Prognostic Value of Choline and Other Metabolites Measured Using 1H-Magnetic Resonance Spectroscopy in Gliomas: A Meta-Analysis and Systemic Review

Glioma is the most prevalent primary central nervous system malignant tumor, with high heterogeneity observed among different grades; therefore, non-invasive prediction of prognosis could improve the clinical management of patients with glioma. 1H-magnetic resonance spectroscopy (MRS) can estimate metabolite levels non-invasively. Multiple studies have investigated its prognostic value in gliomas; however, no consensus has been reached. PubMed and Embase databases were searched up to 20 October 2022 to identify studies investigating the prognostic value of metabolites using 1H-MRS in patients with glioma. Heterogeneity across studies was evaluated using the Q and I2 tests, and a fixed- or random-effects model was used to estimate the combined overall hazard ratio (HR). Funnel plots and Begg tests were used to assess publication bias. Higher choline levels were associated with shorter overall survival (HR = 2.69, 95% CI, 1.92−2.99; p < 0.001) and progression-free survival (HR = 2.20, 95% CI, 1.16−4.17; p = 0.02) in all patients; however, in pediatric gliomas, it showed no significant correlation with overall survival (HR = 1.60, 95% CI, 0.97−2.64; p = 0.06). The estimated choline level by 1H-MRS could be used to non-invasively predict the prognosis of patients with adult gliomas, and more studies are needed to evaluate the prognostic value of other metabolites.

Interrogating Metabolism in Brain Cancer

This article reviews existing and emerging techniques of interrogating metabolism in brain cancer from well-established proton magnetic resonance spectroscopy to the promising hyperpolarized metabolic imaging and chemical exchange saturation transfer and emerging techniques of imaging inflammation. Some of these techniques are at an early stage of development and clinical trials are in progress in patients to establish the clinical efficacy. It is likely that in vivo metabolomics and metabolic imaging is the next frontier in brain cancer diagnosis and assessing therapeutic efficacy; with the combined knowledge of genomics and proteomics a complete understanding of tumorigenesis in brain might be achieved.

Advances in neuro-oncology imaging

Despite the fact that MRI has evolved to become the standard method for diagnosis and monitoring of patients with brain tumours, conventional MRI sequences have two key limitations: the inability to show the full extent of the tumour and the inability to differentiate neoplastic tissue from nonspecific, treatment-related changes after surgery, radiotherapy, chemotherapy or immunotherapy. In the past decade, PET involving the use of radiolabelled amino acids has developed into an important diagnostic tool to overcome some of the shortcomings of conventional MRI. The Response Assessment in Neuro-Oncology working group - an international effort to develop new standardized response criteria for clinical trials in brain tumours - has recommended the additional use of amino acid PET imaging for brain tumour management. Concurrently, a number of advanced MRI techniques such as magnetic resonance spectroscopic imaging and perfusion weighted imaging are under clinical evaluation to target the same diagnostic problems. This Review summarizes the clinical role of amino acid PET in relation to advanced MRI techniques for differential diagnosis of brain tumours; delineation of tumour extent for treatment planning and biopsy guidance; post-treatment differentiation between tumour progression or recurrence versus treatment-related changes; and monitoring response to therapy. An outlook for future developments in PET and MRI techniques is also presented.

Magnetic resonance imaging based functional imaging in paediatric oncology

Imaging is central to management of solid tumours in children. Conventional magnetic resonance imaging (MRI) is the standard imaging modality for tumours of the central nervous system (CNS) and limbs and is increasingly used in the abdomen. It provides excellent structural detail, but imparts limited information about tumour type, aggressiveness, metastatic potential or early treatment response. MRI based functional imaging techniques, such as magnetic resonance spectroscopy, diffusion and perfusion weighted imaging, probe tissue properties to provide clinically important information about metabolites, structure and blood flow. This review describes the role of and evidence behind these functional imaging techniques in paediatric oncology and implications for integrating them into routine clinical practice.

