Potential of MR spectroscopy for assessment of glioma grading. Clin Neurol Neurosurg. 2013;115:146-153. [PMID: 23237636 DOI: 10.1016/j.clineuro.2012.11.002]

Beyond conventional imaging: Advancements in MRI for glioma malignancy prediction and molecular profiling

This review examines the advancements in magnetic resonance imaging (MRI) techniques and their pivotal role in diagnosing and managing gliomas, the most prevalent primary brain tumors. The paper underscores the importance of integrating modern MRI modalities, such as diffusion-weighted imaging and perfusion MRI, which are essential for assessing glioma malignancy and predicting tumor behavior. Special attention is given to the 2021 WHO Classification of Tumors of the Central Nervous System, emphasizing the integration of molecular diagnostics in glioma classification, significantly impacting treatment decisions. The review also explores radiogenomics, which correlates imaging features with molecular markers to tailor personalized treatment strategies. Despite technological progress, MRI protocol standardization and result interpretation challenges persist, affecting diagnostic consistency across different settings. Furthermore, the review addresses MRI's capacity to distinguish between tumor recurrence and pseudoprogression, which is vital for patient management. The necessity for greater standardization and collaborative research to harness MRI's full potential in glioma diagnosis and personalized therapy is highlighted, advocating for an enhanced understanding of glioma biology and more effective treatment approaches.

Applying chemical shift images (in-phase/opposed phased) for differentiating low-grade from high-grade glioma and comparison with magnetic resonance spectroscopy

BACKGROUND

Grading gliomas is essential for treatment decisions and patient prognosis. In this study we evaluated the in-phase and out-of-phase sequences for distinguishing high-grade (HGG) from low-grade glioma (LGG) and the correlation with magnetic resonance spectroscopy (MRS) results.

METHODS

This observational study comprised patients with brain tumors referred to our center for brain MRS. The gold standard for diagnosis was based on the World Health Organization (WHO) glioma classification. A standard tumor protocol was accomplished using a 1.5‑T MRS scanner. Before contrast medium administration, extra in- and out-phase sequences were acquired. Three 20-30-mm2 oval regions of interest (ROIs) were placed in the solid component and the signal loss ratio (SLR) was calculated with the following formula: SLR tumor = (SI In phase - SI Opposed phase) / SI In phase Correlations and comparisons between groups were made using the Pearson, chi-square and, independent samples t tests. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic performance. Statistical significance was set at p < 0.05.

RESULTS

In total, 20 patients were included in the LGG and 13 were included in the HGG group. The mean SLR in the HGG and LGG groups was 3.66 ± 2.12 and 1.63 ± 1.86, respectively (p = 0.01). There was a statistically significant correlation between lipid lactate (0.48, p = 0.004) and free lipid (0.44, p = 0.009) concentrations on MRS with SLR.

CONCLUSIONS

The SLR is a simple, rapid, and noninvasive marker for differentiating between LGG and HGG. There is a significant correlation with both the concentration and presence of free lipid and lipid-lactate peaks in MRS.

Radio-pathomic maps of glioblastoma identify phenotypes of non-enhancing tumor infiltration associated with bevacizumab treatment response

BACKGROUND

Autopsy-based radio-pathomic maps of glioma pathology have shown substantial promise inidentifying areas of non-enhancing tumor presence, which may be able to differentiate subsets of patients that respond favorably to treatments such as bevacizumab that have shown mixed efficacy evidence. We tested the hypthesis that phenotypes of non-enhancing tumor fronts can distinguish between glioblastoma patients that will respond favorably to bevacizumab and will visually capture treatment response.

METHODS

T1, T1C, FLAIR, and ADC images were used to generate radio-pathomic maps of tumor characteristics for 79 pre-treatment patients with a primary GBM or high-grade IDH1-mutant astrocytoma for this study. Novel phenotyping (hypercellular, hypocellular, hybrid, or well-circumscribed front) of the non-enhancing tumor front was performed on each case. Kaplan Meier analyses were then used to assess differences in survival and bevacizumab efficacy between phenotypes. Phenotype compartment segmentations generated longitudinally for a subset of 26 patients over the course of bevacizumab treatment, where a mixed effect model was used to detect longitudinal changes.

RESULTS

Well-Circumscribed patients showed significant/trending increases in survival compared to Hypercellular Front (HR = 2.0, p = 0.05), Hypocellular Front (HR = 2.02, p = 0.03), and Hybrid Front tumors (HR = 1.75, p = 0.09). Only patients with hypocellular or hybrid fronts showed significant survival benefits from bevacizumab treatment (HR = 2.35, p = 0.02; and HR = 2.45, p = 0.03, respectively). Hypocellular volumes decreased by an average 50.52 mm3 per day of bevacizumab treatment (p = 0.002).

CONCLUSION

Patients with a hypocellular tumor front identified by radio-pathomic maps showed improved treatment efficacy when treated with bevacizumab, and reducing hypocellular volumes over the course of treatment may indicate treatment response.

Proton MR spectroscopy shows improved performance to segregate high-grade astrocytoma subgroups when defined with the new 2021 World Health Organization classification of central nervous system tumors

OBJECTIVES

The 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors prioritizes isocitrate dehydrogenase (IDH) mutation to define tumor types in diffuse gliomas, in contrast to the 2016 classification, which prioritized histological features. Our objective was to investigate the influence of this change in the performance of proton MR spectroscopy (1H-MRS) in segregating high-grade diffuse astrocytoma subgroups.

METHODS

Patients with CNS WHO grade 3 and 4 diffuse astrocytoma, known IDH mutation status, and available 1H-MRS were retrospectively retrieved and divided into 4 groups based on IDH mutation status and histological grade. Differences in 1H-MRS between groups were analyzed with the Kruskal-Wallis test. The points on the spectrum that showed the greatest differences were chosen to evaluate the performance of 1H-MRS in discriminating between grades 3 and 4 tumors (WHO 2016 defined), and between IDH-mutant and IDH-wildtype tumors (WHO 2021). ROC curves were constructed with these points, and AUC values were calculated and compared.

RESULTS

The study included 223 patients with high-grade diffuse astrocytoma. Discrimination between IDH-mutant and IDH-wildtype tumors showed higher AUC values (highest AUC short TE, 0.943; long TE, 0.864) and more noticeable visual differences than the discrimination between grade 3 and 4 tumors (short TE, 0.885; long TE, 0.838).

CONCLUSION

Our findings suggest that 1H-MRS is more applicable to classify high-grade astrocytomas defined with the 2021 criteria. Improved metabolomic robustness and more homogeneous groups yielded better tumor type discrimination by 1H-MRS with the new criteria.

CLINICAL RELEVANCE STATEMENT

The 2021 World Health Organization classification of brain tumors empowers molecular criteria to improve tumor characterization. This derives in greater segregation of high-grade diffuse astrocytoma subgroups by MR spectroscopy and warrants further development of brain tumor classification tools with spectroscopy.

KEY POINTS

• The new 2021 updated World Health Organization classification of central nervous system tumors maximizes the role of molecular diagnosis in the classification of brain tumors. • Proton MR spectroscopy performs better to segregate high-grade astrocytoma subgroups when defined with the new criteria. • The study provides additional evidence of improved metabolic characterization of brain tumor subgroups with the new criteria.

Noninvasive Autopsy-Validated Tumor Probability Maps Identify Glioma Invasion Beyond Contrast Enhancement

BACKGROUND AND OBJECTIVES

This study identified a clinically significant subset of patients with glioma with tumor outside of contrast enhancement present at autopsy and subsequently developed a method for detecting nonenhancing tumor using radio-pathomic mapping. We tested the hypothesis that autopsy-based radio-pathomic tumor probability maps would be able to noninvasively identify areas of infiltrative tumor beyond traditional imaging signatures.

METHODS

A total of 159 tissue samples from 65 subjects were aligned to MRI acquired nearest to death for this retrospective study. Demographic and survival characteristics for patients with and without tumor beyond the contrast-enhancing margin were computed. An ensemble algorithm was used to predict pixelwise tumor presence from pathological annotations using segmented cellularity (Cell), extracellular fluid, and cytoplasm density as input (6 train/3 test subjects). A second level of ensemble algorithms was used to predict voxelwise Cell, extracellular fluid, and cytoplasm on the full data set (43 train/22 test subjects) using 5-by-5 voxel tiles from T1, T1 + C, fluid-attenuated inversion recovery, and apparent diffusion coefficient as input. The models were then combined to generate noninvasive whole brain maps of tumor probability.

RESULTS

Tumor outside of contrast was identified in 41.5% of patients, who showed worse survival outcomes (hazard ratio = 3.90, P < .001). Tumor probability maps reliably tracked nonenhancing tumor on a range of local and external unseen data, identifying tumor outside of contrast in 69% of presurgical cases that also showed reduced survival outcomes (hazard ratio = 1.67, P = .027).

