Higher cerebral metabolic rate of oxygen derived from dynamic susceptibility contrast MRI is an independent predictor of poor survival in IDH-wildtype glioblastoma

Price M et al (2024) CBTRUS statistical report: primary brain and other central nervous system tumors diagnosed in the United States in 2017–2021. Neuro Oncol 26:vi1–vi85. https://doi.org/10.1093/neuonc/noae145

Article  PubMed  PubMed Central  Google Scholar 

Weller M et al (2021) EANO guidelines on the diagnosis and treatment of diffuse gliomas of adulthood. Nat Rev Clin Oncol 18:170–186. https://doi.org/10.1038/s41571-020-00447-z

Article  PubMed  Google Scholar 

Stupp R et al (2009) Effects of radiotherapy with concomitant and adjuvant temozolomide versus radiotherapy alone on survival in glioblastoma in a randomised phase III study: 5-year analysis of the EORTC-NCIC trial. Lancet Oncol 10:459–466. https://doi.org/10.1016/s1470-2045(09)70025-7

Article  CAS  PubMed  Google Scholar 

Park YW et al (2024) Incorporating supramaximal resection into survival stratification of IDH-wildtype glioblastoma: a refined multi-institutional recursive partitioning analysis. Clin Cancer Res 30:4866–4875. https://doi.org/10.1158/1078-0432.Ccr-23-3845

Article  CAS  PubMed  PubMed Central  Google Scholar 

Brancato V et al (2020) Predicting survival in glioblastoma patients using diffusion MR imaging metrics—a systematic review. Cancers (Basel). https://doi.org/10.3390/cancers12102858

Article  PubMed  PubMed Central  Google Scholar 

Bae S et al (2018) Radiomic MRI phenotyping of glioblastoma: improving survival prediction. Radiology 289:797–806. https://doi.org/10.1148/radiol.2018180200

Article  PubMed  Google Scholar 

Burth S et al (2016) Clinical parameters outweigh diffusion- and perfusion-derived MRI parameters in predicting survival in newly diagnosed glioblastoma. Neuro-oncology 18:1673–1679. https://doi.org/10.1093/neuonc/now122

Article  PubMed  PubMed Central  Google Scholar 

Romano A et al (2018) Prediction of survival in patients affected by glioblastoma: histogram analysis of perfusion MRI. J Neurooncol 139:455–460. https://doi.org/10.1007/s11060-018-2887-4

Article  CAS  PubMed  Google Scholar 

Kaur B et al (2005) Hypoxia and the hypoxia-inducible-factor pathway in glioma growth and angiogenesis. Neuro-oncology 7:134–153. https://doi.org/10.1215/s1152851704001115

Article  CAS  PubMed  PubMed Central  Google Scholar 

Louis DN et al (2021) The 2021 WHO classification of tumors of the central nervous system: a summary. Neuro Oncol 23:1231–1251. https://doi.org/10.1093/neuonc/noab106

Article  CAS  PubMed  PubMed Central  Google Scholar 

Steinbach JP, Wolburg H, Klumpp A, Probst H, Weller M (2003) Hypoxia-induced cell death in human malignant glioma cells: energy deprivation promotes decoupling of mitochondrial cytochrome c release from caspase processing and necrotic cell death. Cell Death Differ 10:823–832. https://doi.org/10.1038/sj.cdd.4401252

Article  CAS  PubMed  Google Scholar 

Evans SM et al (2004) Hypoxia is important in the biology and aggression of human glial brain tumors. Clin Cancer Res 10:8177–8184. https://doi.org/10.1158/1078-0432.Ccr-04-1081

Article  CAS  PubMed  Google Scholar 

Jespersen SN, Østergaard L (2012) The roles of cerebral blood flow, capillary transit time heterogeneity, and oxygen tension in brain oxygenation and metabolism. J Cereb blood flow metabolism: official J Int Soc Cereb Blood Flow Metabolism 32:264–277. https://doi.org/10.1038/jcbfm.2011.153

Article  CAS  Google Scholar 

Østergaard L et al (2013) The role of the cerebral capillaries in acute ischemic stroke: the extended penumbra model. J Cereb blood flow metabolism: official J Int Soc Cereb Blood Flow Metabolism 33:635–648. https://doi.org/10.1038/jcbfm.2013.18