Advanced MRI may complement histological diagnosis of lower grade gliomas and help in predicting survival

MRI grading of grade II and III gliomas may have an important impact on treatment decisions. Occasionally,both conventional MRI (cMRI) and histology fail to clearly establish the tumour grade. Three cMRI features(no necrosis; no relevant oedema; absent or faint contrast enhancement) previously validated in 196 patients with supratentorial gliomas directed our selection of 68 suspected low-grade gliomas (LGG) that were also investigated by advanced MRI (aMRI), including perfusion weighted imaging (PWI), diffusion weighted imaging(DWI) and spectroscopy. All the gliomas had histopathological diagnoses. Sensitivity and specificity of cMRI preoperative diagnosis were 78.5 and 38.5 %, respectively, and 85.7 and 53.8 % when a MRI was included, respectively. ROC analysis showed that cut-off values of 1.29 for maximum rCBV, 1.69 for minimum rADC, 2.1 for rCho/Cr ratio could differentiate between LGG and HGG with a sensitivity of 61.5, 53.8, and 53.8 % and a specificity of 54.7, 43 and 64.3 %, respectively. A significantly longer OS was observed in patients with a maximum rCBV<1.46 and minimum rADC>1.69 (80 vs 55 months, p = 0.01; 80 vs 51 months, p = 0.002, respectively). This result was also confirmed when cases were stratified according to pathology (LGG vs HGG). The ability of a MRI to differentiate between LGG and HGG and to predict survival improved as the number of a MRI techniques considered increased. In a selected population of suspected LGG,classification by cMRI underestimated the actual fraction of HGG. aMRI slightly increased the diagnostic accuracy compared to histopathology. However, DWI and PWI were prognostic markers independent of histological grade.

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.

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.

Advances in Magnetic Resonance and Positron Emission Tomography Imaging: Assessing Response in the Treatment of Low-Grade Glioma

Following combined-modality therapy for the treatment of low-grade gliomas, the assessment of treatment response and the evaluation of disease progression are uniformly challenging. In this article, we review existing response criteria, and discuss the limitations of conventional magnetic resonance imaging to distinguish between progression and treatment effect. We review the data on advanced imaging techniques including positron emission tomography and functional magnetic resonance imaging, which may enhance the interpretation of posttreatment changes, and enable the earlier assessment of the efficacy and toxicity of therapy in these patients with prolonged survival.

Malignant gliomas: current perspectives in diagnosis, treatment, and early response assessment using advanced quantitative imaging methods

Malignant gliomas consist of glioblastomas, anaplastic astrocytomas, anaplastic oligodendrogliomas and anaplastic oligoastrocytomas, and some less common tumors such as anaplastic ependymomas and anaplastic gangliogliomas. Malignant gliomas have high morbidity and mortality. Even with optimal treatment, median survival is only 12–15 months for glioblastomas and 2–5 years for anaplastic gliomas. However, recent advances in imaging and quantitative analysis of image data have led to earlier diagnosis of tumors and tumor response to therapy, providing oncologists with a greater time window for therapy management. In addition, improved understanding of tumor biology, genetics, and resistance mechanisms has enhanced surgical techniques, chemotherapy methods, and radiotherapy administration. After proper diagnosis and institution of appropriate therapy, there is now a vital need for quantitative methods that can sensitively detect malignant glioma response to therapy at early follow-up times, when changes in management of nonresponders can have its greatest effect. Currently, response is largely evaluated by measuring magnetic resonance contrast and size change, but this approach does not take into account the key biologic steps that precede tumor size reduction. Molecular imaging is ideally suited to measuring early response by quantifying cellular metabolism, proliferation, and apoptosis, activities altered early in treatment. We expect that successful integration of quantitative imaging biomarker assessment into the early phase of clinical trials could provide a novel approach for testing new therapies, and importantly, for facilitating patient management, sparing patients from weeks or months of toxicity and ineffective treatment. This review will present an overview of epidemiology, molecular pathogenesis and current advances in diagnoses, and management of malignant gliomas.

