Advanced magnetic resonance imaging of the physical processes in human glioblastoma

The detrimental effect of biopsy preceding resection in surgically accessible glioblastoma: results from the national cancer database

PURPOSE

Aggressive resection in surgically-accessible glioblastoma (GBM) correlates with improved survival over less extensive resections. However, the clinical impact of performing a biopsy before definitive resection have not been previously evaluated.

METHODS

We analyzed 17,334 GBM patients from the NCDB from 2010-2014. We categorized them into: "upfront resection" and "biopsy followed by resection". The outcomes of interes included OS, 30-day readmission/mortality, 90-day mortality, and length of hospital stay (LOS). The Kaplan-Meier methods and accelerated failure time (AFT) models were applied for survival analysis. Multivariable binary logistic regression were performed to compare differences among groups. Multiple imputation and propensity score matching (PSM) were conducted for validation.

RESULTS

"Upfront resection" had superior OS over "biopsy followed by resection" (median OS:12.4 versus 11.1 months, log-rank p = 0.001). Similarly, multivariable AFT models favored "upfront resection" (time ratio[TR]:0.83, 95%CI: 0.75-0.93, p = 0.001). Patients undergoing "upfront gross-total resection (GTR)" had higher OS over "upfront subtotal resection (STR)", "GTR following STR", and "GTR or STR following initial biopsy" (14.4 vs. 10.3, 13.5, 13.3, and 9.1 months;TR: 1.00 [Ref.], 0.75, 0.82, 0.88, and 0.67). Recent years of diagnosis, higher income, facilities located in Southern regions, and treatment at academic facilities were significantly associated with the higher likelihood of undergoing upfront resection. Multivariable regression showed a decreased 30 and 90-day mortality for patients undergoing "upfront resection", 73% and 44%, respectively (p < 0.001).

CONCLUSIONS

Pre-operative biopsies for surgically accessible GBM are associated with worse survival despite subsequent resection compared to patients undergoing upfront resection.

Clinical, qualitative imaging biomarkers, and tumor oxygenation imaging biomarkers for differentiation of midline-located IDH wild-type glioblastomas and H3 K27-altered diffuse midline gliomas in adults

PURPOSE

To compare the clinical, qualitative and quantitative imaging phenotypes, including tumor oxygenation characteristics of midline-located IDH-wildtype glioblastomas (GBMs) and H3 K27-altered diffuse midline gliomas (DMGs) in adults.

METHODS

Preoperative MRI data of 55 adult patients with midline-located IDH-wildtype GBM or H3 K27-altered DMG (32 IDH-wildtype GBM and 23 H3 K27-altered DMG patients) were included. Qualitative imaging assessment was performed. Quantitative imaging assessment including the tumor volume, normalized cerebral blood volume, capillary transit time heterogeneity (CTH), oxygen extraction fraction (OEF), relative cerebral metabolic rate of oxygen values, and mean ADC value were performed from the tumor mask via automatic segmentation. Univariable and multivariable logistic analyses were performed.

RESULTS

On multivariable analysis, age (odds ratio [OR] = 0.92, P = 0.015), thalamus or medulla location (OR = 10.48, P = 0.013), presence of necrosis (OR = 0.15, P = 0.038), and OEF (OR = 0.01, P = 0.042) were independent predictors to differentiate H3 K27-altered DMG from midline-located IDH-wildtype GBM. The area under the curve, accuracy, sensitivity, and specificity of the multivariable model were 0.88 (95 % confidence interval: 0.77-0.95), 81.8 %, 82.6 %, and 81.3 %, respectively.

CONCLUSIONS

Along with younger age, tumor location, less frequent necrosis, and lower OEF may be useful imaging biomarkers to differentiate H3 K27-altered DMG from midline-located IDH-wildtype GBM. Tumor oxygenation imaging biomarkers may reflect the less hypoxic nature of H3 K27-altered DMG than IDH-wildtype GBM and may contribute to differentiation.

Integrating and optimizing tonabersat in standard glioblastoma therapy: A preclinical study

Glioblastoma (GB), a highly aggressive primary brain tumor, presents a poor prognosis despite the current standard therapy, including radiotherapy and temozolomide (TMZ) chemotherapy. Tumor microtubes involving connexin 43 (Cx43) contribute to glioma progression and therapy resistance, suggesting Cx43 inhibition as a potential treatment strategy. This research aims to explore the adjuvant potential of tonabersat, a Cx43 gap junction modulator and blood-brain barrier-penetrating compound, in combination with the standard of care for GB. In addition, different administration schedules and timings to optimize tonabersat's therapeutic window are investigated. The F98 Fischer rat model will be utilized to investigate tonabersat's impact in a clinically relevant setting, by incorporating fractionated radiotherapy (three fractions of 9 Gy) and TMZ chemotherapy (29 mg/kg). This study will evaluate tonabersat's impact on tumor growth, survival, and treatment response through advanced imaging (CE T1-w MRI) and histological analysis. Results show extended survival in rats receiving tonabersat with standard care, highlighting its adjuvant potential. Daily tonabersat administration, both preceding and following radiotherapy, emerges as a promising approach for maximizing survival outcomes. The study suggests tonabersat's potential to reduce tumor invasiveness, providing a new avenue for GB treatment. In conclusion, this preclinical investigation highlights tonabersat's potential as an effective adjuvant treatment for GB, and its established safety profile from clinical trials in migraine treatment presents a promising foundation for further exploration.

Imaging phenotypes predict overall survival in glioma more accurate than basic demographic and cell mutation profiles

BACKGROUND

Magnetic resonance imaging (MRI), digital pathology imaging (PATH), demographics, and IDH mutation status predict overall survival (OS) in glioma. Identifying and characterizing predictive features in the different modalities may improve OS prediction accuracy.

PURPOSE

To evaluate the OS prediction accuracy of combinations of prognostic markers in glioma patients.

MATERIALS AND METHODS

Multi-contrast MRI, comprising T1-weighted, T1-weighted post-contrast, T2-weighted, T2 fluid-attenuated-inversion-recovery, and pathology images from glioma patients (n = 160) were retrospectively collected (1983-2008) from TCGA alongside age and sex. Phenotypic profiling of tumors was performed by quantifying the radiographic and histopathologic descriptors extracted from the delineated region-of-interest in MRI and PATH images. A Cox proportional hazard model was trained with the MRI and PATH features, IDH mutation status, and basic demographic variables (age and sex) to predict OS. The performance was evaluated in a split-train-test configuration using the concordance-index, computed between the predicted risk score and observed OS.

RESULTS

The average age of patients was 51.2years (women: n = 77, age-range=18-84years; men: n = 83, age-range=21-80years). The median OS of the participants was 494.5 (range,3-4752), 481 (range,7-4752), and 524.5 days (range,3-2869), respectively, in complete dataset, training, and test datasets. The addition of MRI or PATH features improved prediction of OS when compared to models based on age, sex, and mutation status alone or their combination (p < 0.001). The full multi-omics model integrated MRI, PATH, clinical, and genetic profiles and predicted the OS best (c-index= 0.87).

CONCLUSION

The combination of imaging, genetic, and clinical profiles leads to a more accurate prognosis than the clinical and/or mutation status.

