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Roh YH, Cheong EN, Park JE, Choi Y, Jung SC, Song SW, Kim YH, Hong CK, Kim JH, Kim HS. Imaging-Based Molecular Characterization of Adult-Type Diffuse Glioma Using Diffusion and Perfusion MRI in Pre- and Post-Treatment Stage Considering Spatial and Temporal Heterogeneity. J Magn Reson Imaging 2025. [PMID: 40197845 DOI: 10.1002/jmri.29781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2024] [Revised: 03/19/2025] [Accepted: 03/21/2025] [Indexed: 04/10/2025] Open
Abstract
BACKGROUND Imaging-based molecular characterization is important for identifying treatment targets in adult-type diffuse gliomas. PURPOSE To assess isocitrate dehydrogenase (IDH) mutation and epidermal growth factor receptor (EGFR) amplification status in primary and recurrent gliomas using diffusion and perfusion MRI, addressing spatial and temporal heterogeneity. STUDY TYPE Retrospective. SUBJECTS Three-hundred and twelve newly diagnosed (cross-sectional set, 57.9 ± 13.2 years, 52.2% male, 235 IDH-wildtype, 71 EGFR-amplified) and 38 recurrent (longitudinal set, 53.1 ± 13.4 years, 44.7% male, 30 IDH-wildtype, 13 EGFR-amplified) adult-type diffuse glioma patients. FIELD STRENGTH/SEQUENCE 3.0T; diffusion weighted and dynamic susceptibility contrast-perfusion weighted imaging. ASSESSMENT Radiomics features from contrast-enhancing tumors (CET) and non-enhancing lesions (NEL) were extracted from apparent diffusion coefficient and perfusion maps. Spatial heterogeneity was assessed using intersection and Bhattacharyya distance between CET and NEL. Stable imaging features were identified in patients with unchanged genetic profiles in the longitudinal set. The "best model," using features from the cross-sectional set (n = 312), and the "concordant model," using stable features identified in the longitudinal set (n = 38), were constructed using the LASSO for IDH and EGFR status. STATISTICAL TESTS The area under the receiver-operating-characteristic curve (AUC). RESULTS For IDH mutations, both best and concordant models demonstrated high AUCs in the cross-sectional set (0.936; 95% confidence interval [CI]: 0.903-0.969 and 0.964 [0.943-0.986], respectively). Only the concordant model maintained strong performance in recurrent tumors (AUC, 0.919 vs. 0.656). For EGFR amplification in IDH-wildtype, the best and concordant models showed AUCs of 0.821 (95% CI: 0.761-0.881) and 0.746 (95% CI: 0.675-0.817) in newly diagnosed gliomas, but poor performance in recurrent tumors with AUCs of 0.503 (95% CI: 0.34-0.665) and 0.518 (95% CI: 0.357-0.678). DATA CONCLUSION Diffusion and perfusion MRI characterized IDH status in both newly diagnosed and recurrent gliomas, but showed limited diagnostic performance for EGFR, especially for recurrent tumors. EVIDENCE LEVEL 3 TECHNICAL EFFICACY: Stage 3.
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Affiliation(s)
- Yun Hwa Roh
- Department of Radiology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - E-Nae Cheong
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Yangsean Choi
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Seung Chai Jung
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Sang Woo Song
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Young-Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Chang-Ki Hong
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Jeong Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea
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Shahedi F, Naseri S, Momennezhad M, Zare H. MR Imaging Techniques for Microenvironment Mapping of the Glioma Tumors: A Systematic Review. Acad Radiol 2025:S1076-6332(25)00066-2. [PMID: 39894708 DOI: 10.1016/j.acra.2025.01.024] [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: 11/23/2024] [Revised: 01/18/2025] [Accepted: 01/19/2025] [Indexed: 02/04/2025]
Abstract
RATIONALE AND OBJECTIVES The tumor microenvironment (TME) is a critical regulator of cancer progression, metastasis, and treatment response. Currently, various imaging approaches exist to assess the pathophysiological features of the TME. This systematic review provides an overview of magnetic resonance imaging (MRI) methods used in clinical practice to characterize the pathophysiological features of the gliomas TME. METHODS This review involved a systematic comprehensive search of original open-access articles reporting the clinical use of MR imaging in glioma patients of all ages in the PubMed, Scopus, and Web of Science databases between January 2010 and December 2023. We restricted our research to papers published in the English language. RESULTS A total of 1137 studies were preliminarily identified through electronic database searches. After duplicate studies were removed, 44 studies met the eligibility criteria. The glioma TME was accompanied by alterations in metabolism, pH, vascularity, oxygenation, and extracellular matrix components, including tumor-associated macrophages, and sodium concentration. CONCLUSION Multiparametric MRI is capable of noninvasively assessing the pathophysiological features and tumor-supportive niches of the TME, which is in line with its application in personalized medicine.
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Affiliation(s)
- Fateme Shahedi
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran (F.S., S.N., M.M., H.Z.)
| | - Shahrokh Naseri
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran (F.S., S.N., M.M., H.Z.)
| | - Mahdi Momennezhad
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran (F.S., S.N., M.M., H.Z.)
| | - Hoda Zare
- Medical Physics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran (F.S., S.N., M.M., H.Z.); Department of Medical Physics, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran (H.Z.).
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Shrestha B, Stern NB, Zhou A, Dunn A, Porter T. Current trends in the characterization and monitoring of vascular response to cancer therapy. Cancer Imaging 2024; 24:143. [PMID: 39438891 PMCID: PMC11515715 DOI: 10.1186/s40644-024-00767-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 08/26/2024] [Indexed: 10/25/2024] Open
Abstract
Tumor vascular physiology is an important determinant of disease progression as well as the therapeutic outcome of cancer treatment. Angiogenesis or the lack of it provides crucial information about the tumor's blood supply and therefore can be used as an index for cancer growth and progression. While standalone anti-angiogenic therapy demonstrated limited therapeutic benefits, its combination with chemotherapeutic agents improved the overall survival of cancer patients. This could be attributed to the effect of vascular normalization, a dynamic process that temporarily reverts abnormal vasculature to the normal phenotype maximizing the delivery and intratumor distribution of chemotherapeutic agents. Longitudinal monitoring of vascular changes following antiangiogenic therapy can indicate an optimal window for drug administration and estimate the potential outcome of treatment. This review primarily focuses on the status of various imaging modalities used for the longitudinal characterization of vascular changes before and after anti-angiogenic therapies and their clinical prospects.
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Affiliation(s)
- Binita Shrestha
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, 78712, USA.
| | - Noah B Stern
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, 78712, USA
| | - Annie Zhou
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, 78712, USA
| | - Andrew Dunn
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, 78712, USA
| | - Tyrone Porter
- Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX, 78712, USA
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Park JE, Kim HS, Kim N, Borra R, Mouridsen K, Hansen MB, Kim YH, Hong CK, Kim JH. Prediction of pseudoprogression in post-treatment glioblastoma using dynamic susceptibility contrast-derived oxygenation and microvascular transit time heterogeneity measures. Eur Radiol 2024; 34:3061-3073. [PMID: 37848773 DOI: 10.1007/s00330-023-10324-9] [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: 09/01/2022] [Revised: 08/09/2023] [Accepted: 08/18/2023] [Indexed: 10/19/2023]
Abstract
OBJECTIVES To evaluate the added value of MR dynamic susceptibility contrast (DSC)-perfusion-weighted imaging (PWI)-derived tumour microvascular and oxygenation information with cerebral blood volume (CBV) to distinguish pseudoprogression from true progression (TP) in post-treatment glioblastoma. METHODS This retrospective single-institution study included patients with isocitrate dehydrogenase (IDH) wild-type glioblastoma and a newly developed or enlarging measurable contrast-enhancing mass within 12 weeks after concurrent chemoradiotherapy. CBV, capillary transit time heterogeneity (CTH), oxygen extraction fraction (OEF), and cerebral metabolic rate of oxygen (CMRO2) were obtained from DSC-PWI. Predictors were selected using univariable logistic regression, and performance was measured with adjusted diagnostic odds with tumour volume and area under the curve (AUC) of receiver operating characteristics analysis. RESULTS A total of 103 patients were included (mean age, 59.6 years; 59 women), with 67 cases of TP and 36 cases of pseudoprogression. Pseudoprogression exhibited higher CTH (4.0 vs. 3.4, p = .019) and higher OEF (12.7 vs. 10.7, p = .014) than TP, but a similar CBV (1.48 vs. 1.53, p = .13) and CMRO2 (7.7 vs. 7.3s, p = .598). Independent of tumour volume, both high CTH (adjusted odds ratio [OR] 1.52; 95% confidence interval [CI]: 1.11-2.09, p = .009) and high OEF (adjusted OR 1.17; 95% CI:1.03-1.33, p = .016) were predictors of pseudoprogression. The combination of CTH, OEF, and CBV yielded higher diagnostic performance (AUC 0.71) than CBV alone (AUC 0.65). CONCLUSION High intratumoural capillary transit heterogeneity and high oxygen extraction fraction derived from DSC-PWI have enhanced the diagnostic value of CBV in pseudoprogression of post-treatment IDH-wild type glioblastoma. CLINICAL RELEVANCE STATEMENT In the early post-treatment stage of glioblastoma, pseudoprogression exhibited both high oxygen extraction fraction and high capillary transit heterogeneity and these dynamic susceptibility contrast-perfusion weighted imaging derived parameters have added value in cerebral blood volume-based noninvasive differentiation of pseudoprogression from true progression. KEY POINTS • Capillary transit time heterogeneity and oxygen extraction fraction can be measured noninvasively through processing of dynamic susceptibility contrast imaging. • Pseudoprogression exhibited higher capillary transit time heterogeneity and higher oxygen extraction fraction than true progression. • A combination of cerebral blood volume, capillary transit time heterogeneity, and oxygen extraction fraction yielded the highest diagnostic performance (area under the curve 0.71).
