Non-invasive grading of astrocytic tumours from the relative contents of myo-inositol and glycine measured by in vivo MRS

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

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

Robust Conditional Independence maps of single-voxel Magnetic Resonance Spectra to elucidate associations between brain tumours and metabolites

The aim of the paper is two-fold. First, we show that structure finding with the PC algorithm can be inherently unstable and requires further operational constraints in order to consistently obtain models that are faithful to the data. We propose a methodology to stabilise the structure finding process, minimising both false positive and false negative error rates. This is demonstrated with synthetic data. Second, to apply the proposed structure finding methodology to a data set comprising single-voxel Magnetic Resonance Spectra of normal brain and three classes of brain tumours, to elucidate the associations between brain tumour types and a range of observed metabolites that are known to be relevant for their characterisation. The data set is bootstrapped in order to maximise the robustness of feature selection for nominated target variables. Specifically, Conditional Independence maps (CI-maps) built from the data and their derived Bayesian networks have been used. A Directed Acyclic Graph (DAG) is built from CI-maps, being a major challenge the minimization of errors in the graph structure. This work presents empirical evidence on how to reduce false positive errors via the False Discovery Rate, and how to identify appropriate parameter settings to improve the False Negative Reduction. In addition, several node ordering policies are investigated that transform the graph into a DAG. The obtained results show that ordering nodes by strength of mutual information can recover a representative DAG in a reasonable time, although a more accurate graph can be recovered using a random order of samples at the expense of increasing the computation time.

Magnetic resonance spectroscopy in posterior fossa tumours: the tumour spectroscopic signature may improve discrimination in adults among haemangioblastoma, ependymal tumours, medulloblastoma, and metastasis

OBJECTIVES

Assessing a posterior fossa tumour in an adult can be challenging. Metastasis, haemangioblastoma, ependymal tumours, and medulloblastoma are the most common diagnostic possibilities. Our aim was to evaluate the contribution of magnetic resonance spectroscopy (MRS) in the diagnosis of these entities.

METHODS

We retrospectively evaluated 56 consecutive patients with a posterior fossa tumour and histological diagnosis of ependymal tumour, medulloblastoma, haemangioblastoma, and metastasis in which good-quality spectra at short (TE 30 ms) or/and intermediate (TE, 136 ms) TE were available. Spectra were compared using the Mann-Whitney U non-parametric test in order to select the spectral datapoints and the intensity ratios that showed significant differences between groups of lesions. Performance of these datapoints and their ratios were assessed with ROC curves.

RESULTS

The most characteristic signatures on spectroscopy were high choline (Cho) in medulloblastoma (p < 0.001), high myoinositol (mIns) in ependymal tumours (p < 0.05), and high lipids (LIP) in haemangioblastoma (p < 0.01) and metastasis (p < 0.01). Selected ratios between normalised intensity signals of resonances provided accuracy values between 79 and 95% for pairwise comparisons. Intensity ratio NI_{3.21ppm/3.55ppm} provided satisfactory discrimination between medulloblastoma and ependymal tumours (accuracy, 92%), ratio NI_{2.11ppm/1.10ppm} discriminated ependymal tumours from haemangioblastoma (accuracy, 94%), ratio NI_{3.21ppm/1.13ppm} discriminated haemangioblastoma from medulloblastoma (accuracy, 95%), and ratio NI_{1.28ppm/2.02pmm} discriminated haemangioblastoma from metastasis (accuracy, 83%).

CONCLUSIONS

MRS may improve the non-invasive diagnosis of posterior fossa tumours in adults.

KEY POINTS

• High choline suggests a medulloblastoma in a posterior fossa tumour. • High myoinositol suggests an ependymal lesion in a posterior fossa tumour. • High lipids suggest a metastasis or a haemangioblastoma in a posterior fossa tumour.

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.

Myoinositol as a Biomarker in Recurrent Glioblastoma Treated with Bevacizumab: A 1H-Magnetic Resonance Spectroscopy Study

Background

Antiangiogenic treatment of glioblastomas with Bevacizumab lacks predictive markers. Myoinositol (MI) is an organic osmolyte, with intracellular concentration changes depending on the extracellular osmolality. Since Bevacizumab markedly reduces tumor edema and influences the tumor microenvironment, we investigated whether the MI concentration in the tumor changes during therapy.

Methods

We used ¹H-magnetic resonance spectroscopy to measure the MI concentrations in the tumor and contralateral control tissue of 39 prospectively recruited patients with recurrent glioblastomas before and 8–12 weeks after starting therapy. 30 patients received Bevacizumab and 9 patients were treated with CCNU/VM26 as control. We performed a survival analysis to evaluate MI as a predictive biomarker for Bevacizumab therapy.

