Predicting the outcome of grade II glioma treated with temozolomide using proton magnetic resonance spectroscopy

Diagnostic and Therapeutic Issues in Glioma Using Imaging Data: The Challenge of Numerical Twinning

Glial tumors represent the leading etiology of primary brain tumors. Their particularities lie in (i) their location in a highly functional organ that is difficult to access surgically, including for biopsy, and (ii) their rapid, anisotropic mode of extension, notably via the fiber bundles of the white matter, which further limits the possibilities of resection. The use of mathematical tools enables the development of numerical models representative of the oncotype, genotype, evolution, and therapeutic response of lesions. The significant development of digital technologies linked to high-resolution NMR exploration, coupled with the possibilities offered by AI, means that we can envisage the creation of digital twins of tumors and their host organs, thus reducing the use of physical sampling.

A Personalized Longitudinal Strategy in Low-Grade Glioma Patients: Predicting Oncological and Neural Interindividual Variability and Its Changes over Years to Think One Step Ahead

Diffuse low-grade glioma (LGG) is a rare cerebral cancer, mostly involving young adults with an active life at diagnosis. If left untreated, LGG widely invades the brain and becomes malignant, generating neurological worsening and ultimately death. Early and repeat treatments for this incurable tumor, including maximal connectome-based surgical resection(s) in awake patients, enable postponement of malignant transformation while preserving quality of life owing to constant neural network reconfiguration. Due to considerable interindividual variability in terms of LGG course and consecutive cerebral reorganization, a multistage longitudinal strategy should be tailored accordingly in each patient. It is crucial to predict how the glioma will progress (changes in growth rate and pattern of migration, genetic mutation, etc.) and how the brain will adapt (changes in patterns of spatiotemporal redistribution, possible functional consequences such as epilepsy or cognitive decline, etc.). The goal is to anticipate therapeutic management, remaining one step ahead in order to select the optimal (re-)treatment(s) (some of them possibly kept in reserve), at the appropriate time(s) in the evolution of this chronic disease, before malignization and clinical worsening. Here, predictive tumoral and non-tumoral factors, and their ever-changing interactions, are reviewed to guide individual decisions in advance based on patient-specific markers, for the treatment of LGG.

Growth differentiation factor-15 overexpression promotes cell proliferation and predicts poor prognosis in cerebral lower-grade gliomas correlated with hypoxia and glycolysis signature

AIMS

Growth differentiation factor-15 (GDF15) plays complex and controversial roles in cancer. In this study, the prognostic value and the exact biological function of GDF15 in cerebral lower-grade gliomas (LGGs) and its potential molecular targets were examined.

MAIN METHODS

Wilcoxon signed-rank test and logistic regression were applied to analyze associations between GDF15 expression and clinical characteristics using the Cancer Genome Atlas (TCGA) database. Overall survival was analyzed using Kaplan-Meier and Cox analyses. Gene set enrichment analysis (GSEA) and the hypoxia risk model was conducted to identify the potential molecular mechanisms underlying the effects of GDF15 on LGGs tumorigenesis. The biological function of GDF15 was examined using gain- and loss-of-function experiments, and a recombinant hGDF15 protein in LGG SW1783 cells in vitro.

KEY FINDINGS

We found that higher GDF15 expression is associated with poor clinical features in LGG patients, and an independent risk factor for overall survival among LGG patients. GSEA results showed that the poor prognostic role of GDF15 in LGGs is related to hypoxia and glycolysis signatures, which was further validated using the hypoxia risk model. Furthermore, GDF15 overexpression facilitated cell proliferation, while GDF15 siRNA inhibits cell proliferation in LGG SW1783 cells. In addition, GDF15 was upregulated upon CoCl2 treatment which induces hypoxia, correlating with the upregulation of the expressions of HIF-1α and glycolysis-related key genes in SW1783 cells.

