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

Benign Glioma

Benign glioma broadly refers to a heterogeneous group of slow-growing glial tumors with low proliferative rates and a more indolent clinical course. These tumors may also be described as "low-grade" glioma (LGG) and are classified as WHO grade I or II lesions according to the Classification of Tumors of the Central Nervous System (CNS) (Louis et al. in Acta Neuropathol 114:97-109, 2007). Advances in molecular genetics have improved understanding of glioma tumorigenesis, leading to the identification of common mutation profiles with significant treatment and prognostic implications. The most recent WHO 2016 classification system has introduced several notable changes in the way that gliomas are diagnosed, with a new emphasis on molecular features as key factors in differentiation (Wesseling and Capper in Neuropathol Appl Neurobiol 44:139-150, 2018). Benign gliomas have a predilection for younger patients and are among the most frequently diagnosed tumors in children and young adults (Ostrom et al. in Neuro Oncol 22:iv1-iv96, 2020). These tumors can be separated into two clinically distinct subgroups. The first group is of focal, well-circumscribed lesions that notably are not associated with an increased risk of malignant transformation. Primarily diagnosed in pediatric patients, these WHO grade I tumors may be cured with surgical resection alone (Sturm et al. in J Clin Oncol 35:2370-2377, 2017). Recurrence rates are low, and the prognosis for these patients is excellent (Ostrom et al. in Neuro Oncol 22:iv1-iv96, 2020). Diffuse gliomas are WHO grade II lesions with a more infiltrative pattern of growth and high propensity for recurrence. These tumors are primarily diagnosed in young adult patients, and classically present with seizures (Pallud et al. Brain 137:449-462, 2014). The term "benign" is a misnomer in many cases, as the natural history of these tumors is with malignant transformation and recurrence as grade III or grade IV tumors (Jooma et al. in J Neurosurg 14:356-363, 2019). For all LGG, surgery with maximal safe resection is the treatment of choice for both primary and recurrent tumors. The goal of surgery should be for gross total resection (GTR), as complete tumor removal is associated with higher rates of tumor control and seizure freedom. Chemotherapy and radiation therapy (RT), while not typically a component of first-line treatment in most cases, may be employed as adjunctive therapy in high-risk or recurrent tumors and in some select cases. The prognosis of benign gliomas varies widely; non-infiltrative tumor subtypes generally have an excellent prognosis, while diffusely infiltrative tumors, although slow-growing, are eventually fatal (Sturm et al. in J Clin Oncol 35:2370-2377, 2017). This chapter reviews the shared and unique individual features of the benign glioma including diffuse glioma, pilocytic astrocytoma and pilomyxoid astrocytoma (PMA), subependymal giant cell astrocytoma (SEGA), pleomorphic xanthoastrocytoma (PXA), subependymoma (SE), angiocentric glioma (AG), and chordoid glioma (CG). Also discussed is ganglioglioma (GG), a mixed neuronal-glial tumor that represents a notable diagnosis in the differential for other LGG (Wesseling and Capper 2018). Ependymomas of the brain and spinal cord, including major histologic subtypes, are discussed in other chapters.

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.

Magnetic Resonance Spectroscopy in Diagnosis and Follow-Up of Gliomas: State-of-the-Art

Preoperative grade prediction is important in diagnostics of glioma. Even more important can be follow-up after chemotherapy and radiotherapy of high grade gliomas. In this review we provide an overview of MR-spectroscopy (MRS), technical aspects, and different clinical scenarios in the diagnostics and follow-up of gliomas in pediatric and adult populations. Furthermore, we provide a recap of the current research utility and possible future strategies regarding proton- and phosphorous-MRS in glioma research.

