Survival analysis in patients with newly diagnosed glioblastoma using pre- and postradiotherapy MR spectroscopic imaging

Evolving concepts in margin strategies and adaptive radiotherapy for glioblastoma: A new future is on the horizon

Chemoradiotherapy is the standard treatment after maximal safe resection for glioblastoma (GBM). Despite advances in molecular profiling, surgical techniques, and neuro-imaging, there have been no major breakthroughs in radiotherapy (RT) volumes in decades. Although the majority of recurrences occur within the original gross tumor volume (GTV), treatment of a clinical target volume (CTV) ranging from 1.5 to 3.0 cm beyond the GTV remains the standard of care. Over the past 15 years, the incorporation of standard and functional MRI sequences into the treatment workflow has become a routine practice with increasing adoption of MR simulators, and new integrated MR-Linac technologies allowing for daily pre-, intra- and post-treatment MR imaging. There is now unprecedented ability to understand the tumor dynamics and biology of GBM during RT, and safe CTV margin reduction is being investigated with the goal of improving the therapeutic ratio. The purpose of this review is to discuss margin strategies and the potential for adaptive RT for GBM, with a focus on the challenges and opportunities associated with both online and offline adaptive workflows. Lastly, opportunities to biologically guide adaptive RT using non-invasive imaging biomarkers and the potential to define appropriate volumes for dose modification will be discussed.

Integrating multi-modal imaging in radiation treatments for glioblastoma

Advances in diagnostic and treatment technology along with rapid developments in translational research may now allow the realization of precision radiotherapy. Integration of biologically informed multimodality imaging to address the spatial and temporal heterogeneity underlying treatment resistance in glioblastoma is now possible for patient care, with evidence of safety and potential benefit. Beyond their diagnostic utility, several candidate imaging biomarkers have emerged in recent early-phase clinical trials of biologically based radiotherapy, and their definitive assessment in multicenter prospective trials is already in development. In this review, the rationale for clinical implementation of candidate advanced magnetic resonance imaging and positron emission tomography imaging biomarkers to guide personalized radiotherapy, the current landscape, and future directions for integrating imaging biomarkers into radiotherapy for glioblastoma are summarized. Moving forward, response-adaptive radiotherapy using biologically informed imaging biomarkers to address emerging treatment resistance in rational combination with novel systemic therapies may ultimately permit improvements in glioblastoma outcomes and true individualization of patient care.

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.

Mapping of exogenous choline uptake and metabolism in rat glioblastoma using deuterium metabolic imaging (DMI)

Introduction

There is a lack of robust metabolic imaging techniques that can be routinely applied to characterize lesions in patients with brain tumors. Here we explore in an animal model of glioblastoma the feasibility to detect uptake and metabolism of deuterated choline and describe the tumor-to-brain image contrast.

Methods

RG2 cells were incubated with choline and the level of intracellular choline and its metabolites measured in cell extracts using high resolution 1H NMR. In rats with orthotopically implanted RG2 tumors deuterium metabolic imaging (DMI) was applied in vivo during, as well as 1 day after, intravenous infusion of 2H9-choline. In parallel experiments, RG2-bearing rats were infused with [1,1',2,2'-2H4]-choline and tissue metabolite extracts analyzed with high resolution 2H NMR to identify molecule-specific 2H-labeling in choline and its metabolites.

Results

In vitro experiments indicated high uptake and fast phosphorylation of exogenous choline in RG2 cells. In vivo DMI studies revealed a high signal from the 2H-labeled pool of choline + metabolites (total choline, 2H-tCho) in the tumor lesion but not in normal brain. Quantitative DMI-based metabolic maps of 2H-tCho showed high tumor-to-brain image contrast in maps acquired both during, and 24 h after deuterated choline infusion. High resolution 2H NMR revealed that DMI data acquired during 2H-choline infusion consists of free choline and phosphocholine, while the data acquired 24 h later represent phosphocholine and glycerophosphocholine.

Discussion

Uptake and metabolism of exogenous choline was high in RG2 tumors compared to normal brain, resulting in high tumor-to-brain image contrast on DMI-based metabolic maps. By varying the timing of DMI data acquisition relative to the start of the deuterated choline infusion, the metabolic maps can be weighted toward detection of choline uptake or choline metabolism. These proof-of-principle experiments highlight the potential of using deuterated choline combined with DMI to metabolically characterize brain tumors.

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.

Lipid Alterations in Glioma: A Systematic Review

Gliomas are highly lethal tumours characterised by heterogeneous molecular features, producing various metabolic phenotypes leading to therapeutic resistance. Lipid metabolism reprogramming is predominant and has contributed to the metabolic plasticity in glioma. This systematic review aims to discover lipids alteration and their biological roles in glioma and the identification of potential lipids biomarker. This systematic review was conducted using the preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines. Extensive research articles search for the last 10 years, from 2011 to 2021, were conducted using four electronic databases, including PubMed, Web of Science, CINAHL and ScienceDirect. A total of 158 research articles were included in this study. All studies reported significant lipid alteration between glioma and control groups, impacting glioma cell growth, proliferation, drug resistance, patients' survival and metastasis. Different lipids demonstrated different biological roles, either beneficial or detrimental effects on glioma. Notably, prostaglandin (PGE2), triacylglycerol (TG), phosphatidylcholine (PC), and sphingosine-1-phosphate play significant roles in glioma development. Conversely, the most prominent anti-carcinogenic lipids include docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA), and vitamin D3 have been reported to have detrimental effects on glioma cells. Furthermore, high lipid signals were detected at 0.9 and 1.3 ppm in high-grade glioma relative to low-grade glioma. This evidence shows that lipid metabolisms were significantly dysregulated in glioma. Concurrent with this knowledge, the discovery of specific lipid classes altered in glioma will accelerate the development of potential lipid biomarkers and enhance future glioma therapeutics.

Longitudinal MR spectroscopy to detect progression in patients with lower-grade glioma in the surveillance phase

Background

Monitoring lower-grade gliomas (LrGGs) for disease progression is made difficult by the limits of anatomical MRI to distinguish treatment related tissue changes from tumor progression. MR spectroscopic imaging (MRSI) offers additional metabolic information that can help address these challenges. The goal of this study was to compare longitudinal changes in multiparametric MRI, including diffusion weighted imaging, perfusion imaging, and 3D MRSI, for LrGG patients who progressed at the final time-point and those who remained clinically stable.

Methods

Forty-one patients with LrGG who were clinically stable were longitudinally assessed for progression. Changes in anatomical, diffusion, perfusion and MRSI data were acquired and compared between patients who remained clinically stable and those who progressed.

Results

Thirty-one patients remained stable, and 10 patients progressed. Over the study period, progressed patients had a significantly greater increase in normalized choline, choline-to-N-acetylaspartic acid index (CNI), normalized creatine, and creatine-to-N-acetylaspartic acid index (CRNI), than stable patients. CRNI was significantly associated with progression status and WHO type. Progressed astrocytoma patients had greater increases in CRNI than stable astrocytoma patients.

Conclusions

LrGG patients in surveillance with tumors that progressed had significantly increasing choline and creatine metabolite signals on MRSI, with a trend of increasing T2 FLAIR volumes, compared to LrGG patients who remained stable. These data show that MRSI can be used in conjunction with anatomical imaging studies to gain a clearer picture of LrGG progression, especially in the setting of clinical ambiguity.

Precision Radiotherapy for Gliomas: Implementing Novel Imaging Biomarkers to Improve Outcomes With Patient-Specific Therapy

ABSTRACT

Gliomas are the most common primary brain cancer, yet are extraordinarily challenging to treat because they can be aggressive and infiltrative, locally recurrent, and resistant to standard treatments. Furthermore, the treatments themselves, including radiation therapy, can affect patients' neurocognitive function and quality of life. Noninvasive imaging is the standard of care for primary brain tumors, including diagnosis, treatment planning, and monitoring for treatment response. This article explores the ways in which advanced imaging has and will continue to transform radiation treatment for patients with gliomas, with a focus on cognitive preservation and novel biomarkers, as well as precision radiotherapy and treatment adaptation. Advances in novel imaging techniques continue to push the field forward, to more precisely guided treatment planning, radiation dose escalation, measurement of therapeutic response, and understanding of radiation-associated injury.