SIGNIFICANCE

GDF15 may promote LGG tumorigenesis that is associated with the hypoxia and glycolysis pathways, and thus could serve as a promising molecular target for LGG prevention and therapy.

In vivo brain MR spectroscopy in gliomas: clinical and pre-clinical chances

Purpose

Gliomas, the most common primary brain tumours, have recently been re-classified incorporating molecular aspects with important clinical, prognostic, and predictive implications. Concurrently, the reprogramming of metabolism, altering intracellular and extracellular metabolites affecting gene expression, differentiation, and the tumour microenvironment, is increasingly being studied, and alterations in metabolic pathways are becoming hallmarks of cancer. Magnetic resonance spectroscopy (MRS) is a complementary, non-invasive technique capable of quantifying multiple metabolites. The aim of this review focuses on the methodology and analysis techniques in proton MRS (1H MRS), including a brief look at X-nuclei MRS, and on its perspectives for diagnostic and prognostic biomarkers in gliomas in both clinical practice and preclinical research.

Methods

PubMed literature research was performed cross-linking the following key words: glioma, MRS, brain, in-vivo, human, animal model, clinical, pre-clinical, techniques, sequences, 1H, X-nuclei, Artificial Intelligence (AI), hyperpolarization.

Results

We selected clinical works (n = 51), preclinical studies (n = 35) and AI MRS application papers (n = 15) published within the last two decades. The methodological papers (n = 62) were taken into account since the technique first description.

Conclusions

Given the development of treatments targeting specific cancer metabolic pathways, MRS could play a key role in allowing non-invasive assessment for patient diagnosis and stratification, predicting and monitoring treatment responses and prognosis. The characterization of gliomas through MRS will benefit of a wide synergy among scientists and clinicians of different specialties within the context of new translational competences. Head coils, MRI hardware and post-processing analysis progress, advances in research, experts’ consensus recommendations and specific professionalizing programs will make the technique increasingly trustworthy, responsive, accessible.

In vivo detection of dysregulated choline metabolism in paclitaxel-resistant ovarian cancers with proton magnetic resonance spectroscopy

Background

Chemoresistance gradually develops during treatment of epithelial ovarian cancer (EOC). Metabolic alterations, especially in vivo easily detectable metabolites in paclitaxel (PTX)-resistant EOC remain unclear.

Methods

Xenograft models of the PTX-sensitive and PTX-resistant EOCs were built. Using a combination of in vivo proton-magnetic resonance spectroscopy (¹H-MRS), metabolomics and proteomics, we investigated the in vivo metabolites and dysregulated metabolic pathways in the PTX-resistant EOC. Furthermore, we analyzed the RNA expression to validate the key enzymes in the dysregulated metabolic pathway.

Results

On in vivo ¹H-MRS, the ratio of (glycerophosphocholine + phosphocholine) to (creatine + phosphocreatine) ((GPC + PC) to (Cr + PCr))(i.e. Cho/Cr) in the PTX-resistant tumors (1.64 [0.69, 4.18]) was significantly higher than that in the PTX-sensitive tumors (0.33 [0.10, 1.13]) (P = 0.04). Forty-five ex vivo metabolites were identified to be significantly different between the PTX-sensitive and PTX-resistant tumors, with the majority involved of lipids and lipid-like molecules. Spearman’s correlation coefficient analysis indicated in vivo and ex vivo metabolic characteristics were highly consistent, exhibiting the highest positive correlation between in vivo GPC + PC and ex vivo GPC (r = 0.885, P < 0.001). These metabolic data suggested that abnormal choline concentrations were the results from the dysregulated glycerophospholipid metabolism, especially choline metabolism. The proteomics data indicated that the expressions of key enzymes glycerophosphocholine phosphodiesterase 1 (GPCPD1) and glycerophosphodiester phosphodiesterase 1 (GDE1) were significantly lower in the PTX-resistant tumors compared to the PTX-sensitive tumors (both P < 0.01). Decreased expressions of GPCPD1 and GDE1 in choline metabolism led to an increased GPC levels in the PTX-resistant EOCs, which was observed as an elevated total choline (tCho) on in vivo ¹H-MRS.

