Magnetic Resonance Spectroscopy, Positron Emission Tomography and Radiogenomics-Relevance to Glioma

Computational modeling of tumor invasion from limited and diverse data in Glioblastoma

For diseases with high morbidity rates such as Glioblastoma Multiforme, the prognostic and treatment planning pipeline requires a comprehensive analysis of imaging, clinical, and molecular data. Many mutations have been shown to correlate strongly with the median survival rate and response to therapy of patients. Studies have demonstrated that these mutations manifest as specific visual biomarkers in tumor imaging modalities such as MRI. To minimize the number of invasive procedures on a patient and for the overall resource optimization for the prognostic and treatment planning process, the correlation of imaging and molecular features has garnered much interest. While the tumor mass is the most significant feature, the impacted tissue surrounding the tumor is also a significant biomarker contributing to the visual manifestation of mutations - which has not been studied as extensively. The pattern of tumor growth impacts the surrounding tissue accordingly, which is a reflection of tumor properties as well. Modeling how the tumor growth impacts the surrounding tissue can reveal important information about the patterns of tumor enhancement, which in turn has significant diagnostic and prognostic value. This paper presents the first work to automate the computational modeling of the impacted tissue surrounding the tumor using generative deep learning. The paper isolates and quantifies the impact of the Tumor Invasion (TI) on surrounding tissue based on change in mutation status, subsequently assessing its prognostic value. Furthermore, a TI Generative Adversarial Network (TI-GAN) is proposed to model the tumor invasion properties. Extensive qualitative and quantitative analyses, cross-dataset testing, and radiologist blind tests are carried out to demonstrate that TI-GAN can realistically model the tumor invasion under practical challenges of medical datasets such as limited data and high intra-class heterogeneity.

Multiparametric Analysis Combining DSC-MR Perfusion and [18F]FET-PET is Superior to a Single Parameter Approach for Differentiation of Progressive Glioma from Radiation Necrosis

PURPOSE

Perfusion-weighted (PWI) magnetic resonance imaging (MRI) and O‑(2-[18F]fluoroethyl-)-l-tyrosine ([18F]FET) positron emission tomography (PET) are both useful for discrimination of progressive disease (PD) from radiation necrosis (RN) in patients with gliomas. Previous literature showed that the combined use of FET-PET and MRI-PWI is advantageous; hhowever the increased diagnostic performances were only modest compared to the use of a single modality. Hence, the goal of this study was to further explore the benefit of combining MRI-PWI and [18F]FET-PET for differentiation of PD from RN. Secondarily, we evaluated the usefulness of cerebral blood flow (CBF), mean transit time (MTT) and time to peak (TTP) as previous studies mainly examined cerebral blood volume (CBV).

METHODS

In this single center study, we retrospectively identified patients with WHO grades II-IV gliomas with suspected tumor recurrence, presenting with ambiguous findings on structural MRI. For differentiation of PD from RN we used both MRI-PWI and [18F]FET-PET. Dynamic susceptibility contrast MRI-PWI provided normalized parameters derived from perfusion maps (r(relative)CBV, rCBF, rMTT, rTTP). Static [18F]FET-PET parameters including mean and maximum tumor to brain ratios (TBRmean, TBRmax) were calculated. Based on histopathology and radioclinical follow-up we diagnosed PD in 27 and RN in 10 cases. Using the receiver operating characteristic (ROC) analysis, area under the curve (AUC) values were calculated for single and multiparametric models. The performances of single and multiparametric approaches were assessed with analysis of variance and cross-validation.

RESULTS

After application of inclusion and exclusion criteria, we included 37 patients in this study. Regarding the in-sample based approach, in single parameter analysis rTBRmean (AUC = 0.91, p < 0.001), rTBRmax (AUC = 0.89, p < 0.001), rTTP (AUC = 0.87, p < 0.001) and rCBVmean (AUC = 0.84, p < 0.001) were efficacious for discrimination of PD from RN. The rCBFmean and rMTT did not reach statistical significance. A classification model consisting of TBRmean, rCBVmean and rTTP achieved an AUC of 0.98 (p < 0.001), outperforming the use of rTBRmean alone, which was the single parametric approach with the highest AUC. Analysis of variance confirmed the superiority of the multiparametric approach over the single parameter one (p = 0.002). While cross-validation attributed the highest AUC value to the model consisting of TBRmean and rCBVmean, it also suggested that the addition of rTTP resulted in the highest accuracy. Overall, multiparametric models performed better than single parameter ones.

CONCLUSION

A multiparametric MRI-PWI and [18F]FET-PET model consisting of TBRmean, rCBVmean and PWI rTTP significantly outperformed the use of rTBRmean alone, which was the best single parameter approach. Secondarily, we firstly report the potential usefulness of PWI rTTP for discrimination of PD from RN in patients with glioma; however, for validation of our findings the prospective studies with larger patient samples are necessary.

68 Ga-Pentixafor PET/CT for In Vivo Imaging of CXCR4 Receptors in Glioma Demonstrating a Potential for Response Assessment to Radiochemotherapy: Preliminary Results

PURPOSE

The aim of this study was to evaluate the diagnostic potential of 68 Ga-pentixafor PET/CT for in vivo CXCR4 receptors imaging in glioma and its possible role in response assessment to radiochemotherapy (R-CT).

