Evaluation of MR markers that predict survival in patients with newly diagnosed GBM prior to adjuvant therapy

PDZK1 is correlated with DCE-MRI perfusion parameters in high-grade glioma

OBJECTIVE

This study investigated the relationship between PDZK1 expression and Dynamic Contrast-Enhanced MRI (DCE-MRI) perfusion parameters in High-Grade Glioma (HGG).

METHODS

Preoperative DCE-MRI scanning was performed on 80 patients with HGG to obtain DCE perfusion transfer coefficient (Ktrans), vascular plasma volume fraction (vp), extracellular volume fraction (ve), and reverse transfer constant (kep). PDZK1 in HGG patients was detected, and its correlation with DCE-MRI perfusion parameters was assessed by the Pearson method. An analysis of Cox regression was performed to determine the risk factors affecting survival, while Kaplan-Meier and log-rank tests to evaluate PDZK1's prognostic significance, and ROC curve analysis to assess its diagnostic value.

RESULTS

PDZK1 was upregulated in HGG patients and predicted poor overall survival and progression-free survival. Moreover, PDZK1 expression distinguished grade III from grade IV HGG. PDZK1 expression was positively correlated with Ktrans 90, and ve_90, and negatively correlated with kep_max, and kep_90.

CONCLUSION

PDZK1 is upregulated in HGG, predicts poor survival, and differentiates tumor grading in HGG patients. PDZK1 expression is correlated with DCE-MRI perfusion parameters.

Prognostic value of preoperative diffusion restriction in glioblastoma

INTRODUCTION

Although glioblastoma (GBM) has a very poor prognosis, overall survival (OS) in treated patients shows great difference varying from few days to several months. Identifying factors explaining this difference would improve management of patient treatment.

AIM

To determine the relevance of diffusion restriction in newly diagnosed treatment-naïve GBM patients.

METHODS

Preoperative magnetic resonance scans of 33 patients with GBM were reviewed. Regions of interest including all the T2 hyperintense lesion were drawn on diffusion weighted B0 images and transferred to the apparent diffusion coefficient (ADC) map. For each patient, a histogram displaying the ADC values within in the regions of interest was generated. Volumetric parameters including tumor regions with restricted diffusion, parameters derived from histogram and mean ADC value of the tumor were calculated. Their relationship with OS was analyzed.

RESULTS

Patients with mean ADC value < 1415x10-6 mm2/s had a significantly shorter OS (p=0.021). Among volumetric parameters, the percentage of volume within T2 lesion with a normalized ADC value <1.5 times that in white matter was significantly associated with OS (p=0.0045). Patients with a percentage>23.92% had a shorter OS. Among parameters derived from histogram, the 50th percentile showed a trend towards significance for OS (p=0.055) with patients living longer when having higher values of 50th percentile. A difference in OS was observed between patients according to ADC peak of histogram but this difference did not reach statistical significance (p=0.0959).

CONCLUSION

Diffusion magnetic resonance imaging may provide useful information for predicting GBM prognosis.

Advances in Neuro-Oncological Imaging: An Update on Diagnostic Approach to Brain Tumors

This study delineates the pivotal role of imaging within the field of neurology, emphasizing its significance in the diagnosis, prognostication, and evaluation of treatment responses for central nervous system (CNS) tumors. A comprehensive understanding of both the capabilities and limitations inherent in emerging imaging technologies is imperative for delivering a heightened level of personalized care to individuals with neuro-oncological conditions. Ongoing research in neuro-oncological imaging endeavors to rectify some limitations of radiological modalities, aiming to augment accuracy and efficacy in the management of brain tumors. This review is dedicated to the comparison and critical examination of the latest advancements in diverse imaging modalities employed in neuro-oncology. The objective is to investigate their respective impacts on diagnosis, cancer staging, prognosis, and post-treatment monitoring. By providing a comprehensive analysis of these modalities, this review aims to contribute to the collective knowledge in the field, fostering an informed approach to neuro-oncological care. In conclusion, the outlook for neuro-oncological imaging appears promising, and sustained exploration in this domain is anticipated to yield further breakthroughs, ultimately enhancing outcomes for individuals grappling with CNS tumors.

Advanced Hyperpolarized 13C Metabolic Imaging Protocol for Patients with Gliomas: A Comprehensive Multimodal MRI Approach

This study aimed to implement a multimodal 1H/HP-13C imaging protocol to augment the serial monitoring of patients with glioma, while simultaneously pursuing methods for improving the robustness of HP-13C metabolic data. A total of 100 1H/HP [1-13C]-pyruvate MR examinations (104 HP-13C datasets) were acquired from 42 patients according to the comprehensive multimodal glioma imaging protocol. Serial data coverage, accuracy of frequency reference, and acquisition delay were evaluated using a mixed-effects model to account for multiple exams per patient. Serial atlas-based HP-13C MRI demonstrated consistency in volumetric coverage measured by inter-exam dice coefficients (0.977 ± 0.008, mean ± SD; four patients/11 exams). The atlas-derived prescription provided significantly improved data quality compared to manually prescribed acquisitions (n = 26/78; p = 0.04). The water-based method for referencing [1-13C]-pyruvate center frequency significantly reduced off-resonance excitation relative to the coil-embedded [13C]-urea phantom (4.1 ± 3.7 Hz vs. 9.9 ± 10.7 Hz; p = 0.0007). Significantly improved capture of tracer inflow was achieved with the 2-s versus 5-s HP-13C MRI acquisition delay (p = 0.007). This study demonstrated the implementation of a comprehensive multimodal 1H/HP-13C MR protocol emphasizing the monitoring of steady-state/dynamic metabolism in patients with glioma.

Brain Tumor Imaging: Review of Conventional and Advanced Techniques

Approaches to central nervous system (CNS) tumor classification and evaluation have undergone multiple iterations over the past few decades, in large part due to our growing understanding of the influence of genetics on tumor behavior and our refinement of brain tumor imaging techniques. Computed tomography and magnetic resonance imaging (MRI) both play a critical role in the diagnosis and monitoring of brain tumors, although MRI has become especially important due to its superior soft tissue resolution. The purpose of this article will be to briefly review the fundamentals of conventional and advanced techniques used in brain tumor imaging. We will also highlight the applications of these imaging tools in the context of commonly encountered tumors based on the most recently updated 2021 World Health Organization (WHO) classification of CNS tumors framework.

Association of MRI Volume Parameters in Predicting Patient Outcome at Time of Initial Diagnosis of Glioblastoma

PURPOSE

Patients with glioblastoma (GBM) may demonstrate varying patterns of infiltration and relapse. Improving the ability to predict these patterns may influence the management strategies at the time of initial diagnosis. This study aims to examine the impact of the ratio (T2/T1) of the non-enhancing volume in T2-weighted images (T2) to the enhancing volume in MRI T1-weighted gadolinium-enhanced images (T1gad) on patient outcome.

METHODS AND MATERIALS

A retrospective audit was performed from established prospective databases in patients managed consecutively with radiation therapy (RT) for GBM between 2016 and 2019. Patient, tumour and treatment-related factors were assessed in relation to outcome. Volumetric data from the initial diagnostic MRI were obtained via the manual segmentation of the T1gd and T2 abnormalities. A T2/T1 ratio was calculated from these volumes. The initial relapse site was assessed on MRI in relation to the site of the original T1gad volume and surgical cavity. The major endpoints were median relapse-free survival (RFS) from the date of diagnosis and site of initial relapse (defined as either local at the initial surgical site or any distance more than 20 mm from initial T1gad abnormality). The analysis was performed for association between known prognostic factors as well as the radiological factors using log-rank tests for subgroup comparisons, with correction for multiple comparisons.

RESULTS

One hundred and seventy-seven patients with GBM were managed consecutively with RT between 2016 and 2019 and were eligible for the analysis. The median age was 62 years. Seventy-four percent were managed under a 60Gy (Stupp) protocol, whilst 26% were on a 40Gy (Elderly) protocol. Major neuroanatomical subsites were Lateral Temporal (18%), Anterior Temporal (13%) and Medial Frontal (10%). Median volumes on T1gd and T2 were 20 cm3 (q1-3:8-43) and 37 cm3 (q1-3: 17-70), respectively. The median T2/T1 ratio was 2.1. For the whole cohort, the median OS was 16.0 months (95%CI:14.1-18.0). One hundred and forty-eight patients have relapsed with a median RFS of 11.4 months (95%CI:10.4-12.5). A component of distant relapse was evident in 43.9% of relapses, with 23.6% isolated relapse. Better ECOG performance Status (p = 0.007), greater extent of resection (p = 0.020), MGMT methylation (p < 0.001) and RT60Gy Dose (p = 0.050) were associated with improved RFS. Although the continuous variable of initial T1gd volume (p = 0.39) and T2 volume (p = 0.23) were not associated with RFS, the lowest T2/T1 quartile (reflecting a relatively lower T2 volume compared to T1gd volume) was significantly associated with improved RFS (p = 0.016) compared with the highest quartile. The lowest T2/T1 ratio quartile was also associated with a lower risk of distant relapse (p = 0.031).