CONCLUSION

This study developed a multistage model for mapping gliomas using autopsy tissue samples as ground truth, which was able to identify regions of tumor beyond traditional imaging signatures.

Multiparametric MRI and T2/FLAIR mismatch complements the World Health Organization 2021 classification for the diagnosis of IDH-mutant 1p/19q non-co-deleted/ATRX-mutant astrocytoma

AIM

To investigate whether T2-weighted imaging-fluid-attenuated inversion recovery (T2/FLAIR) mismatch, T2∗ dynamic susceptibility contrast (DSC) perfusion, and magnetic resonance spectroscopy (MRS) correlated with the histological diagnosis and grading of IDH (isocitrate dehydrogenase)-mutant, 1p/19q non-co-deleted/ATRX (alpha-thalassemia mental retardation X-linked)-mutant astrocytoma.

MATERIALS

Imaging of 101 IDH-mutant diffuse glioma cases of histological grades 2-3 (2019-2021) were analysed retrospectively by two neuroradiologists blinded to the molecular diagnosis. T2/FLAIR mismatch sign is used for radio-phenotyping, and pre-biopsy multiparametric MRI images were assessed for grading purposes. Cut-off values pre-determined for radiologically high-grade lesions were relative cerebral blood volume (rCBV) ≥2, choline/creatine ratio (Cho/Cr) ≥1.5 (30 ms echo time [TE]), Cho/Cr ≥1.8 (135 ms TE).

RESULTS

Sixteen of the 101 cases showed T2/FLAIR mismatch, all of which were histogenetically confirmed IDH-mutant 1p/19q non-co-deleted/ATRX mutant astrocytomas; 50% were grade 3 (8/16) and 50% grade 2 (8/16). None showed contrast enhancement. Nine of the 16 had adequate multiparametric MRI for analysis. Any positive value by combining rCBV ≥2 with Cho/Cr ≥1.5 (30 ms TE) or Cho/Cr ≥1.8 (135 ms TE) predicted grade 3 histology with sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 100%.

CONCLUSION

The T2/FLAIR mismatch sign detected diffuse astrocytomas with 100% specificity. When combined with high Cho/Cr and raised rCBV, this predicted histological grading with high accuracy. The future direction for imaging should explore a similar integrated layered approach of 2021 classification of central nervous system (CNS) tumours combining radio-phenotyping and grading from structural and multiparametric imaging.

Implantable theranostic device for in vivo real-time NMR evaluation of drug impact in brain tumors

The evaluation of the efficacy of a drug is a fundamental step in the development of new treatments or in personalized therapeutic strategies and patient management. Ideally, this evaluation should be rapid, possibly in real time, easy to perform and reliable. In addition, it should be associated with as few adverse effects as possible for the patient. In this study, we present a device designed to meet these goals for assessing therapeutic response. This theranostic device is based on the use of magnetic resonance imaging and spectroscopy for the diagnostic aspect and on the application of the convection-enhanced delivery technique for the therapeutic aspect. The miniaturized device is implantable and can be used in vivo in a target tissue. In this study, the device was applied to rodent glioma models with local administration of choline kinase inhibitor and acquisition of magnetic resonance images and spectra at 7 Tesla. The variations in the concentration of key metabolites measured by the device during the administration of the molecules demonstrate the relevance of the approach and the potential of the device.

Magnetic Resonance Spectroscopy of Intra-axial Gliomas With Histopathological Correlation in a Tertiary Care Center of Eastern Nepal

Background and objective Magnetic resonance spectroscopy (MRS) is a magnetic resonance imaging technique used to identify in vivo metabolites non-invasively within the tissue of interest. It plays an important role in diagnosing brain lesions, particularly tumors and infections. There are certain metabolites whose levels are increased or decreased in brain tumors, the ratios of which can also be used to grade the tumors as high- or low-grade. This study aimed to assess the spectrum of different metabolites in intraaxial gliomas using magnetic resonance spectroscopy and to assess the usefulness of their ratios for grading gliomas into high-grade and low-grade. Methods This descriptive cross-sectional study was performed in the radiology department of Nobel Medical College and Teaching Hospital, Biratnagar, Nepal over one year (September 2019 to September 2020). Thirty-five patients diagnosed as having intra-axial tumors were enrolled. After taking informed consent the examination findings were recorded in structured proforma. Siemens' 3 Tesla open magnet MAGNETOM Skyra (Siemens Healthineers AG, Munich, Germany) MR scanner was used to evaluate each patient. Data was analyzed using the software Statistical Package for Social Sciences (SPSS), version 26.0 (IBM Corp., Armonk, NY). Results Out of 35 patients scanned, 18 had high-grade glioma and 17 had low-grade glioma. High-grade glioma had a choline/creatine (Cho/Cr) ratio of 2.44 ± 0.78 and a choline/N-acetyl-aspartate (Cho/NAA) ratio of 2.05 ± 0.84. Low-grade glioma had a Cho/Cr ratio of 1.48 ± 0.50 and a Cho/NAA ratio of 1.41 ± 0.19. Fourteen out of eighteen high-grade gliomas had raised lipid/lactate peaks. The sensitivity, specificity, positive and negative predictive values (PPV and NPV), and accuracy for diagnosing high-grade glioma with a Cho/Cr ratio cut-off of 1.5 was 83.3 %, 82.4%, 83.3%,82.4 %, and 82.85% respectively. Conclusion MRS metabolite ratios can be used to diagnose and grade gliomas. Cho/Cr, Cho/NAA, and the presence or absence of lipid/lactate peak can significantly improve the sensitivity, specificity, predictive values, and accuracy of preoperative glioma grading when used in conjunction with conventional MRI.

Radio-pathomic maps of glioblastoma identify phenotypes of non-enhancing tumor infiltration associated with bevacizumab treatment response

Background

Autopsy-based radio-pathomic maps of glioma pathology have shown substantial promise inidentifying areas of non-enhancing tumor presence, which may be able to differentiate subsets of patients that respond favorably to treatments such as bevacizumab that have shown mixed efficacy evidence. We tested the hypthesis that phenotypes of non-enhancing tumor fronts can distinguish between glioblastoma patients that will respond favorably to bevacizumab and will visually capture treatment response.

Methods

T1, T1C, FLAIR, and ADC images were used to generate radio-pathomic maps of tumor characteristics for 79 pre-treatment patients with a primary GBM or high-grade IDH1-mutant astrocytoma for this study. Novel phenotyping (hypercellular, hypocellular, hybrid, or well-circumscribed front) of the non-enhancing tumor front was performed on each case. Kaplan Meier analyses were then used to assess differences in survival and bevacizumab efficacy between phenotypes. Phenotype compartment segmentations generated longitudinally for a subset of 26 patients over the course of bevacizumab treatment, where a mixed effect model was used to detect longitudinal changes.

Results

Well-Circumscribed patients showed significant/trending increases in survival compared to Hypercellular Front (HR = 2.0, p = 0.05), Hypocellular Front (HR = 2.02, p = 0.03), and Hybrid Front tumors (HR = 1.75, p = 0.09). Only patients with hypocellular or hybrid fronts showed significant survival benefits from bevacizumab treatment (HR = 2.35, p = 0.02; and HR = 2.45, p = 0.03, respectively). Hypocellular volumes decreased by an average 50.52 mm3 per day of bevacizumab treatment (p = 0.002).

Conclusion

Patients with a hypocellular tumor front identified by radio-pathomic maps showed improved treatment efficacy when treated with bevacizumab, and reducing hypocellular volumes over the course of treatment may indicate treatment response.

Brain metabolic profile assessed by magnetic resonance spectroscopy in ‎‎children with Down syndrome: Relation to intelligence quotient

BACKGROUND

Down syndrome (DS) is one of the most common causes of intellectual disability. Children with DS have varying intelligence quotient (IQ) that can predict their learning abilities.

AIM

To assess the brain metabolic profiles of children with DS and compare them to standard controls, using magnetic resonance spectroscopy (MRS) and correlating the results with IQ.

METHODS

This case-control study included 40 children with DS aged 6-15 years and 40 age and sex-matched healthy children as controls. MRS was used to evaluate ratios of choline/creatine (Cho/Cr), N-acetyl aspartic acid/creatine (NAA/Cr), and myoinositol/creatine (MI/Cr (in the frontal, temporal, and occipital lobes and basal ganglia and compared to controls and correlated with IQ.

RESULTS

Children with DS showed significant reductions in NAA/Cr and MI/Cr and a non-significant reduction in Cho/Cr in frontal lobes compared to controls. Additionally, we observed significant decreases in NAA/Cr, MI/Cr, and Cho/Cr in the temporal and occipital lobes and basal ganglia in children with DS compared to controls. Furthermore, there was a significant correlation between IQ and metabolic ratios in the brains of children with DS.

CONCLUSION

Brain metabolic profile could be a good predictor of IQ in children with DS.

