Preoperative dynamic contrast-enhanced MRI correlates with molecular markers of hypoxia and vascularity in specific areas of intratumoral microenvironment and is predictive of patient outcome

Review of tracer kinetic models in evaluation of gliomas using dynamic contrast-enhanced imaging

Glioma is the most common type of primary malignant tumor of the central nervous system (CNS), and is characterized by high malignancy, high recurrence rate and poor survival. Conventional imaging techniques only provide information regarding the anatomical location, morphological characteristics, and enhancement patterns. In contrast, advanced imaging techniques such as dynamic contrast-enhanced (DCE) MRI or DCE CT can reflect tissue microcirculation, including tumor vascular hyperplasia and vessel permeability. Although several studies have used DCE imaging to evaluate gliomas, the results of data analysis using conventional tracer kinetic models (TKMs) such as Tofts or extended-Tofts model (ETM) have been ambiguous. More advanced models such as Brix's conventional two-compartment model (Brix), tissue homogeneity model (TH) and distributed parameter (DP) model have been developed, but their application in clinical trials has been limited. This review attempts to appraise issues on glioma studies using conventional TKMs, such as Tofts or ETM model, highlight advancement of DCE imaging techniques and provides insights on the clinical value of glioma management using more advanced TKMs.

Understanding the Significance of Hypoxia-Inducible Factors (HIFs) in Glioblastoma: A Systematic Review

BACKGROUND

The study aims to investigate the role of hypoxia-inducible factors (HIFs) in the development, progression, and therapeutic potential of glioblastomas.

METHODOLOGY

The study, following PRISMA guidelines, systematically examined hypoxia and HIFs in glioblastoma using MEDLINE (PubMed), Web of Science, and Scopus. A total of 104 relevant studies underwent data extraction.

RESULTS

Among the 104 studies, global contributions were diverse, with China leading at 23.1%. The most productive year was 2019, accounting for 11.5%. Hypoxia-inducible factor 1 alpha (HIF1α) was frequently studied, followed by hypoxia-inducible factor 2 alpha (HIF2α), osteopontin, and cavolin-1. Commonly associated factors and pathways include glucose transporter 1 (GLUT1) and glucose transporter 3 (GLUT3) receptors, vascular endothelial growth factor (VEGF), phosphoinositide 3-kinase (PI3K)-Akt-mechanistic target of rapamycin (mTOR) pathway, and reactive oxygen species (ROS). HIF expression correlates with various glioblastoma hallmarks, including progression, survival, neovascularization, glucose metabolism, migration, and invasion.

CONCLUSION

Overcoming challenges such as treatment resistance and the absence of biomarkers is critical for the effective integration of HIF-related therapies into the treatment of glioblastoma with the aim of optimizing patient outcomes.

Advances in determining the gross tumor target volume for radiotherapy of brain metastases

Brain metastases (BMs) are the most prevalent intracranial malignant tumors in adults and are the leading cause of mortality attributed to malignant brain diseases. Radiotherapy (RT) plays a critical role in the treatment of BMs, with local RT techniques such as stereotactic radiosurgery (SRS)/stereotactic body radiotherapy (SBRT) showing remarkable therapeutic effectiveness. The precise determination of gross tumor target volume (GTV) is crucial for ensuring the effectiveness of SRS/SBRT. Multimodal imaging techniques such as CT, MRI, and PET are extensively used for the diagnosis of BMs and GTV determination. With the development of functional imaging and artificial intelligence (AI) technology, there are more innovative ways to determine GTV for BMs, which significantly improve the accuracy and efficiency of the determination. This article provides an overview of the progress in GTV determination for RT in BMs.

Unlocking Bevacizumab's Potential: rCBVmax as a Predictive Biomarker for Enhanced Survival in Glioblastoma IDH-Wildtype Patients

BACKGROUND

Aberrant vascular architecture and angiogenesis are hallmarks of glioblastoma IDH-wildtype, suggesting that these tumors are suitable for antiangiogenic therapy. Bevacizumab was FDA-approved in 2009 following promising results in two clinical trials. However, its use for recurrent glioblastomas remains a subject of debate, as it does not universally improve patient survival.

PURPOSES

In this study, we aimed to analyze the influence of tumor vascularity on the benefit provided by BVZ and propose preoperative rCBVmax at the high angiogenic tumor habitat as a predictive biomarker to select patients who can benefit the most.

METHODS

Clinical and MRI data from 106 patients with glioblastoma IDH-wildtype have been analyzed. Thirty-nine of them received BVZ, and the remaining sixty-seven did not receive a second-line treatment. The ONCOhabitats method was used to automatically calculate rCBV.

RESULTS

We found a median survival from progression of 305 days longer for patients with moderate vascular tumors who received BVZ than those who did not receive any second-line treatment. This contrasts with patients with high-vascular tumors who only presented a median survival of 173 days longer when receiving BVZ. Furthermore, better responses to BVZ were found for the moderate-vascular group with a higher proportion of patients alive at 6, 12, 18, and 24 months after progression.

CONCLUSIONS

We propose rCBVmax as a potential biomarker to select patients who can benefit more from BVZ after tumor progression. In addition, we propose a threshold of 7.5 to stratify patients into moderate- and high-vascular groups to select the optimal second-line treatment.

Current Knowledge about the Peritumoral Microenvironment in Glioblastoma

Glioblastoma is a deadly disease, with a mean overall survival of less than 2 years from diagnosis. Recurrence after gross total surgical resection and adjuvant chemo-radiotherapy almost invariably occurs within the so-called peritumoral brain zone (PBZ). The aim of this narrative review is to summarize the most relevant findings about the biological characteristics of the PBZ currently available in the medical literature. The PBZ presents several peculiar biological characteristics. The cellular landscape of this area is different from that of healthy brain tissue and is characterized by a mixture of cell types, including tumor cells (seen in about 30% of cases), angiogenesis-related endothelial cells, reactive astrocytes, glioma-associated microglia/macrophages (GAMs) with anti-inflammatory polarization, tumor-infiltrating lymphocytes (TILs) with an "exhausted" phenotype, and glioma-associated stromal cells (GASCs). From a genomic and transcriptomic point of view, compared with the tumor core and healthy brain tissue, the PBZ presents a "half-way" pattern with upregulation of genes related to angiogenesis, the extracellular matrix, and cellular senescence and with stemness features and downregulation in tumor suppressor genes. This review illustrates that the PBZ is a transition zone with a pre-malignant microenvironment that constitutes the base for GBM progression/recurrence. Understanding of the PBZ could be relevant to developing more effective treatments to prevent GBM development and recurrence.

Glioblastoma modeling with 3D organoids: progress and challenges

Glioblastoma (GBM) is the most aggressive adult primary brain tumor with nearly universal treatment resistance and recurrence. The mainstay of therapy remains maximal safe surgical resection followed by concurrent radiation therapy and temozolomide chemotherapy. Despite intensive investigation, alternative treatment options, such as immunotherapy or targeted molecular therapy, have yielded limited success to achieve long-term remission. This difficulty is partly due to the lack of pre-clinical models that fully recapitulate the intratumoral and intertumoral heterogeneity of GBM and the complex tumor microenvironment. Recently, GBM 3D organoids originating from resected patient tumors, genetic manipulation of induced pluripotent stem cell (iPSC)-derived brain organoids and bio-printing or fusion with non-malignant tissues have emerged as novel culture systems to portray the biology of GBM. Here, we highlight several methodologies for generating GBM organoids and discuss insights gained using such organoid models compared to classic modeling approaches using cell lines and xenografts. We also outline limitations of current GBM 3D organoids, most notably the difficulty retaining the tumor microenvironment, and discuss current efforts for improvements. Finally, we propose potential applications of organoid models for a deeper mechanistic understanding of GBM and therapeutic development.

T cell exhaustion in malignant gliomas

Despite advances in understanding tumor biology, malignant gliomas remain incurable. While immunotherapy has improved outcomes in other cancer types, comparable efficacy has not yet been demonstrated for primary cancers of the central nervous system (CNS). T cell exhaustion, defined as a progressive decrease in effector function, sustained expression of inhibitory receptors, metabolic dysfunction, and distinct epigenetic and transcriptional alterations, contributes to the failure of immunotherapy in the CNS. Herein, we describe recent advances in understanding the drivers of T cell exhaustion in the glioma microenvironment. We discuss the extrinsic and intrinsic factors that contribute to exhaustion and highlight potential avenues for reversing this phenotype. Our ability to directly target specific immunosuppressive drivers in brain cancers would be a major advance in immunotherapy.