Results

MI concentrations increased significantly during Bevacizumab therapy in tumor (p < .001) and control tissue (p = .001), but not during CCNU/VM26 treatment. For the Bevacizumab cohort, higher MI concentrations in the control tissue at baseline (p = .021) and higher differences between control and tumor tissue (delta MI, p = .011) were associated with longer survival. A Kaplan-Meier analysis showed a median OS of 164 days for patients with a deltaMI < 1,817 mmol/l and 275 days for patients with a deltaMI > 1,817 mmol/l. No differences were observed for the relative changes or the post treatment concentrations. Additionally calculated creatine concentrations showed no differences in between subgroups or between pre and post treatment measurements.

Conclusion

Our data suggest that recurrent glioblastoma shows a strong metabolic reaction to Bevacizumab. Further, our results support the hypothesis that MI might be a marker for early tumor cell invasion. Pre-therapeutic MI concentrations are predictive of overall survival in patients with recurrent glioblastoma treated with Bevacizumab.

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.

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Magnetic resonance spectroscopy is an established technology for non-invasive assessment of pathological tissue.

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Good understanding of the physical principles of the technique can help one exploit it maximally.

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An array of information from the technique is available and needs deep understanding of the results.

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Newer variations of this technology are being invented to evaluate different aspects of pathologies in a more refined manner.

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We also discuss the limitations of this technology and possible solutions there-off.

Multimodal MRI can identify perfusion and metabolic changes in the invasive margin of glioblastomas

PURPOSE

To use perfusion and magnetic resonance (MR) spectroscopy to compare the diffusion tensor imaging (DTI)-defined invasive and noninvasive regions. Invasion of normal brain is a cardinal feature of glioblastomas (GBM) and a major cause of treatment failure. DTI can identify invasive regions.

MATERIALS AND METHODS

In all, 50 GBM patients were imaged preoperatively at 3T with anatomic sequences, DTI, dynamic susceptibility perfusion MR (DSCI), and multivoxel spectroscopy. The DTI and DSCI data were coregistered to the spectroscopy data and regions of interest (ROIs) were made in the invasive (determined by DTI), noninvasive regions, and normal brain. Values of relative cerebral blood volume (rCBV), N-acetyl aspartate (NAA), myoinositol (mI), total choline (Cho), and glutamate + glutamine (Glx) normalized to creatine (Cr) and Cho/NAA were measured at each ROI.

RESULTS

Invasive regions showed significant increases in rCBV, suggesting angiogenesis (invasive rCBV 1.64 [95% confidence interval, CI: 1.5-1.76] vs. noninvasive 1.14 [1.09-1.18]; P < 0.001), Cho/Cr (invasive 0.42 [0.38-0.46] vs. noninvasive 0.35 [0.31-0.38]; P = 0.02) and Cho/NAA (invasive 0.54 [0.41-0.68] vs. noninvasive 0.37 [0.29-0.45]; P = < 0.03), suggesting proliferation, and Glx/Cr (invasive 1.54 [1.27-1.82] vs. noninvasive 1.3 [1.13-1.47]; P = 0.028), suggesting glutamate release; and a significantly reduced NAA/Cr (invasive 0.95 [0.85-1.05] vs. noninvasive 1.19 [1.06-1.31]; P = 0.008). The mI/Cr was not different between the three ROIs (invasive 1.2 [0.99-1.41] vs. noninvasive 1.3 [1.14-1.46]; P = 0.68). In the noninvasive regions, the values were not different from normal brain.

CONCLUSION

Combining DTI to identify the invasive region with perfusion and spectroscopy, we can identify changes in invasive regions not seen in noninvasive regions.

Enduring deficits in memory and neuronal pathology after blast-induced traumatic brain injury

Few preclinical studies have assessed the long-term neuropathology and behavioral deficits after sustaining blast-induced neurotrauma (BINT). Previous studies have shown extensive astrogliosis and cell death at acute stages (<7 days) but the temporal response at a chronic stage has yet to be ascertained. Here, we used behavioral assays, immmunohistochemistry and neurochemistry in limbic areas such as the amygdala (Amy), Hippocampus (Hipp), nucleus accumbens (Nac), and prefrontal cortex (PFC), to determine the long-term effects of a single blast exposure. Behavioral results identified elevated avoidance behavior and decreased short-term memory at either one or three months after a single blast event. At three months after BINT, markers for neurodegeneration (FJB) and microglia activation (Iba-1) increased while index of mature neurons (NeuN) significantly decreased in all brain regions examined. Gliosis (GFAP) increased in all regions except the Nac but only PFC was positive for apoptosis (caspase-3). At three months, tau was selectively elevated in the PFC and Hipp whereas α-synuclein transiently increased in the Hipp at one month after blast exposure. The composite neurochemical measure, myo-inositol+glycine/creatine, was consistently increased in each brain region three months following blast. Overall, a single blast event resulted in enduring long-term effects on behavior and neuropathological sequelae.