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Affiliation(s)
- Ji Eun Park
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, Korea.
| | | | - Ronald Borra
- Cercare Medical, Inge Lehmanns Gade 10, 8000 Aarhus C, Aarhus, Denmark
| | - Kim Mouridsen
- Cercare Medical, Inge Lehmanns Gade 10, 8000 Aarhus C, Aarhus, Denmark
- Center of Functionally Integrative Neuroscience and MINDLab, Institute of Clinical Medicine, Seoul, Korea
| | - Mikkel Bo Hansen
- Cercare Medical, Inge Lehmanns Gade 10, 8000 Aarhus C, Aarhus, Denmark
- Center of Functionally Integrative Neuroscience and MINDLab, Institute of Clinical Medicine, Seoul, Korea
| | - Young-Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Chang-Ki Hong
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Jeong Hoon Kim
- Department of Neurosurgery, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
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Knott M, Hoelter P, Soder L, Schlaffer S, Hoffmanns S, Lang R, Doerfler A, Schmidt MA. Can Perfusion-Based Brain Tissue Oxygenation MRI Support the Understanding of Cerebral Abscesses In Vivo? Diagnostics (Basel) 2023; 13:3346. [PMID: 37958241 PMCID: PMC10647595 DOI: 10.3390/diagnostics13213346] [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: 09/10/2023] [Revised: 10/22/2023] [Accepted: 10/26/2023] [Indexed: 11/15/2023] Open
Abstract
PURPOSE The clinical condition of a brain abscess is a potentially life-threatening disease. The combination of MRI-based imaging, surgical therapy and microbiological analysis is critical for the treatment and convalescence of the individual patient. The aim of this study was to evaluate brain tissue oxygenation measured with dynamic susceptibility contrast perfusion weighted imaging (DSC-PWI) in patients with brain abscess and its potential benefit for a better understanding of the environment in and around brain abscesses. METHODS Using a local database, 34 patients (with 45 abscesses) with brain abscesses treated between January 2013 and March 2021 were retrospectively included in this study. DSC-PWI imaging and microbiological work-up were key inclusion criteria. These data were analysed regarding a correlation between DSC-PWI and microbiological result by quantifying brain tissue oxygenation in the abscess itself, the abscess capsula and the surrounding oedema and by using six different parameters (CBF, CBV, CMRO2, COV, CTH and OEF). RESULTS Relative cerebral blood flow (0.335 [0.18-0.613] vs. 0.81 [0.49-1.08], p = 0.015), relative cerebral blood volume (0.44 [0.203-0.72] vs. 0.87 [0.67-1.2], p = 0.018) and regional cerebral metabolic rate for oxygen (0.37 [0.208-0.695] vs. 0.82 [0.55-1.19], p = 0.022) were significantly lower in the oedema around abscesses without microbiological evidence of a specific bacteria in comparison with microbiological positive lesions. CONCLUSIONS The results of this study indicate a relationship between brain tissue oxygenation status in DSC-PWI and microbiological/inflammatory status. These results may help to better understand the in vivo environment of brain abscesses and support future therapeutic decisions.
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Affiliation(s)
- Michael Knott
- Department of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054 Erlangen, Germany (M.A.S.)
| | - Philip Hoelter
- Department of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054 Erlangen, Germany (M.A.S.)
| | - Liam Soder
- Department of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054 Erlangen, Germany (M.A.S.)
| | - Sven Schlaffer
- Department of Neurosurgery, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054 Erlangen, Germany
| | - Sophia Hoffmanns
- Department of Neurosurgery, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054 Erlangen, Germany
| | - Roland Lang
- Department of Microbiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Wasserturmstraße 3, 91054 Erlangen, Germany
| | - Arnd Doerfler
- Department of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054 Erlangen, Germany (M.A.S.)
| | - Manuel Alexander Schmidt
- Department of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Schwabachanlage 6, 91054 Erlangen, Germany (M.A.S.)
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Joshkon A, Tabouret E, Traboulsi W, Bachelier R, Simoncini S, Roffino S, Jiguet-Jiglaire C, Badran B, Guillet B, Foucault-Bertaud A, Leroyer AS, Dignat-George F, Chinot O, Fayyad-Kazan H, Bardin N, Blot-Chabaud M. Soluble CD146, a biomarker and a target for preventing resistance to anti-angiogenic therapy in glioblastoma. Acta Neuropathol Commun 2022; 10:151. [PMID: 36274147 PMCID: PMC9590138 DOI: 10.1186/s40478-022-01451-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Accepted: 09/28/2022] [Indexed: 11/17/2022] Open
Abstract
Rationale Glioblastoma multiforme (GBM) is a primary brain tumor with poor prognosis. The U.S. food and drug administration approved the use of the anti-VEGF antibody bevacizumab in recurrent GBM. However, resistance to this treatment is frequent and fails to enhance the overall survival of patients. In this study, we aimed to identify novel mechanism(s) responsible for bevacizumab-resistance in CD146-positive glioblastoma. Methods The study was performed using sera from GBM patients and human GBM cell lines in culture or xenografted in nude mice. Results We found that an increase in sCD146 concentration in sera of GBM patients after the first cycle of bevacizumab treatment was significantly associated with poor progression free survival and shorter overall survival. Accordingly, in vitro treatment of CD146-positive glioblastoma cells with bevacizumab led to a high sCD146 secretion, inducing cell invasion. These effects were mediated through integrin αvβ3 and were blocked by mucizumab, a novel humanized anti-sCD146 antibody. In vivo, the combination of bevacizumab with mucizumab impeded CD146 + glioblastoma growth and reduced tumor cell dissemination to an extent significantly higher than that observed with bevacizumab alone. Conclusion We propose sCD146 to be 1/ an early biomarker to predict and 2/ a potential target to prevent bevacizumab resistance in patients with glioblastoma. Supplementary Information The online version contains supplementary material available at 10.1186/s40478-022-01451-3.
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Moon HH, Park JE, Kim YH, Kim JH, Kim HS. Contrast enhancing pattern on pre-treatment MRI predicts response to anti-angiogenic treatment in recurrent glioblastoma: comparison of bevacizumab and temozolomide treatment. J Neurooncol 2022; 157:405-415. [PMID: 35275335 DOI: 10.1007/s11060-022-03980-2] [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: 01/06/2022] [Accepted: 03/04/2022] [Indexed: 11/29/2022]
Abstract
OBJECTIVE To evaluate the value of the contrast enhancing pattern on pre-treatment MRI for predicting the response to anti-angiogenic treatment in patients with IDH-wild type recurrent glioblastoma. METHODS This retrospective study enrolled 65 patients with IDH wild-type recurrent glioblastoma who received standard therapy and then received either bevacizumab (46 patients) or temozolomide (19 patients) as a secondary treatment. The contrast enhancing pattern on pre-treatment MRI was visually analyzed and dichotomized into contrast enhancing lesion (CEL) dominant and non-enhancing lesion (NEL) dominant types. Quantitative volumetric analysis was used to support the dichotomization. The Kaplan-Meier method and Cox proportional hazards regression analysis were used to stratify progression free survival (PFS) according to the treatment in the entire patients, CEL dominant group, and NEL dominant group. RESULTS In all patients, the PFS of those treated with bevacizumab was not significantly different from those treated with temozolomide (log-rank test, P = 0.96). When the contrast enhancing pattern was considered, bevacizumab was associated with longer PFS in the CEL dominant group (P = 0.031), whereas temozolomide showed longer PFS in the NEL dominant group (P = 0.022). Quantitative analysis revealed mean values for the proportion of solid-enhancing tumor of 13.7% for the CEL dominant group and 4.3% for the NEL dominant group. CONCLUSION Patients with the CEL dominant type showed a better treatment response to bevacizumab, whereas NEL dominant types showed a better response to temozolomide. The contrast enhancing pattern on pre-treatment MRI can be used to stratify patients with IDH wild-type recurrent glioblastoma according to the effect of anti-angiogenic treatment.
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Affiliation(s)
- Hye Hyeon Moon
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, South Korea
| | - Ji Eun Park
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, South Korea.
| | - Young-Hoon Kim
- Department of Neurosurgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, South Korea
| | - Jeong Hoon Kim
- Department of Neurosurgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, South Korea
| | - Ho Sung Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, 43 Olympic-ro 88, Songpa-Gu, Seoul, 05505, South Korea
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Stumpo V, Guida L, Bellomo J, Van Niftrik CHB, Sebök M, Berhouma M, Bink A, Weller M, Kulcsar Z, Regli L, Fierstra J. Hemodynamic Imaging in Cerebral Diffuse Glioma-Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions. Cancers (Basel) 2022; 14:1342. [PMID: 35267650 PMCID: PMC8909110 DOI: 10.3390/cancers14051342] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 03/01/2022] [Accepted: 03/02/2022] [Indexed: 02/05/2023] Open
Abstract
Gliomas, and glioblastoma in particular, exhibit an extensive intra- and inter-tumoral molecular heterogeneity which represents complex biological features correlating to the efficacy of treatment response and survival. From a neuroimaging point of view, these specific molecular and histopathological features may be used to yield imaging biomarkers as surrogates for distinct tumor genotypes and phenotypes. The development of comprehensive glioma imaging markers has potential for improved glioma characterization that would assist in the clinical work-up of preoperative treatment planning and treatment effect monitoring. In particular, the differentiation of tumor recurrence or true progression from pseudoprogression, pseudoresponse, and radiation-induced necrosis can still not reliably be made through standard neuroimaging only. Given the abundant vascular and hemodynamic alterations present in diffuse glioma, advanced hemodynamic imaging approaches constitute an attractive area of clinical imaging development. In this context, the inclusion of objective measurable glioma imaging features may have the potential to enhance the individualized care of diffuse glioma patients, better informing of standard-of-care treatment efficacy and of novel therapies, such as the immunotherapies that are currently increasingly investigated. In Part B of this two-review series, we assess the available evidence pertaining to hemodynamic imaging for molecular feature prediction, in particular focusing on isocitrate dehydrogenase (IDH) mutation status, MGMT promoter methylation, 1p19q codeletion, and EGFR alterations. The results for the differentiation of tumor progression/recurrence from treatment effects have also been the focus of active research and are presented together with the prognostic correlations identified by advanced hemodynamic imaging studies. Finally, the state-of-the-art concepts and advancements of hemodynamic imaging modalities are reviewed together with the advantages derived from the implementation of radiomics and machine learning analyses pipelines.
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Affiliation(s)
- Vittorio Stumpo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Lelio Guida
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jacopo Bellomo
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Christiaan Hendrik Bas Van Niftrik
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Martina Sebök
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Moncef Berhouma
- Department of Neurosurgical Oncology and Vascular Neurosurgery, Pierre Wertheimer Neurological and Neurosurgical Hospital, Hospices Civils de Lyon, 69500 Lyon, France;
| | - Andrea Bink
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Michael Weller
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neurology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Zsolt Kulcsar
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
- Department of Neuroradiology, University Hospital Zurich, 8091 Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital Zurich, 8091 Zurich, Switzerland; (L.G.); (J.B.); (C.H.B.V.N.); (M.S.); (L.R.); (J.F.)
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, 8057 Zurich, Switzerland; (A.B.); (M.W.); (Z.K.)
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Henriksen OM, del Mar Álvarez-Torres M, Figueiredo P, Hangel G, Keil VC, Nechifor RE, Riemer F, Schmainda KM, Warnert EAH, Wiegers EC, Booth TC. High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques. Front Oncol 2022; 12:810263. [PMID: 35359414 PMCID: PMC8961422 DOI: 10.3389/fonc.2022.810263] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Accepted: 01/05/2022] [Indexed: 01/16/2023] Open
Abstract
Objective Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments. Methods Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics). Results High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies. Conclusion Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.