How to evaluate extent of resection in diffuse gliomas: from standards to new methods

PURPOSE OF REVIEW

Maximal safe tumor resection represents the current standard of care for patients with newly diagnosed diffuse gliomas. Recent efforts have highlighted the prognostic value of extent of resection measured as residual tumor volume in patients with isocitrate dehydrogenase (IDH)-wildtype and -mutant gliomas. Accurate assessment of such information therefore appears essential in the context of clinical trials as well as patient management.

RECENT FINDINGS

Current recommendations for evaluation of extent of resection rest upon standardized postoperative MRI including contrast-enhanced T1-weighted sequences, T2-weighted/fluid-attenuated-inversion-recovery sequences, and diffusion-weighted imaging to differentiate postoperative tumor volumes from ischemia and nonspecific imaging findings. In this context, correct timing of postoperative imaging within the postoperative period is of utmost importance. Advanced MRI techniques including perfusion-weighted MRI and MR-spectroscopy may add further insight when evaluating residual tumor remnants. Positron emission tomography (PET) using amino acid tracers proves beneficial in identifying metabolically active tumor beyond anatomical findings on conventional MRI.

SUMMARY

Future efforts will have to refine recommendations on postoperative assessment of residual tumor burden in respect to differences between IDH-wildtype and -mutant gliomas, and incorporate the emerging role of advanced imaging modalities like amino acid PET.

Unique magnetic resonance spectroscopy profile of intracranial meningiomas compared to gliomas: a systematic review

BACKGROUND AND PURPOSE

The goal of this study was to systematically review the metabolic profile of meningiomas using magnetic resonance spectroscopy in comparison to gliomas, as measured by mean metabolite ratios.

METHODS

Following the PRISMA guidelines, a systematic literature review was performed using the PubMed, Ovid Embase, Web of Science, and the Cochrane databases from inception to May 2021. Studies were selected based on predetermined inclusion and exclusion criteria.

RESULTS

Eight studies were ultimately selected with 207 patients included. Fifty-nine patients were diagnosed with meningioma (age = 48.4, 66.7% female) and 148 patients diagnosed with glioma (age = 56.4, 49.2% female). Three studies reported elevated Cho/Cr in meningiomas compared to gliomas (5.71 vs. 1.46, p < 0.05, 7.02 vs. 2.62, p < 0.05, and 4.64 vs. 2.52, p = 0.001). One study reported Ala/Cr to be significantly elevated in meningiomas compared to gliomas (1.30 vs. undetectable, p < 0.001). One study reported myo-Inositol/Cr to be significantly elevated in meningiomas in comparison to gliomas (1.44 vs. 1.08, p < 0.05). One study reported Glu/Cr to be significantly elevated in meningiomas in comparison to gliomas (3.47 vs. 0.89, p = 0.002). Two studies reported Cho/NAA to be significantly elevated in meningiomas in comparison to gliomas (4.46 vs. 2.6, p = 0.004, and 5.8 vs. 2.55, p < 0.05). Two studies reported NAA/Cr was significantly elevated in gliomas compared to meningiomas (undetectable vs. 1.54, p < 0.001 and undetectable vs. 0.58, p < 0.05).

CONCLUSIONS

Significant differences in metabolite ratios between tumor types were reported in Cho/Cr, Ala/Cr, Glu/Cr, Cho/NAA, myoI/Cr and NAA/Cr between meningiomas and gliomas.

In vivo MRS study of long-term effects of traumatic intracranial injection of a culture medium in mice

Orthotopic transplantation of glioblastoma cells in the brain of laboratory mice is a common animal model for studying brain tumors. It was shown that 1H magnetic resonance spectroscopy (MRS) enables monitoring of the tumor's occurrence and its development during therapy based on the ratio of several metabolites. However, in studying new approaches to the therapy of glioblastoma in the model of orthotopic xenotransplantation of glioma cells into the brain of mice, it is necessary to understand which metabolites are produced by a growing tumor and which are the result of tumor cells injection along the modeling of the pathology. Currently, there are no data on the dynamic metabolic processes in the brain that occur after the introduction of glioblastoma cells into the brain of mice. In addition, there is a lack of data on the delayed effects of invasive brain damage. Therefore, this study investigates the long-term dynamics of the neurometabolic profile, assessed using 1H MRS, after intracranial injection of a culture medium used in orthotopic modeling of glioma in mice. Levels of N-acetylaspartate, N-acetylaspartylglutamic acid, myoinositol, taurine, glutathione, the sum of glycerophosphocholine and phosphocholine, glutamic acid (Glu), glutamine (Gln), and gamma aminobutyric acid (GABA) indicate patterns of neurometabolites in the early stage after intracranial injection similar to brain trauma ones. Most of the metabolites, with the exception of Gln, Glu and GABA, returned to their original values on day 28 after injection. A progressive increase in the Glu/Gln and Glu/GABA ratio up to 28 days after surgery potentially indicates an impaired turnover of these metabolites or increased neurotransmission. Thus, the data indicate that the recovery processes are largely completed on day 28 after the traumatic event in the brain tissue, leaving open the question of the neurotransmitter system impairment. Consequently, when using animal models of human glioma, researchers should clearly distinguish between which changes in neurometabolites are a response to the injection of cancer cells into the brain, and which processes may indicate the early development of a brain tumor. It is important to keep this in mind when modeling human glioblastoma in mice and monitoring new treatments. In addition, these results may be important in the development of approaches for non-invasive diagnostics of traumatic brain injury as well as recovery and rehabilitation processes of patients after certain brain surgeries.

Diagnostic Approaches to Adult-Type Diffuse Glial Tumors: Comparative Literature and Clinical Practice Study

Gliomas are the most frequent intrinsic central nervous system tumors. The new 2021 WHO Classification of Central Nervous System Tumors brought significant changes into the classification of gliomas, that underline the role of molecular diagnostics, with the adult-type diffuse glial tumors now identified primarily by their biomarkers rather than histology. The status of the isocitrate dehydrogenase (IDH) 1 or 2 describes tumors at their molecular level and together with the presence or absence of 1p/19q codeletion are the most important biomarkers used for the classification of adult-type diffuse glial tumors. In recent years terminology has also changed. IDH-mutant, as previously known, is diagnostically used as astrocytoma and IDH-wildtype is used as glioblastoma. A comprehensive understanding of these tumors not only gives patients a more proper treatment and better prognosis but also highlights new difficulties. MR imaging is of the utmost importance for diagnosing and supervising the response to treatment. By monitoring the tumor on followup exams better results can be achieved. Correlations are seen between tumor diagnostic and clinical manifestation and surgical administration, followup care, oncologic treatment, and outcomes. Minimal resection site use of functional imaging (fMRI) and diffusion tensor imaging (DTI) have become indispensable tools in invasive treatment. Perfusion imaging provides insightful information about the vascularity of the tumor, spectroscopy shows metabolic activity, and nuclear medicine imaging displays tumor metabolism. To accommodate better treatment the differentiation of pseudoprogression, pseudoresponse, or radiation necrosis is needed. In this report, we present a literature review of diagnostics of gliomas, the differences in their imaging features, and our radiology's departments accumulated experience concerning gliomas.

Metabolic Profiles Point Out Metabolic Pathways Pivotal in Two Glioblastoma (GBM) Cell Lines, U251 and U-87MG

Glioblastoma (GBM) is the most lethal central nervous system (CNS) tumor, mainly due to its high heterogeneity, invasiveness, and proliferation rate. These tumors remain a therapeutic challenge, and there are still some gaps in the GBM biology literature. Despite the significant amount of knowledge produced by research on cancer metabolism, its implementation in cancer treatment has been limited. In this study, we explored transcriptomics data from the TCGA database to provide new insights for future definition of metabolism-related patterns useful for clinical applications. Moreover, we investigated the impact of key metabolites (glucose, lactate, glutamine, and glutamate) in the gene expression and metabolic profile of two GBM cell lines, U251 and U-87MG, together with the impact of these organic compounds on malignancy cell features. GBM cell lines were able to adapt to the exposure to each tested organic compound. Both cell lines fulfilled glycolysis in the presence of glucose and were able to produce and consume lactate. Glutamine dependency was also highlighted, and glutamine and glutamate availability favored biosynthesis observed by the increase in the expression of genes involved in fatty acid (FA) synthesis. These findings are relevant and point out metabolic pathways to be targeted in GBM and also reinforce that patients' metabolic profiling can be useful in terms of personalized medicine.

Differentiation of astrocytoma between grades II and III using a combination of methionine positron emission tomography and magnetic resonance spectroscopy

Objective

This study aimed to establish a method for differentiating between grades II and III astrocytomas using preoperative imaging.

Methods

We retrospectively analyzed astrocytic tumors, including 18 grade II astrocytomas (isocitrate dehydrogenase (IDH)-mutant: IDH-wildtype = 8:10) and 56 grade III anaplastic astrocytomas (37:19). We recorded the maximum methionine (MET) uptake ratios (tumor-to-normal: T/N) on positron emission tomography (PET) and three MRS peak ratios: choline (Cho)/creatine (Cr), N-acetyl aspartate (NAA)/Cr, and Cho/NAA, between June 2015 and June 2020. We then evaluated the cut-off values to differentiate between grades II and III. We compared the grading results between contrast enhancement effects on MR and combinational diagnostic methods (CDM) on a scatter chart using the cutoff values of the T/N ratio and MRS parameters.