Conclusions

These findings suggested that dysregulated choline metabolism was associated with PTX-resistance in EOCs and the elevated tCho on in vivo ¹H-MRS could be as an indicator for the PTX-resistance in EOCs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-022-03292-z.

In Vivo Absolute Metabolite Quantification Using a Multiplexed ERETIC-RX Array Coil for Whole-Brain MR Spectroscopic Imaging

BACKGROUND

Absolute quantification of metabolites in MR spectroscopic imaging (MRSI) requires a stable reference signal of known concentration. The Electronic REference To access In vivo Concentrations (ERETIC) has shown great promise but has not been applied in patients and 3D MRSI. ERETIC hardware has not been integrated with receive arrays due to technical challenges, such as coil combination and unwanted coupling between multiple ERETIC and receive channels, for which we developed mitigation strategies.

PURPOSE

To develop absolute quantification for whole-brain MRSI in glioma patients.

STUDY TYPE

Prospective.

POPULATION

Five healthy volunteers and three patients with isocitrate dehydrogenase mutant glioma (27% female). Calibration and coil loading phantoms.

FIELD STRENGTH/SEQUENCE

A 3 T; Adiabatic spin-echo spiral 3D MRSI with real-time motion correction, Fluid Attenuated Inversion Recovery (FLAIR), Gradient Recalled Echo (GRE), Multi-echo Magnetization Prepared Rapid Acquisition of Gradient Echo (MEMPRAGE).

ASSESSMENT

Absolute quantification was performed for five brain metabolites (total N-acetyl-aspartate [NAA]/creatine/choline, glutamine + glutamate, myo-inositol) and the oncometabolite 2-hydroxyglutarate using a custom-built 4x-ERETIC/8x-receive array coil. Metabolite quantification was performed with both EREIC and internal water reference methods. ERETIC signal was transmitted via optical link and used to correct coil loading. Inductive and radiative coupling between ERETIC and receive channels were measured.

STATISTICAL TESTS

ERETIC and internal water methods for metabolite quantification were compared using Bland-Altman (BA) analysis and the nonparametric Mann-Whitney test. P < 0.05 was considered statistically significant.

RESULTS

ERETIC could be integrated in receive arrays and inductive coupling dominated (5-886 times) radiative coupling. Phantoms show proportional scaling of the ERETIC signal with coil loading. The BA analysis demonstrated very good agreement (3.3% ± 1.6%) in healthy volunteers, while there was a large difference (36.1% ± 3.8%) in glioma tumors between metabolite concentrations by ERETIC and internal water quantification.

CONCLUSION

Our results indicate that ERETIC integrated with receive arrays and whole-brain MRSI is feasible for brain metabolites quantification. Further validation is required to probe that ERETIC provides more accurate metabolite concentration in glioma patients.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1.

Glutamate Is a Noninvasive Metabolic Biomarker of IDH1-Mutant Glioma Response to Temozolomide Treatment