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Affiliation(s)
- Otto M. Henriksen
- Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Copenhagen, Denmark
| | | | - Patricia Figueiredo
- Department of Bioengineering and Institute for Systems and Robotics-Lisboa, Instituto Superior Técnico, Universidade de Lisboa, Lisbon, Portugal
| | - Gilbert Hangel
- Department of Neurosurgery, Medical University, Vienna, Austria
- High-Field MR Centre, Department of Biomedical Imaging and Image-Guided Therapy, Medical University, Vienna, Austria
| | - Vera C. Keil
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Amsterdam, Netherlands
| | - Ruben E. Nechifor
- International Institute for the Advanced Studies of Psychotherapy and Applied Mental Health, Department of Clinical Psychology and Psychotherapy, Babes-Bolyai University, Cluj-Napoca, Romania
| | - Frank Riemer
- Mohn Medical Imaging and Visualization Centre (MMIV), Department of Radiology, Haukeland University Hospital, Bergen, Norway
| | - Kathleen M. Schmainda
- Department of Biophysics, Medical College of Wisconsin, Milwaukee, WI, United States
| | | | - Evita C. Wiegers
- Department of Radiology, University Medical Center Utrecht, Utrecht, Netherlands
| | - Thomas C. Booth
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School of Biomedical Engineering and Imaging Sciences, St. Thomas’ Hospital, King’s College London, London, United Kingdom
- Department of Neuroradiology, King’s College Hospital NHS Foundation Trust, London, United Kingdom
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10
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Stumpo V, Sebök M, van Niftrik CHB, Seystahl K, Hainc N, Kulcsar Z, Weller M, Regli L, Fierstra J. Feasibility of glioblastoma tissue response mapping with physiologic BOLD imaging using precise oxygen and carbon dioxide challenge. MAGMA (NEW YORK, N.Y.) 2022; 35:29-44. [PMID: 34874499 DOI: 10.1007/s10334-021-00980-7] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Revised: 11/15/2021] [Accepted: 11/19/2021] [Indexed: 12/15/2022]
Abstract
OBJECTIVES Innovative physiologic MRI development focuses on depiction of heterogenous vascular and metabolic features in glioblastoma. For this feasibility study, we employed blood oxygenation level-dependent (BOLD) MRI with standardized and precise carbon dioxide (CO2) and oxygen (O2) modulation to investigate specific tumor tissue response patterns in patients with newly diagnosed glioblastoma. MATERIALS AND METHODS Seven newly diagnosed untreated patients with suspected glioblastoma were prospectively included to undergo a BOLD study with combined CO2 and O2 standardized protocol. %BOLD signal change/mmHg during hypercapnic, hypoxic, and hyperoxic stimulus was calculated in the whole brain, tumor lesion and segmented volumes of interest (VOI) [contrast-enhancing (CE) - tumor, necrosis and edema] to analyze their tissue response patterns. RESULTS Quantification of BOLD signal change after gas challenges can be used to identify specific responses to standardized stimuli in glioblastoma patients. Integration of this approach with automatic VOI segmentation grants improved characterization of tumor subzones and edema. Magnitude of BOLD signal change during the 3 stimuli can be visualized at voxel precision through color-coded maps overlayed onto whole brain and identified VOIs. CONCLUSIONS Our preliminary investigation shows good feasibility of BOLD with standardized and precise CO2 and O2 modulation as an emerging physiologic imaging technique to detail specific glioblastoma characteristics. The unique tissue response patterns generated can be further investigated to better detail glioblastoma lesions and gauge treatment response.
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Affiliation(s)
- Vittorio Stumpo
- Department of Neurosurgery, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland. .,Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Martina Sebök
- Department of Neurosurgery, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.,Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Christiaan Hendrik Bas van Niftrik
- Department of Neurosurgery, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.,Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Katharina Seystahl
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Nicolin Hainc
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland
| | - Zsolt Kulcsar
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Neuroradiology, University Hospital Zurich, Zurich, Switzerland
| | - Michael Weller
- Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland.,Department of Neurology, University Hospital Zurich, Zurich, Switzerland
| | - Luca Regli
- Department of Neurosurgery, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.,Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Jorn Fierstra
- Department of Neurosurgery, University Hospital Zurich, Frauenklinikstrasse 10, 8091, Zurich, Switzerland.,Clinical Neuroscience Center, University Hospital Zurich, University of Zurich, Zurich, Switzerland
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11
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Park YW, Ahn SS, Moon JH, Kim EH, Kang SG, Chang JH, Kim SH, Lee SK. Dynamic contrast-enhanced MRI may be helpful to predict response and prognosis after bevacizumab treatment in patients with recurrent high-grade glioma: comparison with diffusion tensor and dynamic susceptibility contrast imaging. Neuroradiology 2021; 63:1811-1822. [PMID: 33755766 DOI: 10.1007/s00234-021-02693-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 03/15/2021] [Indexed: 12/20/2022]
Abstract
PURPOSE We aimed to evaluate the utility of diffusion tensor imaging (DTI), dynamic contrast-enhanced (DCE), and dynamic susceptibility contrast (DSC) imaging for stratifying bevacizumab treatment outcomes in patients with recurrent high-grade glioma. METHODS Fifty-three patients with recurrent high-grade glioma who underwent baseline magnetic resonance imaging including DTI, DCE, and DSC before bevacizumab treatment were included. The mean apparent diffusion coefficient, fractional anisotropy, normalized cerebral blood volume, normalized cerebral blood flow, volume transfer constant, rate transfer coefficient (Kep), extravascular extracellular volume fraction, and plasma volume fraction were assessed. Predictors of response status, progression-free survival (PFS), and overall survival (OS) were determined using logistic regression and Cox proportional hazard modeling. RESULTS Responders (n = 16) showed significantly longer PFS and OS (P < 0.001) compared with nonresponders (n = 37). Multivariable analysis revealed that lower mean Kep (odds ratio = 0.01, P = 0.008) was the only independent predictor of favorable response after adjustment for age, isocitrate dehydrogenase (IDH) mutation status, and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation status. Multivariable Cox proportional hazard modeling showed that a higher mean Kep was the only variable associated with shorter PFS (hazard ratio [HR] = 7.90, P = 0.006) and OS (HR = 9.71, P = 0.020) after adjustment for age, IDH mutation status, and MGMT promoter methylation status. CONCLUSION Baseline mean Kep may be a useful biomarker for predicting response and stratifying patient outcomes following bevacizumab treatment in patients with recurrent high-grade glioma.
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Affiliation(s)
- Yae Won Park
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
| | - Sung Soo Ahn
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea.
| | - Ju Hyung Moon
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Eui Hyun Kim
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Seok-Gu Kang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Jong Hee Chang
- Department of Neurosurgery, Yonsei University College of Medicine, Seoul, Korea
| | - Se Hoon Kim
- Department of Pathology, Yonsei University College of Medicine, Seoul, Korea
| | - Seung-Koo Lee
- Department of Radiology and Research Institute of Radiological Science and Center for Clinical Imaging Data Science, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 120-752, Korea
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12
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Advanced magnetic resonance imaging to support clinical drug development for malignant glioma. Drug Discov Today 2020; 26:429-441. [PMID: 33249294 DOI: 10.1016/j.drudis.2020.11.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2020] [Revised: 10/23/2020] [Accepted: 11/18/2020] [Indexed: 11/22/2022]
Abstract
Even though the treatment options and survival of patients with glioblastoma multiforme (GBM), the most common type of malignant glioma, have improved over the past decade, there is still a high unmet medical need to develop novel therapies. Complexity in pathology and therapy require biomarkers to characterize tumors, to define malignant and active areas, to assess disease prognosis, and to quantify and monitor therapy response. While conventional magnetic resonance imaging (MRI) techniques have improved these assessments, limitations remain. In this review, we evaluate the role of various non-invasive biomarkers based on advanced structural and functional MRI techniques in the context of GBM drug development over the past 5 years.
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13
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Østergaard L. Blood flow, capillary transit times, and tissue oxygenation: the centennial of capillary recruitment. J Appl Physiol (1985) 2020; 129:1413-1421. [PMID: 33031017 DOI: 10.1152/japplphysiol.00537.2020] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
The transport of oxygen between blood and tissue is limited by blood's capillary transit time, understood as the time available for diffusion exchange before blood returns to the heart. If all capillaries contribute equally to tissue oxygenation at all times, this physical limitation would render vasodilation and increased blood flow insufficient means to meet increased metabolic demands in the heart, muscle, and other organs. In 1920, Danish physiologist August Krogh was awarded the Nobel Prize in Physiology or Medicine for his mathematical and quantitative, experimental demonstration of a solution to this conceptual problem: capillary recruitment, the active opening of previously closed capillaries to meet metabolic demands. Today, capillary recruitment is still mentioned in textbooks. When we suspect symptoms might represent hypoxia of a vascular origin, however, we search for relevant, flow-limiting conditions in our patients and rarely ascribe hypoxia or hypoxemia to short capillary transit times. This review describes how natural changes in capillary transit-time heterogeneity (CTH) and capillary hematocrit (HCT) across open capillaries during blood flow increases can account for a match of oxygen availability to metabolic demands in normal tissue. CTH and HCT depend on a number of factors: on blood properties, including plasma viscosity, the number, size, and deformability of blood cells, and blood cell interactions with capillary endothelium; on anatomical factors including glycocalyx, endothelial cells, basement membrane, and pericytes that affect the capillary diameter; and on any external compression. The review describes how risk factor- and disease-related changes in CTH and HCT interfere with flow-metabolism coupling and tissue oxygenation and discusses whether such capillary dysfunction contributes to vascular disease pathology.
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Affiliation(s)
- Leif Østergaard
- Center of Functionally Integrative Neuroscience, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark.,Neuroradiology Research Unit, Section of Neuroradiology, Department of Radiology, Aarhus University Hospital, Aarhus, Denmark
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14
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Liapis E, Klemm U, Karlas A, Reber J, Ntziachristos V. Resolution of Spatial and Temporal Heterogeneity in Bevacizumab-Treated Breast Tumors by Eigenspectra Multispectral Optoacoustic Tomography. Cancer Res 2020; 80:5291-5304. [PMID: 32994204 DOI: 10.1158/0008-5472.can-20-1011] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2020] [Revised: 08/05/2020] [Accepted: 09/24/2020] [Indexed: 11/16/2022]
Abstract
Understanding temporal and spatial hemodynamic heterogeneity as a function of tumor growth or therapy affects the development of novel therapeutic strategies. In this study, we employed eigenspectra multispectral optoacoustic tomography (eMSOT) as a next-generation optoacoustic method to impart high accuracy in resolving tumor hemodynamics during bevacizumab therapy in two types of breast cancer xenografts (KPL-4 and MDA-MB-468). Patterns of tumor total hemoglobin concentration (THb) and oxygen saturation (sO2) were imaged in control and bevacizumab-treated tumors over the course of 58 days (KPL-4) and 16 days (MDA-MB-468), and the evolution of functional vasculature "normalization" was resolved macroscopically. An initial sharp drop in tumor sO2 and THb content shortly after the initiation of bevacizumab treatment was followed by a recovery in oxygenation levels. Rim-core subregion analysis revealed steep spatial oxygenation gradients in growing tumors that were reduced after bevacizumab treatment. Critically, eMSOT imaging findings were validated directly by histopathologic assessment of hypoxia (pimonidazole) and vascularity (CD31). These data demonstrate how eMSOT brings new abilities for accurate observation of entire tumor responses to challenges at spatial and temporal dimensions not available by other techniques today. SIGNIFICANCE: Accurate assessment of hypoxia and vascularization over space and time is critical for understanding tumor development and the role of spatial heterogeneity in tumor aggressiveness, metastasis, and response to treatment.
