Cerebral and tumoral blood flow in adult gliomas: a systematic review of results from magnetic resonance imaging

Use of radiofrequency electromagnetic fields applied by capacitive hyperthermia for glioblastoma therapy

INTRODUCTION

Radiofrequency electromagnetic fields applied by capacitive hyperthermia (cRF-HT) might be applicable to improve therapy for glioblastoma patients, but computer simulation data is scarce. We aimed to perform a numerical analysis of cRF-HT treatment in glioblastoma patients.

METHODS

The EHY-2030 cRF-HT system (Oncotherm, Budapest, Hungary) was studied using a round 20 cm diameter electrode. Realistic head models and quasi-electrostatic finite element simulations were created (Sim4Life v7.2, ZurichMedTech, Zürich, Switzerland). First, 109 spherical glioblastoma localizations were created within a healthy head model, and three different electrode setups were used to simulate the specific absorption rate (SAR). Then, in 20 real glioblastoma patients, the E-field and SAR in the gross tumor volume (GTV) and its boundary zone were simulated, and transient temperature simulations were performed.

RESULTS

The simulations conducted on 20 patients revealed that the SAR achieved in the GTV and its surrounding boundary zone is highly dependent on the localization of the tumor, with a mean SAR of 24.3 W/kg (ranging from 11.5 to 46.7 W/kg). The mean temperature within the GTV was higher in patients with a resection cavity (mean T50: 40.1 °C) instead of a macroscopic tumor (mean T50: 37.8 °C). The simulation outcome for the 109 artificial tumor localizations indicated enhanced effectiveness when the electrode is setup as close to the GTV as possible.

CONCLUSION

cRF-HT may induce mild hyperthermia in a subgroup of glioblastoma patients with resection cavities. In macroscopic tumors, temperatures remain below the hyperthermia threshold. Further research is required to assess the clinical benefit of this therapy.

Blood-oxygenation-level-dependent (BOLD) MRI responses to CO2 and O2 inhalation in brain gliomas

PURPOSE

Cerebrovascular abnormalities are intricately involved in gliomas. While static cerebrovascular properties such as cerebral blood flow, volume, and permeability have been extensively studied, dynamic vascular parameters have not been fully understood. This study aimed to characterize the vascular responses to CO2 and O2 inhalation in brain gliomas.

METHODS

In 15 glioma patients, concomitant CO2 and O2 inhalation was applied while BOLD MR images were continuously acquired for nine minutes, resulting in the measurement of O2-reactivity, CO2-reactivity, and bolus arrival time (BAT). Vascular parameters were compared between the tumor regions and contralateral healthy tissue using Student t-tests. The dependence of vascular parameters on glioma grade, glioma subtypes, and molecular biomarkers were assessed using a multiple linear regression.

RESULTS

Visual inspection suggested that reliable O2-reactivity, CO2-reactivity, and BAT maps could be obtained in every patient. Compared to the contralateral healthy tissue, glioma regions on average revealed a diminished O2-reactivity (p < 0.001) and CO2-reactivity (p < 0.001), but a lengthened BAT (p < 0.001). Intra-tumoral heterogeneity in the vascular parameters between core and periphery was also observed. Astrocytomas had a lower CO2-reactivity (p = 0.014) and a longer BAT (p = 0.012) relative to oligodendrogliomas. Glioma grade had no association with O2-reactivity, CO2-reactivity, or BAT. Patients who lost ATRX expression had a lower CO2- and O2-reactivity (p = 0.005 and p = 0.035) compared to patients who retained ATRX expression.

CONCLUSIONS

Gliomas are associated with abnormal CO2- and O2-reactivity measured with MRI. These dynamic parameters may provide new insights into the vascular pathophysiology in gliomas.

Radiomics analysis of cerebral blood flow suggests a possible link between perfusion homogeneity and poor glioblastoma multiforme prognosis