Results

The IDH-mutant group showed significant differences in the Cho/NAA ratio between grades II and III using univariate analysis; however, multiple regression analysis results negated this. The IDH-wildtype group showed no significant differences between the groups. Contrast enhancement effects also showed no significant differences in IDH status. Accordingly, regardless of the IDH status, no statistically independent factors differentiated between grades II and III. However, CDMs showed higher sensitivity and negative predictive value in distinguishing them than MRI contrast examinations for both IDH statuses. We demonstrated a significantly higher diagnostic rate of grade III than of grade II with CDM, which was more striking in the IDH-mutant group than in the wild-type group.

Conclusions

CDM could be valuable in differentiating between grade II and III astrocytic tumors.

Predicting TERT promoter mutation status using 1H-MR spectroscopy and stretched-exponential model of diffusion-weighted imaging in IDH-wildtype diffuse astrocytic glioma without intense enhancement

PURPOSE

Isocitrate dehydrogenase (IDH)-wildtype diffuse astrocytic glioma with telomerase reverse transcriptase (TERT) promoter mutation is defined as glioblastoma by the WHO 2021 criteria, revealing that TERT promotor mutation is highly associated with tumor aggressiveness. The aim of this study was to identify features from MR spectroscopy (MRS) and multi-exponential models of DWI distinguishing wild-type TERT (TERTw) from TERT promoter mutation (TERTm) in IDH-wildtype diffuse astrocytic glioma.

METHODS

Participants comprised 25 adult patients with IDH-wildtype diffuse astrocytic glioma. Participants were classified into TERTw and TERTm groups. Point-resolved spectroscopy sequences were used for MRS data acquisition. DWI was performed with 13 different b-factors. Peak height ratios of NAA/Cr and Cho/Cr were calculated from MRS data. Mean apparent diffusion coefficient (ADC), perfusion fraction (f), diffusion coefficient (D), pseudo-diffusion coefficient (D*), distributed diffusion coefficient (DDC), and heterogeneity index (α) were obtained using multi-exponential models from DWI data. Each parameter was compared between TERTw and TERTm using the Mann-Whitney U test. Correlations between parameters derived from MRS and DWI were also evaluated.

RESULTS

NAA/Cr and Cho/Cr were both higher for TERTw than for TERTm. The α of TERTw was smaller than that of TERTm, while the f of TERTw was higher than that of TERTm. NAA/Cr correlated negatively with α, but not with other DWI parameters. Cho/Cr did not show significant correlations with any DWI parameters.

CONCLUSION

The combination of NAA/Cr and α may have merit in clinical situation to predict the TERT mutation status of IDH-wildtype diffuse astrocytic glioma without intense enhancement.

Single-Voxel MR Spectroscopy of Gliomas with s-LASER at 7T

BACKGROUND AND PURPOSE

Magnetic resonance spectroscopy (MRS)-a method of analysing metabolites in vivo-has been utilized in several studies of brain glioma biomarkers at lower field strengths. At ultra-high field strengths, MRS provides an improved signal-to-noise-ratio and spectral resolution, but 7T studies on patients with gliomas are sparse. The purpose of this exploratory study was to evaluate the potential clinical implication of the use of single-voxel MRS at 7T to assess metabolic information on lesions in a pilot cohort of patients with grade II and III gliomas.

METHODS

We scanned seven patients and seven healthy controls using the semi-localization by adiabatic-selective refocusing sequence on a Philips Achieva 7T system with a standard dual-transmit head coil. The metabolic ratios were calculated relative to water and total creatine. Additionally, 2-hydroxyglutarate (2-HG) MRS was carried out in four of the patients, and the 2-HG concentration was calculated relative to water.

RESULTS

When comparing the tumour data to control regions in both patients and healthy controls, we found that the choline/creatine and myo-inositol/creatine ratios were significantly increased and that the N-acetylaspartate/creatine and the neurotransmitter glutamate/creatine ratios were significantly decreased. The N-acetylaspartate/water and glutamate/water ratios were also significantly decreased. The lactate/water and lactate/creatine ratios showed increases, although not significant. The GABA/water ratio was significantly decreased, but the GABA/creatine ratio was not. MRS spectra showed the presence of 2-HG in three of the four patients studied. Three of the patients, including the MRS 2-HG-negative patient, were operated on, and all of them had the IDH mutation.

CONCLUSION

Our findings were consistent with the existing literature on 3T and 7T MRS.

Is pre-radiotherapy metabolic heterogeneity of glioblastoma predictive of progression-free survival?

BACKGROUND AND PURPOSE

All glioblastoma subtypes share the hallmark of aggressive invasion, meaning that it is crucial to identify their different components if we are to ensure effective treatment and improve survival. Proton MR spectroscopic imaging (MRSI) is a noninvasive technique that yields metabolic information and is able to identify pathological tissue with high accuracy. The aim of the present study was to identify clusters of metabolic heterogeneity, using a large MRSI dataset, and determine which of these clusters are predictive of progression-free survival (PFS).

MATERIALS AND METHODS

MRSI data of 180 patients acquired in a pre-radiotherapy examination were included in the prospective SPECTRO-GLIO trial. Eight features were extracted for each spectrum: Cho/NAA, NAA/Cr, Cho/Cr, Lac/NAA, and the ratio of each metabolite to the sum of all the metabolites. Clustering of data was performed using a mini-batch k-means algorithm. The Cox model and logrank test were used for PFS analysis.

RESULTS

Five clusters were identified as sharing similar metabolic information and being predictive of PFS. Two clusters revealed metabolic abnormalities. PFS was lower when Cluster 2 was the dominant cluster in patients' MRSI data. Among the metabolites, lactate (present in this cluster and in Cluster 5) was the most statistically significant predictor of poor outcome.

CONCLUSION

Results showed that pre-radiotherapy MRSI can be used to reveal tumor heterogeneity. Groups of spectra, which have the same metabolic information, reflect the different tissue components representative of tumor burden proliferation and hypoxia. Clusters with metabolic abnormalities and high lactate are predictive of PFS.

Metabolic changes in glioblastomas in response to choline kinase inhibition: In vivo MRS in rodent models

Changes in glioblastoma (GBM) metabolism was investigated in response to JAS239, a choline kinase inhibitor, using MRS. In addition to the inhibition of phosphocholine synthesis, we investigated changes in other key metabolic pathways associated with GBM progression and treatment response. Three syngeneic rodent models of GBM were used: F98 (N = 12) and 9L (N = 8) models in rats and GL261 (N = 10) in mice. Rodents were intracranially injected with GBM cells in the right cortex and tumor growth was monitored using T₂ -weighted images. Animals were treated once daily with intraperitoneal injections of 4 mg/kg JAS239 (F98 rats, n = 6; 9L rats, n = 6; GL261 mice, n = 5) or saline (control group, F98 rats, n = 6; 9L rats, n = 2; GL261 mice, n = 5) for five consecutive days. Single voxel spectra were acquired on Days 0 (T0, baseline) and 6 (T6, end of treatment) from the tumor as well as the contralateral normal brain using a PRESS sequence. Changes in metabolite ratios (tCho/tCr, tCho/NAA, mI/tCr, Glx/tCr and (Lip + Lac)/Cr) were used to assess metabolic pathway alterations in response to JAS239. Tumor growth arrest was noted in all models in response to JAS239 treatment compared with saline-treated animals, with a significant reduction (p < 0.05) in the F98 model. A reduction in tCho/tCr was observed with JAS239 treatment in all GBM models, indicating reduced phospholipid metabolism, with the highest reduction in 9L followed by GL261 and F98 tumors. A significant reduction (p < 0.05) in the tCho/NAA ratio was observed in the 9L model. A significant reduction in mI/tCr (p < 0.05) was found in JAS239-treated F98 tumors compared with the saline-treated animals. A non-significant trend of reduction in Glx/tCr was observed only in F98 and 9L tumors. JAS239-treated F98 tumors also showed a significant increase in Lip + Lac (p < 0.05), indicating increased cell death. This study demonstrated the utility of MRS in assessing metabolic changes in GBM in response to choline kinase inhibition.

Discovering Glioma Tissue through Its Biomarkers' Detection in Blood by Raman Spectroscopy and Machine Learning

The most commonly occurring malignant brain tumors are gliomas, and among them is glioblastoma multiforme. The main idea of the paper is to estimate dependency between glioma tissue and blood serum biomarkers using Raman spectroscopy. We used the most common model of human glioma when continuous cell lines, such as U87, derived from primary human tumor cells, are transplanted intracranially into the mouse brain. We studied the separability of the experimental and control groups by machine learning methods and discovered the most informative Raman spectral bands. During the glioblastoma development, an increase in the contribution of lactate, tryptophan, fatty acids, and lipids in dried blood serum Raman spectra were observed. This overlaps with analogous results of glioma tissues from direct Raman spectroscopy studies. A non-linear relationship between specific Raman spectral lines and tumor size was discovered. Therefore, the analysis of blood serum can track the change in the state of brain tissues during the glioma development.