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Affiliation(s)
- Evangelos Liapis
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Munich, Neuherberg, Germany.
| | - Uwe Klemm
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Munich, Neuherberg, Germany
| | - Angelos Karlas
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Munich, Neuherberg, Germany.,Chair of Biological Imaging, TranslaTUM Technical University of Munich, Munich, Germany
| | - Josefine Reber
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Munich, Neuherberg, Germany
| | - Vasilis Ntziachristos
- Institute of Biological and Medical Imaging, Helmholtz Zentrum München, Munich, Neuherberg, Germany.,Chair of Biological Imaging, TranslaTUM Technical University of Munich, Munich, Germany
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15
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Abstract
Magnetic resonance imaging (MRI) has been the cornerstone of imaging of brain tumors in the past 4 decades. Conventional MRI remains the workhorse for neuro-oncologic imaging, not only for basic information such as location, extent, and navigation but also able to provide information regarding proliferation and infiltration, angiogenesis, hemorrhage, and more. More sophisticated MRI sequences have extended the ability to assess and quantify these features; for example, permeability and perfusion acquisitions can assess blood-brain barrier disruption and angiogenesis, diffusion techniques can assess cellularity and infiltration, and spectroscopy can address metabolism. Techniques such as fMRI and diffusion fiber tracking can be helpful in diagnostic planning for resection and radiation therapy, and more sophisticated iterations of these techniques can extend our understanding of neurocognitive effects of these tumors and associated treatment responses and effects. More recently, MRI has been used to go beyond such morphological, physiological, and functional characteristics to assess the tumor microenvironment. The current review highlights multiple recent and emerging approaches in MRI to characterize the tumor microenvironment.
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16
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Kickingereder P, Brugnara G, Hansen MB, Nowosielski M, Pflüger I, Schell M, Isensee F, Foltyn M, Neuberger U, Kessler T, Sahm F, Wick A, Heiland S, Weller M, Platten M, von Deimling A, Maier-Hein KH, Østergaard L, van den Bent MJ, Gorlia T, Wick W, Bendszus M. Noninvasive Characterization of Tumor Angiogenesis and Oxygenation in Bevacizumab-treated Recurrent Glioblastoma by Using Dynamic Susceptibility MRI: Secondary Analysis of the European Organization for Research and Treatment of Cancer 26101 Trial. Radiology 2020; 297:164-175. [PMID: 32720870 DOI: 10.1148/radiol.2020200978] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Background Relevance of antiangiogenic treatment with bevacizumab in patients with glioblastoma is controversial because progression-free survival benefit did not translate into an overall survival (OS) benefit in randomized phase III trials. Purpose To perform longitudinal characterization of intratumoral angiogenesis and oxygenation by using dynamic susceptibility contrast agent-enhanced (DSC) MRI and evaluate its potential for predicting outcome from administration of bevacizumab. Materials and Methods In this secondary analysis of the prospective randomized phase II/III European Organization for Research and Treatment of Cancer 26101 trial conducted between October 2011 and December 2015 in 596 patients with first recurrence of glioblastoma, the subset of patients with availability of anatomic MRI and DSC MRI at baseline and first follow-up was analyzed. Patients were allocated into those administered bevacizumab (hereafter, the BEV group; either bevacizumab monotherapy or bevacizumab with lomustine) and those not administered bevacizumab (hereafter, the non-BEV group with lomustine monotherapy). Contrast-enhanced tumor volume, noncontrast-enhanced T2 fluid-attenuated inversion recovery (FLAIR) signal abnormality volume, Gaussian-normalized relative cerebral blood volume (nrCBV), Gaussian-normalized relative blood flow (nrCBF), and tumor metabolic rate of oxygen (nTMRO2) was quantified. The predictive ability of these imaging parameters was assessed with multivariable Cox regression and formal interaction testing. Results A total of 254 of 596 patients were evaluated (mean age, 57 years ± 11; 155 men; 161 in the BEV group and 93 in non-BEV group). Progression-free survival was longer in the BEV group (3.7 months; 95% confidence interval [CI]: 3.0, 4.2) compared with the non-BEV group (2.5 months; 95% CI: 1.5, 2.9; P = .01), whereas OS was not different (P = .15). The nrCBV decreased for the BEV group (-16.3%; interquartile range [IQR], -39.5% to 12.0%; P = .01), but not for the non-BEV group (1.2%; IQR, -17.9% to 23.3%; P = .19) between baseline and first follow-up. An identical pattern was observed for both nrCBF and nTMRO2 values. Contrast-enhanced tumor and noncontrast-enhanced T2 FLAIR signal abnormality volumes decreased for the BEV group (-66% [IQR, -83% to -35%] and -33% [IQR, -71% to -5%], respectively; P < .001 for both), whereas they increased for the non-BEV group (30% [IQR, -17% to 98%], P = .001; and 10% [IQR, -13% to 82%], P = .02, respectively) between baseline and first follow-up. None of the assessed MRI parameters were predictive for OS in the BEV group. Conclusion Bevacizumab treatment decreased tumor volumes, angiogenesis, and oxygenation, thereby reflecting its effectiveness for extending progression-free survival; however, these parameters were not predictive of overall survival (OS), which highlighted the challenges of identifying patients that derive an OS benefit from bevacizumab. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Dillon in this issue.
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Affiliation(s)
- Philipp Kickingereder
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Gianluca Brugnara
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Mikkel Bo Hansen
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Martha Nowosielski
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Irada Pflüger
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Marianne Schell
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Fabian Isensee
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Martha Foltyn
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Ulf Neuberger
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Tobias Kessler
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Felix Sahm
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Antje Wick
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Sabine Heiland
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Michael Weller
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Michael Platten
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Andreas von Deimling
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Klaus H Maier-Hein
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Leif Østergaard
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Martin J van den Bent
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Thierry Gorlia
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Wolfgang Wick
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
| | - Martin Bendszus
- From the Department of Neuroradiology, Heidelberg University Hospital, Im Neuenheimer Feld 400, 69120 Heidelberg, Germany (P.K., G.B., I.P., M.S., M.F., U.N., S.H., M.B.); Center of Functionally Integrative Neuroscience and MINDLab, Aarhus University Hospital, Aarhus, Denmark (M.B.H., L.Ø.); Neurology Clinic, Heidelberg University Hospital, Heidelberg, Germany (M.N., T.K., A.W., W.W.); Department of Neurology, Medical University Innsbruck, Innsbruck, Austria (M.N.); Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.I., K.H.M.H.); Clinical Cooperation Unit Neurooncology, German Cancer Research Center (DKFZ), Heidelberg, Germany (T.K., W.W.); Department of Neuropathology, Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany (F.S., A.v.D.); Clinical Cooperation Unit Neuropathology, German Cancer Research Center (DKFZ), Heidelberg, Germany (F.S., A.v.D.); Department of Neurology, University Hospital and University of Zurich, Zurich, Switzerland (M.W.); Department of Neurology, Medical Faculty Mannheim, MCTN, University of Heidelberg, Mannheim, Germany (M.P.); Pattern Analysis and Learning Group, Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany (K.H.M.H.); Department of Neuroradiology, Aarhus University Hospital, Aarhus, Denmark (L.Ø.); Brain Tumor Center at Erasmus MC Cancer Institute, Rotterdam, the Netherlands (M.J.v.d.B.); and European Organization for Research and Treatment of Cancer (EORTC), Brussels, Belgium (T.G.)
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Whelan CJ, Avdieiev SS, Gatenby RA. Insights From the Ecology of Information to Cancer Control. Cancer Control 2020; 27:1073274820945980. [PMID: 32762341 PMCID: PMC7791475 DOI: 10.1177/1073274820945980] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Revised: 06/18/2020] [Accepted: 07/08/2020] [Indexed: 12/16/2022] Open
Abstract
Uniquely in nature, living systems must acquire, store, and act upon information. The survival and replicative fate of each normal cell in a multicellular organism is determined solely by information obtained from its surrounding tissue. In contrast, cancer cells as single-cell eukaryotes live in a disrupted, heterogeneous environment with opportunities and hazards. Thus, cancer cells, unlike normal somatic cells, must constantly obtain information from their environment to ensure survival and proliferation. In this study, we build upon a simple mathematical modeling framework developed to predict (1) how information promotes population persistence in a highly heterogeneous environment and (2) how disruption of information resulting from habitat fragmentation increases the probability of population extinction. Because (1) tumors grow in a highly heterogeneous microenvironment and (2) many cancer therapies fragment tumors into isolated, small cancer cell populations, we identify parallels between these 2 systems and develop ideas for cancer cure based on lessons gleaned from Anthropocene extinctions. In many Anthropocene extinctions, such as that of the North American heath hen (Tympanuchus cupido cupido), a large and widespread population was initially reduced and fragmented owing to overexploitation by humans (a "first strike"). After this, the small surviving populations are vulnerable to extinction from environmental or demographic stochastic disturbances (a "second strike"). Following this analogy, after a tumor is fragmented into small populations of isolated cancer cells by an initial therapy, additional treatment can be applied with the intent of extinction (cure). Disrupting a cancer cell's ability to acquire and use information in a heterogeneous environment may be an important tactic for causing extinction following an effective initial therapy. Thus, information, from the scale of cells within tumors to that of species within ecosystems, can be used to identify vulnerabilities to extinction and opportunities for novel treatment strategies.