The Role of Multimodal Imaging in Differentiating Vasogenic from Infiltrative Edema: A Systematic Review

Background  High-grade gliomas (HGGs) are the most prevalent primary malignancy of the central nervous system. The tumor results in vasogenic and infiltrative edema . Exact anatomical differentiation of these edemas is so important for surgical planning. Multimodal imaging could be used to differentiate the edema type. Purpose  The aim of this study was to investigate the role of multimodal imaging in the differentiation of vasogenic edema from infiltrative edema in patients with HGG (grade III and grade IV). Data Sources  A search on PubMed, EMBASE, Scopus, and ISI Web of Science Core Collection up to June 2022 using terms related to (a) multimodal imaging AND (b) HGG AND (c) edema. (PROSPERO registration number: CRD42022336131) Study Selection  Two reviewers screened the articles and independently extracted the data. We included original articles assessing the role of multimodal imaging in differentiating vasogenic from infiltrative edema in patients with HGG. Six high-quality articles remained for the narrative synthesis. Data Synthesis  Dynamic susceptibility contrast imaging showed that relative cerebral blood volume and relative cerebral blood flow were higher in the infiltrative edema component than in the vasogenic edema component. Diffusion tensor imaging revealed a dispute on fractional anisotropy. The apparent diffusion coefficient was comparable between the two edematous components. Magnetic resonance spectroscopy exhibited an increment in choline/creatinine ratio and choline/N-acetyl aspartate ratio in the infiltrative edema component. Limitations  Strict study selection, low sample size of relevant published studies, and heterogeneity in endpoint variables were the major drawbacks. Conclusions  Multimodal imaging, including dynamic susceptibility contrast and magnetic resonance spectroscopy, might help differentiate between vasogenic and infiltrative edema.

BCL2L13 promotes mitophagy through DNM1L-mediated mitochondrial fission in glioblastoma

There is an urgent need for novel diagnostic and therapeutic strategies for patients with Glioblastoma multiforme (GBM). Previous studies have shown that BCL2 like 13 (BCL2L13) is a member of the BCL2 family regulating cell growth and apoptosis in different types of tumors. However, the clinical significance, biological role, and potential mechanism in GBM remain unexplored. In this study, we showed that BCL2L13 expression is significantly upregulated in GBM cell lines and clinical GBM tissue samples. Mechanistically, BCL2L13 targeted DNM1L at the Ser616 site, leading to mitochondrial fission and high mitophagy flux. Functionally, these alterations significantly promoted the proliferation and invasion of GBM cells both in vitro and in vivo. Overall, our findings demonstrated that BCL2L13 plays a significant role in promoting mitophagy via DNM1L-mediated mitochondrial fission in GBM. Therefore, the regulation and biological function of BCL2L13 render it a candidate molecular target for treating GBM.

Assessment and prediction of glioblastoma therapy response: challenges and opportunities

Glioblastoma is the most aggressive type of primary adult brain tumour. The median survival of patients with glioblastoma remains approximately 15 months, and the 5-year survival rate is <10%. Current treatment options are limited, and the standard of care has remained relatively constant since 2011. Over the last decade, a range of different treatment regimens have been investigated with very limited success. Tumour recurrence is almost inevitable with the current treatment strategies, as glioblastoma tumours are highly heterogeneous and invasive. Additionally, another challenging issue facing patients with glioblastoma is how to distinguish between tumour progression and treatment effects, especially when relying on routine diagnostic imaging techniques in the clinic. The specificity of routine imaging for identifying tumour progression early or in a timely manner is poor due to the appearance similarity of post-treatment effects. Here, we concisely describe the current status and challenges in the assessment and early prediction of therapy response and the early detection of tumour progression or recurrence. We also summarize and discuss studies of advanced approaches such as quantitative imaging, liquid biomarker discovery and machine intelligence that hold exceptional potential to aid in the therapy monitoring of this malignancy and early prediction of therapy response, which may decisively transform the conventional detection methods in the era of precision medicine.

Imaging biomarkers for clinical applications in neuro-oncology: current status and future perspectives

Biomarker discovery and development are popular for detecting the subtle diseases. However, biomarkers are needed to be validated and approved, and even fewer are ever used clinically. Imaging biomarkers have a crucial role in the treatment of cancer patients because they provide objective information on tumor biology, the tumor's habitat, and the tumor's signature in the environment. Tumor changes in response to an intervention complement molecular and genomic translational diagnosis as well as quantitative information. Neuro-oncology has become more prominent in diagnostics and targeted therapies. The classification of tumors has been actively updated, and drug discovery, and delivery in nanoimmunotherapies are advancing in the field of target therapy research. It is important that biomarkers and diagnostic implements be developed and used to assess the prognosis or late effects of long-term survivors. An improved realization of cancer biology has transformed its management with an increasing emphasis on a personalized approach in precision medicine. In the first part, we discuss the biomarker categories in relation to the courses of a disease and specific clinical contexts, including that patients and specimens should both directly reflect the target population and intended use. In the second part, we present the CT perfusion approach that provides quantitative and qualitative data that has been successfully applied to the clinical diagnosis, treatment and application. Furthermore, the novel and promising multiparametric MR imageing approach will provide deeper insights regarding the tumor microenvironment in the immune response. Additionally, we briefly remark new tactics based on MRI and PET for converging on imaging biomarkers combined with applications of bioinformatics in artificial intelligence. In the third part, we briefly address new approaches based on theranostics in precision medicine. These sophisticated techniques merge achievable standardizations into an applicatory apparatus for primarily a diagnostic implementation and tracking radioactive drugs to identify and to deliver therapies in an individualized medicine paradigm. In this article, we describe the critical principles for imaging biomarker characterization and discuss the current status of CT, MRI and PET in finiding imaging biomarkers of early disease.

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.

Identification and validation of a novel prognostic signature based on mitochondria and oxidative stress related genes for glioblastoma

BACKGROUND

Mitochondria represent a major source of reactive oxygen species (ROS) in cells, and the direct increase in ROS content is the primary cause of oxidative stress, which plays an important role in tumor proliferation, invasion, angiogenesis, and treatment. However, the relationship between mitochondrial oxidative stress-related genes and glioblastoma (GBM) remains unclear. This study aimed to investigate the value of mitochondria and oxidative stress-related genes in the prognosis and therapeutic targets of GBM.

METHODS

We retrieved mitochondria and oxidative stress-related genes from several public databases. The LASSO regression and Cox analyses were utilized to build a risk model and the ROC curve was used to assess its performance. Then, we analyzed the correlation between the model and immunity and mutation. Furthermore, CCK8 and EdU assays were utilized to verify the proliferative capacity of GBM cells and flow cytometry was used to analyze apoptosis rates. Finally, the JC-1 assay and ATP levels were utilized to detect mitochondrial function, and the intracellular ROS levels were determined using MitoSOX and BODIPY 581/591 C11.