Physiological effects of cigarette smoking in the limbic system revealed by 3 tesla magnetic resonance spectroscopy

Several studies and recent models of effects of nicotine, the main addictive and psychoactive component in tobacco, point to action of the drug on the limbic system during maintenance of addiction, either direct or indirect via projections from the ventral tegmental area. The objective of this study was to demonstrate physiological effects of cigarette smoking on the hippocampus and the grey matter of the dorsal anterior cingulate cortex in the human brain with regard to addiction and withdrawal. This aim was achieved by group comparisons of results of magnetic resonance spectroscopy between non-smokers, smokers and smokers during withdrawal. 12 smokers and 12 non-smokers were measured with single voxel proton magnetic resonance spectroscopy for total N-acetyl aspartate, glutamate and glutamine, choline-containing compounds, myo-inositol and total creatine in the right and the left hippocampus and in the right and the left dorsal anterior cingulate cortex. Smokers were examined twice, first during regular cigarette smoking and second on the third day of nicotine withdrawal. The ratios to total creatine were used for better reliability. In our study, Glx/tCr was significantly increased and tCho/tCr was significantly decreased in the left cingulate cortex in smokers compared to non-smokers (p = 0.01, both). Six out of seven smokers showed normalization of the Glx/tCr in the left cingulate cortex during withdrawal. Although these results are preliminary due to the small sample size, our results confirm the assumption that cigarette smoking interferes directly or indirectly with the glutamate circuit in the dorsal anterior cingulate cortex.

Recognition of anaplastic foci within low-grade gliomas using MR spectroscopy

BACKGROUND

The recognition of anaplastic foci within low-grade gliomas is of extreme importance in patients under follow-up for Grade II gliomas. We present the algorithm of MR spectroscopy (MRS)-guided brain biopsy and its correlation with tumour histology.

METHODS

Twenty-seven patients harbouring suspected Grade II/III glioma were examined on our 3T MR. 2D PRESS-CSI metabolite images of Choline/Creatine, Creatine/N-acetylaspartate and Choline/N-acetylaspartate were calculated and exported to the DICOM format. According to these maps, a stereobiopsy was performed at the point of maximum Choline/Creatine ratio prior to tumour resection. In the case of enhancing tumour, a subsequent biopsy was performed from the point of enhancement. Comparisons were made between the histology of the biopsied specimens and the resected tumours.

RESULTS

Eleven tumours were diagnosed as high-grade and sixteen as low-grade lesions. The correlation between main spectroscopic ratios (Cho/Cr and Cho/NAA) was strongly positive at the points of maximum Cho/Cr. Similar results were obtained at the points of contrast enhancement. Comparison of histological parameters of biopsy samples at the points of maximum Cho/Cr and histological examination of the completely resected tumours gives a strong correlation of tumour grade, number of mitoses and Ki-67 expression. The diagnostic accuracy of MRS-guided biopsy was 84%. The absolute value of Cho/NAA was higher in high-grade compared to that of low-grade lesions. The value of Cho/NAA ratio of 0.9 using MRS produced a sensitivity and specificity of 78% in the differentiation between low-grade and high-grade lesions. Combining MRS with structural MR, the sensitivity increased to 86% and the specificity to 80%.

CONCLUSIONS

Strong correlation was demonstrated between Cho/Cr and Ch/NAA ratios. Strong correlation was demonstrated between histological parameters of biopsy samples taken using Cho/Cr ratio and those from total tumour examination. Diagnostic accuracy of MRS-guided biopsy was 84%. Sensitivity and specificity of MRS combined with structural MR reaches 86% and 80%.

Utility of multiparametric 3-T MRI for glioma characterization

INTRODUCTION

Accurate grading of cerebral glioma using conventional structural imaging techniques remains challenging due to the relatively poor sensitivity and specificity of these methods. The purpose of this study was to evaluate the relative sensitivity and specificity of structural magnetic resonance imaging and MR measurements of perfusion, diffusion, and whole-brain spectroscopic parameters for glioma grading.

METHODS

Fifty-six patients with radiologically suspected untreated glioma were studied with T1- and T2-weighted MR imaging, dynamic contrast-enhanced MR imaging, diffusion tensor imaging, and volumetric whole-brain MR spectroscopic imaging. Receiver-operating characteristic analysis was performed using the relative cerebral blood volume (rCBV), apparent diffusion coefficient, fractional anisotropy, and multiple spectroscopic parameters to determine optimum thresholds for tumor grading and to obtain the sensitivity, specificity, and positive and negative predictive values for identifying high-grade gliomas. Logistic regression was performed to analyze all the parameters together.