Survival rate prediction of nasopharyngeal carcinoma patients based on MRI and gene expression using a deep neural network

To achieve a better treatment regimen and follow-up assessment design for intensity-modulated radiotherapy (IMRT)-treated nasopharyngeal carcinoma (NPC) patients, an accurate progression-free survival (PFS) time prediction algorithm is needed. We propose developing a PFS prediction model of NPC patients after IMRT treatment using a deep learning method and comparing that with the traditional texture analysis method. One hundred and fifty-one NPC patients were included in this retrospective study. T1-weighted, proton density and dynamic contrast-enhanced magnetic resonance (MR) images were acquired. The expression level of five genes (HIF-1α, EGFR, PTEN, Ki-67, and VEGF) and infection of Epstein-Barr (EB) virus were tested. A residual network was trained to predict PFS from MR images. The output as well as patient characteristics were combined using a linear regression model to provide a final PFS prediction. The prediction accuracy was compared with that of the traditional texture analysis method. A regression model combining the deep learning output with HIF-1α expression and Epstein-Barr infection provides the best PFS prediction accuracy (Spearman correlation R²  = 0.53; Harrell's C-index = 0.82; receiver operative curve [ROC] analysis area under the curve [AUC] = 0.88; log-rank test hazard ratio [HR] = 8.45), higher than a regression model combining texture analysis with HIF-1α expression (Spearman correlation R²  = 0.14; Harrell's C-index =0.68; ROC analysis AUC = 0.76; log-rank test HR = 2.85). The deep learning method does not require a manually drawn tumor region of interest. MR image processing using deep learning combined with patient characteristics can provide accurate PFS prediction for nasopharyngeal carcinoma patients and does not rely on specific kernels or tumor regions of interest, which is needed for the texture analysis method.

Whole-tumor histogram analysis of diffusion-weighted imaging and dynamic contrast-enhanced MRI for soft tissue sarcoma: correlation with HIF-1alpha expression

OBJECTIVE

To investigate the correlation of histogram metrics from diffusion-weighted imaging (DWI) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters with HIF-1alpha expression in soft tissue sarcoma (STS).

METHODS

We enrolled 71 patients with STS who underwent 3.0-T MRI, including conventional MRI, DWI, and DCE-MRI sequences. Location, maximum tumor diameter, envelope, T2-weighted tumor heterogeneity, peritumoral edema, peritumoral enhancement, necrosis, tail-like pattern, bone invasion, and vessel/nerve invasion and/or encasement were determined using conventional MRI images. The whole-tumor histogram metrics were calculated on the apparent diffusion coefficient (ADC), K^trans, K_ep, and V_e maps. Independent-samples t test and one-way ANOVA were used for testing the differences between normally distributed categorical data with HIF-1alpha expression. Pearson and Spearman correlations and multiple linear regression analyses were performed to determine the correlations between histogram metrics and HIF-1alpha expression. Survival curves were plotted using the Kaplan-Meier method.

RESULTS

Regarding conventional MRI features, only highly heterogeneous on T2-weighted images (55.6 ± 19.9% vs. 45.4 ± 20.5%, p = 0.041) and more than 50% necrotic area (57.3 ± 20.4% vs. 43.9 ± 19.7%, p = 0.002) were prone to indicate STS with higher HIF-1alpha expression. Histogram metrics obtained from ADC (mean, median, 10th, and 25th percentile values), K^trans (mean, median, 75th, and 90th percentile values), and K_ep (90th percentile values) were significantly correlated with HIF-1alpha expression. Multiple linear regression analysis demonstrated that more than 50% necrosis, ADC_skewness, K^trans_90th, and grade III were independently associated with HIF-1alpha expression.

CONCLUSION

DWI and DCE-MRI histogram parameters were significantly correlated with HIF-1alpha expression in STS.

KEY POINTS

• DWI and DCE-MRI histogram parameters are correlated with HIF-1alpha expression in STS. • More than 50% necrosis, ADC_skewness, K^trans_90th, and grade III were independently associated with HIF-1alpha expression in STS.

Assessment of Early Response to Lung Cancer Chemotherapy by Semiquantitative Analysis of Dynamic Contrast-Enhanced MRI

Objective

To evaluate the early chemotherapy response in patients with lung cancer using semiquantitative analysis of dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI).

Methods

Twenty-two patients with lung cancer treated with chemotherapy were subjected to DCE-MRI at two time points: before starting treatment and after one week of therapy. The image data were collected by DCE-MRI, and the semiquantitative parameters including positive enhancement integral (PEI), signal enhancement ratio (SER), maximum slope of increase (MSI), and time to peak (TTP) were calculated. After chemotherapy, the parameters and relevant variations between the responders and nonresponders were compared with Mann–Whitney U tests. Student's t-test for paired samples was used to evaluate the temporal changes between pre- and posttreatment images.

Results

The patients were categorized as 13 responders and 9 nonresponders based on the tumor response evaluation. After chemotherapy, the PEI, SER, and MSI were significantly increased in responders compared with the pretreatment values (P < 0.05), while no obvious decrease in TTP was observed (P > 0.05). However, 9 nonresponders showed no significant changes in PEI, SER, MSI, and TTP values, as compared with those of pretreatment (P > 0.05). Moreover, the increase of PEI was more dramatically in responders than in nonresponders (P < 0.05), but no significantly differences were observed in SER, MSI, and TTP (P > 0.05).

Conclusion

Semiquantitative analysis of DCE-MRI could provide a reliable noninvasive method for assessing early chemotherapy response in lung cancer patients.

Exploratory Analysis of Serial 18F-fluciclovine PET-CT and Multiparametric MRI during Chemoradiation for Glioblastoma

Anti-1-amino-3-18fluorine-fluorocyclobutane-1-carboxylic acid (18F-fluciclovine) positron emission tomography (PET) shows preferential glioma uptake but there is little data on how uptake correlates with post-contrast T1-weighted (Gd-T1) and dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) activity during adjuvant treatment. This pilot study aimed to compare 18F-fluciclovine PET, DCE-MRI and Gd-T1 in patients undergoing chemoradiotherapy for glioblastoma (GBM), and in a parallel pre-clinical GBM model, to investigate correlation between 18F-fluciclovine uptake, MRI findings, and tumour biology. 18F-fluciclovine-PET-computed tomography (PET-CT) and MRI including DCE-MRI were acquired before, during and after adjuvant chemoradiotherapy (60 Gy in 30 fractions with temozolomide) in GBM patients. MRI volumes were manually contoured; PET volumes were defined using semi-automatic thresholding. The similarity of the PET and DCE-MRI volumes outside the Gd-T1 volume boundary was measured using the Dice similarity coefficient (DSC). CT-2A tumour-bearing mice underwent MRI and 18F-fluciclovine PET-CT. Post-mortem mice brains underwent immunohistochemistry staining for ASCT2 (amino acid transporter), nestin (stemness) and Ki-67 (proliferation) to assess for biologically active tumour. 6 patients were recruited (GBM 1-6) and grouped according to overall survival (OS)-short survival (GBM-SS, median OS 249 days) and long survival (GBM-LS, median 903 days). For GBM-SS, PET tumour volumes were greater than DCE-MRI, in turn greater than Gd-T1. For GBM-LS, Gd-T1 and DCE-MRI were greater than PET. Tumour-specific 18F-fluciclovine uptake on pre-clinical PET-CT corresponded to immunostaining for Ki-67, nestin and ASCT2. Results suggest volumes of 18F-fluciclovine-PET activity beyond that depicted by DCE-MRI and Gd-T1 are associated with poorer prognosis in patients undergoing chemoradiotherapy for GBM. The pre-clinical model confirmed 18F-fluciclovine uptake reflected biologically active tumour.

Hemodynamic Imaging in Cerebral Diffuse Glioma—Part B: Molecular Correlates, Treatment Effect Monitoring, Prognosis, and Future Directions

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.

GFAP splice variants fine-tune glioma cell invasion and tumour dynamics by modulating migration persistence

Glioma is the most common form of malignant primary brain tumours in adults. Their highly invasive nature makes the disease incurable to date, emphasizing the importance of better understanding the mechanisms driving glioma invasion. Glial fibrillary acidic protein (GFAP) is an intermediate filament protein that is characteristic for astrocyte- and neural stem cell-derived gliomas. Glioma malignancy is associated with changes in GFAP alternative splicing, as the canonical isoform GFAPα is downregulated in higher-grade tumours, leading to increased dominance of the GFAPδ isoform in the network. In this study, we used intravital imaging and an ex vivo brain slice invasion model. We show that the GFAPδ and GFAPα isoforms differentially regulate the tumour dynamics of glioma cells. Depletion of either isoform increases the migratory capacity of glioma cells. Remarkably, GFAPδ-depleted cells migrate randomly through the brain tissue, whereas GFAPα-depleted cells show a directionally persistent invasion into the brain parenchyma. This study shows that distinct compositions of the GFAPnetwork lead to specific migratory dynamics and behaviours of gliomas.

Multiple Faces of the Glioblastoma Microenvironment

The tumor microenvironment is a highly dynamic accumulation of resident and infiltrating tumor cells, responsible for growth and invasion. The authors focused on the leading-edge concepts regarding the glioblastoma microenvironment. Due to the fact that the modern trend in the research and treatment of glioblastoma is represented by multiple approaches that target not only the primary tumor but also the neighboring tissue, the study of the microenvironment in the peritumoral tissue is an appealing direction for current and future therapies.

GFAP Alternative Splicing and the Relevance for Disease – A Focus on Diffuse Gliomas

Glial fibrillary acidic protein (GFAP) is an intermediate filament protein that is characteristic for astrocytes and neural stem cells, and their malignant analogues in glioma. Since the discovery of the protein 50 years ago, multiple alternative splice variants of the GFAP gene have been discovered, leading to different GFAP isoforms. In this review, we will describe GFAP isoform expression from gene to protein to network, taking the canonical isoforms GFAPα and the main alternative variant GFAPδ as the starting point. We will discuss the relevance of studying GFAP and its isoforms in disease, with a specific focus on diffuse gliomas.