RESULTS

5 mitochondrial oxidative stress-related genes (CTSL, TXNRD2, NUDT1, STOX1, CYP2E1) were screened by differential expression analysis and Cox analysis and incorporated in a risk model which yielded a strong prediction accuracy (AUC value = 0.967). Furthermore, this model was strongly related to immune cell infiltration and mutation status and could identify potential targeted therapeutic drugs for GBM. Finally, we selected NUDT1 for further validation in vitro. The results showed that NUDT1 was elevated in GBM, and knockdown of NUDT1 inhibited the proliferation and induced apoptosis of GBM cells, while knockdown of NUDT1 damaged mitochondrial homeostasis and induced oxidative stress in GBM cells.

CONCLUSION

Our study was the first to propose a prognostic model of mitochondria and oxidative stress-related genes, which provided potential therapeutic strategies for GBM patients.

Transcriptomic analyses of patient peripheral blood with hemoglobin depletion reveal glioblastoma biomarkers

Peripheral blood is gaining prominence as a noninvasive alternative to tissue biopsy to develop biomarkers for glioblastoma (GBM); however, widely utilized blood-based biomarkers in clinical settings have not yet been identified due to the lack of a robust detection approach. Here, we describe the application of globin reduction in RNA sequencing of whole blood (i.e., WBGR) and perform transcriptomic analysis to identify GBM-associated transcriptomic changes. By using WBGR, we improved the detection sensitivity of informatic reads and identified differential gene expression in GBM blood. By analyzing tumor tissues, we identified transcriptomic traits of GBM blood. Further functional enrichment analyses retained the most changed genes in GBM. Subsequent validation elicited a 10-gene panel covering mRNA, long noncoding RNA, and microRNA (i.e., GBM-Dx panel) that has translational potential to aid in the early detection or clinical management of GBM. Here, we report an integrated approach, WBGR, with comprehensive analytic capacity for blood-based marker identification.

Diffusion Weighted Imaging in Neuro-Oncology: Diagnosis, Post-Treatment Changes, and Advanced Sequences-An Updated Review

DWI is an imaging technique commonly used for the assessment of acute ischemia, inflammatory disorders, and CNS neoplasia. It has several benefits since it is a quick, easily replicable sequence that is widely used on many standard scanners. In addition to its normal clinical purpose, DWI offers crucial functional and physiological information regarding brain neoplasia and the surrounding milieu. A narrative review of the literature was conducted based on the PubMed database with the purpose of investigating the potential role of DWI in the neuro-oncology field. A total of 179 articles were included in the study.

Performance of deep learning in classifying malignant primary and metastatic brain tumors using different MRI sequences: A medical analysis study

BACKGROUND

Malignant Primary Brain Tumor (MPBT) and Metastatic Brain Tumor (MBT) are the most common types of brain tumors, which require different management approaches. Magnetic Resonance Imaging (MRI) is the most frequently used modality for assessing the presence of these tumors. The utilization of Deep Learning (DL) is expected to assist clinicians in classifying MPBT and MBT more effectively.

OBJECTIVE

This study aims to examine the influence of MRI sequences on the classification performance of DL techniques for distinguishing between MPBT and MBT and analyze the results from a medical perspective.

METHODS

Total 1,360 images performed from 4 different MRI sequences were collected and preprocessed. VGG19 and ResNet101 models were trained and evaluated using consistent parameters. The performance of the models was assessed using accuracy, sensitivity, and other precision metrics based on a confusion matrix analysis.

RESULTS

The ResNet101 model achieves the highest accuracy of 83% for MPBT classification, correctly identifying 90 out of 102 images. The VGG19 model achieves an accuracy of 81% for MBT classification, accurately classifying 86 out of 102 images. T2 sequence shows the highest sensitivity for MPBT, while T1C and T1 sequences exhibit the highest sensitivity for MBT.

CONCLUSIONS

DL models, particularly ResNet101 and VGG19, demonstrate promising performance in classifying MPBT and MBT based on MRI images. The choice of MRI sequence can impact the sensitivity of tumor detection. These findings contribute to the advancement of DL-based brain tumor classification and its potential in improving patient outcomes and healthcare efficiency.

The MBNL1/circNTRK2/PAX5 pathway regulates aerobic glycolysis in glioblastoma cells by encoding a novel protein NTRK2-243aa

Glioblastoma multiforme (GBM) is the most common tumor of the human central nervous system. Aerobic glycolysis has been strongly related to tumor development and malignant behavior. In this study, we found that MBNL1, circNTRK2, and NTRK2-243aa were markedly downregulated and inhibited glycolysis in GBM, whereas PAX5 was upregulated and promoted glycolysis. Functionally, MBNL1 promoted the expression of circNTRK2 by binding to NTRK2 pre-mRNA, as validated using RNA pull-down and nascent RNA immunoprecipitation assays. Mass spectrometry, western blotting, and immunofluorescence staining methods were used to detect the expression of NTRK2-243aa. NTRK2-243aa-encoded by circNTRK2-phosphorylated PAX5 at Y102, leading to the attenuation of the half-life of PAX5, as validated by in vitro kinase and MG132 rescue assays. Besides, PAX5 transcriptionally facilitated the expression of PKM2 and HK2 by binding to their promoter regions, as verified by luciferase reporter and chromatin immunoprecipitation assays. Finally, overexpression of MBNL1 and circNTRK2 combined with PAX5 knockdown effectively inhibited the formation of GBM xenograft tumors and significantly prolonged the survival of orthotopic nude mice. We have delineated that the MBNL1/circNTRK2/PAX5 pathway plays a crucial role in regulating GBM glycolysis and could provide potential targets and alternative strategies for the treatment of GBM.

Liquid biopsies for early diagnosis of brain tumours: in silico mathematical biomarker modelling

Brain tumours are the biggest cancer killer in those under 40 and reduce life expectancy more than any other cancer. Blood-based liquid biopsies may aid early diagnosis, prediction and prognosis for brain tumours. It remains unclear whether known blood-based biomarkers, such as glial fibrillary acidic protein (GFAP), have the required sensitivity and selectivity. We have developed a novel in silico model which can be used to assess and compare blood-based liquid biopsies. We focused on GFAP, a putative biomarker for astrocytic tumours and glioblastoma multi-formes (GBMs). In silico modelling was paired with experimental measurement of cell GFAP concentrations and used to predict the tumour volumes and identify key parameters which limit detection. The average GBM volumes of 449 patients at Leeds Teaching Hospitals NHS Trust were also measured and used as a benchmark. Our model predicts that the currently proposed GFAP threshold of 0.12 ng ml-1 may not be suitable for early detection of GBMs, but that lower thresholds may be used. We found that the levels of GFAP in the blood are related to tumour characteristics, such as vasculature damage and rate of necrosis, which are biological markers of tumour aggressiveness. We also demonstrate how these models could be used to provide clinical insight.

WDR34 affects PI3K/Akt and Wnt/β-catenin pathways to regulates malignant biological behaviors of glioma cells

PURPOSE

Glioma is the most prevalent primary intracranial tumor globally. WDR34, a member of the WDR superfamily with five WD40 repeats, is involved in the pathogenesis of several tumors. However, the role of WDR34 in glioma progression is unknown.