Challenges and opportunities for advanced neuroimaging of glioblastoma

Glioblastoma is the most aggressive of glial tumours in adults. On conventional magnetic resonance (MR) imaging, these tumours are observed as irregular enhancing lesions with areas of infiltrating tumour and cortical expansion. More advanced imaging techniques including diffusion-weighted MRI, perfusion-weighted MRI, MR spectroscopy and positron emission tomography (PET) imaging have found widespread application to diagnostic challenges in the setting of first diagnosis, treatment planning and follow-up. This review aims to educate readers with regard to the strengths and weaknesses of the clinical application of these imaging techniques. For example, this review shows that the (semi)quantitative analysis of the mentioned advanced imaging tools was found useful for assessing tumour aggressiveness and tumour extent, and aids in the differentiation of tumour progression from treatment-related effects. Although these techniques may aid in the diagnostic work-up and (post-)treatment phase of glioblastoma, so far no unequivocal imaging strategy is available. Furthermore, the use and further development of artificial intelligence (AI)-based tools could greatly enhance neuroradiological practice by automating labour-intensive tasks such as tumour measurements, and by providing additional diagnostic information such as prediction of tumour genotype. Nevertheless, due to the fact that advanced imaging and AI-diagnostics is not part of response assessment criteria, there is no harmonised guidance on their use, while at the same time the lack of standardisation severely hampers the definition of uniform guidelines.

Application of 7T MRS to High-Grade Gliomas

MRS, including single-voxel spectroscopy and MR spectroscopic imaging, captures metabolites in high-grade gliomas. Emerging evidence indicates that 7T MRS may be more sensitive to aberrant metabolic activity than lower-field strength MRS. However, the literature on the use of 7T MRS to visualize high-grade gliomas has not been summarized. We aimed to identify metabolic information provided by 7T MRS, optimal spectroscopic sequences, and areas for improvement in and new applications for 7T MRS. Literature was found on PubMed using "high-grade glioma," "malignant glioma," "glioblastoma," "anaplastic astrocytoma," "7T," "MR spectroscopy," and "MR spectroscopic imaging." 7T MRS offers higher SNR, modestly improved spatial resolution, and better resolution of overlapping resonances. 7T MRS also yields reduced Cramér-Rao lower bound values. These features help to quantify D-2-hydroxyglutarate in isocitrate dehydrogenase 1 and 2 gliomas and to isolate variable glutamate, increased glutamine, and increased glycine with higher sensitivity and specificity. 7T MRS may better characterize tumor infiltration and treatment effect in high-grade gliomas, though further study is necessary. 7T MRS will benefit from increased sample size; reductions in field inhomogeneity, specific absorption rate, and acquisition time; and advanced editing techniques. These findings suggest that 7T MRS may advance understanding of high-grade glioma metabolism, with reduced Cramér-Rao lower bound values and better measurement of smaller metabolite signals. Nevertheless, 7T is not widely used clinically, and technical improvements are necessary. 7T MRS isolates metabolites that may be valuable therapeutic targets in high-grade gliomas, potentially resulting in wider ranging neuro-oncologic applications.

Radiological Prediction of Isocitrate Dehydrogenase (IDH) Mutational Status and Pathological Verification for Lower-Grade Astrocytomas

Background and objective

The isocitrate dehydrogenase (IDH) status of patients with World Health Organization (WHO) grade II or III astrocytoma is essential for understanding its biological features and determining therapeutic strategies. This study aimed to use radiological analysis to predict the IDH status of patients with lower-grade astrocytomas and to verify the pathological implications.

Methods

In this study, 47 patients with grade II (17 cases) or III astrocytomas (30 cases), based on 2016 WHO Classification, underwent methionine (MET) positron emission tomography (PET) and magnetic resonance spectroscopy (MRS) on the same day between January 2013 and June 2020. The patients were retrospectively assessed. Immunohistochemistry showed 23 cases of IDH-mutant and 24 of IDH-wildtype. Based on fluid-attenuated recovery inversion (FLAIR)/T2 imaging, three doctors blinded to clinical data independently allocated 18 patients to the clear boundary group between the tumor and the normal brain and 29 to the unclear boundary group. The peak ratios of N-acetylaspartate (NAA)/creatine (Cr), choline (Cho)/Cr, and Cho/NAA and the tumor-to-normal region (T/N) ratio for maximum accumulation in MET-PET were calculated. For statistical analysis, Fisher’s exact test was used to assess associations between two variables, and the Mann-Whitney U test to compare the values between the IDH-wildtype and IDH-mutant groups. The optimal cut-off values of MET T/N ratio and MRS parameters for discriminating IDH-wildtype from IDH-mutant were obtained using receiver operating characteristics curves.

Results

The unclear boundary group had significantly more IDH-wildtype cases than the clear boundary group (P<0.001). The IDH-wildtype group had significantly lower Cho/Cr (<1.84) and Cho/NAA (<1.62) ratios (P=0.02 and P=0.047, respectively) and a higher MET T/N ratio (>1.44, P=0.02) than the IDH-mutant group. The odds for the IDH-wildtype were 0.22 for patients who fulfilled none of the four criteria, including boundary status and three ratios, and 0.9 for all four criteria.

Conclusions

These results suggest that the combination of MRI, MRS, and MET-PET examination could be helpful for the prediction of IDH status in WHO grade II/III gliomas.

Metabolic and physiologic magnetic resonance imaging in distinguishing true progression from pseudoprogression in patients with glioblastoma

Pseudoprogression (PsP) refers to treatment-related clinico-radiologic changes mimicking true progression (TP) that occurs in patients with glioblastoma (GBM), predominantly within the first 6 months after the completion of surgery and concurrent chemoradiation therapy (CCRT) with temozolomide. Accurate differentiation of TP from PsP is essential for making informed decisions on appropriate therapeutic intervention as well as for prognostication of these patients. Conventional neuroimaging findings are often equivocal in distinguishing between TP and PsP and present a considerable diagnostic dilemma to oncologists and radiologists. These challenges have emphasized the need for developing alternative imaging techniques that may aid in the accurate diagnosis of TP and PsP. In this review, we encapsulate the current state of knowledge in the clinical applications of commonly used metabolic and physiologic magnetic resonance (MR) imaging techniques such as diffusion and perfusion imaging and proton spectroscopy in distinguishing TP from PsP. We also showcase the potential of promising imaging techniques, such as amide proton transfer and amino acid-based positron emission tomography, in providing useful information about the treatment response. Additionally, we highlight the role of "radiomics", which is an emerging field of radiology that has the potential to change the way in which advanced MR techniques are utilized in assessing treatment response in GBM patients. Finally, we present our institutional experiences and discuss future perspectives on the role of multiparametric MR imaging in identifying PsP in GBM patients treated with "standard-of-care" CCRT as well as novel/targeted therapies.

High Myoinositol on Proton MR Spectroscopy Could Be a Potential Signature of Papillary Tumors of the Pineal Region-Case Report of Two Patients

Papillary tumor of the pineal region (PTPR) is an uncommon entity in which a presurgical suspicion may be crucial for patient management. Maximal safe neurosurgical resection is of choice when PTPR is suspected, whereas non-surgical approaches can be considered in other tumors of the pineal region, such as pineocytoma or concrete subtypes of germ-cell tumors. In general terms, imaging features of tumors of the pineal region have been reported to be unspecific. Nevertheless, in this report, we describe two pathology-confirmed PTPRs in which presurgical proton MR spectroscopy demonstrated extremely high myoinositol, a pattern which drastically differs from that of other pineal tumors. We hypothesize that this high myoinositol may be related to PTPR’s known ependymal component, and that it could be used as a specific non-invasive diagnostic signature.

Targeted metabolomics analyses for brain tumor margin assessment during surgery

MOTIVATION

Identification and removal of micro-scale residual tumor tissue during brain tumor surgery are key for survival in glioma patients. For this goal, High-Resolution Magic Angle Spinning Nuclear Magnetic Resonance (HRMAS NMR) spectroscopy-based assessment of tumor margins during surgery has been an effective method. However, the time required for metabolite quantification and the need for human experts such as a pathologist to be present during surgery are major bottlenecks of this technique. While machine learning techniques that analyze the NMR spectrum in an untargeted manner (i.e. using the full raw signal) have been shown to effectively automate this feedback mechanism, high dimensional and noisy structure of the NMR signal limits the attained performance.