Article  Google Scholar 

Vollmuth P et al (2025) A radiologist’s guide to IDH-Wildtype glioblastoma for efficient communication with clinicians: Part I-essential information on preoperative and immediate postoperative imaging. Korean J Radiol 26:246–268. https://doi.org/10.3348/kjr.2024.0982

Article  PubMed  PubMed Central  Google Scholar 

Esteller M et al (2000) Inactivation of the DNA-repair gene MGMT and the clinical response of gliomas to alkylating agents. N Engl J Med 343:1350–1354. https://doi.org/10.1056/nejm200011093431901

Article  CAS  PubMed  Google Scholar 

Na K et al (2019) Targeted next-generation sequencing panel (TruSight Tumor 170) in diffuse glioma: a single institutional experience of 135 cases. J Neurooncol 142:445–454. https://doi.org/10.1007/s11060-019-03114-1

Article  CAS  PubMed  Google Scholar 

Mouridsen K, Hansen MB, Østergaard L, Jespersen SN (2014) Reliable estimation of capillary transit time distributions using DSC-MRI. J Cereb blood flow metabolism: official J Int Soc Cereb Blood Flow Metabolism 34:1511–1521. https://doi.org/10.1038/jcbfm.2014.111

Article  Google Scholar 

Crone C (1963) THE PERMEABILITY OF CAPILLARIES IN VARIOUS ORGANS AS DETERMINED BY USE OF THE “INDICATOR DIFFUSION” METHOD. Acta Physiol Scand 58:292–305. https://doi.org/10.1111/j.1748-1716.1963.tb02652.x

Article  CAS  PubMed  Google Scholar 

Meier P, Zierler KL (1954) On the theory of the indicator-dilution method for measurement of blood flow and volume. J Appl Physiol 6:731–744. https://doi.org/10.1152/jappl.1954.6.12.731

Article  CAS  PubMed  Google Scholar 

Karschnia P et al (2023) A framework for standardised tissue sampling and processing during resection of diffuse intracranial glioma: joint recommendations from four RANO groups. Lancet Oncol 24:e438–e450. https://doi.org/10.1016/s1470-2045(23)00453-9

Article  PubMed  PubMed Central  Google Scholar 

Karschnia P et al (2023) Prognostic validation of a new classification system for extent of resection in glioblastoma: a report of the RANO resect group. Neuro Oncol 25:940–954. https://doi.org/10.1093/neuonc/noac193

Article  CAS  PubMed  PubMed Central  Google Scholar 

Karschnia P et al (2024) Surgical management and outcome of newly diagnosed glioblastoma without contrast enhancement (low-grade appearance): a report of the RANO resect group. Neuro Oncol 26:166–177. https://doi.org/10.1093/neuonc/noad160

Article  PubMed  PubMed Central  Google Scholar 

Kickingereder P et al (2019) Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study. Lancet Oncol 20:728–740. https://doi.org/10.1016/s1470-2045(19)30098-1

Article  PubMed  Google Scholar 

Park YW et al (2022) A fully automatic multiparametric radiomics model for differentiation of adult pilocytic astrocytomas from high-grade gliomas. Eur Radiol 32:4500–4509. https://doi.org/10.1007/s00330-022-08575-z

Article  CAS  PubMed  Google Scholar 

Stadlbauer A et al (2018) Intratumoral heterogeneity of oxygen metabolism and neovascularization uncovers 2 survival-relevant subgroups of IDH1 wild-type glioblastoma. Neuro-oncology 20:1536–1546. https://doi.org/10.1093/neuonc/noy066

Article  CAS  PubMed  PubMed Central  Google Scholar 

Stadlbauer A et al (2021) Tissue hypoxia and alterations in microvascular architecture predict glioblastoma recurrence in humans. Clin Cancer Res 27:1641–1649. https://doi.org/10.1158/1078-0432.Ccr-20-3580

Article  CAS  PubMed  Google Scholar 

Stadlbauer A et al (2020) Physiologic MR imaging of the tumor microenvironment revealed switching of metabolic phenotype upon recurrence of glioblastoma in humans. J Cereb blood flow metabolism: official J Int Soc Cereb Blood Flow Metabolism 40:528–538. https://doi.org/10.1177/0271678x19827885

Article  Google Scholar 

Bonekamp D et al (2017) Assessment of tumor oxygenation and its impact on treatment response in bevacizumab-treated recurrent glioblastoma. J Cereb blood flow metabolism: official J Int Soc Cereb Blood Flow Metabolism 37:485–494. https://doi.org/10.1177/0271678x16630322

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