitotic cell cycle and cell cycle process. Moreover, the genes in the network module mainly participated in the pathways such as cell cycle and cell cycle, mitotic. Drug target analysis showed that seven genes were recorded in Drugbank database, and there were as many as 32 drug records of CHEK1. CONCLUSION The prognostic effect of CHEK1 was validated based on the expression profile data of 615 low-grade glioma and glioblastoma samples. We proposed CHEK1 as prognostic biomarker for HGA. Our work might provide the candidate target for HGA therapy.
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Affiliation(s)
- Jun Yang
- a Department of Neurosurgery, Beijing Luhe Hospital , Capital Medical University , Beijing , China
| | - Ziming Hou
- a Department of Neurosurgery, Beijing Luhe Hospital , Capital Medical University , Beijing , China
| | - Changjiang Wang
- a Department of Neurosurgery, Beijing Luhe Hospital , Capital Medical University , Beijing , China
| | - Hao Wang
- a Department of Neurosurgery, Beijing Luhe Hospital , Capital Medical University , Beijing , China
| | - Hongbing Zhang
- a Department of Neurosurgery, Beijing Luhe Hospital , Capital Medical University , Beijing , China
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40
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Prediction of survival in patients affected by glioblastoma: histogram analysis of perfusion MRI. J Neurooncol 2018; 139:455-460. [DOI: 10.1007/s11060-018-2887-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2017] [Accepted: 04/08/2018] [Indexed: 01/20/2023]
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41
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Pope WB, Brandal G. Conventional and advanced magnetic resonance imaging in patients with high-grade glioma. THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING : OFFICIAL PUBLICATION OF THE ITALIAN ASSOCIATION OF NUCLEAR MEDICINE (AIMN) [AND] THE INTERNATIONAL ASSOCIATION OF RADIOPHARMACOLOGY (IAR), [AND] SECTION OF THE SOCIETY OF RADIOPHARMACEUTICAL CHEMISTRY AND BIOLOGY 2018; 62:239-253. [PMID: 29696946 DOI: 10.23736/s1824-4785.18.03086-8] [Citation(s) in RCA: 53] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Magnetic resonance imaging is integral to the care of patients with high-grade gliomas. Anatomic detail can be acquired with conventional structural imaging, but newer approaches also add capabilities to interrogate image-derived physiologic and molecular characteristics of central nervous system neoplasms. These advanced imaging techniques are increasingly employed to generate biomarkers that better reflect tumor burden and therapy response. The following is an overview of current strategies based on advanced magnetic resonance imaging that are used in the assessment of high-grade glioma patients with an emphasis on how novel imaging biomarkers can potentially advance patient care.
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Affiliation(s)
- Whitney B Pope
- Department of Radiological Sciences, David Geffen School of Medicine, University of California - Los Angeles, Los Angeles, CA, USA -
| | - Garth Brandal
- Department of Radiological Sciences, David Geffen School of Medicine, University of California - Los Angeles, Los Angeles, CA, USA
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Salama GR, Heier LA, Patel P, Ramakrishna R, Magge R, Tsiouris AJ. Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma-Foundations and Future. Front Neurol 2018; 8:660. [PMID: 29403420 PMCID: PMC5786563 DOI: 10.3389/fneur.2017.00660] [Citation(s) in RCA: 30] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Accepted: 11/22/2017] [Indexed: 01/20/2023] Open
Abstract
In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes.