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Affiliation(s)
- Christopher J. Whelan
- Cancer Biology and Evolution Program, Moffitt Cancer Center
& Research Institute, Tampa, FL, USA
- Department of Cancer Physiology, Moffitt Cancer Center &
Research Institute, Tampa, FL, USA
| | - Stanislav S. Avdieiev
- Cancer Biology and Evolution Program, Moffitt Cancer Center
& Research Institute, Tampa, FL, USA
- Department of Integrated Mathematical Oncology, Moffitt
Cancer Center & Research Institute, Tampa, FL, USA
| | - Robert A. Gatenby
- Cancer Biology and Evolution Program, Moffitt Cancer Center
& Research Institute, Tampa, FL, USA
- Department of Integrated Mathematical Oncology, Moffitt
Cancer Center & Research Institute, Tampa, FL, USA
- Department of Diagnostic Imaging and Interventional
Radiology, Moffitt Cancer Center & Research Institute, Tampa, FL,
USA
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18
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Foltyn M, Nieto Taborda KN, Neuberger U, Brugnara G, Reinhardt A, Stichel D, Heiland S, Herold-Mende C, Unterberg A, Debus J, von Deimling A, Wick W, Bendszus M, Kickingereder P. T2/FLAIR-mismatch sign for noninvasive detection of IDH-mutant 1p/19q non-codeleted gliomas: validity and pathophysiology. Neurooncol Adv 2020; 2:vdaa004. [PMID: 32642675 PMCID: PMC7212872 DOI: 10.1093/noajnl/vdaa004] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
Background This study aimed to assess the validity and pathophysiology of the T2/FLAIR-mismatch sign for noninvasive identification of isocitrate dehydrogenase (IDH)-mutant 1p/19q non-codeleted glioma. Methods Magnetic resonance imaging scans from 408 consecutive patients with newly diagnosed glioma (113 lower-grade gliomas and 295 glioblastomas) were evaluated for the presence of T2/FLAIR-mismatch sign by 2 independent reviewers. Sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV) were calculated to assess the performance of the T2/FLAIR-mismatch sign for identifying IDH-mutant 1p/19q non-codeleted tumors. An exploratory analysis of differences in contrast-enhancing tumor volumes, apparent diffusion coefficient (ADC) values, and relative cerebral blood volume (rCBV) values in IDH-mutant gliomas with versus without the presence of a T2/FLAIR-mismatch sign (as well as analysis of spatial differences within tumors with the presence of a T2/FLAIR-mismatch sign) was performed. Results The T2/FLAIR-mismatch sign was present in 12 cases with lower-grade glioma (10.6%), all of them being IDH-mutant 1p/19q non-codeleted tumors (sensitivity = 10.9%, specificity = 100%, PPV = 100%, NPV = 3.0%, accuracy = 13.3%). There was a substantial interrater agreement to identify the T2/FLAIR-mismatch sign (Cohen's kappa = 0.75 [95% CI, 0.57-0.93]). The T2/FLAIR-mismatch sign was not identified in any other molecular subgroup, including IDH-mutant glioblastoma cases (n = 5). IDH-mutant gliomas with a T2/FLAIR-mismatch sign showed significantly higher ADC (P < .0001) and lower rCBV values (P = .0123) as compared to IDH-mutant gliomas without a T2/FLAIR-mismatch sign. Moreover, in IDH-mutant gliomas with T2/FLAIR-mismatch sign the ADC values were significantly lower in the FLAIR-hyperintense rim as compared to the FLAIR-hypointense core of the tumor (P = .0005). Conclusions This study confirms the high specificity of the T2/FLAIR-mismatch sign for noninvasive identification of IDH-mutant 1p/19q non-codeleted gliomas; however, sensitivity is low and applicability is limited to lower-grade gliomas. Whether the higher ADC and lower rCBV values in IDH-mutant gliomas with a T2/FLAIR-mismatch sign (as compared to those without) translate into a measurable prognostic effect requires investigation in future studies. Moreover, spatial differences in ADC values between the core and rim of tumors with a T2/FLAIR-mismatch sign potentially reflect specific distinctions in tumor cellularity and microenvironment.
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Affiliation(s)
- Martha Foltyn
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | | | - Ulf Neuberger
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Annekathrin Reinhardt
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Damian Stichel
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Christel Herold-Mende
- Department of Neurosurgery, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Andreas Unterberg
- Department of Neurosurgery, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, University of Heidelberg Medical Center, Heidelberg Institute of Radiation Oncology and National Center for Radiation Research in Oncology, Heidelberg, Germany.,Division of Molecular and Translational Radiation Oncology, National Center for Tumor Diseases, Heidelberg University Hospital and DKFZ, Heidelberg, Germany
| | - Andreas von Deimling
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany.,Clinical Cooperation Unit Neuropathology, German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wolfgang Wick
- Neurology Clinic, University of Heidelberg Medical Center, Heidelberg, Germany.,Clinical Cooperation Unit Neuro-oncology, DKTK, DKFZ, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Philipp Kickingereder
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
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19
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Gerstner ER, Emblem KE, Yen YF, Dietrich J, Jordan JT, Catana C, Wenchin KL, Hooker JM, Duda DG, Rosen BR, Kalpathy-Cramer J, Jain RK, Batchelor TT. Vascular dysfunction promotes regional hypoxia after bevacizumab therapy in recurrent glioblastoma patients. Neurooncol Adv 2020; 2:vdaa157. [PMID: 33392506 PMCID: PMC7764510 DOI: 10.1093/noajnl/vdaa157] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Hypoxia is a driver of treatment resistance in glioblastoma. Antiangiogenic agents may transiently normalize blood vessels and decrease hypoxia before excessive pruning of vessels increases hypoxia. The time window of normalization is dose and time dependent. We sought to determine how VEGF blockade with bevacizumab modulates tumor vasculature and the impact that those vascular changes have on hypoxia in recurrent glioblastoma patients. METHODS We measured tumor volume, vascular permeability (Ktrans), perfusion parameters (cerebral blood flow/volume, vessel caliber, and mean transit time), and regions of hypoxia in patients with recurrent glioblastoma before and after treatment with bevacizumab alone or with lomustine using [18F]FMISO PET-MRI. We also examined serial changes in plasma biomarkers of angiogenesis and inflammation. RESULTS Eleven patients were studied. The magnitude of global tumor hypoxia was variable across these 11 patients prior to treatment and it did not significantly change after bevacizumab. The hypoxic regions had an inefficient vasculature characterized by elevated cerebral blood flow/volume and increased vessel caliber. In a subset of patients, there were tumor subregions with decreased mean transit times and a decrease in hypoxia, suggesting heterogeneous improvement in vascular efficiency. Bevacizumab significantly changed known pharmacodynamic biomarkers such as plasma VEGF and PlGF. CONCLUSIONS The vascular signature in hypoxic tumor regions indicates a disorganized vasculature which, in most tumors, does not significantly change after bevacizumab treatment. While some tumor regions showed improved vascular efficiency following treatment, bevacizumab did not globally alter hypoxia or normalize tumor vasculature in glioblastoma.
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Affiliation(s)
- Elizabeth R Gerstner
- Stephen E. and Catherine Pappas Center for Neuro-Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Kyrre E Emblem
- Department of Diagnostic Physics, Oslo University, Oslo, Norway
| | - Yi-Fen Yen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Jorg Dietrich
- Stephen E. and Catherine Pappas Center for Neuro-Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Justin T Jordan
- Stephen E. and Catherine Pappas Center for Neuro-Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Ciprian Catana
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Kevin Lou Wenchin
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
| | - Jacob M Hooker
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Dan G Duda
- Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Jayashree Kalpathy-Cramer
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Rakesh K Jain
- Edwin L. Steele Laboratories, Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Tracy T Batchelor
- Department of Neurology, Brigham and Women’s Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
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20
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Tejada Neyra MA, Neuberger U, Reinhardt A, Brugnara G, Bonekamp D, Sill M, Wick A, Jones DTW, Radbruch A, Unterberg A, Debus J, Heiland S, Schlemmer HP, Herold-Mende C, Pfister S, von Deimling A, Wick W, Capper D, Bendszus M, Kickingereder P. Voxel-wise radiogenomic mapping of tumor location with key molecular alterations in patients with glioma. Neuro Oncol 2019; 20:1517-1524. [PMID: 30107597 DOI: 10.1093/neuonc/noy134] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Background This study aims to evaluate the impact of tumor location on key molecular alterations on a single voxel level in patients with newly diagnosed glioma. Methods A consecutive series of n = 237 patients with newly diagnosed glioblastoma and n = 131 patients with lower-grade glioma was analyzed. Volumetric tumor segmentation was performed on preoperative MRI with a semi-automated approach and images were registered to the standard Montreal Neurological Institute 152 space. Using a voxel-based lesion symptom mapping (VLSM) analysis, we identified specific brain regions that were associated with tumor-specific molecular alterations. We assessed a predefined set of n = 17 molecular characteristics in the glioblastoma cohort and n = 2 molecular characteristics in the lower-grade glioma cohort. Permutation adjustment (n = 1000 iterations) was used to correct for multiple testing, and voxel t-values that were greater than the t-value in >95% of the permutations were retained in the VLSM results (α = 0.05, power > 0.8). Results Tumor location predilection for isocitrate dehydrogenase (IDH) mutant tumors was found in both glioblastoma and lower-grade glioma cohorts, each showing a concordant predominance in the frontal lobe adjacent to the rostral extension of the lateral ventricles (permutation-adjusted P = 0.021 for the glioblastoma and 0.013 for the lower-grade glioma cohort). Apart from that, the VLSM analysis did not reveal a significant association of the tumor location with any other key molecular alteration in both cohorts (permutation-adjusted P > 0.05 each). Conclusion Our study highlights the unique properties of IDH mutations and underpins the hypothesis that the rostral extension of the lateral ventricles is a potential location for the cell of origin in IDH-mutant gliomas.
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Affiliation(s)
| | - Ulf Neuberger
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Annekathrin Reinhardt
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Gianluca Brugnara
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - David Bonekamp
- Department of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Martin Sill
- Hopp-Children's Cancer Center at the NCT Heidelberg (KiTZ), Heidelberg, Germany.,Division of Pediatric Neurooncology, DKFZ, Heidelberg, Germany.,German Cancer Consortium (DKTK) Core Center Heidelberg, Heidelberg, Germany
| | - Antje Wick
- Neurology Clinic, University of Heidelberg Medical Center, Heidelberg, Germany
| | - David T W Jones
- Hopp-Children's Cancer Center at the NCT Heidelberg (KiTZ), Heidelberg, Germany.,Division of Pediatric Neurooncology, DKFZ, Heidelberg, Germany.,German Cancer Consortium (DKTK) Core Center Heidelberg, Heidelberg, Germany
| | - Alexander Radbruch
- Department of Radiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Andreas Unterberg
- Department of Neurosurgery, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, University of Heidelberg Medical Center, Heidelberg Institute of Radiation Oncology (HIRO) and National Center for Radiation Research in Oncology (NCOR), Heidelberg, Germany.,Molecular and Translational Radiation Oncology, National Center for Tumor Diseases (NCT), Heidelberg University Hospital and DKFZ, Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | | | - Christel Herold-Mende
- Department of Neurosurgery, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Stefan Pfister
- Hopp-Children's Cancer Center at the NCT Heidelberg (KiTZ), Heidelberg, Germany.,Division of Pediatric Neurooncology, DKFZ, Heidelberg, Germany.,German Cancer Consortium (DKTK) Core Center Heidelberg, Heidelberg, Germany.,Department of Pediatric Oncology, Hematology and Immunology, Heidelberg University Hospital, Heidelberg, Germany
| | - Andreas von Deimling
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany.,DKTK, Clinical Cooperation Unit Neuropathology, DKFZ, Heidelberg, Germany
| | - Wolfgang Wick
- Neurology Clinic, University of Heidelberg Medical Center, Heidelberg, Germany.,Clinical Cooperation Unit Neurooncology, DKTK, DKFZ, Heidelberg, Germany
| | - David Capper
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany.,Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute for Neuropathology, Berlin, Germany.,DKTK, Partner Site Berlin, DKFZ, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Philipp Kickingereder
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
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21
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Zhang K, Yun SD, Triphan SMF, Sturm VJ, Buschle LR, Hahn A, Heiland S, Bendszus M, Schlemmer HP, Shah NJ, Ziener CH, Kurz FT. Vessel architecture imaging using multiband gradient-echo/spin-echo EPI. PLoS One 2019; 14:e0220939. [PMID: 31398234 PMCID: PMC6688807 DOI: 10.1371/journal.pone.0220939] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2018] [Accepted: 07/26/2019] [Indexed: 12/04/2022] Open
Abstract
Objectives To apply the MB (multiband) excitation and blipped-CAIPI (blipped-controlled aliasing in parallel imaging) techniques in a spin and gradient-echo (SAGE) EPI sequence to improve the slice coverage for vessel architecture imaging (VAI). Materials and methods Both MB excitation and blipped-CAIPI with in-plane parallel imaging were incorporated into a gradient-echo (GE)/spin-echo (SE) EPI sequence for simultaneous tracking of the dynamic MR signal changes in both GE and SE contrasts after the injection of contrast agent. MB and singleband (SB) excitation were compared using a 20-channel head coil at 3 Tesla, and high-resolution MB VAI could be performed in 32 glioma patients. Results Whole-brain covered high resolution VAI can be achieved after applying multiband excitation with a factor of 2 and in-plane parallel imaging with a factor of 3. The quality of the images resulting from MB acceleration was comparable to those from the SB method: images were reconstructed without any loss of spatial resolution or severe distortions. In addition, MB and SB signal-to-noise ratios (SNR) were similar. A relative low g-factor induced from the MB acceleration method was achieved after using a blipped-CAIPI technique (1.35 for GE and 1.33 for SE imaging). Performing quantitative VAI, we found that, among all VAI parametric maps, microvessel type indicator (MTI), distance map (I) and vascular-induced bolus peak-time shift (VIPS) were highly correlated. Likewise, VAI parametric maps of slope, slope length and short axis were highly correlated. Conclusions Multiband accelerated SAGE successfully doubles the number of readout slices in the same measurement time when compared to conventional readout sequences. The corresponding VAI parametric maps provide insights into the complexity and heterogeneity of vascular changes in glioma.
