Characterizing hypoxia in human glioma: A simultaneous multimodal MRI and PET study

Abstract

Hypoxia plays an important role for the prognosis and therapy response of cancer. Thus, hypoxia imaging would be a valuable tool for pre-therapeutic assessment of tumor malignancy. However, there is no standard validated technique for clinical application available yet. Therefore, we performed a study in 12 patients with high-grade glioma, where we directly compared the two currently most promising techniques, namely the MR-based relative oxygen extraction fraction (MR-rOEF) and the PET hypoxia marker H-1-(3-[ F]-fluoro-2-hydroxypropyl)-2-nitroimidazole ([ F]-FMISO). MR-rOEF was determined from separate measurements of T , T * and relative cerebral blood volume (rCBV) employing a multi-parametric approach for quantification of the blood-oxygenation-level-dependent (BOLD) effect. With respect to [ F]-FMISO-PET, besides the commonly used late uptake between 120 and 130 min ([ F]-FMISO ), we also analyzed the hypoxia specific uptake rate [ F]-FMISO-k , as obtained by pharmacokinetic modeling of dynamic uptake data. Since pharmacokinetic modeling of partially acquired dynamic [ F]-FMISO data was sensitive to a low signal-to-noise-ratio, analysis was restricted to high-uptake tumor regions. Individual spatial analyses of deoxygenation and hypoxia-related parameter maps revealed that high MR-rOEF values clustered in (edematous) peritumoral tissue, while areas with high [ F]-FMISO concentrated in and around active tumor with disrupted blood-brain barrier, i.e. contrast enhancement in T -weighted MRI. Volume-of-interest-based correlations between MR-rOEF and [ F]-FMISO as well as [ F]-FMISO-k , and voxel-wise analyses in individual patients, yielded limited correlations, supporting the notion that [ F]-FMISO uptake, even after 2 h, might still be influenced by perfusion while [ F]-FMISO-k was severely hampered by noise. According to these results, vascular deoxygenation, as measured by MR-rOEF, and severe tissue hypoxia, as measured by [ F]-FMISO, show a poor spatial correspondence. Overall, the two methods appear to rather provide complementary than redundant information about high-grade glioma biology.

MRI Assessment of Oxygen Metabolism and Hemodynamic Status in Symptomatic Intracranial Atherosclerotic Stenosis: A Pilot Study

“…Since it requires no gas inhalation challenge, it presents the advantage to be implementable in clinical practice where it has the potential to accurately predict ischemic core with StO 2 mapping . However, mqBOLD has been poorly compared with reference standard positron emission tomography (PET) techniques and does not map oxygen extraction fraction as quantitative susceptibility mapping techniques …”

The wavelet power spectrum of perfusion weighted MRI correlates with tumor vascularity in biopsy-proven glioblastoma samples

“…All subjects gave their informed written consent to targeted biopsies during neurosurgical GBM resection as part of an earlier study at our maximum care university hospital site. Data from this cohort got previously published in a different study [8]. The study was approved by the ethics commission of the Technical University of Munich and conducted in accordance with the ethical standards of the 1964 Declaration of Helsinki and its later amendments.…”

“…As described previously [8], VOIs were defined prospectively in consensus with the operating neurosurgeon on the T1w MPRAGE and T2w FLAIR sequences (Fig 2). Each biopsy location was marked with a round VOI of 5 mm diameter.…”

“…Immunohistochemistry was performed using a fully automated staining system (Ventana BenchMark ULTRA; Ventana Medical Systems; Tucson; USA) as described previously [8]. After heat-induced epitope unmasking in pH 8.4 buffer at 95˚C for 32 minutes, the samples were incubated with peroxidase and afterwards charged with anti-Ki67 (monoclonal, mouse; Clone JC70A, dilution 1:50; DakoCytomation Denmark A7S, Denmark) or anti-CD31 (polyclonal, rabbit, dilution 1:100; Thermo Fischer Scientific, USA) antibodies, respectively.…”

Using an artificial neural network for fast mapping of the oxygen extraction fraction with combined QSM and quantitative BOLD

“…Knowledge of tissue oxygenation parameters such as the oxygen extraction fraction (OEF) is valuable in the diseased brain for both treatment planning and assessment because these are proven biomarkers for tissue vitality and viability. 1,2 However, despite the fact that quantification of brain oxygenation using MRI has been extensively studied over the years and successfully applied to stroke, 3,4 carotid artery stenosis, 5 and brain tumors, [6][7][8] for example, thus far no approach has found its way into clinical routine. Many methods require a high SNR [9][10][11] or vascular challenge, 12,13 are prone to biases due to several independent measurements, 14 or are limited to larger vessels.…”