METHODS

Nineteen (12 men, 7 women) patients with glioblastoma multiforme (GBM) underwent 68 Ga-pentixafor PET/CT, contrast-enhanced MR, and MR spectroscopy. Patients were divided in to 2 groups, that is, group I was the presurgical (n = 9) group in which the scanning was done before surgery, and PET findings were correlated with CXCR4 receptors' density. The group II was the postsurgical (n = 10) group in which the scanning was done before and after R-CT and used for treatment response evaluation. The quantitative analysis of 68 Ga-pentixafor PET/CT evaluated the mean SUV max , SUV mean , SUV peak , and T/B values. MR spectroscopy data evaluated the ratios of tumor metabolites (choline, NAA, creatine).

RESULTS

68 Ga-Pentixafor uptake was noted in all (n = 19) the patients. In the group I, the mean SUV max , SUV mean , SUV peak , and T/B values were found to be 4.5 ± 1.6, 0.60 ± 0.26, 1.95 ± 0.8, and 6.9 ± 4.6, respectively. A significant correlation ( P < 0.005) was found between SUV mean and choline/NAA ratio. Immunohistochemistry performed in 7/9 showed CXCR4 receptors' positivity (intensity 3 + ; stained cells >50.0%). In the group II, the mean SUV max at baseline was 4.6 ± 2.1 and did not differ (4.4 ± 1.6) significantly from the value noted at post-R-CT follow-up PET/CT imaging. At 6 months' clinical follow-up, 4 patients showed stable disease. SUV max and T/B ratios at follow-up imaging were lower (3.70 ± 0.90, 2.64 ± 1.35) than the corresponding values (4.40 ± 2.8; 2.91 ± 0.93) noted at baseline. Six (6/10) patients showed disease progression, and the mean SUV max , and T/B ratio in these patients were significantly ( P < 0.05) higher than the corresponding values at baseline and also higher than that noted in the stable patients.

CONCLUSIONS

68 Ga-Pentixafor PET/CT can be used for in vivo mapping of CXCR4 receptors in GBM. The technique after validation in a large cohort of patients may have added diagnostic value for the early detection of GBM recurrence and for treatment response evaluation.

Astrocytoma Mimicking Herpetic Meningoencephalitis: The Role of Non-Invasive Multimodal Monitoring in Neurointensivism

Neuromonitoring is a critical tool for emergency rooms and intensive care units to promptly identify and treat brain injuries. The case report of a patient with status epilepticus necessitating orotracheal intubation and intravenous lorazepam administration is presented. A pattern of epileptiform activity was detected in the left temporal region, and intravenous Acyclovir was administered based on the diagnostic hypothesis of herpetic meningoencephalitis. The neurointensivist opted for multimodal non-invasive bedside neuromonitoring due to the complexity of the patient's condition. A Brain4care (B4C) non-invasive intracranial compliance monitor was utilized alongside the assessment of an optic nerve sheath diameter (ONSD) and transcranial Doppler (TCD). Based on the collected data, a diagnosis of intracranial hypertension (ICH) was made and a treatment plan was developed. After the neurosurgery team's evaluation, a stereotaxic biopsy of the temporal lesion revealed a grade 2 diffuse astrocytoma, and an urgent total resection was performed. Research suggests that monitoring patients in a dedicated neurologic intensive care unit (Neuro ICU) can lead to improved outcomes and shorter hospital stays. In addition to being useful for patients with a primary brain injury, neuromonitoring may also be advantageous for those at risk of cerebral hemodynamic impairment. Lastly, it is essential to note that neuromonitoring technologies are non-invasive, less expensive, safe, and bedside-accessible approaches with significant diagnostic and monitoring potential for patients at risk of brain abnormalities. Multimodal neuromonitoring is a vital tool in critical care units for the identification and management of acute brain trauma as well as for patients at risk of cerebral hemodynamic impairment.

Research Progress of CXCR4-Targeting Radioligands for Oncologic Imaging

C-X-C motif chemokine receptor 4 (CXCR4) plays a key role in various physiological functions, such as immune processes and disease development, and can influence angiogenesis, proliferation, and distant metastasis in tumors. Recently, several radioligands, including peptides, small molecules, and nanoclusters, have been developed to target CXCR4 for diagnostic purposes, thereby providing new diagnostic strategies based on CXCR4. Herein, we focus on the recent research progress of CXCR4-targeting radioligands for tumor diagnosis. We discuss their application in the diagnosis of hematological tumors, such as lymphomas, multiple myelomas, chronic lymphocytic leukemias, and myeloproliferative tumors, as well as nonhematological tumors, including tumors of the esophagus, breast, and central nervous system. Additionally, we explored the theranostic applications of CXCR4-targeting radioligands in tumors. Targeting CXCR4 using nuclear medicine shows promise as a method for tumor diagnosis, and further research is warranted to enhance its clinical applicability.

Brain magnetic resonance spectroscopy to differentiate recurrent neoplasm from radiation necrosis: A systematic review and meta-analysis

BACKGROUND AND PURPOSE

Postradiation treatment necrosis is one of the most serious late sequelae and appears within 6 months. The magnetic resonance spectroscopy imaging (MRSI) has been used for the detection of brain tumors. The study aimed to determine the radiological accuracy and efficacy in distinguishing recurrent brain tumor from radiation-induced necrosis by identifying pseudoprogression.

METHODS

The research was performed in accordance with the preferred reporting items for systematic review and meta-analysis guidelines. International electronic databases including 15 English sources were investigated. A total of 4281 papers with 2159 citations from 15 databases from 2011 to 2021 met the search strategies of magnetic resonance (MR) spectroscopy in recurrent brain tumors and postradiation necrosis.