RESULTS

In this study, we show that identifying informative regions in the HRMAS NMR spectrum and using them for tumor margin assessment improves the prediction power. We use the spectra normalized with the ERETIC (electronic reference to access in vivo concentrations) method which uses an external reference signal to calibrate the HRMAS NMR spectrum. We train models to predict quantities of metabolites from annotated regions of this spectrum. Using these predictions for tumor margin assessment provides performance improvements up to 4.6% the Area Under the ROC Curve (AUC-ROC) and 2.8% the Area Under the Precision-Recall Curve (AUC-PR). We validate the importance of various tumor biomarkers and identify a novel region between 7.97 ppm and 8.09 ppm as a new candidate for a glioma biomarker.

AVAILABILITY AND IMPLEMENTATION

The code is released at https://github.com/ciceklab/targeted_brain_tumor_margin_assessment. The data underlying this article are available in Zenodo, at https://doi.org/10.5281/zenodo.5781769.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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.

Glutamic Acid and Total Creatine as Predictive Markers for Epilepsy in Glioblastoma by Using Magnetic Resonance Spectroscopy Before Surgery

OBJECTIVE

Epilepsy in glioblastoma patients significantly reduces their quality of life; however, little is known about the association between predicting epilepsy and metabolites in tumors. In this study, we used 3.0-T magnetic resonance imaging and ¹H-magnetic resonance spectroscopy (MRS) to quantify metabolite concentrations in patients with varying epilepsy histories.

METHODS

Fifty-one patients with glioblastoma underwent pretreatment 3.0-T MRI/¹H-MRS scanning. Single-voxel (1.5 cm³) MRS, in an enhanced lesion, was acquired using a double-echo point-resolved spectroscopic sequence with chemical-shift selective water suppression. MRS data were quantified with linear combination model (LC-Model) software. We compared the MRS data between groups with and without epilepsy during the postoperative course (EP).

RESULTS

The ratios of glutamate (Glu) and glutamate + glutamine (Glx) to total creatine (Glu/tCr and Glx/tCr) in the tumor were associated with epilepsy history. The receiver operating characteristic curve analysis showed that a Glu/tCr value of 1.81 was 70% sensitive and 90% specific for the prediction of EP (area under curve: 0.82). In the analysis excluding patients with preoperative epilepsy, a Glu/tCr value of 1.81 was 75% sensitive and 88% specific for the prediction (area under curve: 0.87).

CONCLUSIONS

Intratumoral metabolite concentrations measured using pretreatment 3.0-T MRI/¹H-MRS changed characteristically in the group with EP. Our study suggests that the Glu/tCr ratio in tumors has adequate reliability in predicting EP. Pretreatment MRS is a minimally invasive and simple procedure that can provide useful information on glioblastoma patients.

Advanced magnetic resonance imaging findings of cerebellar hemangioblastomas: A report of three cases and a literature review

On conventional magnetic resonance imaging (MRI), hemangioblastomas typically appear as mural nodules with an adjacent surrounding cyst or a solid mass in the cerebellum. However, hemangioblastomas sometimes cannot be reliably distinguished using this imaging technique from other tumors, especially pilocytic astrocytomas and metastatic tumors, because of their similar imaging findings and locations. Herein, we report three cases of cerebellar hemangioblastomas and review their findings on conventional and advanced MRI, including diffusion-weighted imaging (DWI), dynamic susceptibility-weighted contrast-enhanced perfusion-weighted imaging (DSC-PWI), and magnetic resonance spectroscopy (MRS). Solid contrast-enhanced lesions of hemangioblastomas showed increased apparent diffusion coefficient values on DWI, increased relative cerebral blood volume ratio on DSC-PWI, and high lipid/lactate peak on MRS. Therefore, advanced MRI techniques can be helpful in understanding the pathological and metabolic changes of hemangioblastomas and may be useful for their characterization.

1H-MR spectroscopy in grading of cerebral glioma: A new view point, MRS image quality assessment

Background

Noninvasive preoperative prediction of histological grading is essential for clinical management of cerebral glioma.

Purpose

This study aimed to investigate the association between the image quality assessment of 1H magnetic resonance spectroscopy and accurate grading of glioma.

Materials and Methods

98 glioma patients confirmed by pathology were retrospectively recruited in this single-center study. All patients underwent 1H-MRS examination at 3.0T before surgery. According to WHO standards, all cases were divided into two groups: low-grade glioma (grade I and II, 48 cases) and high-grade glioma (grades III and IV, 50 cases). The metabolite ratios in both grades were calculated before and after image quality assessment. The area under the receiver operating characteristic (ROC) curve was used to evaluate the capacity of each ratio in glioma grading.

Results

The Cho/Cr, Cho/NAA and NAA/Cr metabolite ratios had certain differences in each glioma group before and after MRS image quality assessment. In the low-grade glioma group, there was a dramatic difference in the Cho/Cr ratio before and after image quality assessment (p = 0.011). After MRS image quality assessment, the accuracy of glioma grading was significantly improved. The Cho/Cr ratio with 83.3% sensitivity and 93.7% specificity is the best index of glioma grading, with the optimal cutoff value of the Cho/Cr ratio being 3.72.

Conclusion

The image quality of MRS does affect the metabolite ratios and the results of glioma grading. MRS image quality assessment can observably improve the accuracy rate of glioma grading. The Cho/Cr ratio has the best diagnostic performance in differentiating high-grade from low-grade glioma.

Diagnostic Accuracy of Magnetic Resonance Spectroscopy in Predicting the Grade of Glioma Keeping Histopathology as the Gold Standard

Background

Gliomas are the most prevalent intrinsic tumors of the central nervous system and are categorized from grade I to grade IV. Magnetic resonance imaging (MRI) provides exact diagnosis, prognosis, and assessment of tumor response to current chemotherapy/immunotherapy and radiation therapy. With histopathology serving as the gold standard, we aimed to assess the diagnostic accuracy of magnetic resonance spectroscopy (MRS) in predicting glioma grade.

Methodology

This cross-sectional study was conducted in the Department of Radiology, KRL Hospital, Islamabad, from December 15, 2019, to September 30, 2021. After providing written consent, 80 patients with untreated gliomas were included in this study. The voxel of interest was identified using MRI brain conventional contrast-enhanced sequences to assess the grade of the gliomas and link it to the histology report. Following this identification, tissue metabolites were calculated using MRS.

Results

The patients’ age ranged from 13 to 80 years, with a mean age of 49.5 years. Male patients comprised 57.5% of the total study population, while female patients comprised 42.5%. Overall, 23.75% of patients had low-grade tumors, while 76.25% had high-grade tumors. Low-grade tumors had a choline (Cho)/creatine (Cr) metabolite ratio of 1.7421, whereas high-grade tumors had an average Cho/Cr metabolite ratio of 2.5575. N-acetyl aspartate (NAA)/Cr ratio was 1.6368 in low grade and 0.6734 in high-grade tumors. Sensitivity of 77% and specificity of 84.2% were noted, with 78.75% diagnostic accuracy for the Cho/Cr ratio.

Conclusions

Multivoxel MRS has been shown to reliably predict the grade of gliomas despite its non-invasive nature and lack of procedural challenges. When used together Cho/Cr and NAA/Cr ratios and histopathology can accurately determine tumor grade and can be used as a supplementary non-invasive technique.

Cerebral lesions in hematological malignancies: a case report

Background

Progressive multifocal leukoencephalopathy is a rare central nervous system disease, resulting from reactivation of latent John Cunningham virus. Monoclonal antibodies have recently become a relevant risk factor for developing progressive multifocal leukoencephalopathy.

Case summary

We report the case of a 62-year-old Caucasian man who was admitted to our department in June 2020 because of right homonymous hemianopia. Magnetic resonance imaging findings were first interpreted as an intracranial relapsed lymphoma, so brain biopsy was performed, but no neoplastic cell was found. Histological sample only showed a large number of macrophages. The patient came back to our attention because of the worsening of neurological symptoms. A second magnetic resonance imaging showed widespread lesions suggestive of a demyelinating process. John Cunningham virus DNA was detected by polymerase chain reaction assay of the cerebrospinal fluid (over 9 million units/μL). The patient was treated supportively, but the outcome was poor.

Discussion

A multidisciplinary assessment should be performed for differential diagnosis of cerebral lesions in hematologic malignancies. Progressive multifocal leukoencephalopathy should be suspected in cases of subacute neurological symptoms and imaging findings consistent with it, especially if the patient received immunosuppressive or immunomodulatory drugs.

Contrast-Enhanced Magnetic Resonance Imaging, Perfusion Magnetic Resonance Imaging, and 1H-Magnetic Resonance Spectroscopy Distinguish Primary Central Nervous System Vasculitis from Glioblastoma

BACKGROUND

We investigated the ability of magnetic resonance imaging (MRI) to distinguish primary central nervous system vasculitis (PCNSV) from glioblastoma to facilitate the development of an appropriate treatment for PCNSV.