Magnetic resonance biomarkers in radiation oncology: The report of AAPM Task Group 294

A magnetic resonance (MR) biologic marker (biomarker) is a measurable quantitative characteristic that is an indicator of normal biological and pathogenetic processes or a response to therapeutic intervention derived from the MR imaging process. There is significant potential for MR biomarkers to facilitate personalized approaches to cancer care through more precise disease targeting by quantifying normal versus pathologic tissue function as well as toxicity to both radiation and chemotherapy. Both of which have the potential to increase the therapeutic ratio and provide earlier, more accurate monitoring of treatment response. The ongoing integration of MR into routine clinical radiation therapy (RT) planning and the development of MR guided radiation therapy systems is providing new opportunities for MR biomarkers to personalize and improve clinical outcomes. Their appropriate use, however, must be based on knowledge of the physical origin of the biomarker signal, the relationship to the underlying biological processes, and their strengths and limitations. The purpose of this report is to provide an educational resource describing MR biomarkers, the techniques used to quantify them, their strengths and weakness within the context of their application to radiation oncology so as to ensure their appropriate use and application within this field.

Advanced magnetic resonance spectroscopic neuroimaging: Experts' consensus recommendations

Magnetic resonance spectroscopic imaging (MRSI) offers considerable promise for monitoring metabolic alterations associated with disease or injury; however, to date, these methods have not had a significant impact on clinical care, and their use remains largely confined to the research community and a limited number of clinical sites. The MRSI methods currently implemented on clinical MRI instruments have remained essentially unchanged for two decades, with only incremental improvements in sequence implementation. During this time, a number of technological developments have taken place that have already greatly benefited the quality of MRSI measurements within the research community and which promise to bring advanced MRSI studies to the point where the technique becomes a true imaging modality, while making the traditional review of individual spectra a secondary requirement. Furthermore, the increasing use of biomedical MR spectroscopy studies has indicated clinical areas where advanced MRSI methods can provide valuable information for clinical care. In light of this rapidly changing technological environment and growing understanding of the value of MRSI studies for biomedical studies, this article presents a consensus from a group of experts in the field that reviews the state-of-the-art for clinical proton MRSI studies of the human brain, recommends minimal standards for further development of vendor-provided MRSI implementations, and identifies areas which need further technical development.

Recurrent tumor and treatment-induced effects have different MR signatures in contrast enhancing and non-enhancing lesions of high-grade gliomas

BACKGROUND

Differentiating treatment-induced injury from recurrent high-grade glioma is an ongoing challenge in neuro-oncology, in part due to lesion heterogeneity. This study aimed to determine whether different MR features were relevant for distinguishing recurrent tumor from the effects of treatment in contrast-enhancing lesions (CEL) and non-enhancing lesions (NEL).

METHODS

This prospective study analyzed 291 tissue samples (222 recurrent tumor, 69 treatment-effect) with known coordinates on imaging from 139 patients who underwent preoperative 3T MRI and surgery for a suspected recurrence. 8 MR parameter values were tested from perfusion-weighted, diffusion-weighted, and MR spectroscopic imaging at each tissue sample location for association with histopathological outcome using generalized estimating equation models for CEL and NEL tissue samples. Individual cutoff values were evaluated using receiver operating characteristic curve analysis with 5-fold cross-validation.

RESULTS

In tissue samples obtained from CEL, elevated relative cerebral blood volume (rCBV) was associated with the presence of recurrent tumor pathology (P < 0.03), while increases in normalized choline (nCho) and choline-to-NAA index (CNI) were associated with the presence of recurrent tumor pathology in NEL tissue samples (P < 0.008). A mean CNI cutoff value of 2.7 had the highest performance, resulting in mean sensitivity and specificity of 0.61 and 0.81 for distinguishing treatment-effect from recurrent tumor within the NEL.

CONCLUSION

Although our results support prior work that underscores the utility of rCBV in distinguishing the effects of treatment from recurrent tumor within the contrast enhancing lesion, we found that metabolic parameters may be better at differentiating recurrent tumor from treatment-related changes in the NEL of high-grade gliomas.

Ketogenic Diet for Malignant Gliomas: a Review

PURPOSE OF REVIEW

In this review, we examine the postulated mechanisms of therapeutic effect of ketogenic diets in the treatment of gliomas, review the completed clinical trials, and discuss further directions in this field.

RECENT FINDINGS

Cancers including gliomas are characterized by derangements in cellular metabolism. In vitro and animal studies have revealed that dietary interventions to reduce glucose and glycolytic pathways in gliomas may have a therapeutic effect. Early trials in patients with malignant gliomas have shown feasibility, but are not robust enough yet to demonstrate clinical applicability. Therapies for malignant gliomas of the brain are increasingly using a multi-targeted approach. The use of ketogenic diets and its variants may offer a unique and promising anti-glioma treatment by exploiting metabolic alterations seen in cancers including gliomas seen at the cellular level, which may work in concert with other therapies.

Congress of neurological surgeons systematic review and evidence-based guidelines update on the role of emerging developments in the management of newly diagnosed glioblastoma

TARGET POPULATION

These recommendations apply to adult patients with newly diagnosed or suspected glioblastoma.

IMAGING

Question What imaging modalities are in development that may be able to provide improvements in diagnosis, and therapeutic guidance for individuals with newly diagnosed glioblastoma?

RECOMMENDATION

Level III: It is suggested that techniques utilizing magnetic resonance imaging for diffusion weighted imaging, and to measure cerebral blood and magnetic spectroscopic resonance imaging of N-acetyl aspartate, choline and the choline to N-acetyl aspartate index to assist in diagnosis and treatment planning in patients with newly diagnosed or suspected glioblastoma.

SURGERY

Question What new surgical techniques can be used to provide improved tumor definition and resectability to yield better tumor control and prognosis for individuals with newly diagnosed glioblastoma?

RECOMMENDATIONS

Level II: The use of 5-aminolevulinic acid is recommended to improve extent of tumor resection in patients with newly diagnosed glioblastoma. Level II: The use of 5-aminolevulinic acid is recommended to improve median survival and 2 year survival in newly diagnosed glioblastoma patients with clinical characteristics suggesting poor prognosis. Level III: It is suggested that, when available, patients be enrolled in properly designed clinical trials assessing the value of diffusion tensor imaging in improving the safety of patients with newly diagnosed glioblastoma undergoing surgery.

NEUROPATHOLOGY

Question What new pathology techniques and measurement of biomarkers in tumor tissue can be used to provide improved diagnostic ability, and determination of therapeutic responsiveness and prognosis for patients with newly diagnosed glioblastomas?

RECOMMENDATIONS

Level II: Assessment of tumor MGMT promoter methylation status is recommended as a significant predictor of a longer progression free survival and overall survival in patients with newly diagnosed with glioblastoma. Level II: Measurement of tumor expression of neuron-glia-2, neurofilament protein, glutamine synthetase and phosphorylated STAT3 is recommended as a predictor of overall survival in patients with newly diagnosed with glioblastoma. Level III: Assessment of tumor IDH1 mutation status is suggested as a predictor of longer progression free survival and overall survival in patients with newly diagnosed with glioblastoma. Level III: Evaluation of tumor expression of Phosphorylated Mitogen-Activated Protein Kinase protein, EGFR protein, and Insulin-like Growth Factor-Binding Protein-3 is suggested as a predictor of overall survival in patients with newly diagnosed with glioblastoma.

RADIATION

Question What radiation therapy techniques are in development that may be used to provide improved tumor control and prognosis for individuals with newly diagnosed glioblastomas?