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Affiliation(s)
- Gayle R Salama
- Department of Neuroradiology, Weill Cornell Medical College, New York, NY, United States
| | - Linda A Heier
- Department of Neuroradiology, Weill Cornell Medical College, New York, NY, United States
| | - Praneil Patel
- Department of Neuroradiology, Weill Cornell Medical College, New York, NY, United States
| | - Rohan Ramakrishna
- Department of Neurological Surgery, Weill Cornell Medical College, New York, NY, United States
| | - Rajiv Magge
- Department of Neurology, Weill Cornell Medical College, New York, NY, United States
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Saini J, Gupta PK, Sahoo P, Singh A, Patir R, Ahlawat S, Beniwal M, Thennarasu K, Santosh V, Gupta RK. Differentiation of grade II/III and grade IV glioma by combining "T1 contrast-enhanced brain perfusion imaging" and susceptibility-weighted quantitative imaging. Neuroradiology 2017; 60:43-50. [PMID: 29090331 DOI: 10.1007/s00234-017-1942-8] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Accepted: 10/18/2017] [Indexed: 12/28/2022]
Abstract
PURPOSE MRI is a useful method for discriminating low- and high-grade glioma using perfusion MRI and susceptibility-weighted imaging (SWI). The purpose of this study is to evaluate the usefulness of T1-perfusion MRI and SWI in discriminating among grade II, III, and IV gliomas. METHODS T1-perfusion MRI was used to measure relative cerebral blood volume (rCBV) in 129 patients with glioma (70 grade IV, 33 grade III, and 26 grade II tumors). SWI was also used to measure the intratumoral susceptibility signal intensity (ITSS) scores for each tumor in these patients. rCBV and ITSS values were compared to seek differences between grade II vs. grade III, grade III vs. grade IV, and grade III+II vs. grade IV tumors. RESULTS Significant differences in rCBV values of the three grades of the tumors were noted and pairwise comparisons showed significantly higher rCBV values in grade IV tumors as compared to grade III tumors, and similarly increased rCBV was seen in the grade III tumors as compared to grade II tumors (p < 0.001). Grade IV gliomas showed significantly higher ITSS scores on SWI as compared to grade III tumors (p < 0.001) whereas insignificant difference was seen on comparing ITSS scores of grade III with grade II tumors. Combining the rCBV and ITSS resulted in significant improvement in the discrimination of grade III from grade IV tumors. CONCLUSION The combination of rCBV values derived from T1-perfusion MRI and SWI derived ITSS scores improves the diagnostic accuracy for discrimination of grade III from grade IV gliomas.
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Affiliation(s)
- Jitender Saini
- Neuroimaging & Interventional Radiology, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Pradeep Kumar Gupta
- Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurugram, India
| | - Prativa Sahoo
- Philips Health System, Philips India Limited, Bangalore, India.,Beckman Research Institute, Mathematical Oncology, bldg-74, Duarte, CA, USA
| | - Anup Singh
- Center for Biomedical Engineering, Indian Institute of Technology Delhi, Delhi, India
| | - Rana Patir
- Department of Neurosurgery, Fortis Memorial Research Institute, Gurugram, India
| | - Suneeta Ahlawat
- SRL Diagnostics, Fortis Memorial Research Institute, Gurugram, India
| | - Manish Beniwal
- Department of Neurosurgery, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - K Thennarasu
- Department of Biostatistics, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Vani Santosh
- Department of Neuropathology, National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Rakesh Kumar Gupta
- Department of Radiology and Imaging, Fortis Memorial Research Institute, Gurugram, India.
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Dehkordi ANV, Kamali-Asl A, Wen N, Mikkelsen T, Chetty IJ, Bagher-Ebadian H. DCE-MRI prediction of survival time for patients with glioblastoma multiforme: using an adaptive neuro-fuzzy-based model and nested model selection technique. NMR IN BIOMEDICINE 2017; 30:e3739. [PMID: 28543885 DOI: 10.1002/nbm.3739] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2017] [Revised: 03/28/2017] [Accepted: 03/30/2017] [Indexed: 06/07/2023]
Abstract
This pilot study investigates the construction of an Adaptive Neuro-Fuzzy Inference System (ANFIS) for the prediction of the survival time of patients with glioblastoma multiforme (GBM). ANFIS is trained by the pharmacokinetic (PK) parameters estimated by the model selection (MS) technique in dynamic contrast enhanced-magnetic resonance imaging (DCE-MRI) data analysis, and patient age. DCE-MRI investigations of 33 treatment-naïve patients with GBM were studied. Using the modified Tofts model and MS technique, the following physiologically nested models were constructed: Model 1, no vascular leakage (normal tissue); Model 2, leakage without efflux; Model 3, leakage with bidirectional exchange (influx and efflux). For each patient, the PK parameters of the three models were estimated as follows: blood plasma volume (vp ) for Model 1; vp and volume transfer constant (Ktrans ) for Model 2; vp , Ktrans and rate constant (kep ) for Model 3. Using Cox regression analysis, the best combination of the estimated PK parameters, together with patient age, was identified for the design and training of ANFIS. A K-fold cross-validation (K = 33) technique was employed for training, testing and optimization of ANFIS. Given the survival time distribution, three classes of survival were determined and a confusion matrix for the correct classification fraction (CCF) of the trained ANFIS was estimated as an accuracy index of ANFIS's performance. Patient age, kep and ve (Ktrans /kep ) of Model 3, and Ktrans of Model 2, were found to be the most effective parameters for training ANFIS. The CCF of the trained ANFIS was 84.8%. High diagonal elements of the confusion matrix (81.8%, 90.1% and 81.8% for Class 1, Class 2 and Class 3, respectively), with low off-diagonal elements, strongly confirmed the robustness and high performance of the trained ANFIS for predicting the three survival classes. This study confirms that DCE-MRI PK analysis, combined with the MS technique and ANFIS, allows the construction of a DCE-MRI-based fuzzy integrated predictor for the prediction of the survival of patients with GBM.