Although lower grade gliomas are driven by mutations in the isocitrate dehydrogenase 1 (IDH1) gene and are less aggressive than primary glioblastoma, they nonetheless generally recur. IDH1-mutant patients are increasingly being treated with temozolomide, but early detection of response remains a challenge and there is a need for complementary imaging methods to assess response to therapy prior to tumor shrinkage. The goal of this study was to determine the value of magnetic resonance spectroscopy (MRS)-based metabolic changes for detection of response to temozolomide in both genetically engineered and patient-derived mutant IDH1 models. Using 1H MRS in combination with chemometrics identified several metabolic alterations in temozolomide-treated cells, including a significant increase in steady-state glutamate levels. This was confirmed in vivo, where the observed 1H MRS increase in glutamate/glutamine occurred prior to tumor shrinkage. Cells labeled with [1-13C]glucose and [3-13C]glutamine, the principal sources of cellular glutamate, showed that flux to glutamate both from glucose via the tricarboxylic acid cycle and from glutamine were increased following temozolomide treatment. In line with these results, hyperpolarized [5-13C]glutamate produced from [2-13C]pyruvate and hyperpolarized [1-13C]glutamate produced from [1-13C]α-ketoglutarate were significantly higher in temozolomide-treated cells compared with controls. Collectively, our findings identify 1H MRS-detectable elevation of glutamate and hyperpolarized 13C MRS-detectable glutamate production from either pyruvate or α-ketoglutarate as potential translatable metabolic biomarkers of response to temozolomide treatment in mutant IDH1 glioma. SIGNIFICANCE: These findings show that glutamate can be used as a noninvasive, imageable metabolic marker for early assessment of tumor response to temozolomide, with the potential to improve treatment strategies for mutant IDH1 patients.

Italian consensus and recommendations on diagnosis and treatment of low-grade gliomas. An intersociety (SINch/AINO/SIN) document

In 2018, the SINch (Italian Society of Neurosurgery) Neuro-Oncology Section, AINO (Italian Association of Neuro-Oncology) and SIN (Italian Association of Neurology) Neuro-Oncology Section formed a collaborative Task Force to look at the diagnosis and treatment of low-grade gliomas (LGGs). The Task Force included neurologists, neurosurgeons, neuro-oncologists, pathologists, radiologists, radiation oncologists, medical oncologists, a neuropsychologist and a methodologist. For operational purposes, the Task Force was divided into five Working Groups: diagnosis, surgical treatment, adjuvant treatments, supportive therapies, and follow-up. The resulting guidance document is based on the available evidence and provides recommendations on diagnosis and treatment of LGG patients, considering all aspects of patient care along their disease trajectory.

Role of Neuroimaging Modality in the Assessment of Oxidative Stress in Brain: A Comprehensive Review

Background & Objective:

Oxidative stress (OS) is the secondary source of an injury in consequence to the earlier caused primary injury; it is the condition of an imbalance between oxidants and antioxidants within the physiological system. OS causes alterations in proteins and DNA structure, leading to inflammation, apoptotic cell death, and tissue damage. Neurodegenerative diseases (NDDs) such as Alzheimer's disease, Parkinson's disease, Glioma-induced neurodegeneration and the normal aging-related neuro-degeneration are primarily associated with the increased OS. The present review article is committed to delivering a comprehensive overview of the current neuroimaging modalities which estimates an indirect correlate of OS in the brain. OS-induced changes in white matter tracts and the gray matter volumes are reviewed assessing the role of diffusion tensor imaging (DTI) and voxel-based morphometry (VBM) respectively. Further, the role of magnetic resonance spectroscopy (MRS) to assess the OS-induced alterations of chemical moieties, and thus the resultant structural implications in the neurological disorders are also briefly as well as precisely reviewed.

Conclusions:

In the present review article we present an overview of the role of neuroimaging modalities in the diagnosis, and longitudinal assessment during treatment of the OS induced changes.

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.

Detecting tumor progression in glioma: current standards and new techniques

INTRODUCTION

The post-treatment monitoring of glioma patients remains an area of active research and development. Conventional imaging with MRI is a highly sensitive modality for detecting and monitoring primary and secondary brain tumors and includes multi-parametric sequences to better characterize the disease. Standardized schemes for measuring response to treatment are in wide clinical use; however, the introduction of new therapeutics have introduced new patterns of response that can confound interpretation of conventional MRI and can cause uncertainty in the proper management following therapy. Areas covered: A summary of current and evolving techniques for assessing glioma response in this era of new therapies that address these challenges are presented in this review. While this review focuses more on clinical and early clinical methodologies for MRI and nuclear medicine techniques some promising pre-clinical techniques are also presented. Expert commentary: While successful single institution results have been widely reported in the literature, any new methodologies must be undertaken in multi-center settings. Additionally, the need for standardization of protocols in quantitative measured are an important area that must be addressed for new and promising techniques to be implemented to a wide array of patients.