RECOMMENDATIONS

Level III: It is suggested that patients with newly diagnosed glioblastoma undergo pretreatment radio-labeled amino acid tracer positron emission tomography to assess areas at risk for tumor recurrence to assist in radiation treatment planning. Level III: It is suggested that, when available, patients be with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of radiation dose escalation, altered fractionation, or new radiation delivery techniques.

CHEMOTHERAPY

Question What emerging chemotherapeutic agents or techniques are available to provide better tumor control and prognosis for patients with newly diagnosed glioblastomas?

RECOMMENDATION

Level III: As no emerging chemotherapeutic agents or techniques were identified in this review that improved tumor control and prognosis it is suggested that, when available, patients with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of chemotherapy.

MOLECULAR AND TARGETED THERAPY

Question What new targeted therapy agents are available to provide better tumor control and prognosis for individuals with newly diagnosed glioblastomas?

RECOMMENDATION

Level III: As no new molecular and targeted therapies have clearly provided better tumor control and prognosis it is suggested that, when available, patients with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of molecular and targeted therapies IMMUNOTHERAPY: Question What emerging immunotherapeutic agents or techniques are available to provide better tumor control and prognosis for patients with newly diagnosed glioblastomas?

RECOMMENDATION

Level III: As no immunotherapeutic agents have clearly provided better tumor control and prognosis it is suggested that, when available, patients with newly diagnosed glioblastomas be enrolled in properly designed clinical trials of immunologically-based therapies.

NOVEL THERAPIES

Question What novel therapies or techniques are in development to provide better tumor control and prognosis for individuals with newly diagnosed glioblastomas?

RECOMMENDATIONS

Level II: The use of tumor-treating fields is recommended for patients with newly diagnosed glioblastoma who have undergone surgical debulking and completed concurrent chemoradiation without progression of disease at the time of tumor-treating field therapy initiation. Level II: It is suggested that, when available, enrollment in properly designed studies of vector containing herpes simplex thymidine kinase gene and prodrug therapies be considered in patients with newly diagnosed glioblastoma.

Multi-parametric MR Imaging Biomarkers Associated to Clinical Outcomes in Gliomas: A Systematic Review

PURPOSE

To systematically review evidence regarding the association of multiparametric biomarkers with clinical outcomes and their capacity to explain relevant subcompartments of gliomas.

MATERIALS AND METHODS

Scopus database was searched for original journal papers from January 1st, 2007 to February 20th, 2017 according to PRISMA. Four hundred forty-nine abstracts of papers were reviewed and scored independently by two out of six authors. Based on those papers we analyzed associations between biomarkers, subcompartments within the tumor lesion, and clinical outcomes. From all the articles analyzed, the twenty-seven papers with the highest scores were highlighted to represent the evidence about MR imaging biomarkers associated with clinical outcomes. Similarly, eighteen studies defining subcompartments within the tumor region were also highlighted to represent the evidence of MR imaging biomarkers. Their reports were critically appraised according to the QUADAS-2 criteria.

RESULTS

It has been demonstrated that multi-parametric biomarkers are prepared for surrogating diagnosis, grading, segmentation, overall survival, progression-free survival, recurrence, molecular profiling and response to treatment in gliomas. Quantifications and radiomics features obtained from morphological exams (T1, T2, FLAIR, T1c), PWI (including DSC and DCE), diffusion (DWI, DTI) and chemical shift imaging (CSI) are the preferred MR biomarkers associated to clinical outcomes. Subcompartments relative to the peritumoral region, invasion, infiltration, proliferation, mass effect and pseudo flush, relapse compartments, gross tumor volumes, and highrisk regions have been defined to characterize the heterogeneity. For the majority of pairwise cooccurrences, we found no evidence to assert that observed co-occurrences were significantly different from their expected co-occurrences (Binomial test with False Discovery Rate correction, α=0.05). The co-occurrence among terms in the studied papers was found to be driven by their individual prevalence and trends in the literature.

CONCLUSION

Combinations of MR imaging biomarkers from morphological, PWI, DWI and CSI exams have demonstrated their capability to predict clinical outcomes in different management moments of gliomas. Whereas morphologic-derived compartments have been mostly studied during the last ten years, new multi-parametric MRI approaches have also been proposed to discover specific subcompartments of the tumors. MR biomarkers from those subcompartments show the local behavior within the heterogeneous tumor and may quantify the prognosis and response to treatment of gliomas.

Developing a Pipeline for Multiparametric MRI-Guided Radiation Therapy: Initial Results from a Phase II Clinical Trial in Newly Diagnosed Glioblastoma

Quantitative mapping of hyperperfused and hypercellular regions of glioblastoma has been proposed to improve definition of tumor regions at risk for local recurrence following conventional radiation therapy. As the processing of the multiparametric dynamic contrast-enhanced (DCE-) and diffusion-weighted (DW-) magnetic resonance imaging (MRI) data for delineation of these subvolumes requires additional steps that go beyond the standard practices of target definition, we sought to devise a workflow to support the timely planning and treatment of patients. A phase II study implementing a multiparametric imaging biomarker for tumor hyperperfusion and hypercellularity consisting of DCE-MRI and high b-value DW-MRI to guide intensified (75 Gy/30 fractions) radiation therapy (RT) in patients with newly diagnosed glioblastoma was launched. In this report, the workflow and the initial imaging outcomes of the first 12 patients are described. Among all the first 12 patients, treatment was initiated within 6 weeks of surgery and within 2 weeks of simulation. On average, the combined hypercellular volume and high cerebral blood volume/tumor perfusion volume were 1.8 times smaller than the T1 gadolinium abnormality and 10 times smaller than the FLAIR abnormality. Hypercellular volume and high cerebral blood volume/tumor perfusion volume each identified largely distinct regions and showed 57% overlap with the enhancing abnormality, and minimal-to-no extension outside of the FLAIR. These results show the feasibility of implementing a workflow for multiparametric magnetic resonance-guided radiation therapy into clinical trials with a coordinated multidisciplinary team, and the unique and complementary tumor subregions identified by the combination of high b-value DW-MRI and DCE-MRI.

The Use of Quantitative Imaging in Radiation Oncology: A Quantitative Imaging Network (QIN) Perspective

Modern radiation therapy is delivered with great precision, in part by relying on high-resolution multidimensional anatomic imaging to define targets in space and time. The development of quantitative imaging (QI) modalities capable of monitoring biologic parameters could provide deeper insight into tumor biology and facilitate more personalized clinical decision-making. The Quantitative Imaging Network (QIN) was established by the National Cancer Institute to advance and validate these QI modalities in the context of oncology clinical trials. In particular, the QIN has significant interest in the application of QI to widen the therapeutic window of radiation therapy. QI modalities have great promise in radiation oncology and will help address significant clinical needs, including finer prognostication, more specific target delineation, reduction of normal tissue toxicity, identification of radioresistant disease, and clearer interpretation of treatment response. Patient-specific QI is being incorporated into radiation treatment design in ways such as dose escalation and adaptive replanning, with the intent of improving outcomes while lessening treatment morbidities. This review discusses the current vision of the QIN, current areas of investigation, and how the QIN hopes to enhance the integration of QI into the practice of radiation oncology.

A comparison of coil combination strategies in 3D multi-channel MRSI reconstruction for patients with brain tumors

The goal of this study was to find the most robust algorithm for a phase-sensitive coil combination of 3D single-cycle and lactate-edited, multi-channel H-1 point-resolved spectroscopy (PRESS) localized echo planar spectroscopic imaging (EPSI) data for clinical applications in the brain. Data were acquired over 5-10 minutes at 3T using 8- or 32-channel array coils. Peak referencing with residual water and N-acetyl-aspartate, first-point phasing, generalized least squared (GLS) and whitened singular-value decomposition (WSVD) combination algorithms were evaluated relative to unsuppressed water with data from a phantom, six volunteers and 55 patients with brain tumors. Comparison metrics were signal-to-noise ratio, coefficient of variance and percent signal increase. Where residual water was present, using it as a reference peak for phasing and weighting factors from an imaging calibration scan gave the best overall performance. Greater improvement was seen for large selected volumes (>720 cm³ ) and for the 32-channel array (25%) compared with the 8-channel array (19%). Applying voxel-by-voxel phase corrections produced a larger increase in performance for the 32- versus 8-channel coil. We conclude that, for clinically relevant 3D H-1 PRESS localized EPSI studies, the most robust technique employed individual phase maps generated from high residual water and individual amplitude maps generated from calibration scans.