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Affiliation(s)
- Ke Zhang
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany.,Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Seong Dae Yun
- Institute of Neuroscience and Medicine- 4, Medical Imaging Physics, Forschungszentrum Jülich, Germany
| | - Simon M F Triphan
- Department of Diagnostic & Interventional Radiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Volker J Sturm
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany.,Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Lukas R Buschle
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany.,Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Artur Hahn
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.,Department of Physics and Astronomy, University of Heidelberg, Heidelberg, Germany
| | - Sabine Heiland
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | | | - N Jon Shah
- Institute of Neuroscience and Medicine- 4, Medical Imaging Physics, Forschungszentrum Jülich, Germany.,Department of Neurology, Faculty of Medicine, JARA, RWTH Aachen University, Aachen, Germany
| | - Christian H Ziener
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany.,Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
| | - Felix T Kurz
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany.,Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany
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22
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Bell LC, Stokes AM, Quarles CC. Analysis of postprocessing steps for residue function dependent dynamic susceptibility contrast (DSC)-MRI biomarkers and their clinical impact on glioma grading for both 1.5 and 3T. J Magn Reson Imaging 2019; 51:547-553. [PMID: 31206948 DOI: 10.1002/jmri.26837] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 05/30/2019] [Accepted: 05/31/2019] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND Dynamic susceptibility contrast (DSC)-MRI analysis pipelines differ across studies and sites, potentially confounding the clinical value and use of the derived biomarkers. PURPOSE/HYPOTHESIS To investigate how postprocessing steps for computation of cerebral blood volume (CBV) and residue function dependent parameters (cerebral blood flow [CBF], mean transit time [MTT], capillary transit heterogeneity [CTH]) impact glioma grading. STUDY TYPE Retrospective study from The Cancer Imaging Archive (TCIA). POPULATION Forty-nine subjects with low- and high-grade gliomas. FIELD STRENGTH/SEQUENCE 1.5 and 3.0T clinical systems using a single-echo echo planar imaging (EPI) acquisition. ASSESSMENT Manual regions of interest (ROIs) were provided by TCIA and automatically segmented ROIs were generated by k-means clustering. CBV was calculated based on conventional equations. Residue function dependent biomarkers (CBF, MTT, CTH) were found by two deconvolution methods: circular discretization followed by a signal-to-noise ratio (SNR)-adapted eigenvalue thresholding (Method 1) and Volterra discretization with L-curve-based Tikhonov regularization (Method 2). STATISTICAL TESTS Analysis of variance, receiver operating characteristics (ROC), and logistic regression tests. RESULTS MTT alone was unable to statistically differentiate glioma grade (P > 0.139). When normalized, tumor CBF, CTH, and CBV did not differ across field strengths (P > 0.141). Biomarkers normalized to automatically segmented regions performed equally (rCTH AUROC is 0.73 compared with 0.74) or better (rCBF AUROC increases from 0.74-0.84; rCBV AUROC increases 0.78-0.86) than manually drawn ROIs. By updating the current deconvolution steps (Method 2), rCTH can act as a classifier for glioma grade (P < 0.007), but not if processed by current conventional DSC methods (Method 1) (P > 0.577). Lastly, higher-order biomarkers (eg, rCBF and rCTH) along with rCBV increases AUROC to 0.92 for differentiating tumor grade as compared with 0.78 and 0.86 (manual and automatic reference regions, respectively) for rCBV alone. DATA CONCLUSION With optimized analysis pipelines, higher-order perfusion biomarkers (rCBF and rCTH) improve glioma grading as compared with CBV alone. Additionally, postprocessing steps impact thresholds needed for glioma grading. LEVEL OF EVIDENCE 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:547-553.
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Affiliation(s)
- Laura C Bell
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - Ashley M Stokes
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, Arizona, USA
| | - C Chad Quarles
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, Arizona, USA
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23
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Rao M, Dodoo E, Zumla A, Maeurer M. Immunometabolism and Pulmonary Infections: Implications for Protective Immune Responses and Host-Directed Therapies. Front Microbiol 2019; 10:962. [PMID: 31134013 PMCID: PMC6514247 DOI: 10.3389/fmicb.2019.00962] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2019] [Accepted: 04/16/2019] [Indexed: 12/12/2022] Open
Abstract
The biology and clinical efficacy of immune cells from patients with infectious diseases or cancer are associated with metabolic programming. Host immune- and stromal-cell genetic and epigenetic signatures in response to the invading pathogen shape disease pathophysiology and disease outcomes. Directly linked to the immunometabolic axis is the role of the host microbiome, which is also discussed here in the context of productive immune responses to lung infections. We also present host-directed therapies (HDT) as a clinically viable strategy to refocus dysregulated immunometabolism in patients with infectious diseases, which requires validation in early phase clinical trials as adjuncts to conventional antimicrobial therapy. These efforts are expected to be continuously supported by newly generated basic and translational research data to gain a better understanding of disease pathology while devising new molecularly defined platforms and therapeutic options to improve the treatment of patients with pulmonary infections, particularly in relation to multidrug-resistant pathogens.
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Affiliation(s)
- Martin Rao
- ImmunoSurgery Unit, Champalimaud Centre for the Unknown, Lisbon, Portugal
| | - Ernest Dodoo
- Department of Oncology and Haematology, Krankenhaus Nordwest, Frankfurt, Germany
| | - Alimuddin Zumla
- Division of Infection and Immunity, University College London, NIHR Biomedical Research Centre, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Markus Maeurer
- ImmunoSurgery Unit, Champalimaud Centre for the Unknown, Lisbon, Portugal.,Department of Oncology and Haematology, Krankenhaus Nordwest, Frankfurt, Germany
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24
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Zhou Y, Zhang J, Dan Pu, Bi F, Chen Y, Liu J, Li Q, Gou H, Wu B, Qiu M. Tumor calcification as a prognostic factor in cetuximab plus chemotherapy-treated patients with metastatic colorectal cancer. Anticancer Drugs 2019; 30:195-200. [PMID: 30570508 PMCID: PMC6365256 DOI: 10.1097/cad.0000000000000726] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2018] [Accepted: 11/10/2018] [Indexed: 02/07/2023]
Abstract
This study aimed to explore the correlation between survival and tumor calcification in patients with metastatic colorectal cancer who received cetuximab combined with chemotherapy. The study was a single-center retrospective analysis that enrolled 111 patients who had received therapy between April 2011 and October 2016. Tumor calcification and treatment efficacy were evaluated independently by radiologists on the basis of computed tomography scans. Clinical characteristics and follow-up data were collected from electronic medical records. Correlations between tumor calcification and clinical characteristics, tumor response rate, and patient survival were analyzed. Among the 111 enrolled patients, 27 had tumor calcification [27/111 (24.3%)]. The median progression-free survival was significantly longer for patients with tumor calcification than for those without calcification (9.3 vs. 6.2 months, P=0.022). Patients with tumor calcification also had a higher objective response rate (55.6 vs. 31%, P=0.021) and better overall survival (21.9 vs. 16.5 months, P=0.084). The correlation between calcification features and prognosis showed that patients with an increasing number of calcifications after treatment had a significantly longer median overall survival (22.9 vs. 9.1 months, P=0.033). Simultaneously, new liver metastases and multiple calcifications also showed a trend toward better overall survival. There were also no significant correlations between clinical characteristics (sex, age, gene mutation, primary tumor location, pathological type, blood test result) and survival (Supplementary Table 1, Supplemental digital content 1, http://links.lww.com/ACD/A280). Tumor calcification is associated with a better treatment outcome and is a potential prognostic marker.
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Affiliation(s)
- Yuwen Zhou
- Department of Medical Oncology, Cancer Center
| | | | - Dan Pu
- Lung Cancer Center, West China Hospital of Sichuan University, Chengdu, Sichuan, China
| | - Feng Bi
- Department of Medical Oncology, Cancer Center
| | - Ye Chen
- Department of Medical Oncology, Cancer Center
| | - Jiyan Liu
- Department of Medical Oncology, Cancer Center
| | - Qiu Li
- Department of Medical Oncology, Cancer Center
| | | | | | - Meng Qiu
- Department of Medical Oncology, Cancer Center
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25
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Obad N, Espedal H, Jirik R, Sakariassen PO, Brekke Rygh C, Lund-Johansen M, Taxt T, Niclou SP, Bjerkvig R, Keunen O. Lack of functional normalisation of tumour vessels following anti-angiogenic therapy in glioblastoma. J Cereb Blood Flow Metab 2018; 38. [PMID: 28627960 PMCID: PMC6168744 DOI: 10.1177/0271678x17714656] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Neo-angiogenesis represents an important factor for the delivery of oxygen and nutrients to a growing tumour, and is considered to be one of the main pathodiagnostic features of glioblastomas (GBM). Anti-angiogenic therapy by vascular endothelial growth factor (VEGF) blocking agents has been shown to lead to morphological vascular normalisation resulting in a reduction of contrast enhancement as seen by magnetic resonance imaging (MRI). Yet the functional consequences of this normalisation and its potential for improved delivery of cytotoxic agents to the tumour are not known. The presented study aimed at determining the early physiologic changes following bevacizumab treatment. A time series of perfusion MRI and hypoxia positron emission tomography (PET) scans were acquired during the first week of treatment, in two human GBM xenograft models treated with either high or low doses of bevacizumab. We show that vascular morphology was normalised over the time period investigated, but vascular function was not improved, resulting in poor tumoural blood flow and increased hypoxia.