RESULTS

Nine studies were enrolled in the meta-analysis with a total of 354 patients (203 male and 151 female) whose average age ranged from 4 to 74 years. Anbarloui et al., Elias et al., Nemattalla et al., Smith et al., Zeng et al., and Weybright et al. showed strong evidence of heterogeneity regarding choline/N-acetylaspartate (Cho/NAA) ratio in the evaluation of the nine studies. Elias et al., Nemattalla et al., Bobek-Billewicz et al., and Smith et al. showed a high heterogeneity in Cho/creatine (Cr) ratio. Elias et al., Nemattalla et al., Smith et al., and Weybright et al. revealed high heterogeneity in NAA/Cr ratio estimates.

CONCLUSION

MR spectroscopy is effective in distinguishing recurrent brain tumors from necrosis. Our meta-analysis revealed that Cho/NAA, Cho/Cr, and NAA/Cr ratios were significantly better predictor of detected recurrent tumor. Therefore, the MRSI is an informative tool in the distinction of tumor recurrence versus necrosis.

Radiomics analysis of amide proton transfer-weighted and structural MR images for treatment response assessment in malignant gliomas

The purpose of this study was to evaluate the value of amide proton transfer-weighted (APTw) MRI radiomic features for the differentiation of tumor recurrence from treatment effect in malignant gliomas. Eighty-six patients who had suspected tumor recurrence after completion of chemoradiation or radiotherapy, and who had APTw-MRI data acquired at 3 T, were retrospectively analyzed. Using a fluid-attenuated inversion recovery (FLAIR) image-based mask, radiomics analysis was applied to the processed APTw and structural MR images. A chi-square automatic interaction detector decision tree was used for classification analysis. Models with and without APTw features were built using the same strategy. Tenfold cross-validation was applied to obtain the overall classification performance of each model. Sixty patients were confirmed as having tumor recurrence, and the remainder were confirmed as having treatment effect, at median time points of 190 and 171 days after therapy, respectively. There were 525 radiomic features extracted from each of the processed APTw and structural MR images. Based on these, the APTw-based model yielded the highest accuracy (86.0%) for the differentiation of tumor recurrence from treatment effect, compared with 74.4%, 76.7%, 83.7%, and 76.7% for T1 w, T2 w, FLAIR, and Gd-T1 w, respectively. Model classification accuracy was 82.6% when using the combined structural MR images (T1 w, T2 w, FLAIR, Gd-T1 w), and increased to 89.5% when using these structural plus APTw images. The corresponding sensitivity and specificity were 85.0% and 76.9% for the combination of structural MR images, and 85.0% and 100% after adding APTw image features. Adding APTw-based radiomic features increased MRI accuracy in the assessment of the treatment response in post-treatment malignant gliomas.

Towards differentiation of brain tumor from radiation necrosis using multi-parametric MRI: Preliminary results at 4.7 T using rodent models

BACKGROUND

It remains a clinical challenge to differentiate brain tumors from radiation-induced necrosis in the brain. Despite significant improvements, no single MRI method has been validated adequately in the clinical setting.

METHODS

Multi-parametric MRI (mpMRI) was performed to differentiate 9L gliosarcoma from radiation necrosis in animal models. Five types of MRI methods probed complementary information on different scales i.e., T2 (relaxation), CEST based APT (probing mobile proteins/peptides) and rNOE (mobile macromolecules), qMT (macromolecules), diffusion based ADC (cell density) and SSIFT iAUC (cell size), and perfusion based DSC (blood volume and flow).

RESULTS

For single MRI parameters, iAUC and ADC provide the best discrimination of radiation necrosis and brain tumor. For mpMRI, a combination of iAUC, ADC, and APT shows the best classification performance based on a two-step analysis with the Lasso and Ridge regressions.

CONCLUSION

A general mpMRI approach is introduced to choosing candidate multiple MRI methods, identifying the most effective parameters from all the mpMRI parameters, and finding the appropriate combination of chosen parameters to maximize the classification performance to differentiate tumors from radiation necrosis.

Selective Cell Size MRI Differentiates Brain Tumors from Radiation Necrosis

Brain metastasis is a common characteristic of late-stage lung cancers. High doses of targeted radiotherapy can control tumor growth in the brain but can also result in radiotherapy-induced necrosis. Current methods are limited for distinguishing whether new parenchymal lesions following radiotherapy are recurrent tumors or radiotherapy-induced necrosis, but the clinical management of these two classes of lesions differs significantly. Here, we developed, validated, and evaluated a new MRI technique termed selective size imaging using filters via diffusion times (SSIFT) to differentiate brain tumors from radiotherapy necrosis in the brain. This approach generates a signal filter that leverages diffusion time dependence to establish a cell size-weighted map. Computer simulations in silico, cultured cancer cells in vitro, and animals with brain tumors in vivo were used to comprehensively validate the specificity of SSIFT for detecting typical large cancer cells and the ability to differentiate brain tumors from radiotherapy necrosis. SSIFT was also implemented in patients with metastatic brain cancer and radiotherapy necrosis. SSIFT showed high correlation with mean cell sizes in the relevant range of less than 20 μm. The specificity of SSIFT for brain tumors and reduced contrast in other brain etiologies allowed SSIFT to differentiate brain tumors from peritumoral edema and radiotherapy necrosis. In conclusion, this new, cell size-based MRI method provides a unique contrast to differentiate brain tumors from other pathologies in the brain.

SIGNIFICANCE

This work introduces and provides preclinical validation of a new diffusion MRI method that exploits intrinsic differences in cell sizes to distinguish brain tumors and radiotherapy necrosis.