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Affiliation(s)
- Azimeh N V Dehkordi
- Department of Radiation Medicine Engineering, Shahid Beheshti University, Tehran, Iran
| | - Alireza Kamali-Asl
- Department of Radiation Medicine Engineering, Shahid Beheshti University, Tehran, Iran
| | - Ning Wen
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA
| | - Tom Mikkelsen
- Department of Neurosurgery, Henry Ford Hospital, Detroit, Michigan, USA
- Ontario Brain Institute, Toronto, Ontario, Canada
| | - Indrin J Chetty
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA
| | - Hassan Bagher-Ebadian
- Department of Radiation Oncology, Henry Ford Hospital, Detroit, Michigan, USA
- Department of Physics, Oakland University, Rochester, Michigan, USA
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Cao Y, Tseng CL, Balter JM, Teng F, Parmar HA, Sahgal A. MR-guided radiation therapy: transformative technology and its role in the central nervous system. Neuro Oncol 2017; 19:ii16-ii29. [PMID: 28380637 DOI: 10.1093/neuonc/nox006] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Abstract
This review article describes advancement of magnetic resonance imaging technologies in radiation therapy planning, guidance, and adaptation of brain tumors. The potential for MR-guided radiation therapy to improve outcomes and the challenges in its adoption are discussed.
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Affiliation(s)
- Yue Cao
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
- Radiology, University of Michigan, Ann Arbor, Michigan, USA
- Biomedical Engineering, University of Michigan, Ann Arbor, Michigan, USA
| | - Chia-Lin Tseng
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
| | - James M Balter
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
| | - Feifei Teng
- Departments of Radiation Oncology, University of Michigan, Ann Arbor, Michigan, USA
- Department of Radiation Oncology, Shandong Cancer Hospital, Shandong University, Jinan, China
| | | | - Arjun Sahgal
- Department of Radiation Oncology, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Ontario, Canada
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Abstract
Despite the fact that MRI has evolved to become the standard method for diagnosis and monitoring of patients with brain tumours, conventional MRI sequences have two key limitations: the inability to show the full extent of the tumour and the inability to differentiate neoplastic tissue from nonspecific, treatment-related changes after surgery, radiotherapy, chemotherapy or immunotherapy. In the past decade, PET involving the use of radiolabelled amino acids has developed into an important diagnostic tool to overcome some of the shortcomings of conventional MRI. The Response Assessment in Neuro-Oncology working group - an international effort to develop new standardized response criteria for clinical trials in brain tumours - has recommended the additional use of amino acid PET imaging for brain tumour management. Concurrently, a number of advanced MRI techniques such as magnetic resonance spectroscopic imaging and perfusion weighted imaging are under clinical evaluation to target the same diagnostic problems. This Review summarizes the clinical role of amino acid PET in relation to advanced MRI techniques for differential diagnosis of brain tumours; delineation of tumour extent for treatment planning and biopsy guidance; post-treatment differentiation between tumour progression or recurrence versus treatment-related changes; and monitoring response to therapy. An outlook for future developments in PET and MRI techniques is also presented.