Basic Principles and Clinical Applications of Magnetic Resonance Spectroscopy in Neuroradiology

Magnetic resonance spectroscopy is a powerful tool to assist daily clinical diagnostics. This review is intended to give an overview on basic principles of the technology, discuss some of its technical aspects, and present typical applications in daily clinical routine in neuroradiology.

Treatment Response Assessment in IDH-Mutant Glioma Patients by Noninvasive 3D Functional Spectroscopic Mapping of 2-Hydroxyglutarate

PURPOSE

Measurements of objective response rates are critical to evaluate new glioma therapies. The hallmark metabolic alteration in gliomas with mutant isocitrate dehydrogenase (IDH) is the overproduction of oncometabolite 2-hydroxyglutarate (2HG), which plays a key role in malignant transformation. 2HG represents an ideal biomarker to probe treatment response in IDH-mutant glioma patients, and we hypothesized a decrease in 2HG levels would be measureable by in vivo magnetic resonance spectroscopy (MRS) as a result of antitumor therapy.

EXPERIMENTAL DESIGN

We report a prospective longitudinal imaging study performed in 25 IDH-mutant glioma patients receiving adjuvant radiation and chemotherapy. A newly developed 3D MRS imaging was used to noninvasively image 2HG. Paired Student t test was used to compare pre- and posttreatment tumor 2HG values. Test-retest measurements were performed to determine the threshold for 2HG functional spectroscopic maps (fSM). Univariate and multivariate regression were performed to correlate 2HG changes with Karnofsky performance score (KPS).

RESULTS

We found that mean 2HG (2HG/Cre) levels decreased significantly (median = 48.1%; 95% confidence interval = 27.3%-56.5%;P= 0.007) in the posttreatment scan. The volume of decreased 2HG correlates (R(2)= 0.88,P= 0.002) with clinical status evaluated by KPS.

CONCLUSIONS

We demonstrate that dynamic measurements of 2HG are feasible by 3D fSM, and the decrease of 2HG levels can monitor treatment response in patients with IDH-mutant gliomas. Our results indicate that quantitative in vivo 2HG imaging may be used for precision medicine and early response assessment in clinical trials of therapies targeting IDH-mutant gliomas.

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.

Convex-Envelope Based Automated Quantitative Approach to Multi-Voxel 1H-MRS Applied to Brain Tumor Analysis

Background

Magnetic Resonance Spectroscopy (MRS) can measure in vivo brain tissue metabolism that exhibits unique biochemical characteristics in brain tumors. For clinical application, an efficient and versatile quantification method of MRS would be an important tool for medical research, particularly for exploring the scientific problem of tumor monitoring. The objective of our study is to propose an automated MRS quantitative approach and assess the feasibility of this approach for glioma grading, prognosis and boundary detection.

Methods

An automated quantitative approach based on a convex envelope (AQoCE) is proposed in this paper, including preprocessing, convex-envelope based baseline fitting, bias correction, sectional baseline removal, and peak detection, in a total of 5 steps. Some metabolic ratios acquired by this quantification are selected for statistical analysis. An independent sample t-test and the Kruskal-Wallis test are used for distinguishing low-grade gliomas (LGG) and high-grade gliomas (HGG) and for detecting the tumor, peritumoral and contralateral areas, respectively. Seventy-eight cases of pre-operative brain gliomas with pathological reports are included in this study.