Lack of choline elevation on proton magnetic resonance spectroscopy in grade I-III gliomas

Elevated levels of choline are generally emphasized as marker of increased cellularity and cell membrane turnover in gliomas. In this study, we investigated the incidence rate of lack of choline/creatine and choline/water elevation in a population of grade I-III gliomas. A cohort of 41 patients with histopathologically confirmed gliomas underwent multi-voxel proton magnetic resonance spectroscopy on a 3 T magnetic resonance system prior to treatment. Peak areas for choline and myoinositol were measured from all voxels that exhibited hyperintensity on fluid-attenuated inversion recovery images and were normalized to creatine and unsuppressed water from each voxel. The average metabolite/creatine and metabolite/water ratios from these voxels were then computed. Similarly, average metabolite ratios were computed from normal brain parenchyma. Gliomas were considered for lack of choline elevation when choline/creatine and choline/water ratios from neoplastic regions were less than those from normal brain parenchyma regions. Six of 41 (14.6%) grade I-III gliomas showed lack of elevation for choline/creatine and choline/water ratios compared to normal brain parenchyma. Four of these six gliomas also demonstrated elevated levels of myoinositol/creatine ratio. All other gliomas (n = 35) had elevated choline levels from neoplastic regions relative to normal parenchyma. The sensitivity of choline/creatine or choline/water in determining a grade I-III glioma was 85.4%. These findings suggest that a lack of choline/creatine or choline/water elevation may be seen in some gliomas and low choline levels should not prevent us from considering the possibility of a grade I-III glioma.

Diagnostic performance between contrast enhancement, proton MR spectroscopy, and amide proton transfer imaging in patients with brain tumors

PURPOSE

To explore the relationship among parameters of magnetic resonance spectroscopy (MRS) and amide proton transfer (APT) imaging, and to assess the diagnostic performance of MRS and APT imaging for grading brain tumors in comparison with contrast enhancement of conventional MRI for preoperative grading in patients with brain tumor.

MATERIALS AND METHODS

Institutional Review Board approval and written informed consent were obtained. Forty-one patients with suspected brain tumors were enrolled in the study. Single-voxel MRS and 2D APT imaging of the same slice level were conducted using a 3T MRI scanner. Positive or negative contrast enhancement on T₁ -weighted images was assessed by two neuroradiologists. Correlations among metabolite concentrations, metabolite ratios, and calculated histogram parameters, including mean APT (APT_mean ) and the 90th percentile of APT (APT₉₀ ) were assessed using Spearman's correlation coefficient. Diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis for contrast enhancement and MRS and APT imaging. Values of P < 0.05 were considered statistically significant.

RESULTS

Positive correlations with statistical significance were found between total concentration of choline (Cho) and APT₉₀ (r = 0.49), and between Cho/creatine (Cr) and APT_mean (r = 0.65) as well as APT₉₀ (r = 0.49). A negative correlation with statistical significance was observed between NAA/Cr and APT_mean (r = -0.52). According to ROC curves, Cho/Cr, APT_mean , APT₉₀ , demonstrated higher area under the curve (AUC) values than that of contrast enhancement in grading gliomas.

CONCLUSION

Significant correlations were observed between metabolite concentrations and ratios on MRS and APT values. MRS and APT imaging showed comparable diagnostic capability for grading brain tumors, suggesting that both MRS and APT imaging offer potential for quantitatively assessing similar biological characteristics in brain tumors on noncontrast MRI.

LEVEL OF EVIDENCE

2 Technical Efficacy: Stage 2 J. MAGN. RESON. IMAGING 2017;46:732-739.

Magnetic resonance spectroscopy - Revisiting the biochemical and molecular milieu of brain tumors

BACKGROUND

Magnetic resonance spectroscopy (MRS) is an established tool for in-vivo evaluation of the biochemical basis of human diseases. On one hand, such lucid depiction of 'live biochemistry' helps one to decipher the true nature of the pathology while on the other hand one can track the response to therapy at sub-cellular level. Brain tumors have been an area of continuous interrogation and instigation for mankind. Evaluation of these lesions by MRS plays a crucial role in the two aspects of disease management described above.

SCOPE OF REVIEW

Presented is an overview of the window provided by MRS into the biochemical aspects of brain tumors. We systematically visit each metabolite deciphered by MRS and discuss the role of deconvoluting the biochemical aspects of pathologies (here in context of brain tumors) in the disease management cycle. We further try to unify a radiologist's perspective of disease with that of a biochemist to prove the point that preclinical work is the mother of the treatment we provide at bedside as clinicians. Furthermore, an integrated approach by various scientific experts help resolve a query encountered in everyday practice.