METHODS

The expression and prognostic significance of WDR34 in glioma patients were analyzed using GEPIA. WDR34 expression was detected by qRT-PCR. Western blot was employed to determine the expression of Ki67, proliferating cell nuclear antigen (PCNA), matrix metallopeptidase (MMP)2, MMP9, phosphatase and tensin homolog, protein kinase B (Akt), phosphorylated Akt, β-catenin, and c-Myc. CCK-8, BrdU incorporation assay, Transwell invasion assay, flow cytometry analysis, and measurement of caspase-3 and caspase-9 activities were conducted to examine the effects of WDR34 knockdown on glioma cells.

RESULTS

WDR34 was upregulated in glioma, which predicted a poor prognosis in glioma patients. WDR34 knockdown inhibited cell proliferation and reduced the expression of Ki67 and PCNA in glioma cells. WDR34 knockdown repressed the invasive ability of glioma cells by decreasing MMP-2 and MMP-9 expression. WDR34 knockdown increased the apoptotic rate and caspase-3 and caspase-9 activities in glioma cells. The PI3K/Akt and Wnt/β-catenin pathways were inhibited after WDR34 knockdown in glioma cells. Moreover, overexpression of Akt or β-catenin reversed the function of WDR34 knockdown on proliferation, invasion, and apoptosis. WDR34 knockdown reduced tumor growth in vivo.

CONCLUSIONS

WDR34 knockdown inhibited malignant biological behaviors of glioma cells by inactivating the PI3K/Akt and Wnt/β-catenin signaling cascades.

The Application of Image Segmentation to Determine the Ratio of Peritumoral Edema Area to Tumor Area on Primary Malignant Brain Tumor and Metastases through Conventional Magnetic Resonance Imaging

BACKGROUND: Primary malignant brain tumor and metastases on the brain have a similar pattern in conventional Magnetic Resonance Imaging (MRI), even though both require entirely different treatment and management. The pathophysiological difference of peritumoral edema can help to distinguish the case of primary malignant brain tumor and brain metastases. AIM: This study aimed to analyze the ratio of the area of peritumoral edema to the tumor using Otsu’s method of image segmentation technique with a user-friendly Graphical User Interface (GUI). METODS: Data was prepared by obtaining the examination results of Anatomical Pathology and MRI imaging. The area of peritumoral edema was identified from MRI image segmentation with T2/FLAIR sequence. While the area of tumor was identified using MRI image segmentation with T1 sequence. RESULTS: The Mann-Whitney test was employed to analyze the ratio of the area of peritumoral edema to tumor on both groups. Data testing produced a significance level of 0.013 (p < 0.05) with a median value (Nmax-Nmin) of 1.14 (3.31-0.08) for the primary malignant brain tumor group and a median value (Nmax-Nmin) of 1.17 (10.30-0.90) for the brain metastases group. CONCLUSIONS: There was a significant difference in the ratio of the area of peritumoral edema to the area of tumor from both groups, in which brain metastases have a greater value than the primary malignant brain tumor.

Inorganic Nanomaterial for Biomedical Imaging of Brain Diseases

In the past few decades, brain diseases have taken a heavy toll on human health and social systems. Magnetic resonance imaging (MRI), photoacoustic imaging (PA), computed tomography (CT), and other imaging modes play important roles in disease prevention and treatment. However, the disadvantages of traditional imaging mode, such as long imaging time and large noise, limit the effective diagnosis of diseases, and reduce the precision treatment of diseases. The ever-growing applications of inorganic nanomaterials in biomedicine provide an exciting way to develop novel imaging systems. Moreover, these nanomaterials with special physicochemical characteristics can be modified by surface modification or combined with functional materials to improve targeting in different diseases of the brain to achieve accurate imaging of disease regions. This article reviews the potential applications of different types of inorganic nanomaterials in vivo imaging and in vitro detection of different brain disease models in recent years. In addition, the future trends, opportunities, and disadvantages of inorganic nanomaterials in the application of brain diseases are also discussed. Additionally, recommendations for improving the sensitivity and accuracy of inorganic nanomaterials in screening/diagnosis of brain diseases.

Anatomic and Molecular MR Image Synthesis Using Confidence Guided CNNs

Data-driven automatic approaches have demonstrated their great potential in resolving various clinical diagnostic dilemmas in neuro-oncology, especially with the help of standard anatomic and advanced molecular MR images. However, data quantity and quality remain a key determinant, and a significant limit of the potential applications. In our previous work, we explored the synthesis of anatomic and molecular MR image networks (SAMR) in patients with post-treatment malignant gliomas. In this work, we extend this through a confidence-guided SAMR (CG-SAMR) that synthesizes data from lesion contour information to multi-modal MR images, including T1-weighted ( [Formula: see text]), gadolinium enhanced [Formula: see text] (Gd- [Formula: see text]), T2-weighted ( [Formula: see text]), and fluid-attenuated inversion recovery ( FLAIR ), as well as the molecular amide proton transfer-weighted ( [Formula: see text]) sequence. We introduce a module that guides the synthesis based on a confidence measure of the intermediate results. Furthermore, we extend the proposed architecture to allow training using unpaired data. Extensive experiments on real clinical data demonstrate that the proposed model can perform better than current the state-of-the-art synthesis methods. Our code is available at https://github.com/guopengf/CG-SAMR.

Clinical outcomes as a function of the number of samples taken during stereotactic needle biopsies: a meta-analysis

BACKGROUND

Stereotactic needle biopsy remains the cornerstone for tissue diagnosis for tumors located in regions of the brain that are difficult to access through open surgery.

OBJECTIVE

We perform a meta-analysis of the literature to examine the relation between number of samples taken during biopsy and diagnostic yield, morbidity and mortality.

METHODS

We identified 2416 patients from 28 cohorts in studies published in PubMed database that studied stereotactic needle biopsies for tumor indications. Meta-analysis by proportions and meta-regression analyses were performed.

RESULTS

On meta-analysis, the morbidity profile of the published needle biopsy studies clustered into three groups: studies that performed < 3 samples (n = 8), 3-6 samples (n = 13), and > 6 samples during biopsy (n = 7). Pooled estimates for biopsy related morbidity were 4.3%, 16.3%, and 17% for studies reporting < 3, 3-6, and > 6 biopsy samples, respectively. While these morbidity estimates significantly differed (p < 0.001), the diagnostic yields reported for studies performing < 3 biopsies, 3-6 samples, and > 6 samples were comparable. Pooled estimates of diagnostic yield for these three groups were 90.4%, 93.8%, and 88.1%, respectively. Mortality did not significantly differ between studies reporting differing number of samples taken during biopsy.

CONCLUSIONS

Our meta-analysis suggests that morbidity risk in needle biopsy is non-linearly associated with the number of samples taken. There was no association between the number of biopsies taken, and diagnostic yield or mortality.