Results

Cho/NAA, Cho/Cr and Lip-Lac/Cr (LL/Cr) calculated by AQoCE in the tumor area differ significantly between LGG and HGG, with p≤0.005. Using logistic regression combining Cho/NAA, Cho/Cr and LL/Cr to generate a ROC curve, AQoCE achieves a sensitivity of 92.9%, a specificity of 72.2%, and an area under ROC curve (AUC) of 0.860. Moreover, both Cho/NAA and Cho/Cr in the AQoCE approach show a significant difference (p≤0.019) between tumoral, peritumoral, and contralateral areas. The comparison between the results of AQoCE and Siemens MRS processing software are also discussed in this paper.

Conclusions

The AQoCE approach is an automated method of residual water removal and metabolite quantification. It can be applied to multi-voxel ¹H-MRS for evaluating brain glioma grading and demonstrating characteristics of brain glioma metabolism. It can also detect infiltration in the peritumoral area. Under the limited clinical data used, AQoCE is significantly more versatile and efficient compared to the reference approach of Siemens.

Prediction of anaplastic transformation in low-grade oligodendrogliomas based on magnetic resonance spectroscopy and 1p/19q codeletion status

The aim of this study was to assess whether combining multimodal magnetic resonance imaging (MRI) with the determination of the 1p/19q codeletion status could improve the ability to predict anaplastic transformation in low-grade oligodendrogliomas. Twenty patients with grade II oligodendrogliomas were followed-up using multimodal MR [proton MR spectroscopy (MRS), perfusion, and conventional MR imaging]. All patients diagnoses were histologically proven, and 1p/19q codeletion status was analyzed for all patients. Median follow-up was 30.5 ± 11.4 months. Anaplastic transformation was observed in six patients. The only MRI feature that was associated with anaplastic transformation was an elevation of the choline/creatine ratio >2.4 which was observed in 4 out of 6 patients with anaplastic transformation versus 1 out of 14 patients without anaplastic transformation. In patients without 1p/19q codeletion, an elevation of the choline/creatine ratio >2.4 was associated with the occurrence of anaplastic transformation in all cases (4 out of 4 patients), with a mean time of 12 months. In contrast, in patients with a 1p/19q codeletion, no anaplastic transformation was observed in the patient who had an elevation of >2.4 of the choline/creatine ratio and two patients demonstrated an anaplastic transformation without any elevation of this ratio.Prospective validation in a larger series is needed, yet the present study suggests that combining data from in vivo proton MRS and genetic analysis could be a promising strategy to predict time to anaplastic transformation at the individual level in patients with low-grade oligodendrogliomas and may help deciding when chemotherapy and/or radiotherapy should be initiated in these tumors.

Evaluation of the diagnostic performance of magnetic resonance spectroscopy in brain tumors: a systematic review and meta-analysis

Object

The aim of this study was to determine the suitability of magnetic resonance spectroscopy (MRS) for screening brain tumors, based on a systematic review and meta-analysis of published data on the diagnostic performance of MRS.

Methods

The PubMed and PHMC databases were systematically searched for relevant studies up to December 2013. The sensitivities and specificities of MRS in individual studies were calculated and the pooled diagnostic accuracies, with 95% confidence intervals (CI), were assessed under a fixed-effects model.

Results

Twenty-four studies were included, comprising a total of 1013 participants. Overall, no heterogeneity of diagnostic effects was observed between studies. The pooled sensitivity and specificity of MRS were 80.05% (95% CI = 75.97%–83.59%) and 78.46% (95% CI: 73.40%–82.78%), respectively. The area under the summary receiver operating characteristic curve was 0.78. Stratified meta analysis showed higher sensitivity and specificity in child than adult. CSI had higher sensitivity and SV had higher specificity. Higher sensitivity and specificity were obtained in short TE value.

Conclusion

Although the qualities of the studies included in the meta-analysis were moderate, current evidence suggests that MRS may be a valuable adjunct to magnetic resonance imaging for diagnosing brain tumors, but requires selection of suitable technique and TE value.