Pulmonary lesions: correlative study of dynamic triple-phase enhanced CT perfusion imaging with tumor angiogenesis and vascular endothelial growth factor expression

Background

To investigate value of the quantitative perfusion parameters of dynamic triple-phase enhanced CT in differential diagnosis of pulmonary lesions, and explore the correlation between perfusion parameters of lung cancer with microvessel density (MVD) and vascular endothelial growth factor (VEGF).

Methods

73 consecutive patients with lung lesions who successfully underwent pre-operative CT perfusion examination with dynamic triple-phase enhanced CT and received a final diagnosis by postoperative pathology or a clinical follow-up. The cases were divided into malignant and benign groups according to the pathological results. CT perfusion parameters, such as Median, Mean, Standard deviation (Std), Q10, Q25, Q50, Q75, Q90 of pulmonary artery perfusion (PAP), bronchial artery perfusion (BAP), perfusion index (PI) and arterial enhancement fraction (AEF) were obtained by performing computed tomography perfusion imaging (CTPI). Computed tomography perfusion (CTP) parameters were compared between malignant and benign lesions. The receiver operating characteristic (ROC) curve was used to assess the diagnostic efficiency of CTP parameters in diagnosing malignant lesions. The correlations between CTP parameters with MVD and VEGF were analysed in 36 lung cancer patients who had extra sections be used for immunohistochemistry staining of CD34 and VEGF.

Results

BAP (Mean, Std, Q90) and PI Std of benign lesions were higher than malignant lesions (p < 0.05), and PAP (Q10, Q25), PI (Median, Mean, Q10, Q25, Q50) of malignant lesions were higher than the benign (p < 0.05). The area under the ROC curve of PI Mean, PI Q10 and PI Std was 0.722 (95% CI = [0.595–0.845]), 0.728 (95% CI = [0.612–0.844]) and 0.717 (95% CI = [0.598–0.835]) respectively. Partial perfusion parameters of BAP and AEF Q10 were positively correlated with MVD (p value range is < 0.001–0.037, ρ value range is 0.483–0.683), and partial perfusion parameters of PI were negatively correlated with MVD (p value range is 0.001–0.041,ρvalue range is − 0.523–− 0.343). Partial perfusion parameters of BAP and AEF Q10 were positively correlated with VEGF (p value range is 0.001–0.016, ρvalue range is 0.398–0.570), meanwhile some perfusion parameters of PAP and PI were negatively correlated with VEGF (p value range is 0.001–0.040, ρ value range is − 0.657–0.343).

Conclusions

Quantitative parameters of dynamic triple-phase enhanced CT can provide diagnostic basis for the differentiation of lung lesions, and there were connection with tumor angiogenesis and vascular endothelial growth factor expression.

Application of Cluster Analysis of Time Evolution for Magnetic Resonance Imaging -Derived Oxygen Extraction Fraction Mapping: A Promising Strategy for the Genetic Profile Prediction and Grading of Glioma

Background: The intratumoral heterogeneity of oxygen metabolism and angiogenesis are core hallmarks of glioma, unveiling that genetic aberrations associated with magnetic resonance imaging (MRI) phenotypes may aid in the diagnosis and treatment of glioma.

Objective: To explore the predictability of MRI-based oxygen extraction fraction (OEF) mapping using cluster analysis of time evolution (CAT) for genetic profiling and glioma grading.

Methods: Ninety-one patients with histopathologically confirmed glioma were examined with CAT for quantitative susceptibility mapping and quantitative blood oxygen level–dependent magnitude-based OEF mapping and dynamic contrast-enhanced (DCE) MRI. Imaging biomarkers, including oxygen metabolism (OEF) and angiogenesis [volume transfer constant, cerebral blood volume (CBV), and cerebral blood flow], were investigated to predict IDH mutation, O⁶-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status, receptor tyrosine kinase (RTK) subgroup, and differentiation of glioblastoma (GBM) vs. lower-grade glioma (LGG). The corresponding DNA sequencing was also obtained. Results were compared with DCE-MRI using receiver operating characteristic (ROC) analysis.

Results: IDH1-mutated LGGs exhibited significantly lower OEF and hypoperfusion than IDH wild-type tumors (all p < 0.01). OEF and perfusion metrics showed a tendency toward higher values in MGMT unmethylated GBM, but only OEF retained significance (p = 0.01). Relative prevalence of RTK alterations was associated with increased OEF (p = 0.003) and perfusion values (p < 0.05). ROC analysis suggested OEF achieved best performance for IDH mutation detection [area under the curve (AUC) = 0.828]. None of the investigated parameters enabled prediction of MGMT status except OEF with a moderate AUC of 0.784. Predictive value for RTK subgroup was acceptable by using OEF (AUC = 0.764) and CBV (AUC = 0.754). OEF and perfusion metrics demonstrated excellent performance in glioma grading. Moreover, mutational landscape revealed hypoxia or angiogenesis-relevant gene signatures were associated with specific imaging phenotypes.

Conclusion: CAT for MRI-based OEF mapping is a promising technology for oxygen measurement and along with perfusion MRI can predict genetic profiles and tumor grade in a non-invasive and clinically relevant manner.

Clinical Impact: Physiological imaging provides an in vivo portrait of genetic alterations in glioma and offers a potential strategy for non-invasively selecting patients for individualized therapies.

Targeting Glioblastoma Stem Cells: A Review on Biomarkers, Signal Pathways and Targeted Therapy

Glioblastoma (GBM) remains the most lethal and common primary brain tumor, even after treatment with multiple therapies, such as surgical resection, chemotherapy, and radiation. Although great advances in medical development and improvements in therapeutic methods of GBM have led to a certain extension of the median survival time of patients, prognosis remains poor. The primary cause of its dismal outcomes is the high rate of tumor recurrence, which is closely related to its resistance to standard therapies. During the last decade, glioblastoma stem cells (GSCs) have been successfully isolated from GBM, and it has been demonstrated that these cells are likely to play an indispensable role in the formation, maintenance, and recurrence of GBM tumors, indicating that GSCs are a crucial target for treatment. Herein, we summarize the current knowledge regarding GSCs, their related signaling pathways, resistance mechanisms, crosstalk linking mechanisms, and microenvironment or niche. Subsequently, we present a framework of targeted therapy for GSCs based on direct strategies, including blockade of the pathways necessary to overcome resistance or prevent their function, promotion of GSC differentiation, virotherapy, and indirect strategies, including targeting the perivascular, hypoxic, and immune niches of the GSCs. In summary, targeting GSCs provides a tremendous opportunity for revolutionary approaches to improve the prognosis and therapy of GBM, despite a variety of challenges.

A Key Pathway to Cancer Resilience: The Role of Autophagy in Glioblastomas

There are no effective strategies for the successful treatment of glioblastomas (GBM). Current therapeutic modalities effectively target bulk tumor cells but leave behind marginal GBM cells that escape from the surgical margins and radiotherapy field, exhibiting high migratory phenotype and resistance to all available anti-glioma therapies. Drug resistance is mostly driven by tumor cell plasticity: a concept associated with reactivating transcriptional programs in response to adverse and dynamic conditions from the tumor microenvironment. Autophagy, or “self-eating”, pathway is an emerging target for cancer therapy and has been regarded as one of the key drivers of cell plasticity in response to energy demanding stress conditions. Many studies shed light on the importance of autophagy as an adaptive mechanism, protecting GBM cells from unfavorable conditions, while others recognize that autophagy can kill those cells by triggering a non-apoptotic cell death program, called ‘autophagy cell death’ (ACD). In this review, we carefully analyzed literature data and conclude that there is no clear evidence indicating the presence of ACD under pathophysiological settings in GBM disease. It seems to be exclusively induced by excessive (supra-physiological) stress signals, mostly from in vitro cell culture studies. Instead, pre-clinical and clinical data indicate that autophagy is an emblematic example of the ‘dark-side’ of a rescue pathway that contributes profoundly to a pro-tumoral adaptive response. From a standpoint of treating the real human disease, only combinatorial therapy targeting autophagy with cytotoxic drugs in the adjuvant setting for GBM patients, associated with the development of less toxic and more specific autophagy inhibitors, may inhibit adaptive response and enhance the sensibility of glioma cells to conventional therapies.

DCE-MRI in Glioma, Infiltration Zone and Healthy Brain to Assess Angiogenesis: A Biopsy Study

Purpose

To explore the focal predictability of vascular growth factor expression and neovascularization using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) in glioma.

Methods

120 brain biopsies were taken in vital tumor, infiltration zone and normal brain tissue of 30 glioma patients: 17 IDH(isocitrate dehydrogenase)-wildtype glioblastoma (GBM), 1 IDH-wildtype astrocytoma °III (together prognostic group 1), 3 IDH-mutated GBM (group 2), 3 anaplastic astrocytomas IDH-mutated (group 3), 4 anaplastic oligodendrogliomas and 2 low-grade oligodendrogliomas (together prognostic group 4). A mixed linear model evaluated the predictabilities of microvessel density (MVD), vascular area ratio (VAR), mean vessel size (MVS), vascular endothelial growth factor and receptors (VEGF-A, VEGFR‑2) and vascular endothelial-protein tyrosine phosphatase (VE-PTP) expression from Tofts model kinetic and model-free curve parameters.