Distinguishing Tumor Admixed in a Radiation Necrosis (RN) Background: 1H and 2H MR With a Novel Mouse Brain-Tumor/RN Model

Purpose

Distinguishing radiation necrosis (RN) from recurrent tumor remains a vexing clinical problem with important health-care consequences for neuro-oncology patients. Here, mouse models of pure tumor, pure RN, and admixed RN/tumor are employed to evaluate hydrogen (¹H) and deuterium (²H) magnetic resonance methods for distinguishing RN vs. tumor. Furthermore, proof-of-principle, range-finding deuterium (²H) metabolic magnetic resonance is employed to assess glycolytic signatures distinguishing RN vs. tumor.

Materials and Methods

A pipeline of common quantitative ¹H MRI contrasts, including an improved magnetization transfer ratio (MTR) sequence, and ²H magnetic resonance spectroscopy (MRS) following administration of ²H-labeled glucose, was applied to C57BL/6 mouse models of the following: (i) late time-to-onset RN, occurring 4–5 weeks post focal 50-Gy (50% isodose) Gamma Knife irradiation to the left cerebral hemisphere, (ii) glioblastoma, growing ~18–24 days post implantation of 50,000 mouse GL261 tumor cells into the left cerebral hemisphere, and (iii) mixed model, with GL261 tumor growing within a region of radiation necrosis (¹H MRI only). Control C57BL/6 mice were also examined by ²H metabolic magnetic resonance.

Results

Differences in quantitative ¹H MRI parametric values of R1, R2, ADC, and MTR comparing pure tumor vs. pure RN were all highly statistically significant. Differences in these parameter values and DCE_AUC for tumor vs. RN in the mixed model (tumor growing in an RN background) are also all significant, demonstrating that these contrasts—in particular, MTR—can effectively distinguish tumor vs. RN. Additionally, quantitative ²H MRS showed a highly statistically significant dominance of aerobic glycolysis (glucose ➔ lactate; fermentation, Warburg effect) in the tumor vs. oxidative respiration (glucose ➔ TCA cycle) in the RN and control brain.

Conclusions

These findings, employing a pipeline of quantitative ¹H MRI contrasts and ²H MRS following administration of ²H-labeled glucose, suggest a pathway for substantially improving the discrimination of tumor vs. RN in the clinic.

Hydrogen Proton Magnetic Resonance Spectroscopy (MRS) in Differential Diagnosis of Intracranial Tumors: A Systematic Review

Meningioma, glioma, and metastases are the most common intracranial tumors in clinical practice. In order to improve the prognosis of patients, timely diagnosis and early treatment are crucial. Hydrogen proton magnetic resonance spectroscopy (1H-MRS) imaging can noninvasively display the biochemical information of tissues in vivo and has been applied to identify and diagnose intracranial tumors. We want to comprehensively evaluate 1H-MRS identify and diagnose intracranial tumors by meta-analysis. Some databases such as PubMed and Cochrane Library were used to systematically search articles that were about identifying and diagnosing intracranial tumors with 1H-MRS. Then, weighted mean difference (WMD) was used as an effect size to conduct meta-analysis. There are altogether nine articles, including 533 patients. Results of meta-analysis: The Cho/Cr and Cho/NAA ratios in the LGG group were significantly lower than those in the HGG group (WMD = -0.69, 95% CI (-0.92, -0.45), P < 0.001, WMD = -0.76, 95% CI (-1.03, -0.48), P < 0.001). The Cho/Cr ratio of tumor and peritumor in the HGG group was significantly different from that in the metastasis group (0.68, 95% CI (-1.27, 2.62), P < 0.001, WMD = 0.94, 95% CI (0.41, 1.47), P < 0.001). There was no significant difference in the tumor and peritumor NAA/Cr ratio between the HGG group and metastasis group (WMD = -0.64, 95% CI (-1.63, 0.34), P=0.31, WMD = -0.22, 95% CI (-0.59, 0.15), P=0.24). 1H-MRS can provide metabolic information of different intracranial tumors and can effectively diagnose and differentiate glioma and metastasis. 1H-MRS can also provide a reliable basis for the classification of glioma, and has certain clinical application value.

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.

Neuroinflammation and immunoregulation in glioblastoma and brain metastases: Recent developments in imaging approaches

Brain tumors and brain metastases induce changes in brain tissue remodeling that lead to immunosuppression and trigger an inflammatory response within the tumor microenvironment. These immune and inflammatory changes can influence invasion and metastasis. Other neuroinflammatory and necrotic lesions may occur in patients with brain cancer or brain metastases as sequelae from treatment with radiotherapy. Glioblastoma (GBM) is the most aggressive primary malignant brain cancer in adults. Imaging methods such as positron emission tomography (PET) and different magnetic resonance imaging (MRI) techniques are highly valuable for the diagnosis and therapeutic evaluation of GBM and other malignant brain tumors. However, differentiating between tumor tissue and inflamed brain tissue with imaging protocols remains a challenge. Here, we review recent advances in imaging methods that have helped to improve the specificity of primary tumor diagnosis versus evaluation of inflamed and necrotic brain lesions. We also comment on advances in differentiating metastasis from neuroinflammation processes. Recent advances include the radiosynthesis of ¹⁸ F-FIMP, an L-type amino acid transporter 1 (LAT1)-specific PET probe that allows clearer differentiation between tumor tissue and inflammation compared to previous probes, and the combination of different advanced imaging protocols with the inclusion of radiomics and machine learning algorithms.