MAJOR CONCLUSIONS

MR spectroscopy is an integral tool for evaluation and systematic follow-up of brain tumors. A deeper understanding of this technology by a biochemist would help in a swift and more logical development of the technique while a close collaboration with radiologist would enable definitive application of the same.

GENERAL SIGNIFICANCE

The review aims at inciting closer ties between the two specialists enabling a deeper understanding of this valuable technology.

Molecular magnetic resonance imaging in cancer

The ability to identify key biomolecules and molecular changes associated with cancer malignancy and the capacity to monitor the therapeutic outcome against these targets is critically important for cancer treatment. Recent developments in molecular imaging based on magnetic resonance (MR) techniques have provided researchers and clinicians with new tools to improve most facets of cancer care. Molecular imaging is broadly described as imaging techniques used to detect molecular signature at the cellular and gene expression levels. This article reviews both established and emerging molecular MR techniques in oncology and discusses the potential of these techniques in improving the clinical cancer care. It also discusses how molecular MR, in conjunction with other structural and functional MR imaging techniques, paves the way for developing tailored treatment strategies to enhance cancer care.

Functional magnetic resonance imaging in oncology: state of the art

In the investigation of tumors with conventional magnetic resonance imaging, both quantitative characteristics, such as size, edema, necrosis, and presence of metastases, and qualitative characteristics, such as contrast enhancement degree, are taken into consideration. However, changes in cell metabolism and tissue physiology which precede morphological changes cannot be detected by the conventional technique. The development of new magnetic resonance imaging techniques has enabled the functional assessment of the structures in order to obtain information on the different physiological processes of the tumor microenvironment, such as oxygenation levels, cellularity and vascularity. The detailed morphological study in association with the new functional imaging techniques allows for an appropriate approach to cancer patients, including the phases of diagnosis, staging, response evaluation and follow-up, with a positive impact on their quality of life and survival rate.

Fast spectroscopic multiple analysis (FASMA) for brain tumor classification: a clinical decision support system utilizing multi-parametric 3T MR data

INTRODUCTION

A clinical decision support system (CDSS) for brain tumor classification can be used to assist in the diagnosis and grading of brain tumors. A Fast Spectroscopic Multiple Analysis (FASMA) system that uses combinations of multiparametric MRI data sets was developed as a CDSS for brain tumor classification.

METHODS

MRI metabolic ratios and spectra, from long and short TE, respectively, as well as diffusion and perfusion data were acquired from the intratumoral and peritumoral area of 126 patients with untreated intracranial tumors. These data were categorized based on the pathology, and different machine learning methods were evaluated regarding their classification performance for glioma grading and differentiation of infiltrating versus non-infiltrating lesions. Additional databases were embedded to the system, including updated literature values of the related MR parameters and typical tumor characteristics (imaging and histological), for further comparisons. Custom Graphical User Interface (GUI) layouts were developed to facilitate classification of the unknown cases based on the user's available MR data.

RESULTS

The highest classification performance was achieved with a support vector machine (SVM) using the combination of all MR features. FASMA correctly classified 89 and 79% in the intratumoral and peritumoral area, respectively, for cases from an independent test set. FASMA produced the correct diagnosis, even in the misclassified cases, since discrimination between infiltrative versus non-infiltrative cases was possible.

CONCLUSIONS

FASMA is a prototype CDSS, which integrates complex quantitative MR data for brain tumor characterization. FASMA was developed as a diagnostic assistant that provides fast analysis, representation and classification for a set of MR parameters. This software may serve as a teaching tool on advanced MRI techniques, as it incorporates additional information regarding typical tumor characteristics derived from the literature.

Metabolic white matter diseases and the utility of MR spectroscopy

Magnetic resonance spectroscopy (MRS) can be useful as an adjuvant diagnostic tool to traditional MR imaging of the brain. MRS can provide both quantitative and qualitative information about white matter pathologic abnormality. It is important to interpret MRS in conjunction with other clinical factors including but not limited to additional diagnostic neuroimaging, history and physical examination findings, and genetics.