RESULTS

The rCBV individually classified glioma as low and high grade with a sensitivity and specificity of 100 and 88 %, respectively, based on a threshold value of 3.34. On combining all parameters under consideration, the classification was achieved with 2 % error and sensitivity and specificity of 100 and 96 %, respectively.

CONCLUSION

Individually, CBV measurement provides the greatest diagnostic performance for predicting glioma grade; however, the most accurate classification can be achieved by combining all of the imaging parameters.

Potential of MR spectroscopy for assessment of glioma grading

BACKGROUND

Magnetic resonance spectroscopy (MRS) is an imaging diagnostic method based that allows non-invasive measurement of metabolites in tissues. There are a number of metabolites that can be identified by standard brain proton MRS but only a few of them has a clinical significance in diagnosis of gliomas including N-acetylaspartate, choline, creatine, myo-inositol, lactate, and lipids.

METHODS

In this review, we describe potential of MRS for grading of gliomas.

RESULTS

Low-grade gliomas are generally characterized by a relatively high concentration of N-acetylaspartate, low level of choline and absence of lactate and lipids. The increase in creatine concentration indicates low-grade gliomas with earlier progression and malignant transformation. Progression in grade of a glioma is reflected in the progressive decrease in the N-acetylaspartate and myo-inositol levels on the one hand and elevation in choline level up to grade III on the other. Malignant transformation of the glial tumors is also accompanied by the presence of lactate and lipids in MR spectra of grade III but mainly grade IV gliomas. It follows that MRS is a helpful method for detection of glioma regions with aggressive growth or upgrading due to favorable correlation of the choline and N-acetylaspartate levels with histopathological proliferation index Ki-67. Thus, magnetic resonance spectroscopy is also a suitable method for the targeting of brain biopsies.

CONCLUSIONS

Gliomas of each grade have some specific MRS features that can be used for improvement of the diagnostic value of conventional magnetic resonance imaging in non-invasive assessment of glioma grade.

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.

Multimodality assessment of brain tumors and tumor recurrence

Neuroimaging plays a significant role in the diagnosis of intracranial tumors, especially brain gliomas, and must consist of an assessment of location and extent of the tumor and of its biologic activity. Therefore, morphologic imaging modalities and functional, metabolic, or molecular imaging modalities should be combined for primary diagnosis and for following the course and evaluating therapeutic effects. MRI is the gold standard for providing detailed morphologic information and can supply some additional insights into metabolism (MR spectroscopy) and perfusion (perfusion-weighted imaging) but still has limitations in identifying tumor grade, invasive growth into neighboring tissue, and treatment-induced changes, as well as recurrences. These insights can be obtained by various PET modalities, including imaging of glucose metabolism, amino acid uptake, nucleoside uptake, and hypoxia. Diagnostic accuracy can benefit from coregistration of PET results and MRI, combining the high-resolution morphologic images with the biologic information. These procedures are optimized by the newly developed combination of PET and MRI modalities, permitting the simultaneous assessment of morphologic, functional, metabolic, and molecular information on the human brain.

Improved spatial coverage for brain 3D PRESS MRSI by automatic placement of outer-volume suppression saturation bands

PURPOSE

To develop a technique for optimizing coverage of brain 3D (1) H magnetic resonance spectroscopic imaging (MRSI) by automatic placement of outer-volume suppression (OVS) saturation bands (sat bands) and to compare the performance for point-resolved spectroscopic sequence (PRESS) MRSI protocols with manual and automatic placement of sat bands.

MATERIALS AND METHODS

The automated OVS procedure includes the acquisition of anatomic images from the head, obtaining brain and lipid tissue maps, calculating optimal sat band placement, and then using those optimized parameters during the MRSI acquisition. The data were analyzed to quantify brain coverage volume and data quality.

RESULTS

3D PRESS MRSI data were acquired from three healthy volunteers and 29 patients using protocols that included either manual or automatic sat band placement. On average, the automatic sat band placement allowed the acquisition of PRESS MRSI data from 2.7 times larger brain volumes than the conventional method while maintaining data quality.