Results

All kinetic parameters were associated with VEGF‑A (all p < 0.001) expression. K^trans, k_ep and v_e were associated with VAR (p = 0.006, 0.004 and 0.01, respectively) and MVS (p = 0.0001, 0.02 and 0.003, respectively) but not MVD (p = 0.84, 0.74 and 0.73, respectively). Prognostic groups differed in K^trans (p = 0.007) and v_e (p = 0.004) values measured in the infiltration zone. Despite significant differences of VAR, MVS, VEGF‑A, VEGFR‑2, and VE-PTP in vital tumor tissue and the infiltration zone (p = 0.0001 for all), there was no significant difference between kinetic parameters measured in these zones.

Conclusion

The DCE-MRI kinetic parameters show correlations with microvascular parameters in vital tissue and also reveal blood-brain barrier abnormalities in the infiltration zones adequate to differentiate glioma prognostic groups.

Supplementary Information

The online version of this article (10.1007/s00062-021-01015-3) contains supplementary material, which is available to authorized users.

Tumor hypoxia represses γδ T cell-mediated antitumor immunity against brain tumors

The anatomic location and immunologic characteristics of brain tumors result in strong lymphocyte suppression. Consequently, conventional immunotherapies targeting CD8 T cells are ineffective against brain tumors. Tumor cells escape immunosurveillance by various mechanisms and tumor cell metabolism can affect the metabolic states and functions of tumor-infiltrating lymphocytes. Here, we discovered that brain tumor cells had a particularly high demand for oxygen, which affected γδ T cell-mediated antitumor immune responses but not those of conventional T cells. Specifically, tumor hypoxia activated the γδ T cell protein kinase A pathway at a transcriptional level, resulting in repression of the activatory receptor NKG2D. Alleviating tumor hypoxia reinvigorated NKG2D expression and the antitumor function of γδ T cells. These results reveal a hypoxia-mediated mechanism through which brain tumors and γδ T cells interact and emphasize the importance of γδ T cells for antitumor immunity against brain tumors.

Quantifying MRI T1 relaxation in flowing blood: implications for arterial input function measurement in DCE-MRI

OBJECTIVES

To investigate the feasibility of accurately quantifying the concentration of MRI contrast agent in flowing blood by measuring its T1 in a large vessel. Such measures are often used to obtain patient-specific arterial input functions for the accurate fitting of pharmacokinetic models to dynamic contrast enhanced MRI data. Flow is known to produce errors with this technique, but these have so far been poorly quantified and characterised in the context of pulsatile flow with a rapidly changing T1 as would be expected in vivo.

METHODS

A phantom was developed which used a mechanical pump to pass fluid at physiologically relevant rates. Measurements of T₁ were made using high temporal resolution gradient recalled sequences suitable for DCE-MRI of both constant and pulsatile flow. These measures were used to validate a virtual phantom that was then used to simulate the expected errors in the measurement of an AIF in vivo.

RESULTS

The relationship between measured T1 values and flow velocity was found to be non-linear. The subsequent error in quantification of contrast agent concentration in a measured AIF was shown.

CONCLUSIONS

The T1 measurement of flowing blood using standard DCE- MRI sequences are subject to large measurement errors which are non-linear in relation to flow velocity.

ADVANCES IN KNOWLEDGE

This work qualitatively and quantitatively demonstrates the difficulties of accurately measuring the T1 of flowing blood using DCE-MRI over a wide range of physiologically realistic flow velocities and pulsatilities. Sources of error are identified and proposals made to reduce these.

The Role of Hypoxia in Glioblastoma Radiotherapy Resistance

Glioblastoma (GB) (grade IV astrocytoma) is the most malignant type of primary brain tumor with a 16 months median survival time following diagnosis. Despite increasing attention regarding the development of targeted therapies for GB that resulted in around 450 clinical trials currently undergoing, radiotherapy still remains the most clinically effective treatment for these patients. Nevertheless, radiotherapy resistance (radioresistance) is commonly observed in GB patients leading to tumor recurrence and eventually patient death. It is therefore essential to unravel the molecular mechanisms underpinning GB cell radioresistance in order to develop novel strategies and combinational therapies focused on enhancing tumor cell sensitivity to radiotherapy. In this review, we present a comprehensive examination of the current literature regarding the role of hypoxia (O2 partial pressure less than 10 mmHg), a main GB microenvironmental factor, in radioresistance with the ultimate goal of identifying potential molecular markers and therapeutic targets to overcome this issue in the future.

Soft tissue sarcomas: IVIM and DKI correlate with the expression of HIF-1α on direct comparison of MRI and pathological slices

OBJECTIVE

To investigate the correlation of intravoxel incoherent motion (IVIM) and diffusion kurtosis imaging (DKI) parameters with the expression of HIF-1α in soft tissue sarcoma (STS).

METHODS

This prospective study was approved by the institutional ethics committee. Written informed consent was obtained from all patients. Forty patients with STS who underwent 3.0 T MRI, including IVIM and DKI, were included in the study. Standard apparent diffusion coefficient (ADC), true ADC (D_slow), pseudo ADC (D_fast), perfusion fraction (f), mean kurtosis (MK), and mean diffusivity (MD) of each lesion were independently analyzed by two observers. An MRI-pathology control method was used to ensure correspondence between the MRI slices and the pathological sections. Spearman analysis, independent sample t test, Mann-Whitney U test, chi-squared test, and receiver operating characteristic (ROC) curve analysis were performed.

RESULTS

D_slow and MD values showed a negative correlation with HIF-1α expression (r = - 0.469, - 0.588). MK and f values showed a positive correlation with HIF-1α expression (r = 0.779, 0.572). D_slow, MD, MK, and f values showed significant differences between the high- and low-expression groups. The MK value showed the best diagnostic ability. The optimal cut-off MK value of 0.604 was associated with 78.3% sensitivity and 88.2% specificity (area under the curve, 0.867).

CONCLUSIONS

This preliminary study demonstrated the association of IVIM and DKI parameters with the expression of HIF-1α in STS.

KEY POINTS

• IVIM and DKI parameters are correlated with the expression of HIF-1α in STS. • The MRI-pathology control method can be used in clinical studies to ensure correspondence between MRI slices and pathology sections.

Non-Invasive Estimation of Glioma IDH1 Mutation and VEGF Expression by Histogram Analysis of Dynamic Contrast-Enhanced MRI

Objectives

To investigate whether glioma isocitrate dehydrogenase (IDH) 1 mutation and vascular endothelial growth factor (VEGF) expression can be estimated by histogram analysis of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).

Methods

Chinese Glioma Genome Atlas (CGGA) database was wined for differential expression of VEGF in gliomas with different IDH genotypes. The VEGF expression and IDH1 genotypes of 56 glioma samples in our hospital were assessed by immunohistochemistry. Preoperative DCE-MRI data of glioma samples were reviewed. Regions of interest (ROIs) covering tumor parenchyma were delineated. Histogram parameters of volume transfer constant (K^trans) and volume of extravascular extracellular space per unit volume of tissue (V_e) derived from DCE-MRI were obtained. Histogram parameters of K^trans, V_e and VEGF expression of IDH1 mutant type (IDH1^mut) gliomas were compared with the IDH1 wildtype (IDH1^wt) gliomas. Receiver operating characteristic (ROC) curve analysis was performed to differentiate IDH1^mut from IDH1^wt gliomas. The correlation coefficients were determined between histogram parameters of K^trans, V_e and VEGF expression in gliomas.

Results

In CGGA database, VEGF expression in IDH^mut gliomas was lower as compared to wildtype counterpart. The immunohistochemistry of glioma samples in our hospital also confirmed the results. Comparisons demonstrated statistically significant differences in histogram parameters of K^transand V_e [mean, standard deviation (SD), 50th, 75th, 90th. and 95th percentile] between IDH1^mutand IDH1^wtgliomas (P < 0.05, respectively). ROC curve analysis revealed that 50th percentile of K^trans (0.019 min⁻¹) and V_e (0.039) provided the perfect combination of sensitivity and specificity in differentiating gliomas with IDH1^mutfrom IDH1^wt. Irrespective of IDH1 mutation, histogram parameters of K^transand V_e were correlated with VEGF expression in gliomas (P < 0.05, respectively).

Conclusions

VEGF expression is significantly lower in IDH1^mut gliomas as compared to the wildtype counterpart, and it is non-invasively predictable with histogram analysis of DCE-MRI.

DCE-MRI Quantitative Parameters as Predictors of Treatment Response in Patients With Locally Advanced Cervical Squamous Cell Carcinoma Underwent CCRT

Purpose

To evaluate the predictive value of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) quantitative parameters in treatment response to concurrent chemoradiotherapy (CCRT) for locally advanced cervical squamous cell carcinoma (LACSC).

Methods and materials

LACSC patients underwent CCRT had DCE-MRI before (e0) and after 3 days of treatment (e3). Extended Tofts Linear model with a user arterial input function was adopted to generate quantitative measurements. Endothelial transfer constant (K^trans), reflux rate (K_ep), fractional extravascular extracellular space volume (V_e), and fractional plasma volume (V_p) were calculated, and percentage changes ΔK^trans, ΔK_ep, ΔV_e, and ΔV_p were computed. The correlations of these measurements with the tumor regression rate were analyzed. The predictive value of these parameters on treatment outcome was generated by the receiver operating characteristic (ROC) curve. Univariate and multivariate logistic regression analyses were conducted to find the independent variables.