Glioma-Targeted Therapeutics: Computer-Aided Drug Design Prospective

Amongst the several types of brain cancers known to humankind, glioma is one of the most severe and life-threatening types of cancer, comprising 40% of all primary brain tumors. Recent reports have shown the incident rate of gliomas to be 6 per 100,000 individuals per year globally. Despite the various therapeutics used in the treatment of glioma, patient survival rate remains at a median of 15 months after undergoing first-line treatment including surgery, radiation, and chemotherapy with Temozolomide. As such, the discovery of newer and more effective therapeutic agents is imperative for patient survival rate. The advent of computer-aided drug design in the development of drug discovery has emerged as a powerful means to ascertain potential hit compounds with distinctively high therapeutic effectiveness against glioma. This review encompasses the recent advances of bio-computational in-silico modeling that have elicited the discovery of small molecule inhibitors and/or drugs against various therapeutic targets in glioma. The relevant information provided in this report will assist researchers, especially in the drug design domains, to develop more effective therapeutics against this global disease.

BOLD Asynchrony Elucidates Tumor Burden in IDH-Mutated Gliomas

BACKGROUND

Gliomas comprise the most common type of primary brain tumor, are highly invasive, and often fatal. IDH-mutated gliomas are particularly challenging to image and there is currently no clinically accepted method for identifying the extent of tumor burden in these neoplasms. This uncertainty poses a challenge to clinicians who must balance the need to treat the tumor while sparing healthy brain from iatrogenic damage. The purpose of this study was to investigate the feasibility of using resting-state blood oxygen level dependent (BOLD) functional magnetic resonance imaging (fMRI) to detect glioma-related asynchrony in vascular dynamics for distinguishing tumor from healthy brain.

METHODS

Twenty-four stereotactically localized biopsies were obtained during open surgical resection from ten treatment-naïve patients with IDH-mutated gliomas who received standard of care preoperative imaging as well as echo-planar resting-state BOLD fMRI. Signal intensity for BOLD asynchrony and standard of care imaging was compared to cell counts of total cellularity (H&E), tumor density (IDH1 & Sox2), cellular proliferation (Ki67), and neuronal density (NeuN), for each corresponding sample.

RESULTS

BOLD asynchrony was directly related to total cellularity (H&E, p = 4 x 10 -5), tumor density (IDH1, p = 4 x 10 -5; Sox2, p = 3 x 10 -5), cellular proliferation (Ki67, p = 0.002), and as well as inversely related to neuronal density (NeuN, p = 1 x 10 -4).

CONCLUSIONS

Asynchrony in vascular dynamics, as measured by resting-state BOLD fMRI, correlates with tumor burden and provides a radiographic delineation of tumor boundaries in IDH-mutated gliomas.

Biomarkers for differentiating grade II meningiomas from grade I: a systematic review

INTRODUCTION

There are a number of prognostic markers (methylation, CDKN2A/B) described to be useful for the stratification of meningiomas. However, there are currently no clinically validated biomarkers for the preoperative prediction of meningioma grade, which is determined by the histological analysis of tissue obtained from surgery. Accurate preoperative biomarkers would inform the pre-surgical assessment of these tumours, their grade and prognosis and refine the decision-making process for treatment. This review is focused on the more controversial grade II tumours, where debate still surrounds the need for adjuvant therapy, repeat surgery and frequency of follow up.

METHODS

We evaluated current literature for potential grade II meningioma clinical biomarkers, focusing on radiological, biochemical (blood assays) and immunohistochemical markers for diagnosis and prognosis, and how they can be used to differentiate them from grade I meningiomas using the post-2016 WHO classification. To do this, we conducted a PUBMED, SCOPUS, OVID SP, SciELO, and INFORMA search using the keywords; 'biomarker', 'diagnosis', 'atypical', 'meningioma', 'prognosis', 'grade I', 'grade 1', 'grade II' and 'grade 2'.

RESULTS

We identified 1779 papers, 20 of which were eligible for systematic review according to the defined inclusion and exclusion criteria. From the review, we identified radiological characteristics (irregular tumour shape, tumour growth rate faster than 3cm³/year, high peri-tumoural blood flow), blood markers (low serum TIMP1/2, high serum HER2, high plasma Fibulin-2) and histological markers (low H3K27me3, low SMARCE1, low AKAP12, high ARIDB4) that may aid in differentiating grade II from grade I meningiomas.

CONCLUSION

Being able to predict meningioma grade at presentation using the radiological and blood markers described may influence management as the likely grade II tumours will be followed up or treated more aggressively, while the histological markers may prognosticate progression or post-treatment recurrence. This to an extent offers a more personalised treatment approach for patients.

CXCR4 expression in glioblastoma tissue and the potential for PET imaging and treatment with [68Ga]Ga-Pentixafor /[177Lu]Lu-Pentixather

Purpose

CXCR4 (over)expression is found in multiple human cancer types, while expression is low or absent in healthy tissue. In glioblastoma it is associated with a poor prognosis and more extensive infiltrative phenotype. CXCR4 can be targeted by the diagnostic PET agent [⁶⁸Ga]Ga-Pentixafor and its therapeutic counterpart [¹⁷⁷Lu]Lu-Pentixather. We aimed to investigate the expression of CXCR4 in glioblastoma tissue to further examine the potential of these PET agents.