Combining MRI and Histologic Imaging Features for Predicting Overall Survival in Patients with Glioma

Purpose To test the hypothesis that combined features from MR and digital histopathologic images more accurately predict overall survival (OS) in patients with glioma compared with MRI or histopathologic features alone. Materials and Methods Multiparametric MR and histopathologic images in patients with a diagnosis of glioma (high- or low-grade glioma [HGG or LGG]) were obtained from The Cancer Imaging Archive (original images acquired 1983-2008). An extensive set of engineered features such as intensity, histogram, and texture were extracted from delineated tumor regions in MR and histopathologic images. Cox proportional hazard regression and support vector machine classification (SVC) models were applied to (a) MRI features only (MRI_cox/svc), histopathologic features only (HistoPath_cox/svc), and (c) combined MRI and histopathologic features (MRI+HistoPath_cox/svc) and evaluated in a split train-test configuration. Results A total of 171 patients (mean age, 51 years ± 15; 91 men) were included with HGG (n = 75) and LGG (n = 96). Median OS was 467 days (range, 3-4752 days) for all patients, 350 days (range, 15-1561 days) for HGG, and 595 days (range, 3-4752 days) for LGG. The MRI+HistoPath_cox model demonstrated higher concordance index (C-index) compared with MRI_cox and HistoPath_cox models on all patients (C-index, 0.79 vs 0.70 [P = .02; MRI_cox] and 0.67 [P = .01; HistoPath_cox]), patients with HGG (C-index, 0.78 vs 0.68 [P = .03; MRI_cox] and 0.64 [P = .01; HistoPath_cox]), and patients with LGG (C-index, 0.88 vs 0.62 [P = .008; MRI_cox] and 0.62 [P = .006; HistoPath_cox]). In binary classification, the MRI+HistoPath_svc model (area under the receiver operating characteristic curve [AUC], 0.86 [95% CI: 0.80, 0.95]) had higher performance than the MRI_svc model (AUC, 0.68 [95% CI: 0.50, 0.81]; P = .01) and the HistoPath_svc model (AUC, 0.72 [95% CI: 0.60, 0.85]; P = .04). Conclusion The model combining features from MR and histopathologic images had higher accuracy in predicting OS compared with the models with MR or histopathologic images alone. Keywords: Survival Prediction, Gliomas, Digital Pathology Imaging, MR Imaging, Machine Learning Supplemental material is available for this article.

A Multiparametric MRI-Based Radiomics Analysis to Efficiently Classify Tumor Subregions of Glioblastoma: A Pilot Study in Machine Learning

Glioblastoma multiforme (GBM) carries a poor prognosis and usually presents with heterogenous regions of a necrotic core, solid part, peritumoral tissue, and peritumoral edema. Accurate demarcation on magnetic resonance imaging (MRI) between the active tumor region and perifocal edematous extension is essential for planning stereotactic biopsy, GBM resection, and radiotherapy. We established a set of radiomics features to efficiently classify patients with GBM and retrieved cerebral multiparametric MRI, including contrast-enhanced T1-weighted (T1-CE), T2-weighted, T2-weighted fluid-attenuated inversion recovery, and apparent diffusion coefficient images from local patients with GBM. A total of 1316 features on the raw MR images were selected for each annotated area. A leave-one-out cross-validation was performed on the whole dataset, the different machine learning and deep learning techniques tested; random forest achieved the best performance (average accuracy: 93.6% necrosis, 90.4% solid part, 95.8% peritumoral tissue, and 90.4% peritumoral edema). The features from the enhancing tumor and the tumor shape elongation of peritumoral edema region for high-risk groups from T1-CE. The multiparametric MRI-based radiomics model showed the efficient classification of tumor subregions of GBM and suggests that prognostic radiomic features from a routine MRI exam may also be significantly associated with key biological processes that affect the response to chemotherapy in GBM.

Accelerated 3D whole-brain T1, T2, and proton density mapping: feasibility for clinical glioma MR imaging

Purpose

Advanced MRI-based biomarkers offer comprehensive and quantitative information for the evaluation and characterization of brain tumors. In this study, we report initial clinical experience in routine glioma imaging with a novel, fully 3D multiparametric quantitative transient-state imaging (QTI) method for tissue characterization based on T1 and T2 values.

Methods

To demonstrate the viability of the proposed 3D QTI technique, nine glioma patients (grade II–IV), with a variety of disease states and treatment histories, were included in this study. First, we investigated the feasibility of 3D QTI (6:25 min scan time) for its use in clinical routine imaging, focusing on image reconstruction, parameter estimation, and contrast-weighted image synthesis. Second, for an initial assessment of 3D QTI-based quantitative MR biomarkers, we performed a ROI-based analysis to characterize T1 and T2 components in tumor and peritumoral tissue.

Results

The 3D acquisition combined with a compressed sensing reconstruction and neural network-based parameter inference produced parametric maps with high isotropic resolution (1.125 × 1.125 × 1.125 mm³ voxel size) and whole-brain coverage (22.5 × 22.5 × 22.5 cm³ FOV), enabling the synthesis of clinically relevant T1-weighted, T2-weighted, and FLAIR contrasts without any extra scan time. Our study revealed increased T1 and T2 values in tumor and peritumoral regions compared to contralateral white matter, good agreement with healthy volunteer data, and high inter-subject consistency.

Conclusion

3D QTI demonstrated comprehensive tissue assessment of tumor substructures captured in T1 and T2 parameters. Aiming for fast acquisition of quantitative MR biomarkers, 3D QTI has potential to improve disease characterization in brain tumor patients under tight clinical time-constraints.

Combining Magnetic Resonance Imaging with Systemic Monocyte Evaluation for the Implementation of GBM Management

Magnetic resonance imaging (MRI) is the gold standard for glioblastoma (GBM) patient evaluation. Additional non-invasive diagnostic modalities are needed. GBM is heavily infiltrated with tumor-associated macrophages (TAMs) that can be found in peripheral blood. FKBP51s supports alternative-macrophage polarization. Herein, we assessed FKBP51s expression in circulating monocytes from 14 GBM patients. The M2 monocyte phenotype was investigated by qPCR and flow cytometry using antibodies against PD-L1, CD163, FKBP51s, and CD14. MRI assessed morphologic features of the tumors that were aligned to flow cytometry data. PD-L1 expression on circulating monocytes correlated with MRI tumor necrosis score. A wider expansion in circulating CD163/monocytes was measured. These monocytes resulted in a dramatic decrease in patients with an MRI diagnosis of complete but not partial surgical removal of the tumor. Importantly, in patients with residual tumor, most of the peripheral monocytes that in the preoperative stage were CD163/FKBP51s- had turned into CD163/FKBP51s+. After Stupp therapy, CD163/FKBP51s+ monocytes were almost absent in a case of pseudoprogression, while two patients with stable or true disease progression showed sustained levels in such circulating monocytes. Our work provides preliminary but meaningful and novel results that deserve to be confirmed in a larger patient cohort, in support of potential usefulness in GBM monitoring of CD163/FKBP51s/CD14 immunophenotype in adjunct to MRI.