Results

K^trans-e0, K_ep -e0, ΔK^trans, and ΔV_e were positively correlated with the tumor regression rate. Mean values of K^trans-e0, K^trans-e3, ΔK^trans, and ΔV_e were higher in the non-residual tumor group than residual tumor group and were independent prognostic factors for predicting residual tumor occurrence. K^trans-e3 showed the highest area under the curve (AUC) for treatment response prediction.

Conclusions

Quantitative parameters at e0 and e3 from DCE-MRI could be used as potential indicators for predicting treatment response of LACSC.

Hypoxia-Induced Glioma-Derived Exosomal miRNA-199a-3p Promotes Ischemic Injury of Peritumoral Neurons by Inhibiting the mTOR Pathway

The underlying molecular mechanisms that the hypoxic microenvironment could aggravate neuronal injury are still not clear. In this study, we hypothesized that the exosomes, exosomal miRNAs, and the mTOR signaling pathway might be involved in hypoxic peritumoral neuronal injury in glioma. Multimodal radiological images, HE, and HIF-1α staining of high-grade glioma (HGG) samples revealed that the peritumoral hypoxic area overlapped with the cytotoxic edema region and directly contacted with normal neurons. In either direct or indirect coculture system, hypoxia could promote normal mouse hippocampal neuronal cell (HT22) injury, and the growth of HT22 cells was suppressed by C6 glioma cells under hypoxic condition. For administrating hypoxia-induced glioma-derived exosomes (HIGDE) that could aggravate oxygen-glucose deprivation (OGD)/reperfusion neuronal injury, we identified that exosomes may be the communication medium between glioma cells and peritumoral neurons, and we furtherly found that exosomal miR-199a-3p mediated the OGD/reperfusion neuronal injury process by suppressing the mTOR signaling pathway. Moreover, the upregulation of miRNA-199a-3p in exosomes from glioma cells was induced by hypoxia-related HIF-1α activation. To sum up, hypoxia-induced glioma-derived exosomal miRNA-199a-3p can be upregulated by the activation of HIF-1α and is able to increase the ischemic injury of peritumoral neurons by inhibiting the mTOR pathway.

Patient-Centric Head and Neck Cancer Radiation Therapy: Role of Advanced Imaging

The traditional 'one-size-fits-all' approach to H&N cancer therapy is archaic. Advanced imaging can identify radioresistant areas by using biomarkers that detect tumor hypoxia, hypercellularity etc. Highly conformal radiotherapy can target resistant areas with precision. The critical information that can be gleaned about tumor biology from these advanced imaging modalities facilitates individualized radiotherapy. The tumor imaging world is pushing its boundaries. Molecular imaging can now detect protein expression and genotypic variations across tumors that can be exploited for tailoring treatment. The exploding field of radiomics and radiogenomics extracts quantitative, biologic and genetic information and further expands the scope of personalized therapy.

Hypoxia Inducible Factors' Signaling in Pediatric High-Grade Gliomas: Role, Modelization and Innovative Targeted Approaches

The brain tumor microenvironment has recently become a major challenge in all pediatric cancers, but especially in brain tumors like high-grade gliomas. Hypoxia is one of the extrinsic tumor features that interacts with tumor cells, but also with the blood-brain barrier and all normal brain cells. It is the result of a dramatic proliferation and expansion of tumor cells that deprive the tissues of oxygen inflow. However, cancer cells, especially tumor stem cells, can endure extreme hypoxic conditions by rescheduling various genes' expression involved in cell proliferation, metabolism and angiogenesis and thus, promote tumor expansion, therapeutic resistance and metabolic adaptation. This cellular adaptation implies Hypoxia-Inducible Factors (HIF), namely HIF-1α and HIF-2α. In pediatric high-grade gliomas (pHGGs), several questions remained open on hypoxia-specific role in normal brain during gliomagenesis and pHGG progression, as well how to model it in preclinical studies and how it might be counteracted with targeted therapies. Therefore, this review aims to gather various data about this key extrinsic tumor factor in pHGGs.

Assessment of an scFv Antibody Fragment Against ELTD1 in a G55 Glioblastoma Xenograft Model

Glioblastoma (GBM), the most common primary brain tumor found in adults, is extremely aggressive. These high-grade gliomas, which are very diffuse, highly vascular, and invasive, undergo unregulated vascular angiogenesis. Despite available treatments, the median survival for patients is dismal. ELTD1 (EGF, latrophilin, and 7 transmembrane domain containing protein 1) is an angiogenic biomarker highly expressed in human high-grade gliomas. Recent studies have demonstrated that the blood-brain barrier, as well as the blood-tumor barrier, is not equally disrupted in GBM patients. This study therefore aimed to optimize an antibody treatment against ELTD1 using a smaller scFv fragment of a monoclonal antibody that binds against the external region of ELTD1 in a G55 glioma xenograft glioma preclinical model. Morphological magnetic resonance imaging (MRI) was used to determine tumor volumes and quantify perfusion rates. We also assessed percent survival following tumor postdetection. Tumor tissue was also assessed to confirm and quantify the presence of the ELTD1 scFv molecular targeted MRI probe, as well as microvessel density and Notch1 levels. In addition, we used molecular-targeted MRI to localize our antibodies in vivo. This approach showed that our scFv antibody attached-molecular MRI probe was effective in targeting and localizing diffuse tumor regions. Through this analysis, we determined that our anti-ELTD1 scFv antibody treatments were successful in increasing survival, decreasing tumor volumes, and normalizing vascular perfusion and Notch1 levels within tumor regions. This study demonstrates that our scFv fragment antibody against ELTD1 may be useful and potential antiangiogenic treatments against GBM.

Histopathology-validated machine learning radiographic biomarker for noninvasive discrimination between true progression and pseudo-progression in glioblastoma

BACKGROUND

Imaging of glioblastoma patients after maximal safe resection and chemoradiation commonly demonstrates new enhancements that raise concerns about tumor progression. However, in 30% to 50% of patients, these enhancements primarily represent the effects of treatment, or pseudo-progression (PsP). We hypothesize that quantitative machine learning analysis of clinically acquired multiparametric magnetic resonance imaging (mpMRI) can identify subvisual imaging characteristics to provide robust, noninvasive imaging signatures that can distinguish true progression (TP) from PsP.

METHODS

We evaluated independent discovery (n = 40) and replication (n = 23) cohorts of glioblastoma patients who underwent second resection due to progressive radiographic changes suspicious for recurrence. Deep learning and conventional feature extraction methods were used to extract quantitative characteristics from the mpMRI scans. Multivariate analysis of these features revealed radiophenotypic signatures distinguishing among TP, PsP, and mixed response that compared with similar categories blindly defined by board-certified neuropathologists. Additionally, interinstitutional validation was performed on 20 new patients.

RESULTS

Patients who demonstrate TP on neuropathology are significantly different (P < .0001) from those with PsP, showing imaging features reflecting higher angiogenesis, higher cellularity, and lower water concentration. The accuracy of the proposed signature in leave-one-out cross-validation was 87% for predicting PsP (area under the curve [AUC], 0.92) and 84% for predicting TP (AUC, 0.83), whereas in the discovery/replication cohort, the accuracy was 87% for predicting PsP (AUC, 0.84) and 78% for TP (AUC, 0.80). The accuracy in the interinstitutional cohort was 75% (AUC, 0.80).

CONCLUSION

Quantitative mpMRI analysis via machine learning reveals distinctive noninvasive signatures of TP versus PsP after treatment of glioblastoma. Integration of the proposed method into clinical studies can be performed using the freely available Cancer Imaging Phenomics Toolkit.

18F-FAZA PET imaging in tumor hypoxia: A focus on high-grade glioma

The presence of hypoxia is a typical feature of solid tumors and has been identified in many neoplasms, favouring the survival of malignant cells in a hostile environment and the expression of an aggressive phenotype. Malignant brain tumors have large proportions of hypoxic tissue, thus contributing to resistance to radiation and chemotherapy. Positron emission tomography (PET) is an attractive technique to gain a non-invasive assessment of tumor hypoxia within the whole tumor, with 18F-fluoromisonidazole (18F-FMISO) and 18F-flouroazomycin arabinoside (18F-FAZA) being the most promising radiotracers. In this short review, we aim to discuss the available clinical studies focused on the use of 18F-FAZA PET/computed tomography in patients affected by high-grade glioma.

Prognostication of anaplastic astrocytoma patients: application of contrast leakage information of dynamic susceptibility contrast-enhanced MRI and dynamic contrast-enhanced MRI

PURPOSE

To examine the applicability of contrast leakage information from dynamic susceptibility contrast-enhanced (DSC) MRI and dynamic contrast-enhanced (DCE) MRI to determine which one is the most valuable surrogate imaging biomarker for predicting disease progression in anaplastic astrocytoma (AA) patients.

MATERIALS AND METHODS

This study was approved by the institutional review board (IRB), which waived informed consent. A total of seventy-three AA patients who had undergone preoperative DCE and DSC MRI and received standard treatment, including partial resection or biopsy followed by radiation therapy, were included in this retrospective study. Based on Response Assessment in Neuro-Oncology (RANO), patients were sorted into progression (n = 21) and non-progression (n = 52) groups. Tumor boundaries were defined as high-signal intensity (SI) lesions on fluid-attenuated inversion recovery (FLAIR) imaging, where we analyzed mean pharmacokinetic parameters (K_trans, V_p, and V_e) from DCE MRI and contrast leakage information (mean extraction fraction (EF)) from DSC MRI.