Methods

CXCR4 mRNA expression was examined using the R2 genomics platform. Glioblastoma tissue cores were stained for CXCR4. CXCR4 staining in tumor cells was scored. Stained tissue components (cytoplasm and/or nuclei of the tumor cells and blood vessels) were documented. Clinical characteristics and information on IDH and MGMT promoter methylation status were collected. Seven pilot patients with recurrent glioblastoma underwent [⁶⁸Ga]Ga-Pentixafor PET; residual resected tissue was stained for CXCR4.

Results

Two large mRNA datasets (N = 284; N = 540) were assesed. Of the 191 glioblastomas, 426 cores were analyzed using immunohistochemistry. Seventy-eight cores (23 tumors) were CXCR4 negative, while 18 cores (5 tumors) had both strong and extensive staining. The remaining 330 cores (163 tumors) showed a large inter- and intra-tumor variation for CXCR4 expression; also seen in the resected tissue of the seven pilot patients—not directly translatable to [⁶⁸Ga]Ga-Pentixafor PET results. Both mRNA and immunohistochemical analysis showed CXCR4 negative normal brain tissue and no significant correlation between CXCR4 expression and IDH or MGMT status or survival.

Conclusion

Using immunohistochemistry, high CXCR4 expression was found in a subset of glioblastomas as well as a large inter- and intra-tumor variation. Caution should be exercised in directly translating ex vivo CXCR4 expression to PET agent uptake. However, when high CXCR4 expression can be identified with [⁶⁸Ga]Ga-Pentixafor, these patients might be good candidates for targeted radionuclide therapy with [¹⁷⁷Lu]Lu-Pentixather in the future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-021-05196-4.

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.

Imaging Glioblastoma Posttreatment: Progression, Pseudoprogression, Pseudoresponse, Radiation Necrosis

Radiographic monitoring of posttreatment glioblastoma is important for clinical trials and determining next steps in management. Evaluation for tumor progression is confounded by the presence of treatment-related radiographic changes, making a definitive determination less straight-forward. The purpose of this article was to describe imaging tools available for assessing treatment response in glioblastoma, as well as to highlight the definitions, pathophysiology, and imaging features typical of true progression, pseudoprogression, pseudoresponse, and radiation necrosis.

Liquid Biopsy Strategies to Distinguish Progression from Pseudoprogression and Radiation Necrosis in Glioblastomas

Liquid biopsy for the detection and monitoring of central nervous system tumors is of significant clinical interest. At initial diagnosis, the majority of patients with central nervous system tumors undergo magnetic resonance imaging (MRI), followed by invasive brain biopsy to determine the molecular diagnosis of the WHO 2016 classification paradigm. Despite the importance of MRI for long-term treatment monitoring, in the majority of patients who receive chemoradiation therapy for glioblastoma, it can be challenging to distinguish between radiation treatment effects including pseudoprogression, radiation necrosis, and recurrent/progressive disease based on imaging alone. Tissue biopsy-based monitoring is high risk and not always feasible. However, distinguishing these entities is of critical importance for the management of patients and can significantly affect survival. Liquid biopsy strategies including circulating tumor cells, circulating free DNA, and extracellular vesicles have the potential to afford significant useful molecular information at both the stage of diagnosis and monitoring for these tumors. Here, current liquid biopsy-based approaches in the context of tumor monitoring to differentiate progressive disease from pseudoprogression and radiation necrosis are reviewed.

Clinical Imaging for Diagnostic Challenges in the Management of Gliomas: A Review

Neuroimaging plays a critical role in the management of patients with gliomas. While conventional magnetic resonance imaging (MRI) remains the standard imaging modality, it is frequently insufficient to inform clinical decision-making. There is a need for noninvasive strategies for reliably distinguishing low-grade from high-grade gliomas, identifying important molecular features of glioma, choosing an appropriate target for biopsy, delineating target area for surgery or radiosurgery, and distinguishing tumor progression (TP) from pseudoprogression (PsP). One recent advance is the identification of the T2/fluid-attenuated inversion recovery mismatch sign on standard MRI to identify isocitrate dehydrogenase mutant astrocytomas. However, to meet other challenges, neuro-oncologists are increasingly turning to advanced imaging modalities. Diffusion-weighted imaging modalities including diffusion tensor imaging and diffusion kurtosis imaging can be helpful in delineating tumor margins and better visualization of tissue architecture. Perfusion imaging including dynamic contrast-enhanced MRI using gadolinium or ferumoxytol contrast agents can be helpful for grading as well as distinguishing TP from PsP. Positron emission tomography is useful for measuring tumor metabolism, which correlates with grade and can distinguish TP/PsP in the right setting. Magnetic resonance spectroscopy can identify tissue by its chemical composition, can distinguish TP/PsP, and can identify molecular features like 2-hydroxyglutarate. Finally, amide proton transfer imaging measures intracellular protein content, which can be used to identify tumor grade/progression and distinguish TP/PsP.

Imaging Glioblastoma Posttreatment: Progression, Pseudoprogression, Pseudoresponse, Radiation Necrosis

Radiographic monitoring of posttreatment glioblastoma is important for clinical trials and determining next steps in management. Evaluation for tumor progression is confounded by the presence of treatment-related radiographic changes, making a definitive determination less straight-forward. The purpose of this article was to describe imaging tools available for assessing treatment response in glioblastoma, as well as to highlight the definitions, pathophysiology, and imaging features typical of true progression, pseudoprogression, pseudoresponse, and radiation necrosis.