CONCLUSION

In patients diagnosed with GBM, the volumetric parameters of the diagnostic MRI with a ratio of T2 and T1gad abnormality may assist in the prediction of relapse-free survival and patterns of relapse. A further understanding of these relationships has the potential to impact the design of future radiation therapy target volume delineation protocols.

The STEMRI trial: Magnetic resonance spectroscopy imaging can define tumor areas enriched in glioblastoma stem-like cells

Despite maximally safe resection of the magnetic resonance imaging (MRI)-defined contrast-enhanced (CE) central tumor area and chemoradiotherapy, most patients with glioblastoma (GBM) relapse within a year in peritumoral FLAIR regions. Magnetic resonance spectroscopy imaging (MRSI) can discriminate metabolic tumor areas with higher recurrence potential as CNI+ regions (choline/N-acetyl-aspartate index >2) can predict relapse sites. As relapses are mainly imputed to glioblastoma stem-like cells (GSCs), CNI+ areas might be GSC enriched. In this prospective trial, 16 patients with GBM underwent MRSI/MRI before surgery/chemoradiotherapy to investigate GSC content in CNI-/+ biopsies from CE/FLAIR. Biopsy and derived-GSC characterization revealed a FLAIR/CNI+ sample enrichment in GSC and in gene signatures related to stemness, DNA repair, adhesion/migration, and mitochondrial bioenergetics. FLAIR/CNI+ samples generate GSC-enriched neurospheres faster than FLAIR/CNI-. Parameters assessing biopsy GSC content and time-to-neurosphere formation in FLAIR/CNI+ were associated with worse patient outcome. Preoperative MRI/MRSI would certainly allow better resection and targeting of FLAIR/CNI+ areas, as their GSC enrichment can predict worse outcomes.

Multi-parametric hyperpolarized 13C/1H imaging reveals Warburg-related metabolic dysfunction and associated regional heterogeneity in high-grade human gliomas

BACKGROUND

Dynamic hyperpolarized (HP)-13C MRI has enabled real-time, non-invasive assessment of Warburg-related metabolic dysregulation in glioma using a [1-13C]pyruvate tracer that undergoes conversion to [1-13C]lactate and [13C]bicarbonate. Using a multi-parametric 1H/HP-13C imaging approach, we investigated dynamic and steady-state metabolism, together with physiological parameters, in high-grade gliomas to characterize active tumor.

METHODS

Multi-parametric 1H/HP-13C MRI data were acquired from fifteen patients with progressive/treatment-naïve glioblastoma [prog/TN GBM, IDH-wildtype (n = 11)], progressive astrocytoma, IDH-mutant, grade 4 (G4AIDH+, n = 2) and GBM manifesting treatment effects (n = 2). Voxel-wise regional analysis of the cohort with prog/TN GBM assessed imaging heterogeneity across contrast-enhancing/non-enhancing lesions (CEL/NEL) and normal-appearing white matter (NAWM) using a mixed effects model. To enable cross-nucleus parameter association, normalized perfusion, diffusion, and dynamic/steady-state (HP-13C/spectroscopic) metabolic data were collectively examined at the 13C resolution. Prog/TN GBM were similarly compared against progressive G4AIDH+ and treatment effects.

RESULTS

Regional analysis of Prog/TN GBM metabolism revealed statistically significant heterogeneity in 1H choline-to-N-acetylaspartate index (CNI)max, [1-13C]lactate, modified [1-13C]lactate-to-[1-13C]pyruvate ratio (CELval > NELval > NAWMval); [1-13C]lactate-to-[13C]bicarbonate ratio (CELval > NELval/NAWMval); and 1H-lactate (CELval/NELval > NAWMundetected). Significant associations were found between normalized perfusion (cerebral blood volume, nCBV; peak height, nPH) and levels of [1-13C]pyruvate and [1-13C]lactate, as well as between CNImax and levels of [1-13C]pyruvate, [1-13C]lactate and modified ratio. GBM, by comparison to G4AIDH+, displayed lower perfusion %-recovery and modeled rate constants for [1-13C]pyruvate-to-[1-13C]lactate conversion (kPL), and higher 1H-lactate and [1-13C]pyruvate levels, while having higher nCBV, %-recovery, kPL, [1-13C]pyruvate-to-[1-13C]lactate and modified ratios relative to treatment effects.

CONCLUSIONS

GBM consistently displayed aberrant, Warburg-related metabolism and regional heterogeneity detectable by novel HP-13C/1H imaging techniques.

Is pre-radiotherapy metabolic heterogeneity of glioblastoma predictive of progression-free survival?

BACKGROUND AND PURPOSE

All glioblastoma subtypes share the hallmark of aggressive invasion, meaning that it is crucial to identify their different components if we are to ensure effective treatment and improve survival. Proton MR spectroscopic imaging (MRSI) is a noninvasive technique that yields metabolic information and is able to identify pathological tissue with high accuracy. The aim of the present study was to identify clusters of metabolic heterogeneity, using a large MRSI dataset, and determine which of these clusters are predictive of progression-free survival (PFS).

MATERIALS AND METHODS

MRSI data of 180 patients acquired in a pre-radiotherapy examination were included in the prospective SPECTRO-GLIO trial. Eight features were extracted for each spectrum: Cho/NAA, NAA/Cr, Cho/Cr, Lac/NAA, and the ratio of each metabolite to the sum of all the metabolites. Clustering of data was performed using a mini-batch k-means algorithm. The Cox model and logrank test were used for PFS analysis.

RESULTS

Five clusters were identified as sharing similar metabolic information and being predictive of PFS. Two clusters revealed metabolic abnormalities. PFS was lower when Cluster 2 was the dominant cluster in patients' MRSI data. Among the metabolites, lactate (present in this cluster and in Cluster 5) was the most statistically significant predictor of poor outcome.

CONCLUSION

Results showed that pre-radiotherapy MRSI can be used to reveal tumor heterogeneity. Groups of spectra, which have the same metabolic information, reflect the different tissue components representative of tumor burden proliferation and hypoxia. Clusters with metabolic abnormalities and high lactate are predictive of PFS.

Peritumoral ADC Values Correlate with the MGMT Methylation Status in Patients with Glioblastoma

Different results have been reported concerning the relationship of the apparent diffusion coefficient (ADC) values and the status of methylation as the promoter gene for the enzyme methylguanine-DNA methyltransferase (MGMT) in patients with glioblastomas (GBs). The aim of this study was to investigate if there were correlations between the ADC values of the enhancing tumor and peritumoral areas of GBs and the MGMT methylation status. In this retrospective study, we included 42 patients with newly diagnosed unilocular GB with one MRI study prior to any treatment and histopathological data. After co-registration of ADC maps with T1-weighted sequences after contrast administration and dynamic susceptibility contrast (DSC) perfusion, we manually selected one region-of-interest (ROI) in the enhancing and perfused tumor and one ROI in the peritumoral white matter. Both ROIs were mirrored in the healthy hemisphere for normalization. In the peritumoral white matter, absolute and normalized ADC values were significantly higher in patients with MGMT-unmethylated tumors, as compared to patients with MGMT-methylated tumors (absolute values p = 0.002, normalized p = 0.0007). There were no significant differences in the enhancing tumor parts. The ADC values in the peritumoral region correlated with MGMT methylation status, confirmed by normalized ADC values. In contrast to other studies, we could not find a correlation between the ADC values or the normalized ADC values and the MGMT methylation status in the enhancing tumor parts.

Spectroscopic imaging of D-2-hydroxyglutarate and other metabolites in pre-surgical patients with IDH-mutant lower-grade gliomas

Purpose

Prognostically favorable IDH-mutant gliomas are known to produce oncometabolite D-2-hydroxyglutarate (2HG). In this study, we investigated metabolite-based features of patients with grade 2 and 3 glioma using 2HG-specific in vivo MR spectroscopy, to determine their relationship with image-guided tissue pathology and predictive role in progression-free survival (PFS).

Methods

Forty-five patients received pre-operative MRIs that included 3-D spectroscopy optimized for 2HG detection. Spectral data were reconstructed and quantified to compare metabolite levels according to molecular pathology (IDH1R132H, 1p/19q, and p53); glioma grade; histological subtype; and T2 lesion versus normal-appearing white matter (NAWM) ROIs. Levels of 2HG were correlated with other metabolites and pathological parameters (cellularity, MIB-1) from image-guided tissue samples using Pearson’s correlation test. Metabolites predictive of PFS were evaluated with Cox proportional hazards models.