RESULTS

Mean V_e and mean EF were significantly higher in patients with progression-free survival (PFS) < 18 months than in those with PFS ≥ 18 months. For distinguishing the group with PFS < 18 months, AUC values were calculated using the mean V_e value (AUC = 0.716). The Kaplan-Meier survival analysis revealed that mean V_e value was significantly correlated with PFS. In Cox proportional-hazards regression, only the mean V_e value was found to be significantly associated with PFS.

CONCLUSION

We found that the mean V_e value based on high-SI tumor lesions on FLAIR imaging was capable of predicting outcomes of AA patients as a potential surrogate imaging biomarker.

KEY POINTS

• Mean V_e(2.152 ± 1.857 vs. 1.173 ± 1.408) was significantly higher in anaplastic astrocytoma patients with PFS < 18 months that in those with PFS ≥ 18 months (p = 0.02). • Cox proportional-hazards regression showed that only mean V_e(p = 0.034) was significantly associated with PFS, regardless of IDH mutation status, in anaplastic astrocytoma patients.

Multivariate Analysis of Preoperative Magnetic Resonance Imaging Reveals Transcriptomic Classification of de novo Glioblastoma Patients

Glioblastoma, the most frequent primary malignant brain neoplasm, is genetically diverse and classified into four transcriptomic subtypes, i. e., classical, mesenchymal, proneural, and neural. Currently, detection of transcriptomic subtype is based on ex vivo analysis of tissue that does not capture the spatial tumor heterogeneity. In view of accumulative evidence of in vivo imaging signatures summarizing molecular features of cancer, this study seeks robust non-invasive radiographic markers of transcriptomic classification of glioblastoma, based solely on routine clinically-acquired imaging sequences. A pre-operative retrospective cohort of 112 pathology-proven de novo glioblastoma patients, having multi-parametric MRI (T1, T1-Gd, T2, T2-FLAIR), collected from the Hospital of the University of Pennsylvania were included. Following tumor segmentation into distinct radiographic sub-regions, diverse imaging features were extracted and support vector machines were employed to multivariately integrate these features and derive an imaging signature of transcriptomic subtype. Extracted features included intensity distributions, volume, morphology, statistics, tumors' anatomical location, and texture descriptors for each tumor sub-region. The derived signature was evaluated against the transcriptomic subtype of surgically-resected tissue specimens, using a 5-fold cross-validation method and a receiver-operating-characteristics analysis. The proposed model was 71% accurate in distinguishing among the four transcriptomic subtypes. The accuracy (sensitivity/specificity) for distinguishing each subtype (classical, mesenchymal, proneural, neural) from the rest was equal to 88.4% (71.4/92.3), 75.9% (83.9/72.8), 82.1% (73.1/84.9), and 75.9% (79.4/74.4), respectively. The findings were also replicated in The Cancer Genomic Atlas glioblastoma dataset. The obtained imaging signature for the classical subtype was dominated by associations with features related to edge sharpness, whereas for the mesenchymal subtype had more pronounced presence of higher T2 and T2-FLAIR signal in edema, and higher volume of enhancing tumor and edema. The proneural and neural subtypes were characterized by the lower T1-Gd signal in enhancing tumor and higher T2-FLAIR signal in edema, respectively. Our results indicate that quantitative multivariate analysis of features extracted from clinically-acquired MRI may provide a radiographic biomarker of the transcriptomic profile of glioblastoma. Importantly our findings can be influential in surgical decision-making, treatment planning, and assessment of inoperable tumors.

Dynamic Contrast-Enhanced MR Imaging of Nonenhancing T2 High-Signal-Intensity Lesions in Baseline and Posttreatment Glioblastoma: Temporal Change and Prognostic Value

BACKGROUND AND PURPOSE

The prognostic value of dynamic contrast-enhanced MR imaging on nonenhancing T2 high-signal-intensity lesions in patients with glioblastoma has not been thoroughly elucidated to date. We evaluated the temporal change and prognostic value for progression-free survival of dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters on nonenhancing T2 high-signal-intensity lesions in patients with glioblastoma before and after standard treatment, including gross total surgical resection.

MATERIALS AND METHODS

This retrospective study included 33 patients who were newly diagnosed with glioblastoma and treated with gross total surgical resection followed by concurrent chemoradiation therapy and adjuvant chemotherapy with temozolomide in a single institution. All patients underwent dynamic contrast-enhanced MR imaging before surgery as a baseline and after completion of maximal surgical resection and concurrent chemoradiation therapy. On the whole nonenhancing T2 high-signal-intensity lesion, dynamic contrast-enhanced MR imaging-derived pharmacokinetic parameters (volume transfer constant [K ^trans], volume of extravascular extracellular space [v _e]_, and blood plasma volume [v_p ]) were calculated. The Cox proportional hazards regression model analysis was performed to determine the histogram features or percentage changes of pharmacokinetic parameters related to progression-free survival.

RESULTS

Baseline median K ^trans, baseline first quartile K ^trans, and posttreatment median K ^trans were significant independent variables, as determined by univariate analysis (P < .05). By multivariate Cox regression analysis including methylation status of O⁶-methylguanine-DNA methyltransferase, baseline median K ^trans was determined to be the significant independent variable and was negatively related to progression-free survival (hazard ratio = 1.48, P = .003).

CONCLUSIONS

Baseline median K ^trans from nonenhancing T2 high-signal-intensity lesions could be a potential prognostic imaging biomarker in patients undergoing gross total surgical resection followed by standard therapy for glioblastoma.

Radiogenomic analysis of vascular endothelial growth factor in patients with diffuse gliomas

OBJECTIVE

To predict vascular endothelial growth factor (VEGF) expression in patients with diffuse gliomas using radiomic analysis.

MATERIALS AND METHODS

Preoperative magnetic resonance images were retrospectively obtained from 239 patients with diffuse gliomas (World Health Organization grades II-IV). The patients were randomly assigned to a training group (n = 160) or a validation group (n = 79) at a 2:1 ratio. For each patient, a total of 431 radiomic features were extracted. The minimum redundancy maximum relevance (mRMR) algorithm was used for feature selection. A machine-learning model for predicting VEGF status was then developed using the selected features and a support vector machine classifier. The predictive performance of the model was evaluated in both groups using receiver operating characteristic curve analysis, and correlations between selected features were assessed.

RESULTS

Nine radiomic features were selected to generate a VEGF-associated radiomic signature of diffuse gliomas based on the mRMR algorithm. This radiomic signature consisted of two first-order statistics or related wavelet features (Entropy and Minimum) and seven textural features or related wavelet features (including Cluster Tendency and Long Run Low Gray Level Emphasis). The predictive efficiencies measured by the area under the curve were 74.1% in the training group and 70.2% in the validation group. The overall correlations between the 9 radiomic features were low in both groups.

CONCLUSIONS

Radiomic analysis facilitated efficient prediction of VEGF status in diffuse gliomas, suggesting that using tumor-derived radiomic features for predicting genomic information is feasible.

Dynamic contrast-enhanced perfusion parameters in ovarian cancer: Good accuracy in identifying high HIF-1α expression

BACKGROUND

Hypoxia significantly influences treatment response and clinical outcome in solid tumors. A noninvasive marker for hypoxia will help physicians in treatment planning and encourage the efficient use of hypoxia targeted therapies. The purpose of this study was to investigate whether pharmacokinetic dynamic contrast-enhanced (DCE) perfusion parameters are associated with a specific marker of hypoxia, hypoxia-inducible factor 1 alpha (HIF-1α) in ovarian cancer (OC).

MATERIALS AND METHODS

Thirty-eight patients with primary OC were enrolled in this prospective study approved by the local ethical committee. Patients underwent dynamic gadolinium-enhanced 3.0 T MRI as part of their staging investigations. Pharmacokinetic perfusion parameters, including a rate constant for transfer of contrast agent from plasma to extravascular extracellular space (EES) (Ktrans) and a rate constant from EES to plasma (Kep), were measured by drawing two types of regions of interest (ROIs): a large solid lesion (L-ROI) and a solid, most enhancing small area (S-ROI) (NordicICE platform). Tissue samples for immunohistochemical analysis were collected during surgery. Kruskal-Wallis, Mann-Whitney U and Chi-square tests were used in statistical analyses. Receiver Operating Characteristic curve analyzes were done for DCE parameters to discriminate high HIF-1α expression.

RESULTS

Pharmacokinetic perfusion parameters Ktrans and Kep were inversely associated with HIF-1α expression (Ktrans L-ROI P = 0.021; Ktrans S-ROI P = 0.018 and Kep L-ROI P = 0.032; Kep S-ROI P = 0.033). Ktrans and Kep showed good accuracy in identifying high HIF-1α expression (AUC = 0.832 Ktrans L-ROI; 0.840 Ktrans S-ROI; 0.808 Kep L-ROI and 0.808 Kep L-ROI).

CONCLUSION

This preliminary study demonstrated that pharmacokinetic DCE-MRI perfusion parameters are associated with the hypoxia specific marker, HIF-1α in OC. DCE-MRI may be a useful supplementary tool in the characterization of OC tumors in a staging investigation.