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.

Multicentre evaluation of the INTERPRET decision support system 2.0 for brain tumour classification

In a previous study, we have shown the added value of (1) H MRS for the neuroradiological characterisation of adult human brain tumours. In that study, several methods of MRS analysis were used, and a software program, the International Network for Pattern Recognition of Tumours Using Magnetic Resonance Decision Support System 1.0 (INTERPRET DSS 1.0), with a short-TE classifier, provided the best results. Since then, the DSS evolved into a version 2.0 that contains an additional long-TE classifier. This study has two objectives. First, to determine whether clinicians with no experience of spectroscopy are comparable with spectroscopists in the use of the system, when only minimum training in the use of the system was given. Second, to assess whether or not a version with another TE is better than the initial version. We undertook a second study with the same cases and nine evaluators to assess whether the diagnostic accuracy of DSS 2.0 was comparable with the values obtained with DSS 1.0. In the second study, the analysis protocol was flexible in comparison with the first one to mimic a clinical environment. In the present study, on average, each case required 5.4 min by neuroradiologists and 9 min by spectroscopists for evaluation. Most classes and superclasses of tumours gave the same results as with DSS 1.0, except for astrocytomas of World Health Organization (WHO) grade III, in which performance measured as the area under the curve (AUC) decreased: AUC = 0.87 (0.72-1.02) with DSS 1.0 and AUC = 0.62 (0.55-0.70) with DSS 2.0. When analysing the performance of radiologists and spectroscopists with respect to DSS 1.0, the results were the same for most classes. Having data with two TEs instead of one did not affect the results of the evaluation.

Mapping of glycine distributions in gliomas

BACKGROUND AND PURPOSE

Increased glycine concentration in the brain is associated with altered metabolism in cancer and can be detected by using in vivo MR spectroscopy. This has been proposed as a marker for grade IV gliomas; however, little is known about the potential significance and frequency of in vivo glycine observation. The purpose of this study was to examine the rate of occurrence and spatial distribution of glycine observation with respect to other MR imaging parameters.

MATERIALS AND METHODS

Data from volumetric whole-brain MR spectroscopic imaging of 59 subjects with glioma were analyzed with glycine included in the spectral model. The associations of the signal amplitude and spatial distributions of glycine with findings from contrast-enhanced T1, perfusion, and diffusion MR imaging were then examined.

RESULTS

Glycine was detected in 24% of all studies, though with a wide range of signal amplitude and extent of the spatial distributions. While more commonly seen in grade IV tumors (42% of studies), relatively large concentrations were also detected in grade II and III gliomas. Coanalysis with other metabolites indicated a strong association with choline and that glycine was frequently seen to be overlapping with, and adjacent to, areas of high lactate concentration. Increased glycine was always associated with contrast enhancement and areas of increased cerebral blood flow, but without any clear association with other image parameters.

CONCLUSIONS

Detection of increased glycine in gliomas appears to identify a subgroup of tumors and areas of increased proliferation.

Quantifying the CDK inhibitor VMY-1-103's activity and tissue levels in an in vivo tumor model by LC-MS/MS and by MRI

The development of new small molecule-based therapeutic drugs requires accurate quantification of drug bioavailability, biological activity and treatment efficacy. Rapidly measuring these endpoints is often hampered by the lack of efficient assay platforms with high sensitivity and specificity. Using an in vivo model system, we report a simple and sensitive liquid chromatography-tandem mass spectrometry assay to quantify the bioavailability of a recently developed novel cyclin-dependent kinase inhibitor VMY-1-103, a purvalanol B-based analog whose biological activity is enhanced via dansylation. We developed a rapid organic phase extraction technique and validated wide and functional VMY-1-103 distribution in various mouse tissues, consistent with its enhanced potency previously observed in a variety of human cancer cell lines. More importantly, in vivo MRI and single voxel proton MR-Spectroscopy further established that VMY-1-103 inhibited disease progression and affected key metabolites in a mouse model of hedgehog-driven medulloblastoma.