METHODS

We enrolled patients who were treated for PCNSV or glioblastoma at our center between January 2007 and August 2018. We compared the diagnoses of the 2 conditions by retrospectively reviewing patients' data for contrast-enhanced MRI, perfusion MRI, flow-sensitive black-blood (FSBB) imaging, and ¹H-magnetic resonance spectroscopy (MRS).

RESULTS

We evaluated 108 patients (6 PCNSV; 102 glioblastoma). We found a statistically significant correlation between diagnosis and the contrast pattern on MRI. Perivascular enhancement was observed in all cases of PCNSV as follows: ring-like, homogeneous, and irregular patterns were observed in 53 (60%), 18 (20%), and 17 (19%) cases of glioblastoma, respectively. We identified a statistically significant correlation between diagnosis and cerebral blood volume (CBV) in 3 patients with PCNSV who underwent perfusion MRI; and all had low CBVs. Among the 55 patients with glioblastoma who underwent perfusion MRI, low and high CBVs were detected in 3 and 52 patients, respectively. There was no significant correlation between diagnosis and FSBB findings. Evaluation of ¹H-MRS data showed statistically significant differences between PCNSV and glioblastoma as functions of neuronal amino acid levels on long echo time MRS, with a slightly different amino acid profile, including glutamine + glutamate on short echo time MRS.

CONCLUSIONS

Contrast-enhanced MRI, perfusion MRI, and quantitative analysis of ¹H-MRS are valuable techniques for distinguishing PCNSV from glioblastoma before surgery.

Metabolic profiles of human brain parenchyma and glioma for rapid tissue diagnosis by targeted desorption electrospray ionization mass spectrometry

Desorption electrospray ionization mass spectrometry (DESI-MS) is well suited for intraoperative tissue analysis since it requires little sample preparation and offers rapid and sensitive molecular diagnostics. Currently, intraoperative assessment of the tumor cell percentage of glioma biopsies can be made by measuring a single metabolite, N-acetylaspartate (NAA). The inclusion of additional biomarkers will likely improve the accuracy when distinguishing brain parenchyma from glioma by DESI-MS. To explore this possibility, mass spectra were recorded for extracts from 32 unmodified human brain samples with known pathology. Statistical analysis of data obtained from full-scan and multiple reaction monitoring (MRM) profiles identified discriminatory metabolites, namely gamma-aminobutyric acid (GABA), creatine, glutamic acid, carnitine, and hexane-1,2,3,4,5,6-hexol (abbreviated as hexol), as well as the established biomarker NAA. Brain parenchyma was readily differentiated from glioma based on these metabolites as measured both in full-scan mass spectra and by the intensities of their characteristic MRM transitions. New DESI-MS methods (5 min acquisition using full scans and MS/MS), developed to measure ion abundance ratios among these metabolites, were tested using smears of 29 brain samples. Ion abundance ratios based on signals for GABA, creatine, carnitine, and hexol all had sensitivities > 90%, specificities > 80%, and accuracies > 85%. Prospectively, the implementation of diagnostic ion abundance ratios should strengthen the discriminatory power of individual biomarkers and enhance method robustness against signal fluctuations, resulting in an improved DESI-MS method of glioma diagnosis.

Prognostic and therapeutic evaluation of nasopharyngeal carcinoma by dynamic contrast-enhanced (DCE), diffusion-weighted (DW) magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS)

Nasopharyngeal carcinoma (NPC) is an aggressive head and neck malignancy, and radiotherapy (with or without chemotherapy) is the primary treatment modality. Reliable tumour assessment during the treatment phase, which can portend the efficacy of radiotherapy and early identification of potential treatment failure in radioresistant disease, has been implicit for better cancer management. Technological advancement in the last decade has fostered the development of functional magnetic resonance imaging (fMRI) techniques into a promising tool for diagnostic and therapeutic assessments in head and neck cancer. Apart from conventional morphological assessment, early detection of the physiological environment by fMRI allows a more thorough investigation in monitoring tumour response. This article discusses the relevant fMRI utilities in NPC as an early prognostic and monitoring tool for treatment. Challenges and future developments of fMRI in radiation oncology are also discussed.

Joint application of biochemical markers and imaging techniques in the accurate and early detection of glioblastoma

Glioblastoma is a primary brain tumor with the most metastatic effect in adults. Despite the wide range of multidimensional treatments, tumor heterogeneity is one of the main causes of tumor spread and gives great complexity to diagnostic and therapeutic methods. Therefore, featuring noble noninvasive prognostic methods that are focused on glioblastoma heterogeneity is perceived as an urgent need. Imaging neuro-oncological biomarkers including MGMT (O⁶-methylguanine-DNA methyltransferase) promoter methylation status, tumor grade along with other tumor characteristics and demographic features (e.g., age) are commonly referred to during diagnostic, therapeutic and prognostic processes. Therefore, the use of new noninvasive prognostic methods focused on glioblastoma heterogeneity is considered an urgent need. Some neuronal biomarkers, including the promoter methylation status of the promoter MGMT, the characteristics and grade of the tumor, along with the patient's demographics (such as age and sex) are involved in diagnosis, treatment, and prognosis. Among the wide array of imaging techniques, magnetic resonance imaging combined with the more physiologically detailed technique of H-magnetic resonance spectroscopy can be useful in diagnosing neurological cancer patients. In addition, intracranial tumor qualitative analysis and sometimes tumor biopsies help in accurate diagnosis. This review summarizes the evidence for biochemical biomarkers being a reliable biomarker in the early detection and disease management in GBM. Moreover, we highlight the correlation between Imaging techniques and biochemical biomarkers and ask whether they can be combined.

Mapping of Metabolic Heterogeneity of Glioma Using MR-Spectroscopy

Simple Summary

Radiomics is a research field that integrates radiological and genetic information, but the application of the techniques that have been developed to this purpose have not been widely established in daily clinical practice. The purpose of our study is the development of a straightforward tool that can easily be used to preoperatively predict and correlate the metabolic signature of different CNS-lesions. Particularly in gliomas, we hope to integrate the molecular profile of these tumors into our prediction model. Our goal is to deliver an open-software tool with the intention of advancing the diagnostic work-up of gliomas to the latest standards.

Abstract

Proton magnetic resonance spectroscopy (¹H-MRS) delivers information about the non-invasive metabolic landscape of brain pathologies. ¹H-MRS is used in clinical setting in addition to MRI for diagnostic, prognostic and treatment response assessments, but the use of this radiological tool is not entirely widespread. The importance of developing automated analysis tools for ¹H-MRS lies in the possibility of a straightforward application and simplified interpretation of metabolic and genetic data that allow for incorporation into the daily practice of a broad audience. Here, we report a prospective clinical imaging trial (DRKS00019855) which aimed to develop a novel MR-spectroscopy-based algorithm for in-depth characterization of brain lesions and prediction of molecular traits. Dimensional reduction of metabolic profiles demonstrated distinct patterns throughout pathologies. We combined a deep autoencoder and multi-layer linear discriminant models for voxel-wise prediction of the molecular profile based on MRS imaging. Molecular subtypes were predicted by an overall accuracy of 91.2% using a classifier score. Our study indicates a first step into combining the metabolic and molecular traits of lesions for advancing the pre-operative diagnostic workup of brain tumors and improve personalized tumor treatment.

Clinical Applications of Magnetic Resonance Spectroscopy in Brain Tumors: From Diagnosis to Treatment

Magnetic resonance spectroscopy (MRS) is a valuable tool for imaging brain tumors, primarily as an adjunct to conventional imaging and clinical presentation. MRS is useful in initial diagnosis of brain tumors, helping differentiate tumors from possible mimics such as metastatic disease, lymphoma, demyelination, and infection, as well as in the subsequent follow-up of patients after resection and chemoradiation. Unfortunately, the spectroscopic appearance of many pathologies can overlap, and ultimately follow-up or biopsy may be required to make a definitive diagnosis. Future developments may continue to increase the value of MRS for initial diagnosis, treatment planning, and early detection of recurrence.

The Diagnostic Value of Apparent Diffusion Coefficient and Proton Magnetic Resonance Spectroscopy in the Grading of Pediatric Gliomas

The aims of this retrospective study were to assess the value of the quantitative analysis of apparent diffusion coefficient (ADC) and proton magnetic resonance spectroscopy (¹H-MRS) metabolites in differentiating grades of pediatric gliomas.

The utility of magnetic resonance spectroscopy in frame-less stereotactic needle biopsy of glioma

OBJECTIVE

Proton magnetic resonance spectroscopy (¹H-MRS) can benefit the differentiation of gliomas preoperative grading and facilitate guiding biopsy. This study was to investigate the optimal metabolite or metabolic ratios of MRS for the biopsy target delineating by using the technique of MRS imaging guided frame-less stereotactic biopsy.

METHODS

During a 4 year period between the Sep 2012 and Oct 2016, 57 patients (25 women, 32 men; mean age, 46.4) with histologic diagnosis of glioma, who underwent the ¹H-MRS imaging guided frameless stereotactic biopsy, were retrospectively reviewed. The metabolite or metabolic ratios values of MRS was measured. And the sensitivity, specificity, accuracy as well as the area under the curve (AUC) of those parameters for glioma grading are calculated based on the receiver operating characteristic curve (ROC) analysis.