Dynamic contrast-enhanced magnetic resonance imaging perfusion characteristics in meningiomas treated with resection and adjuvant radiosurgery

OBJECTIVE

There is a need for advanced imaging biomarkers to improve radiation treatment planning and response assessment. T1-weighted dynamic contrast-enhanced perfusion MRI (DCE MRI) allows quantitative assessment of tissue perfusion and blood-brain barrier dysfunction and has entered clinical practice in the management of primary and secondary brain neoplasms. The authors sought to retrospectively investigate DCE MRI parameters in meningiomas treated with resection and adjuvant radiation therapy using volumetric segmentation.

METHODS

A retrospective review of more than 300 patients with meningiomas resected between January 2015 and December 2018 identified 14 eligible patients with 18 meningiomas who underwent resection and adjuvant radiotherapy. Patients were excluded if they did not undergo adjuvant radiation therapy or DCE MRI. Demographic and clinical characteristics were obtained and compared to DCE perfusion metrics, including mean plasma volume (vp), extracellular volume (ve), volume transfer constant (Ktrans), rate constant (kep), and wash-in rate of contrast into the tissue, which were derived from volumetric analysis of the enhancing volumes of interest.

RESULTS

The mean patient age was 64 years (range 49–86 years), and 50% of patients (7/14) were female. The average tumor volume was 8.07 cm3 (range 0.21–27.89 cm3). The median Ki-67 in the cohort was 15%. When stratified by median Ki-67, patients with Ki-67 greater than 15% had lower median vp (0.02 vs 0.10, p = 0.002), and lower median wash-in rate (1.27 vs 4.08 sec−1, p = 0.04) than patients with Ki-67 of 15% or below. Logistic regression analysis demonstrated a statistically significant, moderate positive correlation between ve and time to progression (r = 0.49, p < 0.05). Furthermore, there was a moderate positive correlation between Ktrans and time to progression, which approached, but did not reach, statistical significance (r = 0.48, p = 0.05).

CONCLUSIONS

This study demonstrates a potential role for DCE MRI in the preoperative characterization and stratification of meningiomas, laying the foundation for future prospective studies incorporating DCE as a biomarker in meningioma diagnosis and treatment planning.

Insights into Hypoxia: Non-invasive Assessment through Imaging Modalities and Its Application in Breast Cancer

Oxygen is crucial to maintain the homeostasis in aerobic cells. Hypoxia is a condition in which cells are deprived of the oxygen supply necessary for their optimum performance. Whereas oxygen deprivation may occur in normal physiological processes, hypoxia is frequently associated with pathological conditions. It has been identified as a stressor in the tumor microenvironment, acting as a key mediator of cancer development. Numerous pathways are activated in hypoxic cells that affect cell signaling and gene regulation to promote the survival of these cells by stimulating angiogenesis, switching cellular metabolism, slowing their growth rate, and preventing apoptosis. The induction of dysregulated metabolism in cancer cells by hypoxia results in aggressive tumor phenotypes that are characterized by rapid progression, treatment resistance, and poor prognosis. A non-invasive assessment of hypoxia-induced metabolic and architectural changes in tumors is advisable to fully improve breast cancer (BC) patient management, by potentially reducing the need for invasive biopsy procedures and evaluating tumor response to treatment. This review provides a comprehensive overview of the molecular changes in breast tumors secondary to hypoxia and the non-invasive imaging alternatives to evaluate oxygen deprivation, with an emphasis on their application in BC and the advantages and limitations of the currently available techniques.

Highly sensitive electron paramagnetic resonance nanoradicals for quantitative intracellular tumor oxymetric images

Purpose: Tumor oxygenation is a critical parameter influencing the efficacy of cancer therapy. Low levels of oxygen in solid tumor have been recognized as an indicator of malignant progression and metastasis, as well as poor response to chemo- and radiation therapy. Being able to measure oxygenation for an individual's tumor would provide doctors with a valuable way of identifying optimal treatments for patients. Methods: Electron paramagnetic resonance imaging (EPRI) in combination with an oxygen-measuring paramagnetic probe was performed to measure tumor oxygenation in vivo. Triarylmethyl (trityl) radical exhibits high specificity, sensitivity, and resolution for quantitative measurement of O₂ concentration. However, its in vivo applications in previous studies have been limited by the required high dosage, its short half-life, and poor intracellular permeability. To address these limitations, we developed high-capacity nanoformulated radicals that employed fluorescein isothiocyanate-labeled mesoporous silica nanoparticles (FMSNs) as trityl radical carriers. The high surface area nanostructure and easy surface modification of physiochemical properties of FMSNs enable efficient targeted delivery of highly concentrated, nonself-quenched trityl radicals, protected from environmental degradation and dilution. Results: We successfully designed and synthesized a tumor-targeted nanoplatform as a carrier for trityl. In addition, the nanoformulated trityl does not affect oxygen-sensing capacity by a self-relaxation or broadening effect. The FMSN-trityl exhibited high sensitivity/response to oxygen in the partial oxygen pressure range from 0 to 155 mmHg. Furthermore, MSN-trityl displayed outstanding intracellular oxygen mapping in both in vitro and in vivo animal studies. Conclusion: The highly sensitive nanoformulated trityl spin probe can profile intracellular oxygen distributions of tumor in a real-time and quantitative manner using in vivo EPRI.

DCE-MRI in Human Gliomas: A Surrogate for Assessment of Invasive Hypoxia Marker HIF-1Α Based on MRI-Neuronavigation Stereotactic Biopsies

RATIONALE AND OBJECTIVES

The purpose of this study was to correlate dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) parameters with data from a specific marker of hypoxia, hypoxia-inducible factor 1α (HIF-1α), in human gliomas on a point-to-point basis by using coregistered magnetic resonance imaging and frameless stereotactic biopsies.

MATERIALS AND METHODS

Thirty-four patients with treatment-naive gliomas underwent DCE, axial T1-weighted, T2-weighted, T2-weighted fluid acquisition of inversion recovery, and three-dimensional T1-weighted brain volume with gadolinium contrast enhancement sequences on a 3.0-T magnetic resonance scanner before stereotactic surgery. Quantitative perfusion indices such as endothelial transfer constant, fractional extravascular extracellular space volume, fractional plasma volume, and reflux rate were measured at corresponding stereotactic biopsy sites. Each sample was considered an independent measurement, and its histology grade was diagnosed. HIF-1α expression was quantified from the point-to-point biopsy tissues. Analyses of receiver operating characteristic curves were done for HIF-1α to discriminate different grades of glioma. To look for correlations between immunohistochemical parameters and DCE indices, Spearman's correlation coefficient was used.

RESULTS

Seventy biopsy samples from 34 subjects were included in the analysis. Mean immunoreactivity scores of HIF-1α were 2.75 ± 1.11 for grade II (n = 24), 6.20 ± 2.33 for grade III (n = 20), and 10.46 ± 2.42 for grade IV (n = 26). HIF-1α showed very good-to-excellent accuracy in discriminating grade II from III, III from IV, and II from IV (area under the curve = 0.838, 0.862, and 0.994, respectively). Endothelial transfer constant and fractional extravascular extracellular space volume showed a significantly positive correlation with HIF-1α expression (r = 0.686, P < .001; r = 0.549, P < .001, respectively).

CONCLUSION

Our study demonstrated HIF-1α to be a significant predictor of different grades of gliomas with high sensitivity and specificity. DCE-MRI is a useful, noninvasive imaging tool for quantitative evaluation of HIF-1α, and its parameters may be used as a surrogate for HIF-1α expression.

Improving the estimation of prognosis for glioblastoma patients by MR based hemodynamic tissue signatures

Advanced MRI and molecular markers have been raised as crucial to improve prognostic models for patients having glioblastoma (GBM) lesions. In particular, different MR perfusion based markers describing vascular intrapatient heterogeneity have been correlated with tumor aggressiveness, and represent key information to understand tumor resistance against effective therapies of these neoplasms. Recently, hemodynamic tissue signature (HTS) markers based on MR perfusion images have been demonstrated to be useful for describing the heterogeneity of GBM at the voxel level, as well as demonstrating significant correlations with the patient's overall survival. In this work, we analyze the abilities of these markers to improve the conventional prognostic models based on clinical, morphological, and demographic features. Our results, in both the regression and classification tests, show that inclusion of the HTS markers improves the reliability of prognostic models. The HTS method is fully automatic and it is available for research use at http://www.oncohabitats.upv.es.