Results

Quantifiable levels of 2HG in 39/42 (93%) IDH+ and 1/3 (33%) IDH– patients indicated a 91.1% apparent detection accuracy. Myo-inositol/total choline (tCho) showed reduced values in astrocytic (1p/19q-wildtype), p53-mutant, and grade 3 (vs. 2) IDH-mutant gliomas (p < 0.05), all of which exhibited higher proportions of astrocytomas. Compared to NAWM, T2 lesions displayed elevated 2HG+ γ-aminobutyric acid (GABA)/total creatine (tCr) (p < 0.001); reduced glutamate/tCr (p < 0.001); increased myo-inositol/tCr (p < 0.001); and higher tCho/tCr (p < 0.001). Levels of 2HG at sampled tissue locations were significantly associated with tCho (R = 0.62; p = 0.002), total NAA (R = − 0.61; p = 0.002) and cellularity (R = 0.37; p = 0.04) but not MIB-1. Increasing levels of 2HG/tCr (p = 0.0007, HR 5.594) and thresholding (≥ 0.905, median value; p = 0.02) predicted adverse PFS.

Conclusion

In vivo 2HG detection can reasonably be achieved on clinical scanners and increased levels may signal adverse PFS.

Glioblastoma Stem-like Cell Detection Using Perfusion and Diffusion MRI

Simple Summary

Glioblastoma stem-like cells (GSCs) are known to be aggressive and radio-resistant and proliferate heterogeneously in preferred environments. Additionally, quantitative diffusion and perfusion MRI biomarkers provide insight into the tissue micro-environment. This study assessed the sensitivity of these imaging biomarkers to GSCs in the hyperintensities-FLAIR region, where relapses may occur. A total of 16 patients underwent an MRI session and biopsies were extracted to study the GSCs. In vivo and in vitro biomarkers were compared and both Apparent Diffusion Coefficient (ADC) and relative Cerebral Blood Volume (rCBV) MRI metrics were found to be good predictors of GSCs presence and aggressiveness.

Abstract

Purpose: With current gold standard treatment, which associates maximum safe surgery and chemo-radiation, the large majority of glioblastoma patients relapse within a year in the peritumoral non contrast-enhanced region (NCE). A subpopulation of glioblastoma stem-like cells (GSC) are known to be particularly radio-resistant and aggressive, and are thus suspected to be the cause of these relapses. Previous studies have shown that their distribution is heterogeneous in the NCE compartment, but no study exists on the sensitivity of medical imaging for localizing these cells. In this work, we propose to study the magnetic resonance (MR) signature of these infiltrative cells. Methods: In the context of a clinical trial on 16 glioblastoma patients, relative Cerebral Blood Volume (rCBV) and Apparent Diffusion Coefficient (ADC) were measured in a preoperative diffusion and perfusion MRI examination. During surgery, two biopsies were extracted using image-guidance in the hyperintensities-FLAIR region. GSC subpopulation was quantified within the biopsies and then cultivated in selective conditions to determine their density and aggressiveness. Results: Low ADC was found to be a good predictor of the time to GSC neurospheres formation in vitro. In addition, GSCs were found in higher concentrations in areas with high rCBV. Conclusions: This study confirms that GSCs have a critical role for glioblastoma aggressiveness and supports the idea that peritumoral sites with low ADC or high rCBV should be preferably removed when possible during surgery and targeted by radiotherapy.

Combined Diagnostic Accuracy of Diffusion and Perfusion MR Imaging to Differentiate Radiation-Induced Necrosis from Recurrence in Glioblastoma

We aimed to use quantitative values derived from perfusion and diffusion-weighted MR imaging (PWI and DWI) to differentiate radiation-induced necrosis (RIN) from tumor recurrence in Glioblastoma (GBM) and investigate the best parameters for improved diagnostic accuracy and clinical decision-making. Methods: A retrospective analysis of follow-up MRI with new enhancing observations was performed in histopathologically confirmed subjects of post-treated GBM, who underwent re-surgical exploration. Quantitative estimation of rCBV (relative cerebral blood volume) from PWI and three methods of apparent diffusion coefficient (ADC) estimation were performed, namely ADC R1 (whole cross-sectional area of tumor), ADC R2 (only solid enhancing lesion), and ADC R3 (central necrosis). ROC curve and logistic regression analysis was completed. A confusion matrix table created using Excel provided the best combination parameters to ameliorate false-positive and false-negative results. Results: Forty-four subjects with a mean age of 46 years (range, 19−70 years) underwent re-surgical exploration with RIN in 28 (67%) and recurrent tumor in 16 (33%) on histopathology. rCBV threshold of >3.4 had the best diagnostic accuracy (AUC = 0.93, 81% sensitivity and 89% specificity). A multiple logistic regression model showed significant contributions from rCBV (p < 0.001) and ADC R3 (p = 0.001). After analysis of confusion matrix ADC R3 > 2032 × 10−6 mm2 achieved 100% specificity with gain in sensitivity (94% vs. 56%). Conclusions: A combination of parameters had better diagnostic performance, and a stepwise combination of rCBV and ADC R3 obviated unnecessary biopsies in 10% (3/28), leading to improved clinical decision-making.

High-Grade Glioma Treatment Response Monitoring Biomarkers: A Position Statement on the Evidence Supporting the Use of Advanced MRI Techniques in the Clinic, and the Latest Bench-to-Bedside Developments. Part 1: Perfusion and Diffusion Techniques

Objective

Summarize evidence for use of advanced MRI techniques as monitoring biomarkers in the clinic, and highlight the latest bench-to-bedside developments.

Methods

Experts in advanced MRI techniques applied to high-grade glioma treatment response assessment convened through a European framework. Current evidence regarding the potential for monitoring biomarkers in adult high-grade glioma is reviewed, and individual modalities of perfusion, permeability, and microstructure imaging are discussed (in Part 1 of two). In Part 2, we discuss modalities related to metabolism and/or chemical composition, appraise the clinic readiness of the individual modalities, and consider post-processing methodologies involving the combination of MRI approaches (multiparametric imaging) or machine learning (radiomics).

Results

High-grade glioma vasculature exhibits increased perfusion, blood volume, and permeability compared with normal brain tissue. Measures of cerebral blood volume derived from dynamic susceptibility contrast-enhanced MRI have consistently provided information about brain tumor growth and response to treatment; it is the most clinically validated advanced technique. Clinical studies have proven the potential of dynamic contrast-enhanced MRI for distinguishing post-treatment related effects from recurrence, but the optimal acquisition protocol, mode of analysis, parameter of highest diagnostic value, and optimal cut-off points remain to be established. Arterial spin labeling techniques do not require the injection of a contrast agent, and repeated measurements of cerebral blood flow can be performed. The absence of potential gadolinium deposition effects allows widespread use in pediatric patients and those with impaired renal function. More data are necessary to establish clinical validity as monitoring biomarkers. Diffusion-weighted imaging, apparent diffusion coefficient analysis, diffusion tensor or kurtosis imaging, intravoxel incoherent motion, and other microstructural modeling approaches also allow treatment response assessment; more robust data are required to validate these alone or when applied to post-processing methodologies.

Conclusion

Considerable progress has been made in the development of these monitoring biomarkers. Many techniques are in their infancy, whereas others have generated a larger body of evidence for clinical application.

Determining the optimum tumor control probability model in radiotherapy of glioblastoma multiforme using magnetic resonance imaging data pre- and post- radiation therapy

Background:

Glioblastoma multiforme (GBM) is the most common and malignant brain tumor. The current standard of care is surgery followed by radiation therapy (RT). Radiotherapy treatment plan evaluation relies on radiobiological models for accurate estimation of tumor control probability (TCP). This study aimed to assess the impact of obtained magnetic resonance imaging (MRI) data before and 12 weeks after RT to achieve the optimum TCP model to improve dose prescriptions in radiation therapy of GBM.

Materials and Methods::

In this quasi-experimental study, MR images and its relevant data from 30 patients consisting of 9 females and 21 males (mean age of 46.3 ± 15.8 years) diagnosed with GBM, whose referred for radiotherapy were selected. The data of age, gender, tumor size, volume, and signal intensity using analysis of MRI data pre- and postradiotherapy were used for calculating TCP. TCP was calculated from three common radiobiological models including Poisson, linear quadratic, and equivalent uniform dose. The impact of some radiobiological parameters on final TCP in all patients planned with three-dimensional conformal radiation therapy was obtained.

Results:

A statistically significant difference was found among TCP in Poisson model compared to the other two models (P < 0.001). Changes in tumor volume and size after treatment were statistically significant (P < 0.05). Different combinations of radiobiological parameters (α/β and SF₂ in all models) observed were meaningful (P < 0.05).

Conclusion:

The results showed that among TCP radiobiological models, the optimum is the Poisson. The results also identified the importance of TCP radiobiological models in order to improve radiotherapy dose prescriptions.

Rapid Interval Recurrence of Glioblastoma Following Gross Total Resection: A Possible Indication for GammaTileⓇ Brachytherapy

Glioblastoma recurrence between initial resection and standard-of-care adjuvant chemoradiotherapy (CRT) is a negative prognostic factor in an already highly aggressive disease. Re-resection with GammaTileⓇ(GT Medical Technologies Inc., Tempe, AZ) placement affords expedited adjuvant radiation to mitigate the likelihood of such growth. Here, we report a glioblastoma patient who underwent re-resection and GammaTileⓇ (GT) placement within two months of the initial gross total resection due to regrowth that reached the size of the original presenting tumor. The patient subsequently received concurrent temozolomide and 60 Gy external beam to regions outside of the brachytherapy range, fulfilling the generally accepted Stupp regimen. The patient tolerated the treatment without complication. The dosimetrics and implications of the case presentation are reviewed.