Objectives. This study investigates the association between cerebral blood flow (CBF) and overall survival (OS) in glioblastoma multiforme (GBM) patients receiving chemoradiation. Identifying CBF biomarkers could help predict patient response to this treatment, facilitating the development of personalized therapeutic strategies.Materials and Methods. This retrospective study analyzed CBF data from dynamic susceptibility contrast (DSC) MRI in 30 newly diagnosed GBM patients (WHO grade IV). Radiomics features were extracted from CBF maps, tested for robustness, and correlated with OS. Kaplan-Meier analysis was used to assess the predictive value of radiomic features significantly associated with OS, aiming to stratify patients into groups with distinct post-treatment survival outcomes.Results. While mean relative CBF and CBV failed to serve as independent prognostic markers for OS, the prognostic potential of radiomic features extracted from CBF maps was explored. Ten out of forty-three radiomic features with highest intraclass correlation coefficients (ICC > 0.9), were selected for characterization. While Correlation and Zone Size Variance (ZSV) features showed significant OS correlations, indicating prognostic potential, Kaplan-Meier analysis did not significantly stratify patients based on these features. Visual analysis of the graphs revealed a predominant association between the identified radiomic features and OS under two years. Focusing on this subgroup, Correlation, ZSV, and Gray-Level Nonuniformity (GLN) emerged as significant, suggesting that a lack of heterogeneity in perfusion patterns may be indicative of a poorer outcome. Kaplan-Meier analysis effectively stratified this cohort based on the features mentioned above. Receiver operating characteristic (ROC) analysis further validated their prognostic value, with ZSV demonstrating the highest sensitivity and specificity (0.75 and 0.85, respectively).Conclusion. Our findings underscored radiomics features sensitive to CBF heterogeneity as pivotal predictors for patient stratification. Our results suggest that these markers may have the potential to identify patients who are unlikely to benefit from standard chemoradiation therapy.

Looking through the imaging perspective: the importance of imaging necrosis in glioma diagnosis and prognostic prediction - single centre experience

BACKGROUND

The aim of the study was to investigate the diagnostic value of imaging necrosis (Imnecrosis) in grading, predict the genotype and prognosis of gliomas, and further assess tumor necrosis by dynamic contrast-enhanced MR perfusion imaging (DCE-MRI).

PATIENTS AND METHODS

We retrospectively included 150 patients (104 males, mean age: 46 years old) pathologically proved as adult diffuse gliomas and all diagnosis was based on the 2021 WHO central nervous system (CNS) classification. The pathological necrosis (Panecrosis) and gene mutation information were collected. All patients underwent conventional and DCE-MRI examinations and had been followed until May 31, 2021. The Imnecrosis was determined by two experienced neuroradiologists. DCE-MRI derived metric maps have been post-processed, and the mean value of each metric in the tumor parenchyma, peritumoral and contralateral area were recorded.

RESULTS

There was a strong degree of inter-observer agreement in defining Imnecrosis (Kappa = 0.668, p < 0.001) and a strong degree of agreement between Imnecrosis and Panecrosis (Kappa = 0.767, p < 0.001). Compared to low-grade gliomas, high-grade gliomas had more Imnecrosis (85.37%, p < 0.001), and Imnecrosis significantly increased with the grade of gliomas increasing. And Imnecrosis was significantly more identified in IDH-wildtype, 1p19q-non-codeletion, and CDKN2A/B-homozygous-deletion gliomas. Using multivariate Cox regression analysis, Imnecrosis was an independent and unfavorable prognosis factor (Hazard Ratio = 2.113, p = 0.046) in gliomas. Additionally, extravascular extracellular volume fraction (ve) in tumor parenchyma derived from DCE-MRI demonstrated the highest diagnostic efficiency in identifying Panecrosis and Imnecrosis with high specificity (83.3% and 91.9%, respectively).

CONCLUSIONS

Imnecrosis can provide supplementary evidence beyond Panecrosis in grading, predicting the genotype and prognosis of gliomas, and ve in tumor parenchyma can help to predict tumor necrosis with high specificity.

The surgical management of diffuse gliomas: Current state of neurosurgical management and future directions

After recent updates to the World Health Organization pathological criteria for diagnosing and grading diffuse gliomas, all major North American and European neuro-oncology societies recommend a maximal safe resection as the initial management of a diffuse glioma. For neurosurgeons to achieve this goal, the surgical plan for both low- and high-grade gliomas should be to perform a supramaximal resection when feasible based on preoperative imaging and the patient's performance status, utilizing every intraoperative adjunct to minimize postoperative neurological deficits. While the surgical approach and technique can vary, every effort must be taken to identify and preserve functional cortical and subcortical regions. In this summary statement on the current state of the field, we describe the tools and technologies that facilitate the safe removal of diffuse gliomas and highlight intraoperative and postoperative management strategies to minimize complications for these patients. Moreover, we discuss how surgical resections can go beyond cytoreduction by facilitating biological discoveries and improving the local delivery of adjuvant chemo- and radiotherapies.