A comparison of coil combination strategies in 3D multi-channel MRSI reconstruction for patients with brain tumors

The goal of this study was to find the most robust algorithm for a phase-sensitive coil combination of 3D single-cycle and lactate-edited, multi-channel H-1 point-resolved spectroscopy (PRESS) localized echo planar spectroscopic imaging (EPSI) data for clinical applications in the brain. Data were acquired over 5-10 minutes at 3T using 8- or 32-channel array coils. Peak referencing with residual water and N-acetyl-aspartate, first-point phasing, generalized least squared (GLS) and whitened singular-value decomposition (WSVD) combination algorithms were evaluated relative to unsuppressed water with data from a phantom, six volunteers and 55 patients with brain tumors. Comparison metrics were signal-to-noise ratio, coefficient of variance and percent signal increase. Where residual water was present, using it as a reference peak for phasing and weighting factors from an imaging calibration scan gave the best overall performance. Greater improvement was seen for large selected volumes (>720 cm³ ) and for the 32-channel array (25%) compared with the 8-channel array (19%). Applying voxel-by-voxel phase corrections produced a larger increase in performance for the 32- versus 8-channel coil. We conclude that, for clinically relevant 3D H-1 PRESS localized EPSI studies, the most robust technique employed individual phase maps generated from high residual water and individual amplitude maps generated from calibration scans.

Relationship of In Vivo MR Parameters to Histopathological and Molecular Characteristics of Newly Diagnosed, Nonenhancing Lower-Grade Gliomas

The goal of this research was to elucidate the relationship between WHO 2016 molecular classifications of newly diagnosed, nonenhancing lower grade gliomas (LrGG), tissue sample histopathology, and magnetic resonance (MR) parameters derived from diffusion, perfusion, and ¹H spectroscopic imaging from the tissue sample locations and the entire tumor. A total of 135 patients were scanned prior to initial surgery, with tumor cellularity scores obtained from 88 image-guided tissue samples. MR parameters were obtained from corresponding sample locations, and histograms of normalized MR parameters within the T2 fluid-attenuated inversion recovery lesion were analyzed in order to evaluate differences between subgroups. For tissue samples, higher tumor scores were related to increased normalized apparent diffusion coefficient (nADC), lower fractional anisotropy (nFA), lower cerebral blood volume (nCBV), higher choline (nCho), and lower N-acetylaspartate (nNAA). Within the T2 lesion, higher tumor grade was associated with higher nADC, lower nFA, and higher Cho to NAA index. Pathological analysis confirmed that diffusion and metabolic parameters increased and perfusion decreased with tumor cellularity. This information can be used to select targets for tissue sampling and to aid in making decisions about treating residual disease.

Imaging biomarkers from multiparametric magnetic resonance imaging are associated with survival outcomes in patients with brain metastases from breast cancer

OBJECTIVES

The aim of this study is to investigate the correlation of survival outcomes with imaging biomarkers from multiparametric magnetic resonance imaging (MRI) in patients with brain metastases from breast cancer (BMBC).

METHODS

This study was approved by the institutional review board. Twenty-two patients with BMBC who underwent treatment involving bevacizumab on day 1, etoposide on days 2-4, and cisplatin on day 2 in 21-day cycles were prospectively enrolled for a phase II study. Three brain MRIs were performed: before the treatment, on day 1, and on day 21. Eight imaging biomarkers were derived from dynamic contrast-enhanced MRI (Peak, IAUC₆₀, K^trans, k_ep, v_e), diffusion-weighted imaging [apparent diffusion coefficient (ADC)], and MR spectroscopy (choline/N-acetylaspartate and choline/creatine ratios). The relative changes (Δ) in these biomarkers were correlated with the central nervous system (CNS)-specific progression-free survival (PFS) and overall survival (OS) using the Kaplan-Meier and Cox proportional hazard models.

RESULTS

There were no significant differences in the survival outcomes as per the changes in the biomarkers on day 1. On day 21, those with a low ΔK^trans (p = 0.024) or ΔADC (p = 0.053) reduction had shorter CNS-specific PFS; further, those with a low ΔPeak (p = 0.012) or ΔIAUC₆₀ (p = 0.04) reduction had shorter OS compared with those with high reductions. In multivariate analyses, ΔK^trans and ΔPeak were independent prognostic factors for CNS-specific PFS and OS, respectively, after controlling for age, size, hormone receptors, and performance status.

CONCLUSIONS

Multiparametric MRI may help predict the survival outcomes in patients with BMBC.

KEY POINTS

• Decreased angiogenesis after chemotherapy on day 21 indicated good survival outcome. • ΔK ^trans was an independent prognostic factors for CNS-specific PFS. • ΔPeak was an independent prognostic factors for OS. • Multiparametric MRI helps clinicians to assess patients with BMBC. • High-risk patients may benefit from more intensive follow-up or treatment strategies.

Comparison between Short and Long Echo Time Magnetic Resonance Spectroscopic Imaging at 3T and 7T for Evaluating Brain Metabolites in Patients with Glioma

Three-dimensional proton magnetic resonance spectroscopic imaging (MRSI) is a powerful non-invasive tool for characterizing spatial variations in metabolic profiles for patients with glioma. Metabolic parameters obtained using this technique have been shown to predict treatment response, disease progression, and transformation to a more malignant phenotype. The availability of ultra-high-field MR systems has the potential to improve the characterization of metabolites. The purpose of this study was to compare the metabolite profiles acquired with conventional long echo time (TE) MRSI at 3T with those obtained with short TE MRSI at 3T and 7T in patients with glioma. The data acquisition parameters were optimized separately for each echo time and field strength to obtain volumetric coverage within clinically feasible data acquisition times of 5-10 min. While a higher field strength did provide better detection of metabolites with overlapping peaks, spatial coverage was reduced and the use of inversion recovery to reduce lipid precluded the detection of lipid in regions of necrosis. For serial evaluation of large, heterogeneous lesions, the use of 3T short TE MRSI may thus be preferred. Despite the limited number of metabolites that it is able to detect, the use of 3T long TE MRSI gives the best contrast in choline/N-acetyl aspartate between normal appearing brain and tumor and also allows the separate detection of lactate and lipid. It may therefore be preferred for serial evaluation of patients with high-grade glioma and for detection of malignant transformation in patients with low-grade glioma.

Characterization of Metabolic, Diffusion, and Perfusion Properties in GBM: Contrast-Enhancing versus Non-Enhancing Tumor

BACKGROUND

Although the contrast-enhancing (CE) lesion on T₁-weighted MR images is widely used as a surrogate for glioblastoma (GBM), there are also non-enhancing regions of infiltrative tumor within the T₂-weighted lesion, which elude radiologic detection. Because non-enhancing GBM (Enh-) challenges clinical patient management as latent disease, this study sought to characterize ex vivo metabolic profiles from Enh- and CE GBM (Enh+) samples, alongside histological and in vivo MR parameters, to assist in defining criteria for estimating total tumor burden.

METHODS

Fifty-six patients with newly diagnosed GBM received a multi-parametric pre-surgical MR examination. Targets for obtaining image-guided tissue samples were defined based on in vivo parameters that were suspicious for tumor. The actual location from where tissue samples were obtained was recorded, and half of each sample was analyzed for histopathology while the other half was scanned using HR-MAS spectroscopy.