RESULTS

65 stereotactic biopsy samples from 57 patients were histopathologically clarified to HGGs (25) or LGGs (40) for quantitative analysis. The Cho, Cho/NAA and Cho/Cr values of LGGs group were significantly lower than that of HGGs (P = 0.09, 0.001, 0.003), and the NAA value of LGGs group was significantly higher than that of HGGs (P = 0.001). The cutoff value of 3.65 for the Cho/NAA ratio provided the best combination of sensitivity (92.0%), specificity (95.0%), and diagnostic accuracy (93.8%) for identifying glioma grade, which was superior to other parameters.

CONCLUSION

The results of our study provided evidence that Cho/NAA ratio had the superior diagnostic performance in distinguishing glioma grade, indicating that the spot of highest Cho/NAA ratio was optimal metabolic targets for spectroscopic guided tissue sampling in homogenous glioma.

Unique challenges for glioblastoma immunotherapy-discussions across neuro-oncology and non-neuro-oncology experts in cancer immunology. Meeting Report from the 2019 SNO Immuno-Oncology Think Tank

Cancer immunotherapy has made remarkable advances with over 50 separate Food and Drug Administration (FDA) approvals as first- or second-line indications since 2015. These include immune checkpoint blocking antibodies, chimeric antigen receptor-transduced T cells, and bispecific T-cell-engaging antibodies. While multiple cancer types now benefit from these immunotherapies, notable exceptions thus far include brain tumors, such as glioblastoma. As such, it seems critical to gain a better understanding of unique mechanistic challenges underlying the resistance of malignant gliomas to immunotherapy, as well as to acquire insights into the development of future strategies. An Immuno-Oncology Think Tank Meeting was held during the 2019 Annual Society for Neuro-Oncology Scientific Conference. Discussants in the fields of neuro-oncology, neurosurgery, neuro-imaging, medical oncology, and cancer immunology participated in the meeting. Sessions focused on topics such as the tumor microenvironment, myeloid cells, T-cell dysfunction, cellular engineering, and translational aspects that are critical and unique challenges inherent with primary brain tumors. In this review, we summarize the discussions and the key messages from the meeting, which may potentially serve as a basis for advancing the field of immune neuro-oncology in a collaborative manner.

Multi-parametric magnetic resonance imaging evaluation of cerebral amyloid angiopathy related inflammation: Case series and review of literature

Cerebral amyloid angiopathy related inflammation is a rare disorder in the spectrum of cerebral amyloid angiopathy which is characterized by vascular and/or perivascular inflammation related to Aβ deposits. Clinically, the patient typically presents with acute to subacute encephalitis-like symptoms with focal neurological deficits, rapidly cognitive decline, and/or seizures. Typical magnetic resonance imaging findings include asymmetric mass-like non-enhancing white matter hyperintensity with scattered microhemorrhages. Additionally, in these cases diffusion weighted imaging, perfusion weighted imaging and magnetic resonance spectroscopy help to exclude neoplastic processes and could determine the correct diagnosis.

The use of hyperpolarised 13C-MRI in clinical body imaging to probe cancer metabolism

Metabolic reprogramming is one of the hallmarks of cancer and includes the Warburg effect, which is exhibited by many tumours. This can be exploited by positron emission tomography (PET) as part of routine clinical cancer imaging. However, an emerging and alternative method to detect altered metabolism is carbon-13 magnetic resonance imaging (MRI) following injection of hyperpolarised [1-13C]pyruvate. The technique increases the signal-to-noise ratio for the detection of hyperpolarised 13C-labelled metabolites by several orders of magnitude and facilitates the dynamic, noninvasive imaging of the exchange of 13C-pyruvate to 13C-lactate over time. The method has produced promising preclinical results in the area of oncology and is currently being explored in human imaging studies. The first translational studies have demonstrated the safety and feasibility of the technique in patients with prostate, renal, breast and pancreatic cancer, as well as revealing a successful response to treatment in breast and prostate cancer patients at an earlier stage than multiparametric MRI. This review will focus on the strengths of the technique and its applications in the area of oncological body MRI including noninvasive characterisation of disease aggressiveness, mapping of tumour heterogeneity, and early response assessment. A comparison of hyperpolarised 13C-MRI with state-of-the-art multiparametric MRI is likely to reveal the unique additional information and applications offered by the technique.

Investigating the regional effect of the chemical shift displacement artefact on the J-modulated lactate signal at ultra high-field

The present work aims to show the applicability of an analytical model for the optimisation of the STEAM sequence timing parameters for lactate detection at ultra high-field. The effects of the chemical shift displacement artefact on the J-modulated signal for a weakly-coupled spin system were considered in the three applied directions of field gradients and the product operator formalism was used to obtain expressions for the signal modulation in each compartment of the excited volume. The validity of this model was demonstrated experimentally at 7 T in a phantom and acquisitions with optimised parameters were performed on a healthy volunteer. The spectra acquired with TE = 144 ms with the optimised mixing time and TE = 288 ms showed easily detectable lactate peaks in the normal human brain. Additionally, the acquisition with the longer TE resulted in a spectrum with less lipid/macromolecular contamination. The simulations shown here demonstrated that the proposed analytical model is suitable for correctly predicting the resulting lactate signal. With the optimised parameters, it was possible to use a simple sequence with sufficient signal-to-noise ratio to reliably distinguish lactate from overlapping resonances in a healthy brain.

Magnetic resonance spectroscopy for the study of cns malignancies

Despite intensive research, brain tumors are amongst the malignancies with the worst prognosis; therefore, a prompt diagnosis and thoughtful assessment of the disease is required. The resistance of brain tumors to most forms of conventional therapy has led researchers to explore the underlying biology in search of new vulnerabilities and biomarkers. The unique metabolism of brain tumors represents one potential vulnerability and the basis for a system of classification. Profiling this aberrant metabolism requires a method to accurately measure and report differences in metabolite concentrations. Magnetic resonance-based techniques provide a framework for examining tumor tissue and the evolution of disease. Nuclear Magnetic Resonance (NMR) analysis of biofluids collected from patients suffering from brain cancer can provide biological information about disease status. In particular, urine and plasma can serve to monitor the evolution of disease through the changes observed in the metabolic profiles. Moreover, cerebrospinal fluid can be utilized as a direct reporter of cerebral activity since it carries the chemicals exchanged with the brain tissue and the tumor mass. Metabolic reprogramming has recently been included as one of the hallmarks of cancer. Accordingly, the metabolic rewiring experienced by these tumors to sustain rapid growth and proliferation can also serve as a potential therapeutic target. The combination of 13C tracing approaches with the utilization of different NMR spectral modalities has allowed investigations of the upregulation of glycolysis in the aggressive forms of brain tumors, including glioblastomas, and the discovery of the utilization of acetate as an alternative cellular fuel in brain metastasis and gliomas. One of the major contributions of magnetic resonance to the assessment of brain tumors has been the non-invasive determination of 2-hydroxyglutarate (2HG) in tumors harboring a mutation in isocitrate dehydrogenase 1 (IDH1). The mutational status of this enzyme already serves as a key feature in the clinical classification of brain neoplasia in routine clinical practice and pilot studies have established the use of in vivo magnetic resonance spectroscopy (MRS) for monitoring disease progression and treatment response in IDH mutant gliomas. However, the development of bespoke methods for 2HG detection by MRS has been required, and this has prevented the wider implementation of MRS methodology into the clinic. One of the main challenges for improving the management of the disease is to obtain an accurate insight into the response to treatment, so that the patient can be promptly diverted into a new therapy if resistant or maintained on the original therapy if responsive. The implementation of 13C hyperpolarized magnetic resonance spectroscopic imaging (MRSI) has allowed detection of changes in tumor metabolism associated with a treatment, and as such has been revealed as a remarkable tool for monitoring response to therapeutic strategies. In summary, the application of magnetic resonance-based methodologies to the diagnosis and management of brain tumor patients, in addition to its utilization in the investigation of its tumor-associated metabolic rewiring, is helping to unravel the biological basis of malignancies of the central nervous system.

Diagnosis of Glioma Molecular Markers by Terahertz Technologies

This review considers glioma molecular markers in brain tissues and body fluids, shows the pathways of their formation, and describes traditional methods of analysis. The most important optical properties of glioma markers in the terahertz (THz) frequency range are also presented. New metamaterial-based technologies for molecular marker detection at THz frequencies are discussed. A variety of machine learning methods, which allow the marker detection sensitivity and differentiation of healthy and tumor tissues to be improved with the aid of THz tools, are considered. The actual results on the application of THz techniques in the intraoperative diagnosis of brain gliomas are shown. THz technologies’ potential in molecular marker detection and defining the boundaries of the glioma’s tissue is discussed.