Quantitative volumetric assessment of baseline enhancing tumor volume as an imaging biomarker predicts overall survival in patients with glioblastoma

BACKGROUND

Glioblastoma multiforme (GBM) is the commonest malignant primary brain tumor and still has one of the worst prognoses among cancers in general. There is a need for non-invasive methods to predict individual prognosis in patients with GBM.

PURPOSE

To evaluate quantitative volumetric tissue assessment of enhancing tumor volume on cranial magnetic resonance imaging (MRI) as an imaging biomarker for predicting overall survival (OS) in patients with GBM.

MATERIAL AND METHODS

MRI scans of 49 patients with histopathologically confirmed GBM were analyzed retrospectively. Baseline contrast-enhanced (CE) MRI sequences were transferred to a segmentation-based three-dimensional quantification tool, and the enhancing tumor component was analyzed. Based on a cut-off percentage of the enhancing tumor volume (PoETV) of >84.78%, samples were dichotomized, and the OS and intracranial progression-free survival (PFS) were evaluated. Univariable and multivariable analyses, including variables such as sex, Karnofsky Performance Status score, O⁶-methylguanine-DNA-methyltransferase status, age, and resection status, were performed using the Cox regression model.

RESULTS

The median OS and PFS were 16.9 and 7 months in the entire cohort, respectively. Patients with a CE tumor volume of >84.78% showed a significantly shortened OS (12.9 months) compared to those with a CE tumor volume of ≤84.78% (17.7 months) (hazard ratio [HR] 2.72; 95% confidence interval [CI] 1.22-6.03; P = 0.01). Multivariable analysis confirmed that PoETV had a significant prognostic role (HR 2.47; 95% CI 1.08-5.65; P = 0.03).

CONCLUSION

We observed a correlation between PoETV and OS. This imaging biomarker may help predict the OS of patients with GBM.

Multiparametric MRI assessment of response to convection-enhanced intratumoral delivery of MDNA55, an interleukin-4 receptor targeted immunotherapy, for recurrent glioblastoma

Background

Glioblastoma (GBM) is the most common malignant brain tumor and carries a dismal prognosis. Attempts to develop biologically targeted therapies are challenging as the blood-brain barrier can limit drugs from reaching their target when administered through conventional (intravenous or oral) routes. Furthermore, systemic toxicity of drugs often limits their therapeutic potential. To circumvent these problems, convection-enhanced delivery (CED) provides direct, targeted, intralesional therapy with a secondary objective to alter the tumor microenvironment from an immunologically "cold" (nonresponsive) to an "inflamed" (immunoresponsive) tumor.

Case Description

We report a patient with right occipital recurrent GBM harboring poor prognostic genotypes who was treated with MRI-guided CED of a fusion protein MDNA55 (a targeted toxin directed toward the interleukin-4 receptor). The patient underwent serial anatomical, diffusion, and perfusion MRI scans before initiation of targeted therapy and at 1, 3-month posttherapy. Increased mean diffusivity along with decreased fractional anisotropy and maximum relative cerebral blood volume was noted at follow-up periods relative to baseline.

Conclusion

Our findings suggest that diffusion and perfusion MRI techniques may be useful in evaluating early response to CED of MDNA55 in recurrent GBM patients.

Targeting pyruvate dehydrogenase kinase signaling in the development of effective cancer therapy

Pyruvate is irreversibly decarboxylated to acetyl coenzyme A by mitochondrial pyruvate dehydrogenase complex (PDC). Decarboxylation of pyruvate is considered a crucial step in cell metabolism and energetics. The cancer cells prefer aerobic glycolysis rather than mitochondrial oxidation of pyruvate. This attribute of cancer cells allows them to sustain under indefinite proliferation and growth. Pyruvate dehydrogenase kinases (PDKs) play critical roles in many diseases because they regulate PDC activity. Recent findings suggest an altered metabolism of cancer cells is associated with impaired mitochondrial function due to PDC inhibition. PDKs inhibit the PDC activity via phosphorylation of the E1a subunit and subsequently cause a glycolytic shift. Thus, inhibition of PDK is an attractive strategy in anticancer therapy. This review highlights that PDC/PDK axis could be implicated in cancer's therapeutic management by developing potential small-molecule PDK inhibitors. In recent years, a dramatic increase in the targeting of the PDC/PDK axis for cancer treatment gained an attention from the scientific community. We further discuss breakthrough findings in the PDC-PDK axis. In addition, structural features, functional significance, mechanism of activation, involvement in various human pathologies, and expression of different forms of PDKs (PDK1-4) in different types of cancers are discussed in detail. We further emphasized the gene expression profiling of PDKs in cancer patients to prognosis and therapeutic manifestations. Additionally, inhibition of the PDK/PDC axis by small molecule inhibitors and natural compounds at different clinical evaluation stages has also been discussed comprehensively.

Predicting response to radiotherapy of intracranial metastases with hyperpolarized [Formula: see text]C MRI

BACKGROUND

Stereotactic radiosurgery (SRS) is used to manage intracranial metastases in a significant fraction of patients. Local progression after SRS can often only be detected with increased volume of enhancement on serial MRI scans which may lag true progression by weeks or months.

METHODS

Patients with intracranial metastases (N = 11) were scanned using hyperpolarized [Formula: see text]C MRI prior to treatment with stereotactic radiosurgery (SRS). The status of each lesion was then recorded at six months post-treatment follow-up (or at the time of death).

RESULTS

The positive predictive value of [Formula: see text]C-lactate signal, measured pre-treatment, for prediction of progression of intracranial metastases at six months post-treatment with SRS was 0.8 [Formula: see text], and the AUC from an ROC analysis was 0.77 [Formula: see text]. The distribution of [Formula: see text]C-lactate z-scores was different for intracranial metastases from different primary cancer types (F = 2.46, [Formula: see text]).

CONCLUSIONS

Hyperpolarized [Formula: see text]C imaging has potential as a method for improving outcomes for patients with intracranial metastases, by identifying patients at high risk of treatment failure with SRS and considering other therapeutic options such as surgery.

MR-Guided Radiotherapy for Brain and Spine Tumors

MRI is the standard modality to assess anatomy and response to treatment in brain and spine tumors given its superb anatomic soft tissue contrast (e.g., T1 and T2) and numerous additional intrinsic contrast mechanisms that can be used to investigate physiology (e.g., diffusion, perfusion, spectroscopy). As such, hybrid MRI and radiotherapy (RT) devices hold unique promise for Magnetic Resonance guided Radiation Therapy (MRgRT). In the brain, MRgRT provides daily visualizations of evolving tumors that are not seen with cone beam CT guidance and cannot be fully characterized with occasional standalone MRI scans. Significant evolving anatomic changes during radiotherapy can be observed in patients with glioblastoma during the 6-week fractionated MRIgRT course. In this review, a case of rapidly changing symptomatic tumor is demonstrated for possible therapy adaptation. For stereotactic body RT of the spine, MRgRT acquires clear isotropic images of tumor in relation to spinal cord, cerebral spinal fluid, and nearby moving organs at risk such as bowel. This visualization allows for setup reassurance and the possibility of adaptive radiotherapy based on anatomy in difficult cases. A review of the literature for MR relaxometry, diffusion, perfusion, and spectroscopy during RT is also presented. These techniques are known to correlate with physiologic changes in the tumor such as cellularity, necrosis, and metabolism, and serve as early biomarkers of chemotherapy and RT response correlating with patient survival. While physiologic tumor investigations during RT have been limited by the feasibility and cost of obtaining frequent standalone MRIs, MRIgRT systems have enabled daily and widespread physiologic measurements. We demonstrate an example case of a poorly responding tumor on the 0.35 T MRIgRT system with relaxometry and diffusion measured several times per week. Future studies must elucidate which changes in MR-based physiologic metrics and at which timepoints best predict patient outcomes. This will lead to early treatment intensification for tumors identified to have the worst physiologic responses during RT in efforts to improve glioblastoma survival.

Simultaneous multi-slice spin- and gradient-echo dynamic susceptibility-contrast perfusion-weighted MRI of gliomas

Although combined spin- and gradient-echo (SAGE) dynamic susceptibility-contrast (DSC) MRI can provide perfusion quantification that is sensitive to both macrovessels and microvessels while correcting for T₁ -shortening effects, spatial coverage is often limited in order to maintain a high temporal resolution for DSC quantification. In this work, we combined a SAGE echo-planar imaging (EPI) sequence with simultaneous multi-slice (SMS) excitation and blipped controlled aliasing in parallel imaging (blipped CAIPI) at 3 T to achieve both high temporal resolution and whole brain coverage. Two protocols using this sequence with multi-band (MB) acceleration factors of 2 and 3 were evaluated in 20 patients with treated gliomas to determine the optimal scan parameters for clinical use. ΔR₂ *(t) and ΔR₂ (t) curves were derived to calculate dynamic signal-to-noise ratio (dSNR), ΔR₂ *- and ΔR₂ -based relative cerebral blood volume (rCBV), and mean vessel diameter (mVD) for each voxel. The resulting SAGE DSC images acquired using MB acceleration of 3 versus 2 appeared visually similar in terms of image distortion and contrast. The difference in the mean dSNR from normal-appearing white matter (NAWM) and that in the mean dSNR between NAWM and normal-appearing gray matter were not statistically significant between the two protocols. ΔR₂ *- and ΔR₂ -rCBV maps and mVD maps provided unique contrast and spatial heterogeneity within tumors.