RESULTS

The Enh+ and Enh- tumor samples demonstrated comparable mitotic activity, but also significant heterogeneity in microvascular morphology. Ex vivo spectroscopic parameters indicated similar levels of total choline and N-acetylaspartate between these contrast-based radiographic subtypes of GBM, and characteristic differences in the levels of myo-inositol, creatine/phosphocreatine, and phosphoethanolamine. Analysis of in vivo parameters at the sample locations were consistent with histological and ex vivo metabolic data.

CONCLUSIONS

The similarity between ex vivo levels of choline and NAA, and between in vivo levels of choline, NAA and nADC in Enh+ and Enh- tumor, indicate that these parameters can be used in defining non-invasive metrics of total tumor burden for patients with GBM.

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.

Pediatric and adult glioblastoma radiosensitization induced by PI3K/mTOR inhibition causes early metabolic alterations detected by nuclear magnetic resonance spectroscopy

Poor outcome for patients with glioblastomas is often associated with radioresistance. PI3K/mTOR pathway deregulation has been correlated with radioresistance; therefore, PI3K/mTOR inhibition could render tumors radiosensitive. In this study, we show that NVP-BEZ235, a dual PI3K/mTOR inhibitor, potentiates the effects of irradiation in both adult and pediatric glioblastoma cell lines, resulting in early metabolic changes detected by nuclear magnetic resonance (NMR) spectroscopy. NVP-BEZ235 radiosensitises cells to X ray exposure, inducing cell death through the inhibition of CDC25A and the activation of p21cip1(CDKN1A). Lactate and phosphocholine levels, increased with radiation, are decreased after NVP-BEZ235 and combination treatment, suggesting that inhibiting the PI3K/mTOR pathway reverses radiation induced metabolic changes. Importantly, NVP-BEZ235 potentiates the effects of irradiation in a xenograft model of adult glioblastoma, where we observed a decrease in lactate and phosphocholine levels after seven days of combination treatment. Although tumor size was not affected due to the short length of the treatment, a significant increase in CASP3 mRNA was observed in the combination group. Taken together, our data suggest that NMR metabolites could be used as biomarkers to detect an early response to combination therapy with PI3K/mTOR inhibitors and radiotherapy in adult and pediatric 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.

MR-guided radiation therapy: transformative technology and its role in the central nervous system

This review article describes advancement of magnetic resonance imaging technologies in radiation therapy planning, guidance, and adaptation of brain tumors. The potential for MR-guided radiation therapy to improve outcomes and the challenges in its adoption are discussed.

Early changes in glioblastoma metabolism measured by MR spectroscopic imaging during combination of anti-angiogenic cediranib and chemoradiation therapy are associated with survival

Precise assessment of treatment response in glioblastoma during combined anti-angiogenic and chemoradiation remains a challenge. In particular, early detection of treatment response by standard anatomical imaging is confounded by pseudo-response or pseudo-progression. Metabolic changes may be more specific for tumor physiology and less confounded by changes in blood-brain barrier permeability. We hypothesize that metabolic changes probed by magnetic resonance spectroscopic imaging can stratify patient response early during combination therapy. We performed a prospective longitudinal imaging study in newly diagnosed glioblastoma patients enrolled in a phase II clinical trial of the pan-vascular endothelial growth factor receptor inhibitor cediranib in combination with standard fractionated radiation and temozolomide (chemoradiation). Forty patients were imaged weekly during therapy with an imaging protocol that included magnetic resonance spectroscopic imaging, perfusion magnetic resonance imaging, and anatomical magnetic resonance imaging. Data were analyzed using receiver operator characteristics, Cox proportional hazards model, and Kaplan-Meier survival plots. We observed that the ratio of total choline to healthy creatine after 1 month of treatment was significantly associated with overall survival, and provided as single parameter: (1) the largest area under curve (0.859) in receiver operator characteristics, (2) the highest hazard ratio (HR = 85.85, P = 0.006) in Cox proportional hazards model, (3) the largest separation (P = 0.004) in Kaplan-Meier survival plots. An inverse correlation was observed between total choline/healthy creatine and cerebral blood flow, but no significant relation to tumor volumetrics was identified. Our results suggest that in vivo metabolic biomarkers obtained by magnetic resonance spectroscopic imaging may be an early indicator of response to anti-angiogenic therapy combined with standard chemoradiation in newly diagnosed glioblastoma.

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.

Metabolic Profiling of IDH Mutation and Malignant Progression in Infiltrating Glioma

Infiltrating low grade gliomas (LGGs) are heterogeneous in their behavior and the strategies used for clinical management are highly variable. A key factor in clinical decision-making is that patients with mutations in the isocitrate dehydrogenase 1 and 2 (IDH1/2) oncogenes are more likely to have a favorable outcome and be sensitive to treatment. Because of their relatively long overall median survival, more aggressive treatments are typically reserved for patients that have undergone malignant progression (MP) to an anaplastic glioma or secondary glioblastoma (GBM). In the current study, ex vivo metabolic profiles of image-guided tissue samples obtained from patients with newly diagnosed and recurrent LGG were investigated using proton high-resolution magic angle spinning spectroscopy (¹H HR-MAS). Distinct spectral profiles were observed for lesions with IDH-mutated genotypes, between astrocytoma and oligodendroglioma histologies, as well as for tumors that had undergone MP. Levels of 2-hydroxyglutarate (2HG) were correlated with increased mitotic activity, axonal disruption, vascular neoplasia, and with several brain metabolites including the choline species, glutamate, glutathione, and GABA. The information obtained in this study may be used to develop strategies for in vivo characterization of infiltrative glioma, in order to improve disease stratification and to assist in monitoring response to therapy.

Patterns of failure for patients with glioblastoma following O-(2-[18F]fluoroethyl)-L-tyrosine PET- and MRI-guided radiotherapy

BACKGROUND AND PURPOSE

To evaluate the patterns of failure following clinical introduction of amino-acid O-(2-[¹⁸F]fluoroethyl)-L-tyrosine (FET)-PET-guided target definition for radiotherapy (RT) of glioblastoma patients.

MATERIALS AND METHODS

The first 66 consecutive patients with confirmed histology, scanned using FET-PET/CT and MRI were selected for evaluation. Chemo-radiotherapy was delivered to a volume based on both MRI and FET-PET (PET_vol). The volume of recurrence (RV) was defined on MRI data collected at the time of progression according to RANO criteria.

RESULTS

Fifty patients were evaluable, with median follow-up of 45months. Central, in-field, marginal and distant recurrences were observed for 82%, 10%, 2%, and 6% of the patients, respectively. We found a volumetric overlap of 26%, 31% and 39% of the RV with the contrast-enhancing MR volume, PET_vol and the composite MRPET_vol, respectively. MGMT-methylation (p=0.03), larger PET_vol (p<0.001), and less extensive surgery (p<0.001), were associated with larger PET_vol overlap.

CONCLUSION

The combined MRPET_vol had a stronger association with the recurrence volume than either of the modalities alone. Larger overlap of PET_vol and RV was observed for patients with MGMT-methylation, less extensive surgery, and large PET_vol on the RT-planning scans.

Early postoperative tumor progression predicts clinical outcome in glioblastoma-implication for clinical trials

Molecular markers define the diagnosis of glioblastoma in the new WHO classification of 2016, challenging neuro-oncology centers to provide timely treatment initiation. The aim of this study was to determine whether a time delay to treatment initiation was accompanied by signs of early tumor progression in an MRI before the start of radiotherapy, and, if so, whether this influences the survival of glioblastoma patients. Images from 61 patients with early post-surgery MRI and a second MRI just before the start of radiotherapy were examined retrospectively for signs of early tumor progression. Survival information was analyzed using the Kaplan–Meier method, and a Cox multivariate analysis was performed to identify independent variables for survival prediction. 59 percent of patients showed signs of early tumor progression after a mean time of 24.1 days from the early post-surgery MRI to the start of radiotherapy. Compared to the group without signs of early tumor progression, which had a mean time of 23.3 days (p = 0.685, Student’s t test), progression free survival was reduced from 320 to 185 days (HR 2.3; CI 95% 1.3–4.0; p = 0.0042, log-rank test) and overall survival from 778 to 329 days (HR 2.9; CI 95% 1.6–5.1; p = 0.0005). A multivariate Cox regression analysis revealed that the Karnofsky performance score, O-6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation, and signs of early tumor progression are prognostic markers of overall survival. Early tumor progression at the start of radiotherapy is associated with a worse prognosis for glioblastoma patients. A standardized baseline MRI might allow for better patient stratification.