Hyperpolarized 13C-glucose magnetic resonance highlights reduced aerobic glycolysis in vivo in infiltrative glioblastoma

Glioblastoma (GBM) is the most aggressive brain tumor type in adults. GBM is heterogeneous, with a compact core lesion surrounded by an invasive tumor front. This front is highly relevant for tumor recurrence but is generally non-detectable using standard imaging techniques. Recent studies demonstrated distinct metabolic profiles of the invasive phenotype in GBM. Magnetic resonance (MR) of hyperpolarized 13C-labeled probes is a rapidly advancing field that provides real-time metabolic information. Here, we applied hyperpolarized 13C-glucose MR to mouse GBM models. Compared to controls, the amount of lactate produced from hyperpolarized glucose was higher in the compact GBM model, consistent with the accepted "Warburg effect". However, the opposite response was observed in models reflecting the invasive zone, with less lactate produced than in controls, implying a reduction in aerobic glycolysis. These striking differences could be used to map the metabolic heterogeneity in GBM and to visualize the infiltrative front of GBM.

The Nomogram of MRI-based Radiomics with Complementary Visual Features by Machine Learning Improves Stratification of Glioblastoma Patients: A Multicenter Study

BACKGROUND

Glioblastomas (GBMs) represent both the most common and the most highly malignant primary brain tumors. The subjective visual imaging features from MRI make it challenging to predict the overall survival (OS) of GBM. Radiomics can quantify image features objectively as an emerging technique. A pragmatic and objective method in the clinic to assess OS is strongly in need.

PURPOSE

To construct a radiomics nomogram to stratify GBM patients into long- vs. short-term survival.

STUDY TYPE

Retrospective.

POPULATION

One-hundred and fifty-eight GBM patients from Brain Tumor Segmentation Challenge 2018 (BRATS2018) were for model construction and 32 GBM patients from the local hospital for external validation.

FIELD STRENGTH/SEQUENCE

1.5 T and 3.0 T MRI Scanners, T₁ WI, T₂ WI, T₂ FLAIR, and contrast-enhanced T₁ WI sequences ASSESSMENT: All patients were divided into long-term or short-term based on a survival of greater or fewer than 12 months. All BRATS2018 subjects were divided into training and test sets, and images were assessed for ependymal and pia mater involvement (EPI) and multifocality by three experienced neuroradiologists. All tumor tissues from multiparametric MRI were fully automatically segmented into three subregions to calculate the radiomic features. Based on the training set, the most powerful radiomic features were selected to constitute radiomic signature.

STATISTICAL TESTS

Receiver operating characteristic (ROC) curve, sensitivity, specificity, and the Hosmer-Lemeshow test.

RESULTS

The nomogram had a survival prediction accuracy of 0.878 and 0.875, a specificity of 0.875 and 0.583, and a sensitivity of 0.704 and 0.833, respectively, in the training and test set. The ROC curve showed the accuracy of the nomogram, radiomic signature, age, and EPI for external validation set were 0.858, 0.826, 0.664, and 0.66 in the validate set, respectively.

DATA CONCLUSION

Radiomics nomogram integrated with radiomic signature, EPI, and age was found to be robust for the stratification of GBM patients into long- vs. short-term survival.

LEVEL OF EVIDENCE

3 TECHNICAL EFFICACY STAGE: 2.

Higher Cho/NAA Ratio in Postoperative Peritumoral Edema Zone Is Associated With Earlier Recurrence of Glioblastoma

Objective: To explore the prognostic significance of metabolic parameters in postoperative peritumoral edema zone (PEZ) of patients with glioblastoma (GBM) based on proton magnetic resonance spectroscopy (MRS).

Methods: The postoperative MRS data of 67 patients with GBM from Beijing Tiantan Hospital were retrospectively reviewed. Metabolite ratios including Cho/NAA, Cho/Cr, and NAA/Cr in both postoperative PEZ and contralateral normal brain region were recorded. Log-rank analysis and Cox regression model were used to identify parameters correlated with progression-free survival (PFS) and overall survival (OS).

Results: Compared with the contralateral normal brain region, postoperative PEZ showed a lower ratio of NAA/Cr (1.20 ± 0.42 vs. 1.81 ± 0.48, P < 0.001), and higher ratios of Cho/Cr and Cho/NAA (1.36 ± 0.44 vs. 1.02 ± 0.27, P < 0.001 and 1.32 ± 0.59 vs. 0.57 ± 0.14, P < 0.001). Both the ratios of Cho/NAA and NAA/Cr were identified as prognostic factors in univariate analysis (P < 0.05), while only Cho/NAA ≥ 1.31 was further confirmed as an independent risk factor for early recurrence in the Cox regression model (P < 0.01). According to the factors of MGMT promoter unmethylation, without radiotherapy and Cho/NAA ≥ 1.31, a prognostic scoring scale for GBM was established, which could divide patients into low-risk, moderate-risk, and high-risk groups. There was a significant difference of survival rate between the three groups (P < 0.001).

Conclusions: Higher Cho/NAA ratio in the postoperative PEZ of GBM predicts earlier recurrence and is associated with poor prognosis. The prognostic scoring scale based on clinical, molecular and metabolic parameters of patients with GBM can help doctors to make more precise prediction of survival time and to adjust therapeutic regimens.

Microarray analysis of aberrant microRNA expression patterns in spinal cord gliomas of different grades

MicroRNAs (miRNAs) are involved in the development of several types of tumor; however, their role in spinal gliomas remains unknown. The present study aimed to identify potentially novel spinal cord gliomas (SCG)-associated miRNAs and to characterize their roles in the development and progression of SCG. miRNA expression levels in low-grade SCG (classed as stage I–II SCG based on the World Health Organization grading system), high-grade SCG (classed as stage IV SCG based on the World Health Organization grading system) and 5 control cases were measured using a miRNA expression microarray. Subsequently, blood samples from the spinal cord of patients with differing grades of SCG were screened for differentially expressed miRNAs (DEmiRNAs). Compared with the control group, 7 upregulated and 36 downregulated miRNAs were identified in the low-grade SCG group and a total of 70 upregulated and 20 downregulated miRNAs were identified in the high-grade SCG group (P≤0.05, fold change >2). Gene Ontology analysis revealed that the regulation of cellular metabolic processes, negative regulation of biological processes and axon guidance were primarily involved. Moreover, pathway analysis showed that the target genes of DEmiRNAs were enriched in tumor-related signaling pathways, such as the MAPK and Wnt signaling pathway. The results suggest that DEmiRNAs in peripheral blood may serve as novel target markers with high specificity and sensitivity for the diagnosis of SCG.

Glutamate Is a Noninvasive Metabolic Biomarker of IDH1-Mutant Glioma Response to Temozolomide Treatment

Although lower grade gliomas are driven by mutations in the isocitrate dehydrogenase 1 (IDH1) gene and are less aggressive than primary glioblastoma, they nonetheless generally recur. IDH1-mutant patients are increasingly being treated with temozolomide, but early detection of response remains a challenge and there is a need for complementary imaging methods to assess response to therapy prior to tumor shrinkage. The goal of this study was to determine the value of magnetic resonance spectroscopy (MRS)-based metabolic changes for detection of response to temozolomide in both genetically engineered and patient-derived mutant IDH1 models. Using 1H MRS in combination with chemometrics identified several metabolic alterations in temozolomide-treated cells, including a significant increase in steady-state glutamate levels. This was confirmed in vivo, where the observed 1H MRS increase in glutamate/glutamine occurred prior to tumor shrinkage. Cells labeled with [1-13C]glucose and [3-13C]glutamine, the principal sources of cellular glutamate, showed that flux to glutamate both from glucose via the tricarboxylic acid cycle and from glutamine were increased following temozolomide treatment. In line with these results, hyperpolarized [5-13C]glutamate produced from [2-13C]pyruvate and hyperpolarized [1-13C]glutamate produced from [1-13C]α-ketoglutarate were significantly higher in temozolomide-treated cells compared with controls. Collectively, our findings identify 1H MRS-detectable elevation of glutamate and hyperpolarized 13C MRS-detectable glutamate production from either pyruvate or α-ketoglutarate as potential translatable metabolic biomarkers of response to temozolomide treatment in mutant IDH1 glioma. SIGNIFICANCE: These findings show that glutamate can be used as a noninvasive, imageable metabolic marker for early assessment of tumor response to temozolomide, with the potential to improve treatment strategies for mutant IDH1 patients.