Neutrophil-lymphocyte ratio dynamics are useful for distinguishing between recurrence and pseudoprogression in high-grade gliomas

Objective

Distinguishing recurrence and pseudoprogression is a major challenge in the clinical practice of treatment for high-grade gliomas (HGGs). The neutrophil-lymphocyte ratio (NLR) has been reported to be closely related to survival in HGGs. We aimed to assess the predictive value of NLR in the differential diagnosis of recurrence and pseudoprogression.

Materials and Methods

A total of 135 patients with histologically confirmed HGGs were studied. All patients underwent focal radiotherapy and concomitant temozolomide (TMZ), followed by 6 cycles of TMZ if MRI showed no progressive enlargement of contrast-enhancing lesions. MRI evaluation was taken 4 weeks after concurrent chemoradiotherapy and then every 2 months later. NLR was calculated at 4 time points of preoperation, before concurrent RT-TMZ (pretreatment), 4 weeks following completion of RT-TMZ, and MRI showed lesion enlarged or treatment completed.

Results

In 135 patients, 47 (34.8%) were found to be pseudoprogression (PsPD), and 28 (20.7%) were early disease progression (ePD). The mean pretreatment and post-treatment NLR were 4.2±2.1 and 5.1±3.5, respectively. The median overall survival in the PsPD group (25.2 months) was significantly longer than in the ePD (15.4 months) and no progression group (nPD) (21.6 months) (p<0.001). Overall survival was significantly shorter in the baseline NLR≥4 cohort compared with NLR<4 (p=0.03), but no significant difference was found between PsPD and ePD (p=0.197). Patients with decreased NLR showed significantly longer survival than no decreased group (p<0.001), and decreased NLR was found to be a significant difference between PsPD and ePD (p=0.022). Univariate and multivariate logistic regression analyses suggested that decreased NLR was an independent prognosis factor (p=0.031).

Conclusion

Decreased NLR is an independent prognostic factor and is useful for distinguishing between recurrence and pseudoprogression in HGGs.

Conventional Magnetic Resonance Features for Predicting 1p19q Codeletion Status of World Health Organization Grade II and III Diffuse Gliomas

PURPOSE

The conventional magnetic resonance features of World Health Organization (WHO) grade II and III diffuse gliomas in relation to chromosome 1p and 19q deletions (1p19q codeletion) were analyzed.

METHODS

We identified 147 cases of WHO grade II and III diffuse gliomas (1p/19q codeletion, 36 cases; no 1p/19q codeletion, 111 cases). χ Test and univariate and multivariate binary logistic regression analyses were conducted to evaluate the association between the imaging features and 1p19q codeletion status of WHO grade II and III diffuse gliomas in the discovery group, including the WHO grade II and III subgroups.

RESULTS

(1) In the entire population, multivariate regression demonstrated that proportion contrast-enhanced tumor (>5% vs ≤5%; odds ratio [OR], 0.169; P = 0.009), enhancing margin (poorly vs well defined; OR, 12.435; P = 0.002), and hemorrhage (yes vs no; OR, 21.082; P < 0.001) were associated with a higher incidence of 1p19q codeletion status. The nomogram showed good discrimination (area under the curve [AUC], 0.803) and calibration. (2) For grade II tumors, subgroup analysis found that enhancing margin (poorly vs well defined; OR, 0.308; P = 0.007) and subventricular zone (presence vs absence-; OR, 0.137; P < 0.001) were associated with a higher incidence of 1p19q codeletion status (AUC, 0.779). (3) For grade III tumors, subgroup analysis found that age (≥40 years vs <40 years; OR, 5.977; P = 0.03) and hemorrhage (yes vs no; OR, 18.051; P < 0.001) were associated with a higher incidence of 1p19q codeletion status (AUC, 0.816).

CONCLUSIONS

Conventional magnetic resonance features can be conveniently used to facilitate the preoperative prediction of 1p19q codeletion status of WHO grade II and III diffuse gliomas. Decision curve analysis demonstrated that the nomogram was clinically useful.

The surgical perspective in precision treatment of diffuse gliomas

Over the last decade, advances in molecular and imaging-based biomarkers have induced a more versatile diagnostic classification and prognostic evaluation of glioma patients. This, in combination with a growing therapeutic armamentarium, enables increasingly individualized, risk-benefit-optimized treatment strategies. This path to precision medicine in glioma patients requires surgical procedures to be reassessed within multidimensional management considerations. This article attempts to integrate the surgical intervention into a dynamic network of versatile diagnostic characterization, prognostic assessment, and multimodal treatment options in the light of the latest 2016 World Health Organization (WHO) classification of diffuse brain tumors, WHO grade II, III, and IV. Special focus is set on surgical aspects such as resectability, extent of resection, and targeted surgical strategies including minimal invasive stereotactic biopsy procedures, convection enhanced delivery, and photodynamic therapy. Moreover, the influence of recent advances in radiomics/radiogenimics on the process of surgical decision-making will be touched.

MRI based texture analysis to classify low grade gliomas into astrocytoma and 1p/19q codeleted oligodendroglioma

PURPOSE

Texture analysis performed on MR images can detect quantitative features that are imperceptible to human visual assessment. The purpose of this study was to evaluate the feasibility of texture analysis on preoperative conventional MRI to discriminate between histological subtypes in low-grade gliomas (LGGs), and to determine the utility of texture analysis compared to histogram analysis alone.