Probing tumor microenvironment in patients with newly diagnosed glioblastoma during chemoradiation and adjuvant temozolomide with functional MRI

Functional MRI may identify critical windows of opportunity for drug delivery and distinguish between early treatment responders and non-responders. Using diffusion-weighted, dynamic contrast-enhanced, and dynamic susceptibility contrast MRI, as well as pro-angiogenic and pro-inflammatory blood markers, we prospectively studied the physiologic tumor-related changes in fourteen newly diagnosed glioblastoma patients during standard therapy. 153 MRI scans and blood collection were performed before chemoradiation (baseline), weekly during chemoradiation (week 1–6), monthly before each cycle of adjuvant temozolomide (pre-C1-C6), and after cycle 6. The apparent diffusion coefficient, volume transfer coefficient (K^trans), and relative cerebral blood volume (rCBV) and flow (rCBF) were calculated within the tumor and edema regions and compared to baseline. Cox regression analysis was used to assess the effect of clinical variables, imaging, and blood markers on progression-free (PFS) and overall survival (OS). After controlling for additional covariates, high baseline rCBV and rCBF within the edema region were associated with worse PFS (microvessel rCBF: HR = 7.849, p = 0.044; panvessel rCBV: HR = 3.763, p = 0.032; panvessel rCBF: HR = 3.984; p = 0.049). The same applied to high week 5 and pre-C1 K^trans within the tumor region (week 5 K^trans: HR = 1.038, p = 0.003; pre-C1 K^trans: HR = 1.029, p = 0.004). Elevated week 6 VEGF levels were associated with worse OS (HR = 1.034; p = 0.004). Our findings suggest a role for rCBV and rCBF at baseline and K^trans and VEGF levels during treatment as markers of response. Functional imaging changes can differ substantially between tumor and edema regions, highlighting the variable biologic and vascular state of tumor microenvironment during therapy.

rCBV- and ADC-based Grading of Meningiomas With Glimpse Into Emerging Molecular Diagnostics

Introduction

This study was conducted to grade meningiomas based on relative Cerebral Blood Volume (rCBV) and Apparent Diffusion Coefficient (ADC) to help surgeons plan the approach and extent of operation as well as decide on the need of any adjuvant radio/chemo therapy. The current and evolving genomic, proteomic, and spectroscopic technologies are also discussed which can supplement the current radiologic methods and procedures in grading meningiomas.

Methods

A total of 35 patients with meningioma prospectively underwent basic MR sequences (T1W, T2W, T2W/FLAIR) in axial, sagittal and coronal planes followed by Diffusion Weighted (DW) imaging having b value of 1000 (minimum ADC values used for analysis). Then, gadobenate dimeglumine/meglumine gadoterate was administered (0.1 mmol/kg at a rate of 4 mL/s) followed by saline flush (20 mL at a rate of 4 mL/s). Next, T₂*W/FFE dynamic images were acquired; dynamics showing maximum fall in intensity was used for creating rCBV and relative Cerebral Blood Flow (rCBF) maps and calculating rCBV.

Results

Both maximum rCBV and minimum ADC within the tumor were not significant for differentiating benign from malignant meningiomas. A cut-off maximum rCBV of 2.5 mL/100 g in peritumoral edema was 75% sensitive, 84.6% specific, and 83.3% accurate in differentiating benign from malignant meningiomas.

Conclusion

Benign and malignant meningiomas can be differentiated based on maximum rCBV in peritumoral edema but ADC values within the tumor are insignificant in differentiating benign and malignant tumors. rCBV values within tumor, however, may be helpful in subtyping meningiomas, especially transitional and meningothelial meningiomas.

Clinical imaging of hypoxia: Current status and future directions

Tissue hypoxia is a key feature of many important causes of morbidity and mortality. In pathologies such as stroke, peripheral vascular disease and ischaemic heart disease, hypoxia is largely a consequence of low blood flow induced ischaemia, hence perfusion imaging is often used as a surrogate for hypoxia to guide clinical diagnosis and treatment. Importantly, ischaemia and hypoxia are not synonymous conditions as it is not universally true that well perfused tissues are normoxic or that poorly perfused tissues are hypoxic. In pathologies such as cancer, for instance, perfusion imaging and oxygen concentration are less well correlated, and oxygen concentration is independently correlated to radiotherapy response and overall treatment outcomes. In addition, the progression of many diseases is intricately related to maladaptive responses to the hypoxia itself. Thus there is potentially great clinical and scientific utility in direct measurements of tissue oxygenation. Despite this, imaging assessment of hypoxia in patients is rarely performed in clinical settings. This review summarises some of the current methods used to clinically evaluate hypoxia, the barriers to the routine use of these methods and the newer agents and techniques being explored for the assessment of hypoxia in pathological processes.

Preoperative and intraoperative perfusion magnetic resonance imaging in a RELA fusion-positive anaplastic ependymoma: A case report

Background

Ependymomas are rare neuroepithelial tumors thought to arise from radial glial precursor cells lining the walls of the ventricles and central canal of the brain and spinal cord, respectively. Histopathological classification, according to World Health Organization criteria, has only recently defined the RELA-fusion positive ependymoma. These tumors may account for 70% of supratentorial ependymomas in children and represent an aggressive entity distinct from other ependymomas.

Case Description

Here we present the case of a patient with RELA-fusion positive ependymoma of the frontal lobe in whom we used preoperative and intraoperative magnetic resonance (MR) perfusion imaging. In this first demonstrated intraoperative evaluation of MR perfusion in ependymoma, increased peripheral perfusion of the lesion in a ring-like manner with a discrete cutoff around the surgical margin correlated with intraoperative findings of a clear border between the tumor and brain, as well as pathological findings of increased MIB index and hypercellularity-specifically within solid tumor components. An abnormal perfusion pattern also suggested an aggressive lesion, which was later confirmed on pathological analysis. In addition, intraoperative MR perfusion improved detection of tumor tissue in combination with traditional T1-weighted contrast-enhanced methods, which increased extent of resection.

Conclusions

MR perfusion imaging may be a useful method for delineating tumor aggressiveness and borders, which can be prognostic.

The Role of Advanced Brain Tumor Imaging in the Care of Patients with Central Nervous System Malignancies

OPINION STATEMENT

T1-weighted post-contrast and T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance imaging (MRI) constitute the gold standard for diagnosis and response assessment in neuro-oncologic patients but are limited in their ability to accurately reflect tumor biology and metabolism, particularly over the course of a patient's treatment. Advanced MR imaging methods are sensitized to different biophysical processes in tissue, including blood perfusion, tumor metabolism, and chemical composition of tissue, and provide more specific information on tissue physiology than standard MRI. This review provides an overview of the most common and emerging advanced imaging modalities in the field of brain tumor imaging and their applications in the care of neuro-oncologic patients.

Can dynamic contrast-enhanced MRI evaluate VEGF expression in brain glioma? An MRI-guided stereotactic biopsy study

PURPOSE

To investigate whether pharmacokinetic parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) can be used to evaluate vascular endothelial growth factor (VEGF) expression in brain glioma based on a point-to-point basis.

MATERIALS AND METHODS

Forty-seven patients with treatment-naïve glioma received preoperative DCE-MRI before stereotactic biopsy. We histologically quantified VEGF from section of stereotactic biopsies, and co-registered biopsy locations with localized measurements of DCE-MRI parameters including volume transfer coefficient (K^trans), reverse reflux rate constant (Kep), extracellular extravascular volume fraction (Ve) and blood plasma volume (Vp). The correlations between DCE-MRI parameters (K^trans, Kep, Ve and Vp) and VEGF were determined using Spearman correlation coefficient. P≤.05 was considered statistically significant.

RESULTS

Seventy-nine biopsy samples were obtained and graded into 45 high-grade gliomas (HGGs) and 34 low-grade gliomas (LGGs). K^trans showed a significant positive correlation with VEGF expression in HGGs group (ρ=0.505, P<0.001) and in combined group (LGGs+HGGs) (ρ=0.549, P<0.001), but not in LGGs group (P>0.05). Kep, Ve or Vp was not correlated with VEGF even though a positive trend showed (P>0.05).

CONCLUSIONS

DCE-MRI is a useful, non-invasive imaging technique for quantitative evaluation of VEGF, and its parameter K^trans other than Kep, Ve or Vp may be used as a surrogate for VEGF expression in brain gliomas.

Investigation of hypoxia conditions using oxygen-enhanced magnetic resonance imaging measurements in glioma models

The objective of this study was to determine whether using oxygen-enhanced magnetic resonance imaging (OE-MRI) to assess hypoxia is feasible and whether historical measurements, pO2 changes, and percentage of signal intensity changes (PSIC) are correlated in an animal model of glioma. A total of 25 Sprague-Dawley rats were used to establish C6 brain or subcutaneous glioma model. Nine rats with brain gliomas underwent OE-MRI followed by histopathologic analysis to assess microvessel density and hypoxia. Another 11 rats were underwent OE-MRI and were followed for a survival analysis. Time-T1-weighted MR signal intensity (SI) curves and PSIC maps were derived from the OE-MRI data. High-regions of interests (ROI-h; PSIC > 10%) and low-ROIs (ROI-l; PSIC < 10%) were defined on the PSIC maps. To validate the PSIC map for identifying tumor hypoxia, we subjected an additional 5 rats with subcutaneous glioma to OE-MRI and pO2 measurements. All tumors showed regional heterogeneity on the PSIC maps. For the brain tumors, the time-SI curves for the ROIs-h showed a greater increase in SI than those for the ROIs-l did. The percentage of tumor area with a low PSIC was significantly correlated with the percentage of hypoxia staining and necrosis (r =0.71; P<0.05). ROIs with a higher PSIC typically had more vessels (r=0.88; P<0.05). A significant difference in survival was shown (log-rank P = 0.035). The time-pO2 curves of the subcutaneous tumors were similar to the time-SI curves. PSIC was significantly correlated with pO2 changes (r =0.82; P<0.05). These findings suggest that OE-MRI measurements can be used to assess hypoxia in C6 glioma models. In these models, the PSIC value was correlated with survival, indicating that PSIC could serve as a prognostic marker for glioma.