Deep Learning in Selected Cancers' Image Analysis-A Survey

Deep learning algorithms have become the first choice as an approach to medical image analysis, face recognition, and emotion recognition. In this survey, several deep-learning-based approaches applied to breast cancer, cervical cancer, brain tumor, colon and lung cancers are studied and reviewed. Deep learning has been applied in almost all of the imaging modalities used for cervical and breast cancers and MRIs for the brain tumor. The result of the review process indicated that deep learning methods have achieved state-of-the-art in tumor detection, segmentation, feature extraction and classification. As presented in this paper, the deep learning approaches were used in three different modes that include training from scratch, transfer learning through freezing some layers of the deep learning network and modifying the architecture to reduce the number of parameters existing in the network. Moreover, the application of deep learning to imaging devices for the detection of various cancer cases has been studied by researchers affiliated to academic and medical institutes in economically developed countries; while, the study has not had much attention in Africa despite the dramatic soar of cancer risks in the continent.

Long noncoding RNA LIFR-AS1 suppresses proliferation, migration and invasion and promotes apoptosis through modulating miR-4262/NF-κB pathway in glioma

AIM

This study aimed to explore the role of lncRNA leukemia inhibitory factor receptor antisense RNA 1 (LIFR-AS1) on glioma and its underlying molecular mechanism.

METHODS

The expression of LIFR-AS1 and miR-4262 was detected by quantitative real-time polymerase chain reaction (qRT-RCR) in both glioma tissues and cell lines. Colony formation assay, 5-ethynyl-20-deoxyuridine (EdU) assay, flow cytometry and transwell assay were respectively conducted to detect cell clones, proliferation, apoptosis, migration and invasion. The effect of LIFR-AS1 on the chemoresistance to temozolomide (TMZ) of glioma cells was also analyzed. In addition, dual-luciferase reporter gene assay was performed to evaluate the luciferase activity. The expressions of nuclear factor-κB (NF-κB) p65, p-NF-κB p65 and inhibitor of κBα (IκBα) in glioma cells were measured by western blot.

RESULTS

LIFR-AS1 was lowly expressed and miR-4262 was highly expressed in glioma tissues and cell lines. LIFR-AS1 overexpression inhibited the proliferation, migration and invasion and promoted apoptosis of glioma cells. LIFR-AS1 overexpression also reduced the chemoresistance to TMZ of glioma cells. Moreover, LIFR-AS1 overexpression suppressed the activation of NF-κB signaling pathway in glioma cells. miR-4262 was the target gene of LIFR-AS1. We also found that miR-4262 abrogated the functions of LIFR-AS1 on cell proliferation, apoptosis, migration and invasion of glioma cells in the NF-κB pathway.

CONCLUSION

LIFR-AS1 could suppress the proliferation, migration and invasion and promote the apoptosis through modulating miR-4262/NF-κB pathway in glioma.

D-galactose induces senescence of glioblastoma cells through YAP-CDK6 pathway

Treatment of glioblastoma using radiotherapy and chemotherapy has various outcomes, key among them being cellular senescence. However, the molecular mechanisms of this process remain unclear. In the present study, we tested the ability of D-galactose (D-gal), a reducing sugar, to induce senescence in glioblastoma cells. Following pretreatment with D-gal, glioblastoma cell lines (C6 and U87MG) showed typical characteristics of senescence. These included the reduced cell proliferation, hypertrophic morphology, increased senescence-associated β-galactosidase activity, downregulation of Lamin B1, and upregulation of several senescence-associated genes such as p16, p53, and NF-κB. Furthermore, our results showed that D-gal was more suitable than etoposide (a DNA-damage drug) in inducing senescence of glioblastoma cells. Mechanistically, D-gal inactivated the YAP-CDK6 signaling pathway, while overexpression of YAP or CDK6 could restore D-gal-induced senescence of C6 cells. Finally, metformin, an anti-aging agent, activated the YAP-CDK6 pathway and suppressed D-gal-induced senescence of C6 cells. Taken together, these findings established a new model for analyzing senescence in glioblastoma cells, which occurred through the YAP-CDK6 pathway. This is expected to provide a basis for development of novel therapies for the treatment of glioblastoma.

Radioresistance in Glioblastoma and the Development of Radiosensitizers

Ionizing radiation is a common and effective therapeutic option for the treatment of glioblastoma (GBM). Unfortunately, some GBMs are relatively radioresistant and patients have worse outcomes after radiation treatment. The mechanisms underlying intrinsic radioresistance in GBM has been rigorously investigated over the past several years, but the complex interaction of the cellular molecules and signaling pathways involved in radioresistance remains incompletely defined. A clinically effective radiosensitizer that overcomes radioresistance has yet to be identified. In this review, we discuss the current status of radiation treatment in GBM, including advances in imaging techniques that have facilitated more accurate diagnosis, and the identified mechanisms of GBM radioresistance. In addition, we provide a summary of the candidate GBM radiosensitizers being investigated, including an update of subjects enrolled in clinical trials. Overall, this review highlights the importance of understanding the mechanisms of GBM radioresistance to facilitate the development of effective radiosensitizers.

Near Infrared Fluorescent Nanoplatform for Targeted Intraoperative Resection and Chemotherapeutic Treatment of Glioblastoma

Despite significant efforts to improve glioblastoma multiforme (GBM) treatment, GBM remains one of the most lethal cancers. Effective GBM treatments require sensitive intraoperative tumor visualization and effective postoperative chemotherapeutic delivery. Unfortunately, the diffusive and infiltrating nature of GBM limits the detection of GBM tumors, and current intraoperative visualization methods limit complete tumor resection. In addition, although chemotherapy is often used to eliminate any cancerous tissue remaining after surgery, most chemotherapeutic drugs do not effectively cross the brain-blood barrier (BBB) or enter GBM tumors. As a result, GBM has limited treatment options with high recurrence rates, and methods that improve its complete visualization during surgery and treatment are needed. Herein, we report a fluorescent nanoparticle platform for the near-infrared fluorescence (NIRF)-based tumor boundary visualization and image-guided drug delivery into GBM tumors. Our nanoplatform is based on ferumoxytol (FMX), an FDA-approved magnetic resonance imaging-sensitive superparamagnetic iron oxide nanoparticle, which is conjugated with hepthamethine cyanine (HMC), a NIRF ligand that specifically targets the organic anion transporter polypeptides that are overexpressed in GBM. We have shown that HMC-FMX nanoparticles cross the BBB and selectively accumulate in the tumor using orthotopic GBM mouse models, enabling NIRF-based visualization of infiltrating tumor tissue. In addition, HMC-FMX can encapsulate chemotherapeutic drugs, such as paclitaxel or cisplatin, and deliver these agents into GBM tumors, reducing tumor size and increasing survival. Taken together, these observations indicate that HMC-FMX is a promising nanoprobe for GBM surgical visualization and drug delivery.