A Simple Automated Method for Detecting Recurrence in High-Grade Glioma

Our aim was to develop an automated multiparametric MR imaging analysis of routinely acquired imaging sequences to identify areas of focally recurrent high-grade glioma. Data from 141 patients treated with radiation therapy with a diagnosis of high-grade glioma were reviewed. Strict inclusion/exclusion criteria identified a homogeneous cohort of 12 patients with a nodular recurrence of high-grade glioma that was amenable to focal re-irradiation (cohort 1). T1WI, FLAIR, and DWI data were used to create subtraction maps across time points. Linear regression was performed to identify the pattern of change in these 3 imaging sequences that best correlated with recurrence. The ability of these parameters to guide treatment decisions in individual patients was assessed in a separate cohort of 4 patients who were treated with radiosurgery for recurrent high-grade glioma (cohort 2). A leave-one-out analysis of cohort 1 revealed that automated subtraction maps consistently predicted the radiologist-identified area of recurrence (median area under the receiver operating characteristic curve = 0.91). The regression model was tested in preradiosurgery MRI in cohort 2 and identified 8 recurrent lesions. Six lesions were treated with radiosurgery and were controlled on follow-up imaging, but the remaining 2 lesions were not treated and progressed, consistent with the predictions of the model. Multiparametric subtraction maps can predict areas of nodular progression in patients with previously treated high-grade gliomas. This automated method based on routine imaging sequences is a valuable tool to be prospectively validated in subsequent studies of treatment planning and posttreatment surveillance.

Serial analysis of 3D H-1 MRSI for patients with newly diagnosed GBM treated with combination therapy that includes bevacizumab

Interpretation of changes in the T1- and T2-weighted MR images from patients with newly diagnosed glioblastoma (GBM) treated with standard of care in conjunction with anti-angiogenic agents is complicated by pseudoprogression and pseudoresponse. The hypothesis being tested in this study was that 3D H-1 magnetic resonance spectroscopic imaging (MRSI) provides estimates of levels of choline, creatine, N-acetylaspartate (NAA), lactate and lipid that change in response to treatment and that metrics describing these characteristics are associated with survival. Thirty-one patients with newly diagnosed GBM and being treated with radiation therapy (RT), temozolomide, erlotinib and bevacizumab were recruited to receive serial MR scans that included 3-D lactate edited MRSI at baseline, mid-RT, post-RT and at specific follow-up time points. The data were processed to provide estimates of metrics representing changes in metabolite levels relative to normal appearing brain. Cox proportional hazards analysis was applied to examine the relationship of these parameters with progression free survival (PFS) and overall survival (OS). There were significant reductions in parameters that describe relative levels of choline to NAA and creatine, indicating that the treatment caused a decrease in tumor cellularity. Changes in the levels of lactate and lipid relative to the NAA from contralateral brain were consistent with vascular normalization. Metabolic parameters from the first serial follow-up scan were associated with PFS and OS, when accounting for age and extent of resection. Integrating metabolic parameters into the assessment of patients with newly diagnosed GBM receiving therapies that include anti-angiogenic agents may be helpful for tracking changes in tumor burden, resolving ambiguities in anatomic images caused by non-specific treatment effects and for predicting outcome.

Choline-to-N-acetyl aspartate and lipids-lactate-to-creatine ratios together with age assemble a significant Cox's proportional-hazards regression model for prediction of survival in high-grade gliomas

OBJECTIVE

A long-lasting concern has prevailed for the identification of predictive biomarkers for high-grade gliomas (HGGs) using MRI. However, a consensus of which imaging parameters assemble a significant survival model is still missing in the literature; we investigated the significant positive or negative contribution of several MR biomarkers in this tumour prognosis.

METHODS

A retrospective cohort of supratentorial HGGs [11 glioblastoma multiforme (GBM) and 17 anaplastic astrocytomas] included 28 patients (9 females and 19 males, respectively, with a mean age of 50.4 years, standard deviation: 16.28 years; range: 13-85 years). Oedema and viable tumour measurements were acquired using regions of interest in T₁ weighted, T₂ weighted, fluid-attenuated inversion recovery, apparent diffusion coefficient (ADC) and MR spectroscopy (MRS). We calculated Kaplan-Meier curves and obtained Cox's proportional hazards.

RESULTS

During the follow-up period (3-98 months), 17 deaths were recorded. The median survival time was 1.73 years (range, 0.287-8.947 years). Only 3 out of 20 covariates (choline-to-N-acetyl aspartate and lipids-lactate-to-creatine ratios and age) showed significance in explaining the variability in the survival hazards model; score test: χ² (3) = 9.098, p = 0.028.

CONCLUSION

MRS metabolites overcome volumetric parameters of peritumoral oedema and viable tumour, as well as tumour region ADC measurements. Specific MRS ratios (Cho/Naa, L-L/Cr) might be considered in a regular follow-up for these tumours. Advances in knowledge: Cho/Naa ratio is the strongest survival predictor with a log-hazard function of 2.672 in GBM. Low levels of lipids-lactate/Cr ratio represent up to a 41.6% reduction in the risk of death in GBM.

Application of iron oxide nanoparticles in glioma imaging and therapy: from bench to bedside

Gliomas are the most common primary brain tumors and have a very dismal prognosis. However, recent advancements in nanomedicine and nanotechnology provide opportunities for personalized treatment regimens to improve the poor prognosis of patients suffering from glioma. This comprehensive review starts with an outline of the current status facing glioma. It then provides an overview of the state-of-the-art applications of iron oxide nanoparticles (IONPs) to glioma diagnostics and therapeutics, including MR contrast enhancement, drug delivery, cell labeling and tracking, magnetic hyperthermia treatment and magnetic particle imaging. It also addresses current challenges associated with the biological barriers and IONP design with an emphasis on recent advances and innovative approaches for glioma targeting strategies. Opportunities for future development are highlighted.

Patterns and Time Dependence of Unspecific Enhancement in Postoperative Magnetic Resonance Imaging After Glioblastoma Resection

OBJECTIVE

Postoperative magnetic resonance imaging (MRI) is recommended soon after glioma surgery to avoid reactive nonneoplastic contrast enhancement indistinguishable from tumor. The purpose of this study was to analyze these patterns of postoperative contrast enhancement at 3 T to define the optimal time frame for postoperative MRI.

METHODS

MRI for 206 glioblastoma surgeries in 173 patients who underwent pre- and postoperative and at least 1 follow-up 3T MRI for each surgery were analyzed retrospectively. Postoperative MRI was assessed in consensus by 2 neuroradiologists, blinded to the time after surgery. Postoperative contrast enhancement marginal to the resection cavity was analyzed and classified as vascular, linear, or nodular. The cause of the contrast enhancement (ie, reactive vs. tumor) was assessed by comparing pre-, postoperative, and follow-up MRI.

RESULTS

Within 45 hours after surgery, reactive enhancement appeared in 17.9% of cases. After 45 hours, the fraction of reactive changes increased to 34.1%. Linear enhancement was more often reactive (66.1%, 39/59 cases), whereas nodular enhancement was mainly residual tumor (93.2%, 68/73 cases). Specificity of nodular enhancement was high for tumor recurrence/tumor progression (91.5%).