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Affiliation(s)
- Nina Obad
- 1 Department of Biomedecine, University of Bergen, Bergen, Norway.,2 Department of Neurosurgery, Haukeland University Hospital, Bergen, Norway.,3 KG Jebsen Brain Tumor research Center, University of Bergen, Bergen, Norway
| | - Heidi Espedal
- 1 Department of Biomedecine, University of Bergen, Bergen, Norway.,3 KG Jebsen Brain Tumor research Center, University of Bergen, Bergen, Norway
| | - Radovan Jirik
- 4 Institute of Scientific Instruments of the Czech Academy of Sciences, Brno, Czech Republic
| | | | - Cecilie Brekke Rygh
- 1 Department of Biomedecine, University of Bergen, Bergen, Norway.,5 Bergen University College, Bergen, Norway
| | - Morten Lund-Johansen
- 2 Department of Neurosurgery, Haukeland University Hospital, Bergen, Norway.,6 Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Torfinn Taxt
- 1 Department of Biomedecine, University of Bergen, Bergen, Norway
| | - Simone P Niclou
- 3 KG Jebsen Brain Tumor research Center, University of Bergen, Bergen, Norway.,7 Norlux Neuro-Oncology Laboratory, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Rolf Bjerkvig
- 1 Department of Biomedecine, University of Bergen, Bergen, Norway.,3 KG Jebsen Brain Tumor research Center, University of Bergen, Bergen, Norway.,7 Norlux Neuro-Oncology Laboratory, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg
| | - Olivier Keunen
- 7 Norlux Neuro-Oncology Laboratory, Department of Oncology, Luxembourg Institute of Health, Luxembourg, Luxembourg
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26
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Kickingereder P, Neuberger U, Bonekamp D, Piechotta PL, Götz M, Wick A, Sill M, Kratz A, Shinohara RT, Jones DTW, Radbruch A, Muschelli J, Unterberg A, Debus J, Schlemmer HP, Herold-Mende C, Pfister S, von Deimling A, Wick W, Capper D, Maier-Hein KH, Bendszus M. Radiomic subtyping improves disease stratification beyond key molecular, clinical, and standard imaging characteristics in patients with glioblastoma. Neuro Oncol 2018; 20:848-857. [PMID: 29036412 PMCID: PMC5961168 DOI: 10.1093/neuonc/nox188] [Citation(s) in RCA: 157] [Impact Index Per Article: 22.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
Background The purpose of this study was to analyze the potential of radiomics for disease stratification beyond key molecular, clinical, and standard imaging features in patients with glioblastoma. Methods Quantitative imaging features (n = 1043) were extracted from the multiparametric MRI of 181 patients with newly diagnosed glioblastoma prior to standard-of-care treatment (allocated to a discovery and a validation set, 2:1 ratio). A subset of 386/1043 features were identified as reproducible (in an independent MRI test-retest cohort) and selected for analysis. A penalized Cox model with 10-fold cross-validation (Coxnet) was fitted on the discovery set to construct a radiomic signature for predicting progression-free and overall survival (PFS and OS). The incremental value of a radiomic signature beyond molecular (O6-methylguanine-DNA methyltransferase [MGMT] promoter methylation, DNA methylation subgroups), clinical (patient's age, KPS, extent of resection, adjuvant treatment), and standard imaging parameters (tumor volumes) for stratifying PFS and OS was assessed with multivariate Cox models (performance quantified with prediction error curves). Results The radiomic signature (constructed from 8/386 features identified through Coxnet) increased the prediction accuracy for PFS and OS (in both discovery and validation sets) beyond the assessed molecular, clinical, and standard imaging parameters (P ≤ 0.01). Prediction errors decreased by 36% for PFS and 37% for OS when adding the radiomic signature (compared with 29% and 27%, respectively, with molecular + clinical features alone). The radiomic signature was-along with MGMT status-the only parameter with independent significance on multivariate analysis (P ≤ 0.01). Conclusions Our study stresses the role of integrating radiomics into a multilayer decision framework with key molecular and clinical features to improve disease stratification and to potentially advance personalized treatment of patients with glioblastoma.
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Affiliation(s)
- Philipp Kickingereder
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Ulf Neuberger
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - David Bonekamp
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany
| | - Paula L Piechotta
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Michael Götz
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Antje Wick
- Neurology Clinic, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Martin Sill
- Division of Biostatistics, German Cancer Research Center, Heidelberg, Germany
| | - Annekathrin Kratz
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany
- German Cancer Consortium, Clinical Cooperation Unit Neuropathology, German Cancer Research Center, Heidelberg, Germany
| | - Russell T Shinohara
- Department of Biostatistics, Epidemiology, and Informatics, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David T W Jones
- Division of Pediatric Neurooncology, German Cancer Research Center, Heidelberg, Germany
- German Cancer Consortium Core Center Heidelberg, Heidelberg, Germany
| | - Alexander Radbruch
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
- Department of Radiology, German Cancer Research Center, Heidelberg, Germany
| | - John Muschelli
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Andreas Unterberg
- Department of Neurosurgery, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Jürgen Debus
- Department of Radiation Oncology, University of Heidelberg Medical Center, Heidelberg Institute of Radiation Oncology and National Center for Radiation Research in Oncology, Heidelberg, Germany
- Molecular and Translational Radiation Oncology, National Center for Tumor Diseases, Heidelberg University Hospital and German Cancer Research Center, Heidelberg, Germany
| | | | | | - Stefan Pfister
- Division of Pediatric Neurooncology, German Cancer Research Center, Heidelberg, Germany
- German Cancer Consortium Core Center Heidelberg, Heidelberg, Germany
- Department of Pediatric Oncology, Hematology, and Immunology, Heidelberg University Hospital, Heidelberg, Germany
| | - Andreas von Deimling
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany
- German Cancer Consortium, Clinical Cooperation Unit Neuropathology, German Cancer Research Center, Heidelberg, Germany
| | - Wolfgang Wick
- Neurology Clinic, University of Heidelberg Medical Center, Heidelberg, Germany
- Clinical Cooperation Unit Neurooncology, German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
| | - David Capper
- Department of Neuropathology, University of Heidelberg Medical Center, Heidelberg, Germany
- German Cancer Consortium, Clinical Cooperation Unit Neuropathology, German Cancer Research Center, Heidelberg, Germany
- Charité – Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Institute for Neuropathology, Berlin, Germany
| | - Klaus H Maier-Hein
- Division of Medical Image Computing, German Cancer Research Center, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
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27
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Stadlbauer A, Mouridsen K, Doerfler A, Bo Hansen M, Oberndorfer S, Zimmermann M, Buchfelder M, Heinz G, Roessler K. Recurrence of glioblastoma is associated with elevated microvascular transit time heterogeneity and increased hypoxia. J Cereb Blood Flow Metab 2018; 38:422-432. [PMID: 28273720 PMCID: PMC5851132 DOI: 10.1177/0271678x17694905] [Citation(s) in RCA: 30] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Dynamic susceptibility contrast (DSC) perfusion MRI provide information about differences in macro- and microvasculature when executed with gradient-echo (GE; sensitive to macrovasculature) and spin-echo (SE; sensitive to microvasculature) contrast. This study investigated whether there are differences between macro- and microvascular transit time heterogeneity (MVTH and µVTH) and tissue oxygen tension (PO2mit) in newly-diagnosed and recurrent glioblastoma. Fifty-seven patients with glioblastoma (25 newly-diagnosed/32 recurrent) were examined with GE- and SE-DSC perfusion sequences, and a quantitative blood-oxygen-level-dependent (qBOLD) approach. Maps of MVTH, µVTH and coefficient of variation (MCOV and µCOV) were calculated from GE- and SE-DSC data, respectively, using an extended flow-diffusion equation. PO2mit maps were calculated from qBOLD data. Newly-diagnosed and recurrent glioblastoma showed significantly lower ( P ≤ 0.001) µCOV values compared to both normal brain and macrovasculature (MCOV) of the lesions. Recurrent glioblastoma had significantly higher µVTH ( P = 0.014) and µCOV ( P = 0.039) as well as significantly lower PO2mit values ( P = 0.008) compared to newly-diagnosed glioblastoma. The macrovasculature, however, showed no significant differences. Our findings provide evidence of microvascular adaption in the disorganized tumor vasculature for retaining the metabolic demands in stress response of therapeutically-uncontrolled glioblastomas. Thus, µVTH and PO2mit mapping gives insight into the tumor microenvironment (vascular and hypoxic niches) responsible for therapy resistance.
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Affiliation(s)
- Andreas Stadlbauer
- 1 Department of Neurosurgery, University of Erlangen-Nürnberg, Erlangen, Germany.,2 Institute of Medical Radiology, University Clinic of St. Pölten, St. Pölten, Austria
| | - Kim Mouridsen
- 3 Center of Functionally Integrative Neuroscience and MIND Lab, Institute of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Arnd Doerfler
- 4 Department of Neuroradiology, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Mikkel Bo Hansen
- 3 Center of Functionally Integrative Neuroscience and MIND Lab, Institute of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Stefan Oberndorfer
- 5 Department of Neurology, University Clinic of St. Pölten, St. Pölten, Austria
| | - Max Zimmermann
- 1 Department of Neurosurgery, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Michael Buchfelder
- 1 Department of Neurosurgery, University of Erlangen-Nürnberg, Erlangen, Germany
| | - Gertraud Heinz
- 2 Institute of Medical Radiology, University Clinic of St. Pölten, St. Pölten, Austria
| | - Karl Roessler
- 1 Department of Neurosurgery, University of Erlangen-Nürnberg, Erlangen, Germany
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28
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Vessel radius mapping in an extended model of transverse relaxation. MAGNETIC RESONANCE MATERIALS IN PHYSICS BIOLOGY AND MEDICINE 2018; 31:531-551. [DOI: 10.1007/s10334-018-0677-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/18/2017] [Revised: 01/14/2018] [Accepted: 01/15/2018] [Indexed: 10/18/2022]
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29
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Kubíková T, Kochová P, Tomášek P, Witter K, Tonar Z. Numerical and length densities of microvessels in the human brain: Correlation with preferential orientation of microvessels in the cerebral cortex, subcortical grey matter and white matter, pons and cerebellum. J Chem Neuroanat 2017; 88:22-32. [PMID: 29113946 DOI: 10.1016/j.jchemneu.2017.11.005] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2017] [Revised: 11/03/2017] [Accepted: 11/03/2017] [Indexed: 12/19/2022]
Abstract
To provide basic data on the local differences in density of microvessels between various parts of the human brain, including representative grey and white matter structures of the cerebral hemispheres, the brain stem and the cerebellum, we quantified the numerical density NV and the length density LV of microvessels in two human brains. We aimed to correlate the density of microvessels with previously published data on their preferential orientation (anisotropy). Microvessels were identified using immunohistochemistry for laminin in 32 samples harvested from the following brain regions of two adult individuals: the cortex of the telencephalon supplied by the anterior, middle, and posterior cerebral artery; the basal ganglia (putamen and globus pallidus); the thalamus; the subcortical white matter of the telencephalon; the internal capsule; the pons; the cerebellar cortex; and the cerebellar white matter. NV was calculated from the number of vascular branching points and their valence, which were assessed using the optical disector in 20-μm-thick sections. LV was estimated using counting frames applied to routine sections with randomized cutting planes. After correction for shrinkage, NV in the cerebral cortex was 1311±326mm-3 (mean±SD) and LV was 255±119mm-2. Similarly, in subcortical grey matter (which included the basal ganglia and thalamus), NV was 1350±445mm-3 and LV was 328±117mm-2. The vascular networks of cortical and subcortical grey matter were comparable. Their densities were greater than in the white matter, with NV=222±147mm-3 and LV=160±96mm-2. NV was moderately correlated with LV. In parts of brain with greater NV, blood vessels lacked a preferential orientation. Our data were in agreement with other studies on microvessel density focused on specific brain regions, but showed a greater variability, thus mapping the basic differences among various parts of brain. To facilitate the planning of other studies on brain vascularity and to support the development of computational models of human brain circulation based on real microvascular morphology; stereological data in form of continuous variables are made available as supplements.