CONCLUSION

The technique developed helps solve two of the most significant problems with brain PRESS MRSI acquisitions: limited brain coverage and difficulty in prescription. This new method will facilitate routine clinical brain 3D MRSI exams and will be important for performing serial evaluation of response to therapy in patients with brain tumors and other neurological diseases.

Advances in MRI assessment of gliomas and response to anti-VEGF therapy

Bevacizumab is thought to normalize tumor vasculature and restore the blood–brain barrier, decreasing enhancement and peritumoral edema. Conventional measurements of tumor response rely upon dimensions of enhancing tumor. After bevacizumab treatment, glioblastomas are more prone to progress as nonenhancing tumor. The RANO (Response Assessment in Neuro-Oncology) criteria for glioma response use fluid-attenuated inversion recovery (FLAIR)/T2 hyperintensity as a surrogate for nonenhancing tumor; however, nonenhancing tumor can be difficult to differentiate from other causes of FLAIR/T2 hyperintensity (eg, radiation-induced gliosis). Due to these difficulties, recent efforts have been directed toward identifying new biomarkers that either predict treatment response or accurately measure response of both enhancing and nonenhancing tumor shortly after treatment initiation. This will allow for earlier treatment decisions, saving patients from the adverse effects of ineffective therapies while allowing them to try alternative therapies sooner. An active area of research is the use of physiologic imaging, which can potentially detect treatment effects before changes in tumor size are evident.

MR spectroscopy differentiation between high and low grade astrocytomas: a comparison between paediatric and adult tumours

OBJECTIVE

To investigate whether pathologically similar astrocytomas in adults and children may also show metabolic similarities in proton magnetic resonance spectroscopy ((1)H-MRS) and whether the MRS data could help to differentiate between low and high grade gliomas for the different groups.

MATERIAL AND METHODS

Twelve children (5 WHO II astrocytomas, 7 WHO III astrocytomas) and 37 adults (21 WHO II astrocytomas, 16 WHO III astrocytomas) were included in this study. MR spectroscopic data were evaluated retrospectively using normalized measures of total choline (tCho), N-acetyl-aspartate (NAA) and total creatine (tCr). These metabolites were used to differentiate between WHO II and WHO III astrocytomas in children and adults. Histopathological grading was performed using WHO criteria. (1)H-MRS was carried out prior to the commencement of any treatment. Signal intensities of tCho, NAA and tCr were normalized to their values in contralateral brain tissue. The resulting concentration ratios were then used to calculate the change in the intratumoural ratio of NAA to tCho. A Mann-Whitney U-Test was performed to evaluate differences within the respective groups.

RESULTS

In both groups, loss of NAA and increase of tCho were more pronounced in WHO III than in WHO II astrocytoma. The best discriminator to differentiate between low and high grade gliomas was found to be the ratio of NAA/tCho (p < 0.01).

CONCLUSION

The normalized metabolite signal intensities ratio NAA to tCho is the most accurate in differentiating between low and high grade astrocytomas in both children and adults.

Advanced MRI and PET imaging for assessment of treatment response in patients with gliomas

Imaging techniques are important for accurate diagnosis and follow-up of patients with gliomas. T1-weighted MRI, with or without gadolinium, is the gold standard method. However, this technique only reflects biological activity of the tumour indirectly by detecting the breakdown of the blood-brain barrier. Therefore, especially for low-grade glioma or after treatment, T1-weighted MRI enhanced with gadolinium has substantial limitations. Development of more advanced imaging methods to improve outcomes for individual patients is needed. New imaging methods based on MRI and PET can be employed in various stages of disease to target the biological activity of the tumour cells (eg, increased uptake of aminoacids or nucleoside analogues), the changes in diffusivity through the interstitial space (diffusion-weighted MRI), the tumour-induced neovascularisation (perfusion-weighted MRI or contrast-enhanced MRI, or increased uptake of aminoacids in endothelial wall), and the changes in concentrations of metabolites (magnetic resonance spectroscopy). These techniques have advantages and disadvantages, and should be used in conjunction to best help individual patients. Advanced imaging techniques need to be validated in clinical trials to ensure standardisation and evidence-based implementation in routine clinical practice.