Application of Magnetic Resonance Imaging in the Evaluation of Disease Activity in Graves' Ophthalmopathy

OBJECTIVE

To evaluate magnetic resonance imaging parameters, T2 signal intensity ratios (SIRs), and normalized apparent diffusion coefficients (n-ADC) of the extraocular muscles (EOMs) in the identification of different stages of Graves' ophthalmopathy (GO) and to find out the correlation of T2-SIRs and n-ADC values with disease changes after anti-inflammatory treatment.

METHODS

Altogether, 43 patients (86 orbits) were enrolled and classified into "active" or "inactive" stages by clinical activity score (CAS). Twenty-three (53.5%) patients received anti-inflammatory treatment and underwent a follow-up evaluation. Fifteen age- and gender-matched control participants (30 orbits) were included. T2-SIRs and n-ADC values of EOMs were calculated among GO and healthy controls and were correlated with CAS. Changes in these parameters were also evaluated before and after anti-inflammatory treatment.

RESULTS

Mean T2-SIRs and n-ADC values were both significantly higher in GO patients than in controls and higher in active GO than in inactive GO. In the inactive stage, n-ADC values of inferior rectus muscles were still higher than those in healthy controls. Both T2-SIRs and n-ADC values decreased after intravenous steroid pulse therapy. The cutoff value of pretreatment n-ADC was 1.780 to detect stages with specificity of 93.7% and sensitivity of 48.3% (P = .035).

CONCLUSION

T2-SIRs and n-ADC values are valuable magnetic resonance imaging indicators of the inflammatory activity in GO by detecting involvement of EOMs. They are also ideal tools to monitor the efficacy of anti-inflammatory treatment in patients with active stage GO. n-ADC values, when combined with CAS, can be promising predictive factors in the detection of stages of diseases.

Dynamic contrast-enhanced magnetic resonance imaging for monitoring the anti-angiogenesis efficacy in a C6 glioma rat model

BACKGROUND

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is useful in predicting responses to angiogenic therapy of malignant tumors.

PURPOSE

To observe the dynamics of DCE-MRI parameters in evaluating early effects of antiangiogenic therapy in a C6 glioma rat model.

MATERIAL AND METHODS

The Bevacizumab or vehicle treatment was started from the 14th day after glioma model was established. The treated and control groups (n = 13 per group) underwent DCE-MRI scans on days 0, 1, 3, 5, and 7 after treatment. Tumor volume was calculated according to T2-weighted images. Hematoxylin and eosin, microvessel density (MVD), and proliferating cell nuclear antigen (PCNA) examination were performed on day 7. The MRI parameters between the two groups were compared and correlations with immunohistochemical scores were analyzed.

RESULTS

The average tumor volume of treated group was significantly lower than that of control group on day 7 (81.764 ± 1.043 vs. 103.634 ± 3.868 mm³, P = 0.002). K^trans and K_ep decreased in the treated group while they increased in the control group. The differences were observed on day 5 (K^trans: 0.045 ± 0.018 vs. 0.093 ± 0.014 min^-1, P < 0.001; K_ep: 0.062 ± 0.018 vs. 0.134 ± 0.047 min^-1, P = 0.005) and day 7 (K^trans: 0.032 ± 0.010 vs. 0.115 ± 0.025 min^-1, P < 0.001; K_ep: 0.045 ± 0.016 vs. 0.144 ± 0.042 min^-1, P < 0.001). The difference of V_e was observed on day 5 (0.847 ± 0.248 vs. 0.397 ± 0.151, P = 0.009) and 7 (0.920 ± 0.154 vs. 0.364 ± 0.105, P = 0.006). K^trans and K_ep showed positive correlations with MVD and V_e showed negative correlation with PCNA.

CONCLUSION

DCE-MRI can assess the changes of early effects of anti-angiogenic therapy in preclinical practice.

Glioblastoma survival is better analyzed on preradiotherapy MRI than on postoperative MRI residual volumes: A retrospective observational study

OBJECTIVES

Establishing an overall survival prognosis for resected glioblastoma during routine postoperative management remains a challenge. The aim of our single-center study was to assess the usefulness of basing survival analyses on preradiotherapy MRI (PRMR) rather than on postoperative MRI (POMR).

PATIENTS AND METHODS

A retrospective review was undertaken of 75 patients with glioblastoma treated at our institute. We collected overall survival and MRI volumetric data. We analyzed two types of volumetric data: residual tumor volume and extent of resection. Overall survival rates were compared according to these two types of volumetric data, calculated on either POMR or PRMR and according to the presence or absence of residual enhancement.

RESULTS

Analysis of volumetric data revealed progression of some residual tumors between POMR and PRMR. Kaplan-Meier analysis of the correlations between extent of resection, residual tumor volume, and overall survival revealed significant differences between POMR and PRMR data. Both MRI scans indicated a difference between the complete resection subgroup and the incomplete resection subgroup, as median overall survival was longer in patients with complete resection. However, differences were significant for PRMR (25.3 vs. 15.5, p =  0.012), but not for POMR (21.3 vs. 15.8 months, p =  0.145). With a residual tumor volume cut-off value of 3 cm³, Kaplan-Meier survival analysis revealed non-significant differences on POMR (p =  0.323) compared with PRMR (p =  0.007).

CONCLUSION

Survival in patients with resected glioblastoma was more accurately predicted by volumetric data acquired with PRMR. Differences in predicted survival between the POMR and PRMR groups can be attributed to changes in tumor behavior before adjuvant therapy.

Lactate dehydrogenase expression modulates longevity and neurodegeneration in Drosophila melanogaster

Lactate dehydrogenase (LDH) catalyzes the conversion of glycolysis-derived pyruvate to lactate. Lactate has been shown to play key roles in brain energetics and memory formation. However, lactate levels are elevated in aging and Alzheimer's disease patients, and it is not clear whether lactate plays protective or detrimental roles in these contexts. Here we show that Ldh transcript levels are elevated and cycle with diurnal rhythm in the heads of aged flies and this is associated with increased LDH protein, enzyme activity, and lactate concentrations. To understand the biological significance of increased Ldh gene expression, we genetically manipulated Ldh levels in adult neurons or glia. Overexpression of Ldh in both cell types caused a significant reduction in lifespan whereas Ldh down-regulation resulted in lifespan extension. Moreover, pan-neuronal overexpression of Ldh disrupted circadian locomotor activity rhythms and significantly increased brain neurodegeneration. In contrast, reduction of Ldh in neurons delayed age-dependent neurodegeneration. Thus, our unbiased genetic approach identified Ldh and lactate as potential modulators of aging and longevity in flies.

Diffusion- and perfusion-weighted MRI radiomics model may predict isocitrate dehydrogenase (IDH) mutation and tumor aggressiveness in diffuse lower grade glioma

OBJECTIVES

To determine whether diffusion- and perfusion-weighted MRI-based radiomics features can improve prediction of isocitrate dehydrogenase (IDH) mutation and tumor aggressiveness in lower grade gliomas (LGGs) METHODS: Radiomics features (n = 6472) were extracted from multiparametric MRI including conventional MRI, apparent diffusion coefficient (ADC), and normalized cerebral blood volume, acquired on 127 LGG patients with determined IDH mutation status and grade (WHO II or III). Radiomics models were constructed using machine learning-based feature selection and generalized linear model classifiers. Segmentation stability was calculated between two readers using concordance correlation coefficients (CCCs). Diagnostic performance to predict IDH mutation and tumor grade was compared between the multiparametric and conventional MRI radiomics models using the area under the receiver operating characteristics curve (AUC). The models were tested using a temporally independent validation set (n = 28).

RESULTS

The multiparametric MRI radiomics model was optimized with a random forest feature selector, with segmentation stability of a CCC threshold of 0.8. For IDH mutation, multiparametric MR radiomics showed similar performance (AUC 0.795) to the conventional radiomics model (AUC 0.729). In tumor grading, multiparametric model with ADC features showed higher performance (AUC 0.932) than the conventional model (AUC 0.555). The independent validation set showed the same trend with AUCs of 0.747 for IDH prediction and 0.819 for tumor grading with multiparametric MRI radiomics model.

CONCLUSION

Multiparametric MRI radiomics model showed improved diagnostic performance in tumor grading and comparable diagnostic performance in IDH mutation status, with ADC features playing a significant role.