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Affiliation(s)
- Karl-Josef Langen
- Institute of Neuroscience and Medicine (INM-3, INM-4) Forschungszentrum Jülich, Wilhelm-Johnen-Strasse, D-52425 Jülich, Germany.,Departments of Nuclear Medicine and Neurology, RWTH Aachen University Clinic, Pauwelsstrasse 30, D-52074 Aachen, Germany
| | - Norbert Galldiks
- Institute of Neuroscience and Medicine (INM-3, INM-4) Forschungszentrum Jülich, Wilhelm-Johnen-Strasse, D-52425 Jülich, Germany.,Department of Neurology, University of Cologne, Kerpener Strasse 62, D-50937 Cologne, Germany.,Center for Integrated Oncology, Josef-Stelzmann-Strasse 9, D-50937 Cologne, Germany
| | - Elke Hattingen
- Department of Neuroradiology and Center for Integrated Oncology, University of Bonn, Sigmund-Freud-Strasse 25, D-53127 Bonn, Germany
| | - Nadim Jon Shah
- Institute of Neuroscience and Medicine (INM-3, INM-4) Forschungszentrum Jülich, Wilhelm-Johnen-Strasse, D-52425 Jülich, Germany.,Departments of Nuclear Medicine and Neurology, RWTH Aachen University Clinic, Pauwelsstrasse 30, D-52074 Aachen, Germany.,Monash Institute of Medical Engineering, Department of Electrical and Computer Systems Engineering, and Monash Biomedical Imaging, School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton Campus, Wellington Road, Melbourne, Victoria 3800, Australia
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Lucas JT, Knapp BJ, Uh J, Hua CH, Merchant TE, Hwang SN, Patay Z, Broniscer A. Posttreatment DSC-MRI is Predictive of Early Treatment Failure in Children with Supratentorial High-Grade Glioma Treated with Erlotinib. Clin Neuroradiol 2017; 28:393-400. [PMID: 28382379 DOI: 10.1007/s00062-017-0580-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2016] [Accepted: 03/15/2017] [Indexed: 02/01/2023]
Abstract
BACKGROUND AND PURPOSE The role of perfusion imaging in the management of pediatric high grade glioma is unclear. We evaluated the ability of dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI) to determine grade, evaluate post-treatment response and predict treatment failure. MATERIAL AND METHODS In this study 22 patients with high-grade glioma underwent biopsy and were treated with concurrent and sequential radiotherapy and erlotinib as part of a phase I/II clinical trial (NCT00124657). Preradiotherapy, immediate postradiotherapy, 6‑month and treatment failure DSC MR images were reviewed, registered, and processed for the ratio of cerebral blood flow (CBF) and cerebral blood volume (CBV). Processed, derived perfusion, and T1-weighted images (T1WI), T2WI, and fluid attenuation inversion recovery (FLAIR) MRI sequences were used for segmentation and extraction of tumor perfusion parameters at all time points. Patient, tumor, treatment, and outcome data were summarized and related to perfusion data. RESULTS Regional CBF in tumors increased from diagnosis to postradiotherapy, while they decreased to levels below those at diagnosis from postradiotherapy to 6‑month follow-up. At 6 months, the median regional CBF was higher in tumors that progressed (median 1.16) than in those that did not (median, 0.95; P < 0.05). Patients with regional CBF ratios above 1.4 at diagnosis had shorter survival times than did those with regional CBF ratios below 1.4 (P = 0.77). Tumors with a regional CBV above 1.15 at the postradiotherapy (1-3 months) follow-up scan were associated with an earlier time to death than that of tumors with a regional CBV below 1.15 (P < 0.05). CONCLUSION Posttreatment perfusion characteristics are prognostic and may help predict survival. Overall, perfusion MRI is useful for managing pediatric high-grade glioma and should be incorporated into future clinical trials.
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Affiliation(s)
- John T Lucas
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, MS 210, 38105-3678, Memphis, TN, USA.