Low-grade gliomas: the challenges of imaging

WHO grade II gliomas are a major challenge for magnetic resonance imaging (MRI) due to their delayed anaplastic transformation. Today it is possible to individually characterize tumor progression from diagnosis to anaplastic transformation based on the many parameters identified in studies in the literature and the possibility of integrating these data into mathematical models. Early identification of negative morphological and metabolic factors, as well as treatment follow-up, help identify predictive factors of tumor progression, as well as determine treatment response to adapt management of this disease.

Chemotherapy in low-grade gliomas

PURPOSE OF REVIEW

This review summarizes the recent studies in adults' diffuse low-grade gliomas (LGGs) chemotherapy, including response assessment and potential predictive biomarkers of chemosensitivity.

RECENT FINDINGS

Recent studies have confirmed that chemotherapy is an interesting treatment option in LGGs. About 25-50% of LGGs achieve radiological responses with temozolomide or a procarbazine-CCNU-vincristine (PCV) regimen. Clinical and quality-of-life improvements are commonly observed with more than half of the patients with epilepsy, demonstrating a significant reduction of seizure frequency. Dynamic volumetric studies have provided a better description of LGGs evolution after chemotherapy. They have shown that an ongoing volume decrease can be observed many months after chemotherapy discontinuation, particularly after PCV, raising the question of how and for how long should LGGs be treated. New response criteria have been defined by the Response Assessment in Neuro-Oncology group. In addition to 1p/19q codeletion and MGMT promoter methylation, IDH1 mutation might also be a potential predictive biomarker of chemosensitivity.

SUMMARY

It has now been widely accepted that chemotherapy is an interesting treatment option in LGGs. However, several questions remain unanswered regarding its optimal use. Ongoing phase III studies will allow a better delineation of the role of chemotherapy in LGGs and will also help to better determine the potential predictive value of a 1p/19q codeletion, a MGMT promoter methylation and an IDH1 mutation.

Functional imaging in adult and paediatric brain tumours

Imaging is a key component in the management of brain tumours, with MRI being the preferred modality for most clinical scenarios. However, although conventional MRI provides mainly structural information, such as tumour size and location, it leaves many important clinical questions, such as tumour type, aggressiveness and prognosis, unanswered. An increasing number of studies have shown that additional information can be obtained using functional imaging methods (which probe tissue properties), and that these techniques can give key information of clinical importance. These techniques include diffusion imaging, which can assess tissue structure, and perfusion imaging and magnetic resonance spectroscopy, which measures tissue metabolite profiles. Tumour metabolism can also be investigated using PET, with 18F-deoxyglucose being the most readily available tracer. This Review discusses these methods and the studies that have investigated their clinical use. A strong emphasis is placed on the measurement of quantitative parameters, which is a move away from the qualitative nature of conventional radiological reporting and presents major challenges, particularly for multicentre studies.

Low-grade gliomas: when and how to treat

Low-grade gliomas are uncommon tumors whose optimal management remains to be determined. Although well-designed clinical trials have been mounted to address certain aspects of postoperative radiotherapeutic management, additional studies are required to refine management based on tumor-specific and patient-specific variables. There is mounting evidence that the relative completeness of surgical resection can improve survival, and the molecular and histopathologic characterization of the glioma requires adequate samples for analysis. Current imaging and operative techniques can direct surgical resection, and the same imaging techniques can help monitor patients postoperatively and predict prognosis.

[Multimodal magnetic resonance imaging of brain tumors]

Magnetic resonance imaging arose as a reference for diagnosis, pre-therapeutic and follow-up of brain tumors. Among parameters obtained from standard MRI (of low specificity), only volumetric growth allows prognostic information. The multiple "advanced" sequences have leaded to increase both sensitivity and specificity of brain MRI. Yet, perfusion-weighted imaging and spectroscopy provide metabolic information, and diffusion tensor imaging and cortical activation provide functional information. Characterization, grading, therapeutic management and follow-up have improved, with prognostic information.