KEY POINTS

• The multiparametric MRI radiomics model was comparable with conventional MRI radiomics model in predicting IDH mutation. • The multiparametric MRI radiomics model outperformed conventional MRI in glioma grading. • Apparent diffusion coefficient played an important role in glioma grading and predicting IDH mutation status using radiomics.

Translating preclinical MRI methods to clinical oncology

The complexity of modern in vivo magnetic resonance imaging (MRI) methods in oncology has dramatically changed in the last 10 years. The field has long since moved passed its (unparalleled) ability to form images with exquisite soft-tissue contrast and morphology, allowing for the enhanced identification of primary tumors and metastatic disease. Currently, it is not uncommon to acquire images related to blood flow, cellularity, and macromolecular content in the clinical setting. The acquisition of images related to metabolism, hypoxia, pH, and tissue stiffness are also becoming common. All of these techniques have had some component of their invention, development, refinement, validation, and initial applications in the preclinical setting using in vivo animal models of cancer. In this review, we discuss the genesis of quantitative MRI methods that have been successfully translated from preclinical research and developed into clinical applications. These include methods that interrogate perfusion, diffusion, pH, hypoxia, macromolecular content, and tissue mechanical properties for improving detection, staging, and response monitoring of cancer. For each of these techniques, we summarize the 1) underlying biological mechanism(s); 2) preclinical applications; 3) available repeatability and reproducibility data; 4) clinical applications; and 5) limitations of the technique. We conclude with a discussion of lessons learned from translating MRI methods from the preclinical to clinical setting, and a presentation of four fundamental problems in cancer imaging that, if solved, would result in a profound improvement in the lives of oncology patients. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:1377-1392.

Low perfusion compartments in glioblastoma quantified by advanced magnetic resonance imaging and correlated with patient survival

BACKGROUND AND PURPOSE

Glioblastoma exhibits profound intratumoral heterogeneity in perfusion. Particularly, low perfusion may induce treatment resistance. Thus, imaging approaches that define low perfusion compartments are crucial for clinical management.

MATERIALS AND METHODS

A total of 112 newly diagnosed glioblastoma patients were prospectively recruited for maximal safe resection. The apparent diffusion coefficient (ADC) and relative cerebral blood volume (rCBV) were calculated from diffusion and perfusion imaging, respectively. Based on the overlapping regions of lowest rCBV quartile (rCBVL) with the lowest ADC quartile (ADCL) and highest ADC quartile (ADCH) in each tumor, two low perfusion compartments (ADCH-rCBVL and ADCL-rCBVL) were identified for volumetric analysis. Lactate and macromolecule/lipid levels were determined from multivoxel MR spectroscopic imaging. Progression-free survival (PFS) and overall survival (OS) were analyzed using Kaplan-Meier's and multivariate Cox regression analyses, to evaluate the effects of compartment volume and lactate level on survival.

RESULTS

Two compartments displayed higher lactate and macromolecule/lipid levels compared to contralateral normal-appearing white matter (each P < 0.001). The proportion of the ADCL-rCBVL compartment in the contrast-enhancing tumor was associated with a larger infiltration on FLAIR (P < 0.001, rho = 0.42). The minimally invasive phenotype displayed a lower proportion of the ADCL-rCBVL compartment than the localized (P = 0.031) and diffuse phenotypes (not significant). Multivariate Cox regression showed higher lactate level in the ADCL-rCBVL compartment was associated with worsened survival (PFS: HR 2.995, P = 0.047; OS: HR 4.974, P = 0.005).

CONCLUSIONS

Our results suggest that the ADCL-rCBVL compartment may potentially indicate a clinically measurable resistant compartment.

Dose-painting multicenter phase III trial in newly diagnosed glioblastoma: the SPECTRO-GLIO trial comparing arm A standard radiochemotherapy to arm B radiochemotherapy with simultaneous integrated boost guided by MR spectroscopic imaging

Background

Glioblastoma, a high-grade glial infiltrating tumor, is the most frequent malignant brain tumor in adults and carries a dismal prognosis. External beam radiotherapy (EBRT) increases overall survival but this is still low due to local relapses, mostly occurring in the irradiation field. As the ratio of spectra of choline/N acetyl aspartate> 2 (CNR2) on MR spectroscopic imaging has been described as predictive for the site of local relapse, we hypothesized that dose escalation on these regions would increase local control and hence global survival.

Methods/design

In this multicenter prospective phase III trial for newly diagnosed glioblastoma, 220 patients having undergone biopsy or surgery are planned for randomization to two arms. Arm A is the Stupp protocol (EBRT 60 Gy on contrast enhancement + 2 cm margin with concomitant temozolomide (TMZ) and 6 months of TMZ maintenance); Arm B is the same treatment with an additional simultaneous integrated boost of intensity-modulated radiotherapy (IMRT) of 72Gy/2.4Gy delivered on the MR spectroscopic imaging metabolic volumes of CHO/NAA > 2 and contrast-enhancing lesions or resection cavity. Stratification is performed on surgical and MGMT status.

Discussion

This is a dose-painting trial, i.e. delivery of heterogeneous dose guided by metabolic imaging. The principal endpoint is overall survival. An online prospective quality control of volumes and dose is performed in the experimental arm. The study will yield a large amount of longitudinal multimodal MR imaging data including planning CT, radiotherapy dosimetry, MR spectroscopic, diffusion and perfusion imaging.

Trial registration

NCT01507506, registration date December 20, 2011.

Molecular intricacies of aerobic glycolysis in cancer: current insights into the classic metabolic phenotype

Aerobic glycolysis is the process of oxidation of glucose into pyruvate followed by lactate production under normoxic condition. Distinctive from its anaerobic counterpart (i.e. glycolysis that occurs under hypoxia), aerobic glycolysis is frequently witnessed in cancers, popularly known as the "Warburg effect", and it is one of the earliest known evidences of metabolic alteration in neoplasms. Intracellularly, aerobic glycolysis circumvents mitochondrial oxidative phosphorylation (OxPhos), facilitating an increased rate of glucose hydrolysis. This in turn enables cancer cells to successfully compete with normal cells for glucose uptake in order to maintain uninterrupted growth. In addition, evading OxPhos mitigates excessive generation/accumulation of reactive oxygen species that otherwise may be deleterious to cells. Emerging data indicate that aerobic glycolysis in cancer also promotes glutaminolysis to satisfy the precursor requirements of certain biosynthetic processes (e.g. nucleic acids). Next, the metabolic intermediates of aerobic glycolysis also feed the pentose phosphate pathway (PPP) to facilitate macromolecular biosynthesis necessary for cancer cell growth and proliferation. Extracellularly, the extrusion of the end-product of aerobic glycolysis, i.e. lactate, alters the tumor microenvironment, and impacts cancer-associated cells. Collectively, accumulating data unequivocally demonstrate that aerobic glycolysis implicates myriad of molecular and functional processes to support cancer progression. This review, in the light of recent research, dissects the molecular intricacies of its regulation, and also deliberates the emerging paradigms to target aerobic glycolysis in cancer therapy.

Molecular PET imaging in adaptive radiotherapy: brain

INTRODUCTION

Owing to their heterogeneity and radioresistance, the prognosis of primitive brain tumors, which are mainly glial tumors, remains poor. Dose escalation in radioresistant areas is a potential issue for improving local control and overall survival. This review focuses on advances in biological and metabolic imaging of brain tumors that are proving to be essential for defining tumor target volumes in radiation therapy (RT) and for increasing the use of DPRT (dose painting RT) and ART (adaptative RT), to optimize dose in radio-resistant areas.

EVIDENCE ACQUISITION

Various biological imaging modalities such as PET (hypoxia, glucidic metabolism, protidic metabolism, cellular proliferation, inflammation, cellular membrane synthesis) and MRI (spectroscopy) may be used to identify these areas of radioresistance. The integration of these biological imaging modalities improves the diagnosis, prognosis and treatment of brain tumors.

EVIDENCE SYNTHESIS

Technological improvements (PET and MRI), the development of research, and intensive cooperation between different departments are necessary before using daily metabolic imaging (PET and MRI) to treat patients with brain tumors.

CONCLUSIONS

The adaptation of treatment volumes during RT (ART) seems promising, but its development requires improvements in several areas and an interdisciplinary approach involving radiology, nuclear medicine and radiotherapy. We review the literature on biological imaging to outline the perspectives for using DPRT and ART in brain tumors.

Hypoxia-Driven Immunosuppressive Metabolites in the Tumor Microenvironment: New Approaches for Combinational Immunotherapy

Hypoxia is not only a prominent contributor to the heterogeneity of solid tumors but also a crucial stressor in the microenvironment to drive adaptations for tumors to evade immunosurveillance. Herein, we discuss the potential role of hypoxia within the microenvironment contributing to immune resistance and immune suppression of tumor cells. We outline recent discoveries of hypoxia-driven adaptive mechanisms that diminish immune cell response via skewing the expression of important immune checkpoint molecules (e.g., cluster of differentiation 47, programmed death ligand 1, and human leukocyte antigen G), altered metabolism and metabolites, and pH regulation. Importantly, inhibition of hypoxic stress-relevant pathways can collectively enhance T-cell-mediated tumor cell killing. Furthermore, we discuss how manipulation of hypoxia stress may pose a promising new strategy for a combinational therapeutic intervention to enhance immunotherapy of solid tumors.