CONCLUSIONS

To avoid an increasing number of MRIs with reactive contrast enhancement, postoperative MRI at 3 T should be performed within 45 hours after surgery. However, reactive contrast enhancement can occur at all time points. In these cases, the pattern of the contrast enhancement may help to differentiate its cause.

Magnetic resonance analysis of malignant transformation in recurrent glioma

Background

Patients with low-grade glioma (LGG) have a relatively long survival, and a balance is often struck between treating the tumor and impacting quality of life. While lesions may remain stable for many years, they may also undergo malignant transformation (MT) at the time of recurrence and require more aggressive intervention. Here we report on a state-of-the-art multiparametric MRI study of patients with recurrent LGG.

Methods

One hundred and eleven patients previously diagnosed with LGG were scanned at either 1.5 T or 3 T MR at the time of recurrence. Volumetric and intensity parameters were estimated from anatomic, diffusion, perfusion, and metabolic MR data. Direct comparisons of histopathological markers from image-guided tissue samples with metrics derived from the corresponding locations on the in vivo images were made. A bioinformatics approach was applied to visualize and interpret these results, which included imaging heatmaps and network analysis. Multivariate linear-regression modeling was utilized for predicting transformation.

Results

Many advanced imaging parameters were found to be significantly different for patients with tumors that had undergone MT versus those that had not. Imaging metrics calculated at the tissue sample locations highlighted the distinct biological significance of the imaging and the heterogeneity present in recurrent LGG, while multivariate modeling yielded a 76.04% accuracy in predicting MT.

Conclusions

The acquisition and quantitative analysis of such multiparametric MR data may ultimately allow for improved clinical assessment and treatment stratification for patients with recurrent LGG.

Role of Increased n-acetylaspartate Levels in Cancer

BACKGROUND

The clinical and biological effects of metabolic alterations in cancer are not fully understood.

METHODS

In high-grade serous ovarian cancer (HGSOC) samples (n = 101), over 170 metabolites were profiled and compared with normal ovarian tissues (n = 15). To determine NAT8L gene expression across different cancer types, we analyzed the RNA expression of cancer types using RNASeqV2 data available from the open access The Cancer Genome Atlas (TCGA) website (http://www.cbioportal.org/public-portal/). Using NAT8L siRNA, molecular techniques and histological analysis, we determined cancer cell viability, proliferation, apoptosis, and tumor growth in in vitro and in vivo (n = 6-10 mice/group) settings. Data were analyzed with the Student's t test and Kaplan-Meier analysis. Statistical tests were two-sided.

RESULTS

Patients with high levels of tumoral NAA and its biosynthetic enzyme, aspartate N-acetyltransferase (NAT8L), had worse overall survival than patients with low levels of NAA and NAT8L. The overall survival duration of patients with higher-than-median NAA levels (3.6 years) was lower than that of patients with lower-than-median NAA levels (5.1 years, P = .03). High NAT8L gene expression in other cancers (melanoma, renal cell, breast, colon, and uterine cancers) was associated with worse overall survival. NAT8L silencing reduced cancer cell viability (HEYA8: control siRNA 90.61% ± 2.53, NAT8L siRNA 39.43% ± 3.00, P < .001; A2780: control siRNA 90.59% ± 2.53, NAT8L siRNA 7.44% ± 1.71, P < .001) and proliferation (HEYA8: control siRNA 74.83% ± 0.92, NAT8L siRNA 55.70% ± 1.54, P < .001; A2780: control siRNA 50.17% ± 4.13, NAT8L siRNA 26.52% ± 3.70, P < .001), which was rescued by addition of NAA. In orthotopic mouse models (ovarian cancer and melanoma), NAT8L silencing reduced tumor growth statistically significantly (A2780: control siRNA 0.52 g ± 0.15, NAT8L siRNA 0.08 g ± 0.17, P < .001; HEYA8: control siRNA 0.79 g ± 0.42, NAT8L siRNA 0.24 g ± 0.18, P = .008, A375-SM: control siRNA 0.55 g ± 0.22, NAT8L siRNA 0.21 g ± 0.17 g, P = .001). NAT8L silencing downregulated the anti-apoptotic pathway, which was mediated through FOXM1.

CONCLUSION

These findings indicate that the NAA pathway has a prominent role in promoting tumor growth and represents a valuable target for anticancer therapy.Altered energy metabolism is a hallmark of cancer (1). Proliferating cancer cells have much greater metabolic requirements than nonproliferating differentiated cells (2,3). Moreover, altered cancer metabolism elevates unique metabolic intermediates, which can promote cancer survival and progression (4,5). Furthermore, emerging evidence suggests that proliferating cancer cells exploit alternative metabolic pathways to meet their high demand for energy and to accumulate biomass (6-8).

Imaging tumor metabolism using in vivo magnetic resonance spectroscopy

Magnetic resonance spectroscopy (MRS) is a powerful tool for noninvasively investigating normal and abnormal metabolism. When used in combination with imaging strategies, multinuclear MRS methods provide detailed biochemical information that can be directly correlated with anatomical features. Hyperpolarized C MRS is a new technology that reflects real-time metabolic conversion and is likely to be extremely valuable in managing patients with cancer. This article reviews the use of in vivo P, H, and C MRS for assessing cancer metabolism in order to provide information for diagnosis, planning treatment, assessing response to therapy, and predicting survival for patients with cancer.

Metabolic approach for tumor delineation in glioma surgery: 3D MR spectroscopy image-guided resection

OBJECT The extent of resection is one of the most essential factors that influence the outcomes of glioma resection. However, conventional structural imaging has failed to accurately delineate glioma margins because of tumor cell infiltration. Three-dimensional proton MR spectroscopy ((1)H-MRS) can provide metabolic information and has been used in preoperative tumor differentiation, grading, and radiotherapy planning. Resection based on glioma metabolism information may provide for a more extensive resection and yield better outcomes for glioma patients. In this study, the authors attempt to integrate 3D (1)H-MRS into neuronavigation and assess the feasibility and validity of metabolically based glioma resection. METHODS Choline (Cho)-N-acetylaspartate (NAA) index (CNI) maps were calculated and integrated into neuronavigation. The CNI thresholds were quantitatively analyzed and compared with structural MRI studies. Glioma resections were performed under 3D (1)H-MRS guidance. Volumetric analyses were performed for metabolic and structural images from a low-grade glioma (LGG) group and high-grade glioma (HGG) group. Magnetic resonance imaging and neurological assessments were performed immediately after surgery and 1 year after tumor resection. RESULTS Fifteen eligible patients with primary cerebral gliomas were included in this study. Three-dimensional (1)H-MRS maps were successfully coregistered with structural images and integrated into navigational system. Volumetric analyses showed that the differences between the metabolic volumes with different CNI thresholds were statistically significant (p < 0.05). For the LGG group, the differences between the structural and the metabolic volumes with CNI thresholds of 0.5 and 1.5 were statistically significant (p = 0.0005 and 0.0129, respectively). For the HGG group, the differences between the structural and metabolic volumes with CNI thresholds of 0.5 and 1.0 were statistically significant (p = 0.0027 and 0.0497, respectively). All patients showed no tumor progression at the 1-year follow-up. CONCLUSIONS This study integrated 3D MRS maps and intraoperative navigation for glioma margin delineation. Optimum CNI thresholds were applied for both LGGs and HGGs to achieve resection. The results indicated that 3D (1)H-MRS can be integrated with structural imaging to provide better outcomes for glioma resection.

Magnetic Resonance (MR) Metabolic Imaging in Glioma

This review is focused on describing the use of magnetic resonance (MR) spectroscopy for metabolic imaging of brain tumors. We will first review the MR metabolic imaging findings generated from preclinical models, focusing primarily on in vivo studies, and will then describe the use of metabolic imaging in the clinical setting. We will address relatively well-established (1) H MRS approaches, as well as (31) P MRS, (13) C MRS and emerging hyperpolarized (13) C MRS methodologies, and will describe the use of metabolic imaging for understanding the basic biology of glioma as well as for improving the characterization and monitoring of brain tumors in the clinic.