| | - Brendan J Knapp
- Indiana University School of Medicine, Indianapolis, IN, USA
| | - Jinsoo Uh
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, MS 210, 38105-3678, Memphis, TN, USA
| | - Chia-Ho Hua
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, MS 210, 38105-3678, Memphis, TN, USA
| | - Thomas E Merchant
- Department of Radiation Oncology, St. Jude Children's Research Hospital, 262 Danny Thomas Place, MS 210, 38105-3678, Memphis, TN, USA
| | - Scott N Hwang
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Zoltan Patay
- Department of Diagnostic Imaging, St. Jude Children's Research Hospital, Memphis, TN, USA
| | - Alberto Broniscer
- Department of Oncology, St. Jude Children's Research Hospital, Memphis, TN, USA.,Department of Pediatrics, University of Tennessee Health Science Center, Memphis, TN, USA
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Filss CP, Cicone F, Shah NJ, Galldiks N, Langen KJ. Amino acid PET and MR perfusion imaging in brain tumours. Clin Transl Imaging 2017; 5:209-223. [PMID: 28680873 PMCID: PMC5487907 DOI: 10.1007/s40336-017-0225-z] [Citation(s) in RCA: 45] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2016] [Accepted: 02/28/2017] [Indexed: 12/17/2022]
Abstract
Purpose Despite the excellent capacity of the conventional MRI to image brain tumours, problems remain in answering a number of critical diagnostic questions. To overcome these diagnostic shortcomings, PET using radiolabeled amino acids and perfusion-weighted imaging (PWI) are currently under clinical evaluation. The role of amino acid PET and PWI in different diagnostic challenges in brain tumours is controversial. Methods Based on the literature and experience of our centres in correlative imaging with PWI and PET using O-(2-[18F]fluoroethyl)-l-tyrosine or 3,4-dihydroxy-6-[18F]-fluoro-l-phenylalanine, the current role and shortcomings of amino acid PET and PWI in different diagnostic challenges in brain tumours are reviewed. Literature searches were performed on PubMed, and additional literature was retrieved from the reference lists of identified articles. In particular, all studies in which amino acid PET was directly compared with PWI were included. Results PWI is more readily available, but requires substantial expertise and is more sensitive to artifacts than amino acid PET. At initial diagnosis, PWI and amino acid PET can help to define a site for biopsy but amino acid PET appears to be more powerful to define the tumor extent. Both methods are helpful to differentiate progression or recurrence from unspecific posttherapeutic changes. Assessment of therapeutic efficacy can be achieved especially with amino acid PET, while the data with PWI are sparse. Conclusion Both PWI and amino acid PET add valuable diagnostic information to the conventional MRI in the assessment of patients with brain tumours, but further studies are necessary to explore the complementary nature of these two methods.
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Affiliation(s)
- Christian P Filss
- Institute of Neuroscience and Medicine (INM-3, INM-4), Forschungszentrum Jülich, Jülich, Germany.,Departments of Nuclear Medicine and Neurology, RWTH Aachen University Clinic, Aachen, Germany
| | - Francesco Cicone
- Unit of Nuclear Medicine, Department of Surgical and Medical Sciences and Translational Medicine, Sapienza University of Rome, Rome, Italy.,Nuclear Medicine and Molecular Medicine Department, University Hospital of Lausanne, Lausanne, Switzerland
| | - Nadim Jon Shah
- Institute of Neuroscience and Medicine (INM-3, INM-4), Forschungszentrum Jülich, Jülich, Germany.,Departments of Nuclear Medicine and Neurology, RWTH Aachen University Clinic, Aachen, Germany.,JARA-Jülich Aachen Research Alliance, Jülich, Germany.,Monash Institute of Medical Engineering, Department of Electrical and Computer Systems Engineering, and Monash Biomedical Imaging, School of Psychological Sciences, Monash University, Melbourne, VIC Australia
| | - Norbert Galldiks
- Institute of Neuroscience and Medicine (INM-3, INM-4), Forschungszentrum Jülich, Jülich, Germany.,Department of Neurology, University of Cologne, Cologne, Germany.,Center of Integrated Oncology (CIO), University of Cologne and Bonn, Cologne, Germany
| | - Karl-Josef Langen
- Institute of Neuroscience and Medicine (INM-3, INM-4), Forschungszentrum Jülich, Jülich, Germany.,Departments of Nuclear Medicine and Neurology, RWTH Aachen University Clinic, Aachen, Germany.,JARA-Jülich Aachen Research Alliance, Jülich, Germany
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Post-treatment changes of tumour perfusion parameters can help to predict survival in patients with high-grade astrocytoma. Eur Radiol 2016; 27:3392-3400. [DOI: 10.1007/s00330-016-4699-2] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2016] [Revised: 11/07/2016] [Accepted: 12/05/2016] [Indexed: 11/27/2022]
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