Multisite Concordance of DSC-MRI Analysis for Brain Tumors: Results of a National Cancer Institute Quantitative Imaging Network Collaborative Project

BACKGROUND AND PURPOSE

Standard assessment criteria for brain tumors that only include anatomic imaging continue to be insufficient. While numerous studies have demonstrated the value of DSC-MR imaging perfusion metrics for this purpose, they have not been incorporated due to a lack of confidence in the consistency of DSC-MR imaging metrics across sites and platforms. This study addresses this limitation with a comparison of multisite/multiplatform analyses of shared DSC-MR imaging datasets of patients with brain tumors.

MATERIALS AND METHODS

DSC-MR imaging data were collected after a preload and during a bolus injection of gadolinium contrast agent using a gradient recalled-echo-EPI sequence (TE/TR = 30/1200 ms; flip angle = 72°). Forty-nine low-grade (n = 13) and high-grade (n = 36) glioma datasets were uploaded to The Cancer Imaging Archive. Datasets included a predetermined arterial input function, enhancing tumor ROIs, and ROIs necessary to create normalized relative CBV and CBF maps. Seven sites computed 20 different perfusion metrics. Pair-wise agreement among sites was assessed with the Lin concordance correlation coefficient. Distinction of low- from high-grade tumors was evaluated with the Wilcoxon rank sum test followed by receiver operating characteristic analysis to identify the optimal thresholds based on sensitivity and specificity.

RESULTS

For normalized relative CBV and normalized CBF, 93% and 94% of entries showed good or excellent cross-site agreement (0.8 ≤ Lin concordance correlation coefficient ≤ 1.0). All metrics could distinguish low- from high-grade tumors. Optimum thresholds were determined for pooled data (normalized relative CBV = 1.4, sensitivity/specificity = 90%:77%; normalized CBF = 1.58, sensitivity/specificity = 86%:77%).

CONCLUSIONS

By means of DSC-MR imaging data obtained after a preload of contrast agent, substantial consistency resulted across sites for brain tumor perfusion metrics with a common threshold discoverable for distinguishing low- from high-grade tumors.

Normalization of ADC does not improve correlation with overall survival in patients with high-grade glioma (HGG)

Mixed reports leave uncertainty about whether normalization of apparent diffusion coefficient (ADC) to a within-subject white matter reference is necessary for assessment of tumor cellularity. We tested whether normalization improves the previously reported correlation of resection margin ADC with 15-month overall survival (OS) in HGG patients. Spin-echo echo-planar DWI was retrieved from 3 T MRI acquired between maximal resection and radiation in 37 adults with new-onset HGG (25 glioblastoma; 12 anaplastic astrocytoma). ADC maps were produced with the FSL DTIFIT tool (Oxford Centre for Functional MRI). 3 neuroradiologists manually selected regions of interest (ROI) in normal appearing white matter (NAWM) and in non-enhancing tumor (NT) < 2 cm from the margin of residual enhancing tumor or resection cavity. Normalized ADC (nADC) was computed as the ratio of absolute NT ADC to NAWM ADC. Reproducibility of nADC and absolute ADC among the readers' ROI was assessed using intra-class correlation coefficient (ICC) and within-subject coefficient of variation (wCV). Correlations of ADC and nADC with OS were compared using receiver operating characteristics (ROC) analysis. A p value 0.05 was considered statistically significant. Both mean ADC and nADC differed significantly between patients subgrouped by 15-month OS (p = 0.0014 and 0.0073 respectively). wCV and ICC among the readers were similar for absolute and normalized ADC. In ROC analysis of correlation with OS, nADC did not perform significantly better than absolute ADC. Normalization does not significantly improve the correlation of absolute ADC with OS in HGG, suggesting that normalization is not necessary for clinical or research ADC analysis in HGG patients.

Diffusion Weighted/Tensor Imaging, Functional MRI and Perfusion Weighted Imaging in Glioblastoma-Foundations and Future

In this article, we review the basics of diffusion tensor imaging and functional MRI, their current utility in preoperative neurosurgical mapping, and their limitations. We also discuss potential future applications, including implementation of resting state functional MRI. We then discuss perfusion and diffusion-weighted imaging and their application in advanced neuro-oncologic practice. We explain how these modalities can be helpful in guiding surgical biopsies and differentiating recurrent tumor from treatment related changes.

Therapeutic Targeting of the Pyruvate Dehydrogenase Complex/Pyruvate Dehydrogenase Kinase (PDC/PDK) Axis in Cancer

The mitochondrial pyruvate dehydrogenase complex (PDC) irreversibly decarboxylates pyruvate to acetyl coenzyme A, thereby linking glycolysis to the tricarboxylic acid cycle and defining a critical step in cellular bioenergetics. Inhibition of PDC activity by pyruvate dehydrogenase kinase (PDK)-mediated phosphorylation has been associated with the pathobiology of many disorders of metabolic integration, including cancer. Consequently, the PDC/PDK axis has long been a therapeutic target. The most common underlying mechanism accounting for PDC inhibition in these conditions is post-transcriptional upregulation of one or more PDK isoforms, leading to phosphorylation of the E1α subunit of PDC. Such perturbations of the PDC/PDK axis induce a "glycolytic shift," whereby affected cells favor adenosine triphosphate production by glycolysis over mitochondrial oxidative phosphorylation and cellular proliferation over cellular quiescence. Dichloroacetate is the prototypic xenobiotic inhibitor of PDK, thereby maintaining PDC in its unphosphorylated, catalytically active form. However, recent interest in the therapeutic targeting of the PDC/PDK axis for the treatment of cancer has yielded a new generation of small molecule PDK inhibitors. Ongoing investigations of the central role of PDC in cellular energy metabolism and its regulation by pharmacological effectors of PDKs promise to open multiple exciting vistas into the biochemical understanding and treatment of cancer and other diseases.

Semi-Automated Volumetric and Morphological Assessment of Glioblastoma Resection with Fluorescence-Guided Surgery

PURPOSE

Glioblastoma (GBM) neurosurgical resection relies on contrast-enhanced MRI-based neuronavigation. However, it is well-known that infiltrating tumor extends beyond contrast enhancement. Fluorescence-guided surgery (FGS) using 5-aminolevulinic acid (5-ALA) was evaluated to improve extent of resection (EOR) of GBMs. Preoperative morphological tumor metrics were also assessed.

PROCEDURES

Thirty patients from a phase II trial evaluating 5-ALA FGS in newly diagnosed GBM were assessed. Tumors were segmented preoperatively to assess morphological features as well as postoperatively to evaluate EOR and residual tumor volume (RTV).

RESULTS

Median EOR and RTV were 94.3 % and 0.821 cm(3), respectively. Preoperative surface area to volume ratio and RTV were significantly associated with overall survival, even when controlling for the known survival confounders.

CONCLUSIONS

This study supports claims that 5-ALA FGS is helpful at decreasing tumor burden and prolonging survival in GBM. Moreover, morphological indices are shown to impact both resection and patient survival.

Impact of the Tumor Microenvironment on Tumor-Infiltrating Lymphocytes: Focus on Breast Cancer

Immunotherapy is revolutionizing cancer care across disciplines. The original success of immune checkpoint blockade in melanoma has already been translated to Food and Drug Administration-approved therapies in a number of other cancers, and a large number of clinical trials are underway in many other disease types, including breast cancer. Here, we review the basic requirements for a successful antitumor immune response, with a focus on the metabolic and physical barriers encountered by lymphocytes entering breast tumors. We also review recent clinical trials of immunotherapy in breast cancer and provide a number of interesting questions that will need to be answered for successful breast cancer immunotherapy.

Association of early changes in 1H MRSI parameters with survival for patients with newly diagnosed glioblastoma receiving a multimodality treatment regimen

Background

The heterogeneous biology of glioblastoma (GBM) emphasizes the need for imaging methods to assess tumor burden and assist in evaluating individual patients. The purpose of this study was to investigate early changes in metrics from 3D 1H magnetic resonance spectroscopic imaging (MRSI) data, compare them with anatomic lesion volumes, and determine whether they were associated with survival for patients with newly diagnosed GBM receiving a multimodality treatment regimen.

Methods

Serial MRI and MRSI scans provided estimates of anatomic lesion volumes and levels of choline, creatine, N-acetylaspartate, lactate, and lipid. The association of metrics derived from these data with survival was assessed using Cox proportional hazards models with adjustments for age, Karnofsky performance score, and extent of resection. Temporal changes in parameters were evaluated using a Wilcoxon signed rank test.