Improved Brain Tumor Classification by Sodium MR Imaging: Prediction of IDH Mutation Status and Tumor Progression

BACKGROUND AND PURPOSE

MR imaging in neuro-oncology is challenging due to inherent ambiguities in proton signal behavior. Sodium-MR imaging may substantially contribute to the characterization of tumors because it reflects the functional status of the sodium-potassium pump and sodium channels.

MATERIALS AND METHODS

Sodium-MR imaging data of patients with treatment-naïve glioma WHO grades I-IV (n = 34; mean age, 51.29 ± 17.77 years) were acquired by using a 7T MR system. For acquisition of sodium-MR images, we applied density-adapted 3D radial projection reconstruction pulse sequences. Proton-MR imaging data were acquired by using a 3T whole-body system.

RESULTS

We demonstrated that the initial sodium signal of a treatment-naïve brain tumor is a significant predictor of isocitrate dehydrogenase (IDH) mutation status (P < .001). Moreover, independent of this correlation, the Cox proportional hazards model confirmed the sodium signal of treatment-naïve brain tumors as a predictor of progression (P = .003). Compared with the molecular signature of IDH mutation status, information criteria of model comparison revealed that the sodium signal is even superior to IDH in progression prediction. In addition, sodium-MR imaging provides a new approach to noninvasive tumor classification. The sodium signal of contrast-enhancing tumor portions facilitates differentiation among most glioma types (P < .001).

CONCLUSIONS

The information of sodium-MR imaging may help to classify neoplasias at an early stage, to reduce invasive tissue characterization such as stereotactic biopsy specimens, and overall to promote improved and individualized patient management in neuro-oncology by novel imaging signatures of brain tumors.

Circulating biomarkers for gliomas

Currently, gliomas are diagnosed by neuroimaging, and refined diagnosis requires resection or biopsy to obtain tumour tissue for histopathological classification and grading. Blood-derived biomarkers, therefore, would be useful as minimally invasive markers that could support diagnosis and enable monitoring of tumour growth and response to treatment. Such circulating biomarkers could distinguish true progression from therapy-associated changes such as radiation necrosis, and help evaluate the persistence or disappearance of a therapeutic target, such as an oncoprotein or a targetable gene mutation, after targeted therapy. Unlike for other tumours, circulating biomarkers for gliomas are still being defined and are not yet in use in clinical practice. Circulating tumour DNA (ctDNA) isolated from plasma has been shown to reflect the mutational status of glioblastoma, and extracellular vesicles (EVs) containing ctDNA, microRNA and proteins function as rapidly adapting reservoirs for glioma biomarkers such as typical DNA mutations, regulatory microRNAs and oncoproteins. Ideally, circulating tumour cells could enable profiling of the whole-tumour genome, but they are difficult to detect and can reflect only a single cell type of the heterogeneous tumour composition, whereas EVs reflect the complex heterogeneity of the whole tumour, as well as its adaptations to therapy. Although all categories of potential blood-derived biomarkers need to be developed further, findings from other tumour types suggest that EVs are the most promising biomarkers.

Case-Based Review: newly diagnosed glioblastoma

Glioblastoma (WHO grade IV astrocytoma) is the most common and most aggressive primary brain tumor in adults. Optimal treatment of a patient with glioblastoma requires collaborative care across numerous specialties. The diagnosis of glioblastoma may be suggested by the symptomatic presentation and imaging, but it must be pathologically confirmed via surgery, which can have dual diagnostic and therapeutic roles. Standard of care postsurgical treatment for newly diagnosed patients involves radiation therapy and oral temozolomide chemotherapy. Despite numerous recent trials of novel therapeutic approaches, this standard of care has not changed in over a decade. Treatment options under active investigation include molecularly targeted therapies, immunotherapeutic approaches, and the use of alternating electrical field to disrupt tumor cell division. These trials may be aided by new insights into glioblastoma heterogeneity, allowing for focused evaluation of new treatments in the patient subpopulations most likely to benefit from them. Because glioblastoma is incurable by current therapies, frequent clinical and radiographic assessment is needed after initial treatment to allow for early intervention upon progressive tumor when it occurs.

Advanced magnetic resonance imaging of the physical processes in human glioblastoma

The most common malignant primary brain tumor, glioblastoma multiforme (GBM) is a devastating disease with a grim prognosis. Patient survival is typically less than two years and fewer than 10% of patients survive more than five years. Magnetic resonance imaging (MRI) can have great utility in the diagnosis, grading, and management of patients with GBM as many of the physical manifestations of the pathologic processes in GBM can be visualized and quantified using MRI. Newer MRI techniques such as dynamic contrast enhanced and dynamic susceptibility contrast MRI provide functional information about the tumor hemodynamic status. Diffusion MRI can shed light on tumor cellularity and the disruption of white matter tracts in the proximity of tumors. MR spectroscopy can be used to study new tumor tissue markers such as IDH mutations. MRI is helping to noninvasively explore the link between the molecular basis of gliomas and the imaging characteristics of their physical processes. We, here, review several approaches to MR-based imaging and discuss the potential for these techniques to quantify the physical processes in glioblastoma, including tumor cellularity and vascularity, metabolite expression, and patterns of tumor growth and recurrence. We conclude with challenges and opportunities for further research in applying physical principles to better understand the biologic process in this deadly disease. See all articles in this Cancer Research section, "Physics in Cancer Research."

Multimodal imaging of gliomas in the context of evolving cellular and molecular therapies

The vast majority of malignant gliomas relapse after surgery and standard radio-chemotherapy. Novel molecular and cellular therapies are thus being developed, targeting specific aspects of tumor growth. While histopathology remains the gold standard for tumor classification, neuroimaging has over the years taken a central role in the diagnosis and treatment follow up of brain tumors. It is used to detect and localize lesions, define the target area for biopsies, plan surgical and radiation interventions and assess tumor progression and treatment outcome. In recent years the application of novel drugs including anti-angiogenic agents that affect the tumor vasculature, has drastically modulated the outcome of brain tumor imaging. To properly evaluate the effects of emerging experimental therapies and successfully support treatment decisions, neuroimaging will have to evolve. Multi-modal imaging systems with existing and new contrast agents, molecular tracers, technological advances and advanced data analysis can all contribute to the establishment of disease relevant biomarkers that will improve disease management and patient care. In this review, we address the challenges of glioma imaging in the context of novel molecular and cellular therapies, and take a prospective look at emerging experimental and pre-clinical imaging techniques that bear the promise of meeting these challenges.

In vitro stimulation of calcium overload and apoptosis by sonodynamic therapy combined with hematoporphyrin monomethyl ether in C6 glioma cells

The present study investigated enhancement of apoptosis induction and the mechanisms underlying calcium overload on C6 glioma cells in vitro, stimulated by low-level ultrasound in combination with hematoporphyrin monomethyl ether (HMME). The optimum frequency of ultrasound was determined by 3-(4,5-dimethythiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. The apoptotic rate, reactive oxygen species concentration and decreased mitochondrial membrane potential (MMP) were analyzed by flow cytometry. Morphological changes were detected by a transmission electron microscope, and the concentration of intracellular Ca²⁺, [Ca²⁺]_i, was detected by a confocal laser scanning microscope. In addition, the release of cytochrome c (cyt-c) was measured by western blot analysis. The results revealed that an increased apoptotic effect was induced by sonodynamic therapy (SDT), and this was found to correlate with the overloaded [Ca²⁺]_i, derived from the intra- and extracellular sources in the early apoptotic process. The results also revealed an increased level of ROS production, a decreased MMP and an increased release of cyt-c. The present study indicated that low-level ultrasound in combination with HMME improved the apoptotic effect in C6 glioma cells. The overloaded [Ca²⁺]_i was involved in the mechanism by which apoptosis was stimulated and enhanced by SDT.