METHODS

A total of 41 patients with LGG, 21 astrocytoma and 20 1p/19q codeleted oligodendroglioma were included in this study. Patients were randomly divided into training (60%) and testing (40%) sets. Texture analysis was performed on conventional MRI sequences to obtain the most discriminant factor (MDF) values for both the training and testing data. Receiver operating characteristic (ROC) curve analyses were then performed using the MDF values and 9 histogram parameters in the training data to obtain cut-off values for determining the correct rate of discriminating between astrocytoma and oligodendroglioma in the testing data.

RESULTS

The ROC analyses using MDF values resulted in an area under the curve (AUC) of 0.91 (sensitivity 86%, specificity 87%) for T2w FLAIR, 0.94 (87%, 89%) for ADC, 0.98 (93%, 95%) for T1w, and 0.88 (78%, 86%) for T1w + Gd sequences. Using the best cut-off values, MDF correctly discriminated between the two groups in 94%, 82%, 100%, and 88% of cases in the testing data, respectively. The MDF outperformed all 9 of the histogram parameters.

CONCLUSION

Texture analysis performed on conventional preoperative MRI images can accurately predict histological subtype of LGGs, which would have an impact on clinical management.

Tubular brain tumor biopsy improves diagnostic yield for subcortical lesions

PURPOSE

Molecular data has become an essential part of the updated World Health Organization (WHO) grading of central nervous system tumors. However, stereotactic needle biopsies provide only small volume specimens and limit the extent of histologic and molecular testing that can be performed. We assessed the use of a tubular retractor-based minimally invasive biopsy technique to provide improved tissue yield and diagnostic data compared to needle biopsy.

METHODS

Eighteen patients underwent an open transtubular biopsy compared to 146 stereotactic biopsies during the years of 2010-2018.

RESULTS

Tubular biopsies resulted in a higher volume of tissue provided to the pathologist than needle biopsies (1.26 cm³ vs. 0.3 cm³; p < 0.0001). There was a higher rate of non-diagnostic sample with stereotactic compared to transtubular biopsy (13% vs. 0%; p = 0.13). Six patients who underwent stereotactic biopsy required reoperation for diagnosis, while no transtubular biopsy patient required reoperation in order to obtain a diagnostic specimen. Postoperative hematoma was the most common post-operative complication in both groups.

CONCLUSIONS

Stereotactic transtubular biopsies are a viable alternative to stereotactic needle biopsies with excellent rates of diagnostic success and acceptable morbidity relative to the needle biopsy technique. As molecular data begins to increasingly drive treatment decisions, additional biopsy techniques that afford large tissue volumes may be necessary to adapt to the new needs of pathologists and treating oncologists.

Glioblastoma Treatments: An Account of Recent Industrial Developments

The different drugs and medical devices, which are commercialized or under industrial development for glioblastoma treatment, are reviewed. Their different modes of action are analyzed with a distinction being made between the effects of radiation, the targeting of specific parts of glioma cells, and immunotherapy. Most of them are still at a too early stage of development to firmly conclude about their efficacy. Optune, which triggers antitumor activity by blocking the mitosis of glioma cells under the application of an alternating electric field, seems to be the only recently developed therapy with some efficacy reported on a large number of GBM patients. The need for early GBM diagnosis is emphasized since it could enable the treatment of GBM tumors of small sizes, possibly easier to eradicate than larger tumors. Ways to improve clinical protocols by strengthening preclinical studies using of a broader range of different animal and tumor models are also underlined. Issues related with efficient drug delivery and crossing of blood brain barrier are discussed. Finally societal and economic aspects are described with a presentation of the orphan drug status that can accelerate the development of GBM therapies, patents protecting various GBM treatments, the different actors tackling GBM disease, the cost of GBM treatments, GBM market figures, and a financial analysis of the different companies involved in the development of GBM therapies.

Sequencing the next generation of glioblastomas

The most aggressive brain malignancy, glioblastoma, accounts for 60-70% of all gliomas and is uniformly fatal. According to the molecular signature, glioblastoma is divided into four subtypes (proneural, neural, classical, and mesenchymal), each with its own genetic background. The Cancer Genome Atlas project provides information about the most common genetic changes in glioblastoma. They involve mutations in TP53, TERT, and PTEN, and amplifications in EFGR, PDGFRA, CDK4, CDK6, MDM2, and MDM4. Recently, epigenetics was used to demonstrate the oncogenic roles of miR-124, miR-137, and miR-128. The most important findings so far are mutations in IDH1/2 and MGMT promoter methylation, which are routinely used as predictive biomarkers in patient care. Current clinical treatment leaves patients with only a 10% chance for 5-year survival. Attempts to define the mutational profile of glioblastoma to identify clinically relevant changes have not yet yielded significant results. This can be attributed to inter- and intra-tumor heterogeneity that is present in most glioblastomas, as well as hypermutation that appears as a consequence of chemotherapy. The evolving field of radiogenomics aims to classify glioblastoma using a combination of magnetic resonance imaging and genomic information. In the era of genomic medicine, next-generation sequencing is extensively used in glioblastoma research because it can detect multiple changes in a single biological sample; its potential in detecting circulating cell-free DNA has been tested in cerebrospinal fluid and plasma, and it shows promise in the examination of the cellular content of extracellular vesicles as a potential source of biomarkers. Next-generation sequencing is making its way into glioblastoma diagnostics. Gene panels like GlioSeq, which includes the most commonly mutated genes, are currently being tested on snap frozen and formalin fixed paraffin embedded tissues. This new methodology is helping to define the "next generation of glioblastomas" - clinically defined and better understood, with greater potential to improve patient care. However, limitations of the necessary infrastructure, space for data storage, technical expertise, and data ownership need to be considered carefully.