Results

Anatomic lesion volumes at the post-radiotherapy (RT) scan, metabolic lesion volume at mid-RT and post-RT scans, as well as metrics describing levels of choline, lactate, and lipid were associated with overall survival. There was a significant reduction in the enhancing lesion volume, increase in T2 lesion volume from mid-RT to post-RT, and decrease in parameters describing metabolite levels during these early time points.

Conclusion

The MRSI data provided metrics that described the effects of treatment on the metabolic lesion burden and were associated with overall survival. This suggests that adding these parameters to standard assessments of changes in anatomic lesion volumes could contribute to making early decisions about the efficacy of such combination therapies.

Elderly patients with newly diagnosed glioblastoma: can preoperative imaging descriptors improve the predictive power of a survival model?

The purpose of this study was to identify independent prognostic factors among preoperative imaging features in elderly glioblastoma patients and to evaluate whether these imaging features, in addition to clinical features, could enhance the predictive power of survival models. This retrospective study included 108 patients ≥65 years of age with newly diagnosed glioblastoma. Preoperative clinical features (age and KPS), postoperative clinical features (extent of surgery and postoperative treatment), and preoperative MRI features were assessed. Univariate and multivariate cox proportional hazards regression analyses for overall survival were performed. The integrated area under the receiver operating characteristic curve (iAUC) was calculated to evaluate the added value of imaging features in the survival model. External validation was independently performed with 40 additional patients ≥65 years of age with newly diagnosed glioblastoma. Eloquent area involvement, multifocality, and ependymal involvement on preoperative MRI as well as clinical features including age, preoperative KPS, extent of resection, and postoperative treatment were significantly associated with overall survival on univariate Cox regression. On multivariate analysis, extent of resection and ependymal involvement were independently associated with overall survival and preoperative KPS showed borderline significance. The model with both preoperative clinical and imaging features showed improved prediction of overall survival compared to the model with preoperative clinical features (iAUC, 0.670 vs. 0.600, difference 0.066, 95% CI 0.021-0.121). Analysis of the validation set yielded similar results (iAUC, 0.790 vs. 0.670, difference 0.123, 95% CI 0.021-0.260), externally validating this observation. Preoperative imaging features, including eloquent area involvement, multifocality, and ependymal involvement, in addition to clinical features, can improve the predictive power for overall survival in elderly glioblastoma patients.

Pretreatment serum lactate level as a prognostic biomarker in patients undergoing supratentorial primary brain tumor resection

Introduction

Malignant primary brain tumors are one of the most aggressive cancers. Pretreatment serum nonneuronal biomarkers closely associated with postoperative outcomes are of high clinical relevance. The present study aimed to identify potential pretreatment serum biomarkers that may influence oncological outcomes in patients with primary brain tumors.

Methods

A total of 74 patients undergoing supratentorial primary brain tumor resection were enrolled. Before tumor resection, serum neuronal biomarkers, namely neuron-specific enolase (NSE), S100β, and glial fibrillary acidic protein (GFAP), and serum nonneuronal biomarkers, namely neutrophil gelatinase-associated lipocalin (NGAL), lactate dehydrogenase (LDH), and lactate, were measured and associated postoperative oncological outcomes, including brain tumor grading, progression-free survival (PFS), and overall survival (OS), were compared.

Results

Patients with high-grade brain tumors had significantly higher pretreatment serum lactate levels (p = 0.011). By contrast, other biomarkers were comparable between patients with high-grade and low-grade brain tumors. Receiver operating characteristic curve analysis of serum lactate levels yielded an area under the curve of 0.71 for differentiating between high-grade and low-grade brain tumors. Kaplan–Meier survival analysis revealed patients with high serum lactate levels (≧2.0 mmol/L) had shorter PFS and OS (p = 0.021 and p = 0.093, respectively). In a multiple regression model, only elevated serum lactate levels were associated with poor PFS and OS (p = 0.021 and p = 0.048, respectively).

Conclusions

An elevated pretreatment serum lactate level is a prognostic biomarker of high-grade primary brain tumors and is significantly associated with poor PFS in patients with supratentorial brain tumors undergoing tumor resection. By contrast, other serum biomarkers are not significantly associated with oncological outcomes.

Adult Brain Tumors: Clinical Applications of Magnetic Resonance Spectroscopy

Proton magnetic resonance spectroscopy (H-MRS) may be helpful in suggesting tumor histology and tumor grade and may better define tumor extension and the ideal site for biopsy compared with conventional magnetic resonance (MR) imaging. A multifunctional approach with diffusion-weighted imaging, perfusion-weighted imaging, and permeability maps, along with H-MRS, may enhance the accuracy of the diagnosis and characterization of brain tumors and estimation of therapeutic response. Integration of advanced imaging techniques with conventional MR imaging and the clinical history help to improve the accuracy, sensitivity, and specificity in differentiating tumors and nonneoplastic lesions.

Intraoperative serum lactate is not a predictor of survival after glioblastoma surgery

BACKGROUND

Cancer cells can produce lactate in high concentrations. Two previous studies examined the clinical relevance of serum lactate as a biomarker in patients with brain tumors. Patients with high-grade tumors have higher serum concentrations of lactate than those with low-grade tumors. We hypothesized that serum lactic could be used of biomarker to predictor of survival in patients with glioblastoma (GB).

METHODS

This was a retrospective study. Demographic, lactate concentrations and imaging data from 275 adult patients with primary GB was included in the analysis. The progression free survival (PFS) and overall survival (OS) rates were compared in patients who had above and below the median concentrations of lactate. We also investigated the correlation between lactate concentrations and tumor volume. Multivariate analyses were conducted to test the association lactate, tumor volume and demographic variables with PFS and OS.

RESULTS

The median serum concentration of lactate was 2.3mmol/L. A weak correlation was found between lactate concentrations and tumor volume. Kaplan-Meier curves demonstrated similar survival in patients with higher or lower than 2.3mmol/L of lactate. The multivariate analysis indicated that the intraoperative levels of lactate were not independently associated with changes in survival. On another hand, a preoperative T1 volume was an independent predictor PFS (HR 95%CI: 1.41, 1.02-1.82, p=0.006) and OS (HR 95%CI: 1.47, 1.11-1.96, p=0.006).

CONCLUSION

This retrospective study suggests that the serum concentrations of lactate cannot be used as a biomarker to predict survival after GB surgery. To date, there are no clinically available serum biomarkers to determine prognosis in patients with high-grade gliomas. These tumors may produce high levels of lactic acid. We hypothesized that serum lactic could be used of biomarker to predictor of survival in patients with glioblastoma (GB). In this study, we collected perioperative and survival data from 275 adult patients with primary high-grade gliomas to determine whether intraoperative serum acid lactic concentrations can serve as a marker of prognosis. The median serum concentration of lactate was 2.3mmol/L. Our analysis indicated the intraoperative levels of lactate were not independently associated with changes in survival. This retrospective study suggests that the serum concentrations of lactate cannot be used as a biomarker to predict survival after GB surgery.

Restriction Spectrum Imaging Improves Risk Stratification in Patients with Glioblastoma

BACKGROUND AND PURPOSE

ADC as a marker of tumor cellularity has been promising for evaluating the response to therapy in patients with glioblastoma but does not successfully stratify patients according to outcomes, especially in the upfront setting. Here we investigate whether restriction spectrum imaging, an advanced diffusion imaging model, performed after an operation but before radiation therapy, could improve risk stratification in patients with newly diagnosed glioblastoma relative to ADC.

MATERIALS AND METHODS

Pre-radiation therapy diffusion-weighted and structural imaging of 40 patients with glioblastoma were examined retrospectively. Restriction spectrum imaging and ADC-based hypercellularity volume fraction (restriction spectrum imaging-FLAIR volume fraction, restriction spectrum imaging-contrast-enhanced volume fraction, ADC-FLAIR volume fraction, ADC-contrast-enhanced volume fraction) and intensities (restriction spectrum imaging-FLAIR 90th percentile, restriction spectrum imaging-contrast-enhanced 90th percentile, ADC-FLAIR 10th percentile, ADC-contrast-enhanced 10th percentile) within the contrast-enhanced and FLAIR hyperintensity VOIs were calculated. The association of diffusion imaging metrics, contrast-enhanced volume, and FLAIR hyperintensity volume with progression-free survival and overall survival was evaluated by using Cox proportional hazards models.

RESULTS

Among the diffusion metrics, restriction spectrum imaging-FLAIR volume fraction was the strongest prognostic metric of progression-free survival (P = .036) and overall survival (P = .007) in a multivariate Cox proportional hazards analysis, with higher values indicating earlier progression and shorter survival. Restriction spectrum imaging-FLAIR 90th percentile was also associated with overall survival (P = .043), with higher intensities, indicating shorter survival. None of the ADC metrics were associated with progression-free survival/overall survival. Contrast-enhanced volume exhibited a trend toward significance for overall survival (P = .063).

CONCLUSIONS

Restriction spectrum imaging-derived cellularity in FLAIR hyperintensity regions may be a more robust prognostic marker than ADC and conventional imaging for early progression and poorer survival in patients with glioblastoma. However, future studies with larger samples are needed to explore its predictive ability.