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Affiliation(s)
- Tereza Kubíková
- NTIS, European Centre of Excellence, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Pilsen, Czech Republic
| | - Petra Kochová
- NTIS, European Centre of Excellence, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Pilsen, Czech Republic
| | - Petr Tomášek
- NTIS, European Centre of Excellence, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Pilsen, Czech Republic; Department of Histology and Embryology, Faculty of Medicine in Pilsen, Charles University, Karlovarska 48, 301 66 Pilsen, Czech Republic; Department of Forensic Medicine, Second Faculty of Medicine, Charles University, Budinova 2, 180 81 Prague 8, Prague, Czech Republic
| | - Kirsti Witter
- Institute of Anatomy, Histology and Embryology, Department of Pathobiology, University of Veterinary Medicine Vienna, Veterinärplatz 1, A-1210 Vienna, Austria
| | - Zbyněk Tonar
- NTIS, European Centre of Excellence, Faculty of Applied Sciences, University of West Bohemia, Univerzitni 8, 306 14 Pilsen, Czech Republic.
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30
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Qin Y, Takahashi M, Sheets K, Soto H, Tsui J, Pelargos P, Antonios JP, Kasahara N, Yang I, Prins RM, Braun J, Gordon LK, Wadehra M. Epithelial membrane protein-2 (EMP2) promotes angiogenesis in glioblastoma multiforme. J Neurooncol 2017; 134:29-40. [PMID: 28597184 DOI: 10.1007/s11060-017-2507-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2016] [Accepted: 05/21/2017] [Indexed: 12/27/2022]
Abstract
Glioblastoma multiforme (GBM) is the most aggressive malignant brain tumor and is associated with an extremely poor clinical prognosis. One pathologic hallmark of GBM is excessive vascularization with abnormal blood vessels. Extensive investigation of anti-angiogenic therapy as a treatment for recurrent GBM has been performed. Bevacizumab, a monoclonal anti-vascular endothelial growth factor A (VEGF-A), suggests a progression-free survival benefit but no overall survival benefit. Developing novel anti-angiogenic therapies are urgently needed in controlling GBM growth. In this study, we demonstrate tumor expression of epithelial membrane protein-2 (EMP2) promotes angiogenesis both in vitro and in vivo using cell lines from human GBM. Mechanistically, this pro-angiogenic effect of EMP2 was partially through upregulating tumor VEGF-A levels. A potential therapeutic effect of a systemic administration of anti-EMP2 IgG1 on intracranial xenografts was observed resulting in both significant reduction of tumor load and decreased tumor vasculature. These results suggest the potential for anti-EMP2 IgG1 as a promising novel anti-angiogenic therapy for GBM. Further investigation is needed to fully understand the molecular mechanisms how EMP2 modulates GBM pathogenesis and progression and to further characterize anti-EMP2 therapy in GBM.
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Affiliation(s)
- Yu Qin
- Department of Ophthalmology, Stein Eye Institute, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA
| | | | - Kristopher Sheets
- Department of Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA
| | - Horacio Soto
- Department of Neurosurgery, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA
| | - Jessica Tsui
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA
| | - Panayiotis Pelargos
- Department of Neurosurgery, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA
| | - Joseph P Antonios
- Department of Neurosurgery, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA
| | - Noriyuki Kasahara
- Department of Cell Biology and Pathology, University of Miami, Miami, FL, 33136, USA
| | - Isaac Yang
- Department of Neurosurgery, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA.,Department of Radiation Oncology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA.,Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA
| | - Robert M Prins
- Department of Neurosurgery, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA.,Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA.,Department of Molecular and Medical Pharmacology, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA
| | - Jonathan Braun
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA.,Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA
| | - Lynn K Gordon
- Department of Ophthalmology, Stein Eye Institute, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA.,Department of Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA
| | - Madhuri Wadehra
- Department of Pathology and Laboratory Medicine, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA. .,Jonsson Comprehensive Cancer Center, David Geffen School of Medicine, University of California-Los Angeles, Los Angeles, CA, 90095, USA.
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31
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Kickingereder P, Götz M, Muschelli J, Wick A, Neuberger U, Shinohara RT, Sill M, Nowosielski M, Schlemmer HP, Radbruch A, Wick W, Bendszus M, Maier-Hein KH, Bonekamp D. Large-scale Radiomic Profiling of Recurrent Glioblastoma Identifies an Imaging Predictor for Stratifying Anti-Angiogenic Treatment Response. Clin Cancer Res 2016; 22:5765-5771. [PMID: 27803067 DOI: 10.1158/1078-0432.ccr-16-0702] [Citation(s) in RCA: 199] [Impact Index Per Article: 22.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2016] [Revised: 06/23/2016] [Accepted: 07/07/2016] [Indexed: 01/03/2023]
Abstract
PURPOSE Antiangiogenic treatment with bevacizumab, a mAb to the VEGF, is the single most widely used therapeutic agent for patients with recurrent glioblastoma. A major challenge is that there are currently no validated biomarkers that can predict treatment outcome. Here we analyze the potential of radiomics, an emerging field of research that aims to utilize the full potential of medical imaging. EXPERIMENTAL DESIGN A total of 4,842 quantitative MRI features were automatically extracted and analyzed from the multiparametric tumor of 172 patients (allocated to a discovery and validation set with a 2:1 ratio) with recurrent glioblastoma prior to bevacizumab treatment. Leveraging a high-throughput approach, radiomic features of patients in the discovery set were subjected to a supervised principal component (superpc) analysis to generate a prediction model for stratifying treatment outcome to antiangiogenic therapy by means of both progression-free and overall survival (PFS and OS). RESULTS The superpc predictor stratified patients in the discovery set into a low or high risk group for PFS (HR = 1.60; P = 0.017) and OS (HR = 2.14; P < 0.001) and was successfully validated for patients in the validation set (HR = 1.85, P = 0.030 for PFS; HR = 2.60, P = 0.001 for OS). CONCLUSIONS Our radiomic-based superpc signature emerges as a putative imaging biomarker for the identification of patients who may derive the most benefit from antiangiogenic therapy, advances the knowledge in the noninvasive characterization of brain tumors, and stresses the role of radiomics as a novel tool for improving decision support in cancer treatment at low cost. Clin Cancer Res; 22(23); 5765-71. ©2016 AACR.
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Affiliation(s)
- Philipp Kickingereder
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Michael Götz
- Medical Image Computing, Division Medical and Biological Informatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - John Muschelli
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Antje Wick
- Neurology Clinic, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Ulf Neuberger
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Russell T Shinohara
- Department of Biostatistics and Epidemiology, Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Martin Sill
- Division of Biostatistics, DKFZ, Heidelberg, Germany
| | - Martha Nowosielski
- Department of Neurology, The Medical University of Innsbruck, Innsbruck, Austria
| | | | - Alexander Radbruch
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany.,Department of Radiology, DKFZ, Heidelberg, Germany
| | - Wolfgang Wick
- Neurology Clinic, University of Heidelberg Medical Center, Heidelberg, Germany.,Clinical Cooperation Unit Neurooncology, German Cancer Consortium (DKTK), DKFZ, Heidelberg, Germany
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany
| | - Klaus H Maier-Hein
- Medical Image Computing, Division Medical and Biological Informatics, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - David Bonekamp
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany.,Department of Radiology, DKFZ, Heidelberg, Germany
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32
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Burth S, Kickingereder P, Eidel O, Tichy D, Bonekamp D, Weberling L, Wick A, Löw S, Hertenstein A, Nowosielski M, Schlemmer HP, Wick W, Bendszus M, Radbruch A. Clinical parameters outweigh diffusion- and perfusion-derived MRI parameters in predicting survival in newly diagnosed glioblastoma. Neuro Oncol 2016; 18:1673-1679. [PMID: 27298312 DOI: 10.1093/neuonc/now122] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2016] [Accepted: 05/03/2016] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND The purpose of this study was to determine the relevance of clinical data, apparent diffusion coefficient (ADC), and relative cerebral blood volume (rCBV) from dynamic susceptibility contrast (DSC) perfusion and the volume transfer constant (ktrans) from dynamic contrast-enhanced (DCE) perfusion for predicting overall survival (OS) and progression-free survival (PFS) in newly diagnosed treatment-naïve glioblastoma patients. METHODS Preoperative MR scans including standardized contrast-enhanced T1 (cT1), T2 - fluid-attenuated inversion recovery (FLAIR), ADC, DSC, and DCE of 125 patients with subsequent histopathologically confirmed glioblastoma were performed on a 3 Tesla MRI scanner. ADC, DSC, and DCE parameters were analyzed in semiautomatically segmented tumor volumes on contrast-enhanced (CE) cT1 and hyperintense signal changes on T2 FLAIR (ED). Univariate and multivariable Cox regression analyses including age, sex, extent of resection (EOR), and KPS were performed to assess the influence of each parameter on OS and PFS. RESULTS Univariate Cox regression analysis demonstrated a significant association of age, KPS, and EOR with PFS and age, KPS, EOR, lower ADC, and higher rCBV with OS. Multivariable analysis showed independent significance of male sex, KPS, EOR, and increased rCBVCE for PFS, and age, sex, KPS, and EOR for OS. CONCLUSIONS MRI parameters help to predict OS in a univariate Cox regression analysis, and increased rCBVCE is associated with shorter PFS in the multivariable model. In summary, however, our findings suggest that the relevance of MRI parameters is outperformed by clinical parameters in a multivariable analysis, which limits their prognostic value for survival prediction at the time of initial diagnosis.
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Affiliation(s)
- Sina Burth
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Philipp Kickingereder
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Oliver Eidel
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Diana Tichy
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - David Bonekamp
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Lukas Weberling
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Antje Wick
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Sarah Löw
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Anne Hertenstein
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Martha Nowosielski
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Heinz-Peter Schlemmer
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Wolfgang Wick
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Martin Bendszus
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
| | - Alexander Radbruch
- Department of Neuroradiology, University of Heidelberg Medical Center, Heidelberg, Germany (S.B., P.K., O.E., D.B., L.W., M.B., A.R.); Division of Bioststatistics, German Cancer Research Center, Heidelberg, Germany (D.T.); Department of Neurology, University of Heidelberg Medical Center, Heidelberg, Germany (A.W., S.L., A.H., W.W.); Department of Neurology, Innsbruck Medical University, Innsbruck, Austria (M.N.); Department of Radiology, German Cancer Research Center, Heidelberg, Germany (H.S.)
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