Visualising spatial heterogeneity in glioblastoma using imaging habitats

Glioblastoma is a high-grade aggressive neoplasm characterised by significant intra-tumoral spatial heterogeneity. Personalising therapy for this tumour requires non-invasive tools to visualise its heterogeneity to monitor treatment response on a regional level. To date, efforts to characterise glioblastoma's imaging features and heterogeneity have focussed on individual imaging biomarkers, or high-throughput radiomic approaches that consider a vast number of imaging variables across the tumour as a whole. Habitat imaging is a novel approach to cancer imaging that identifies tumour regions or 'habitats' based on shared imaging characteristics, usually defined using multiple imaging biomarkers. Habitat imaging reflects the evolution of imaging biomarkers and offers spatially preserved assessment of tumour physiological processes such perfusion and cellularity. This allows for regional assessment of treatment response to facilitate personalised therapy. In this review, we explore different methodologies to derive imaging habitats in glioblastoma, strategies to overcome its technical challenges, contrast experiences to other cancers, and describe potential clinical applications.

Assessment of brain tumors by magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging and computed tomography perfusion: a comparison study

PURPOSE

To investigate the association and agreement between magnetic resonance dynamic susceptibility contrast perfusion-weighted imaging (DSC-PWI) and computed tomography perfusion (CTP) in determining vascularity and permeability of primary and secondary brain tumors.

MATERIAL AND METHODS

DSC-PWI and CTP studies from 97 patients with high-grade glioma, low-grade glioma and solitary brain metastasis were retrospectively reviewed. Normalized cerebral blood flow (nCBF), cerebral blood volume (nCBV), capillary transfer constant (nK2) and permeability surface area product (nPS) values were obtained. Variables among groups were compared, and correlation and agreement between DSC-PWI and CTP were tested.

RESULTS

All DSC-PWI and CTP parameters were higher in high-grade than in low-grade gliomas (p < 0.01 and p < 0.001). Metastases had greater DSC-PWI nCBV (p < 0.05), nCTP-CBF (p < 0.05), nCTP-CBV (p < 0.01) and nCTP-PS (p < 0.0001) than low-grade gliomas and more elevated nCTP-PS (p < 0.01) than high-grade gliomas. The correlation was strong between DSC-PWI nCBF and CTP nCBF (r = 0.79; p < 0.00001) and between DSC-PWI nCBV and CTP nCBV (r = 0.83; p < 0.00001), weaker between DSC-PWI nK2 and CTP nPS (r = 0.29; p < 0.01). Bland-Altman plots indicated that the agreement was strong between DSC-PWI nCBF and CTP nCBF, good between DSC-PWI nCBV and CTP nCBV and poorer between DSC-PWI nK2 and CTP nPS.

CONCLUSION

DSC-PWI and CTP CBF and CBV maps were comparable and interchangeable in the assessment of tumor vascularity, unlike DSC-PWI K2 and CTP PS maps that were more discordant in the analysis of tumor permeability. CTP could be an alternative method to quantify tumor neoangiogenesis when MRI is not available or when the patient does not tolerate it.

Non-parametric deconvolution using Bézier curves for quantification of cerebral perfusion in dynamic susceptibility contrast MRI

Objective

Deconvolution is an ill-posed inverse problem that tends to yield non-physiological residue functions R(t) in dynamic susceptibility contrast magnetic resonance imaging (DSC-MRI). In this study, the use of Bézier curves is proposed for obtaining physiologically reasonable residue functions in perfusion MRI.

Materials and methods

Cubic Bézier curves were employed, ensuring R(0) = 1, bounded-input, bounded-output stability and a non-negative monotonically decreasing solution, resulting in 5 parameters to be optimized. Bézier deconvolution (BzD), implemented in a Bayesian framework, was tested by simulation under realistic conditions, including effects of arterial delay and dispersion. BzD was also applied to DSC-MRI data from a healthy volunteer.

Results

Bézier deconvolution showed robustness to different underlying residue function shapes. Accurate perfusion estimates were observed, except for boxcar residue functions at low signal-to-noise ratio. BzD involving corrections for delay, dispersion, and delay with dispersion generally returned accurate results, except for some degree of cerebral blood flow (CBF) overestimation at low levels of each effect. Maps of mean transit time and delay were markedly different between BzD and block-circulant singular value decomposition (oSVD) deconvolution.

Discussion

A novel DSC-MRI deconvolution method based on Bézier curves was implemented and evaluated. BzD produced physiologically plausible impulse response, without spurious oscillations, with generally less CBF underestimation than oSVD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10334-021-00995-0.