Hypoxia, metabolism, and the circadian clock: new links to overcome radiation resistance in high-grade gliomas

Radiotherapy is the cornerstone of treatment of high-grade gliomas (HGGs). It eradicates tumor cells by inducing oxidative stress and subsequent DNA damage. Unfortunately, almost all HGGs recur locally within several months secondary to radioresistance with intricate molecular mechanisms. Therefore, unravelling specific underlying mechanisms of radioresistance is critical to elucidating novel strategies to improve the radiosensitivity of tumor cells, and enhance the efficacy of radiotherapy. This review addresses our current understanding of how hypoxia and the hypoxia-inducible factor 1 (HIF-1) signaling pathway have a profound impact on the response of HGGs to radiotherapy. In addition, intriguing links between hypoxic signaling, circadian rhythms and cell metabolism have been recently discovered, which may provide insights into our fundamental understanding of radioresistance. Cellular pathways involved in the hypoxic response, DNA repair and metabolism can fluctuate over 24-h periods due to circadian regulation. These oscillatory patterns may have consequences for tumor radioresistance. Timing radiotherapy for specific times of the day (chronoradiotherapy) could be beneficial in patients with HGGs and will be discussed.

Perfusion-driven Intravoxel Incoherent Motion (IVIM) MRI in Oncology: Applications, Challenges, and Future Trends

Recent developments in MR hardware and software have allowed a surge of interest in intravoxel incoherent motion (IVIM) MRI in oncology. Beyond diffusion-weighted imaging (and the standard apparent diffusion coefficient mapping most commonly used clinically), IVIM provides information on tissue microcirculation without the need for contrast agents. In oncology, perfusion-driven IVIM MRI has already shown its potential for the differential diagnosis of malignant and benign tumors, as well as for detecting prognostic biomarkers and treatment monitoring. Current developments in IVIM data processing, and its use as a method of scanning patients who cannot receive contrast agents, are expected to increase further utilization. This paper reviews the current applications, challenges, and future trends of perfusion-driven IVIM in oncology.

A comprehensive overview on the molecular biology of human glioma: what the clinician needs to know

The molecular biology of human glioma is a complex and fast-growing field in which basic research needs to meet clinical expectations in terms of anti-tumor efficacy. Although much effort is being done in molecular biology research, significant contribution to the quality of life and overall survival still lacks. The vastness of molecular biology literature makes it virtually impossible for clinicians to keep up to date in the field. This paper reviews some practical concepts regarding glioma tumorigenesis from the clinician's perspective. Five main aspects are discussed: major intracellular signaling pathways involved in glioma formation; genomic, epigenetic and transcriptomic relevant features of glioma; the prognostic and predictive values of molecular markers according to the new WHO classification of glial tumors; the importance of molecular and cellular heterogeneity in glioblastoma, responsible for its therapy resistance; and the interaction between glioma and the immune system, in view of the novel and promising targeted therapies.

Circulating biomarkers in patients with glioblastoma

Gliomas are the most common tumours of the central nervous system and the most aggressive form is glioblastoma (GBM). Despite advances in treatment, patient survival remains low. GBM diagnosis typically relies on imaging techniques and postoperative pathological diagnosis; however, both procedures have their inherent limitations. Imaging modalities cannot differentiate tumour progression from treatment-related changes that mimic progression, known as pseudoprogression, which might lead to misinterpretation of therapy response and delay clinical interventions. In addition to imaging limitations, tissue biopsies are invasive and most of the time cannot be performed over the course of treatment to evaluate 'real-time' tumour dynamics. In an attempt to address these limitations, liquid biopsies have been proposed in the field. Blood sampling is a minimally invasive procedure for a patient to endure and could provide tumoural information to guide therapy. Tumours shed tumoural content, such as circulating tumour cells, cell-free nucleic acids, proteins and extracellular vesicles, into the circulation, and these biomarkers are reported to cross the blood-brain barrier. The use of liquid biopsies is emerging in the field of GBM. In this review, we aim to summarise the current literature on circulating biomarkers, namely circulating tumour cells, circulating tumour DNA and extracellular vesicles as potential non-invasively sampled biomarkers to manage the treatment of patients with GBM.

Prediction of survival and progression in glioblastoma patients using temporal perfusion changes during radiochemotherapy

BACKGROUND

The aim of this study was to investigate changes in structural magnetic resonance imaging (MRI) according to the RANO criteria and perfusion- and permeability related metrics derived from dynamic contrast-enhanced MRI (DCE) and dynamic susceptibility contrast MRI (DSC) during radiochemotherapy for prediction of progression and survival in glioblastoma.

METHODS

Twenty-three glioblastoma patients underwent biweekly structural and perfusion MRI before, during, and two weeks after a six weeks course of radiochemotherapy. Temporal trends of tumor volume and the perfusion-derived parameters cerebral blood volume (CBV) and blood flow (CBF) from DSC and DCE, in addition to contrast agent capillary transfer constant (K^trans) from DCE, were assessed. The patients were separated in two groups by median survival and differences between the two groups explored. Clinical- and MRI metrics were investigated using univariate and multivariate survival analysis and a predictive survival index was generated.

RESULTS

Median survival was 19.2 months. A significant decrease in contrast-enhancing tumor size and CBV and CBF in both DCE- and DSC-derived parameters was seen during and two weeks past radiochemotherapy (p < 0.05). A 10%/30% increase in K^trans/CBF two weeks after finishing radiochemotherapy resulted in significant shorter survival (13.9/16.8 vs. 31.5/33.1 months; p < 0.05). Multivariate analysis revealed an index using change in K^trans and relative CBV from DSC significantly corresponding with survival time in months (r² = 0.843; p < 0.001).

CONCLUSIONS

Significant temporal changes are evident during radiochemotherapy in tumor size (after two weeks) and perfusion-weighted MRI-derived parameters (after four weeks) in glioblastoma patients. While DCE-based metrics showed most promise for early survival prediction, a multiparametric combination of both DCE- and DSC-derived metrics gave additional information.

Management of Glioblastoma, Present and Future

Glioblastomas are the most common malignant brain tumor and despite extensive research have a dismal prognosis. This review focuses on the current treatment paradigms of glioblastoma and highlights current advances in surgical approaches, imaging techniques, molecular diagnostics, and translational efforts. Several promising clinical trials in immunotherapy and personalized medicine are discussed and the importance of quality of life in the patients and their caregivers both during active treatment and survivorship is also commented on.

The Impact of MRI Features and Observer Confidence on the Treatment Decision-Making for Patients with Untreated Glioma

In a blind, dual-center, multi-observer setting, we here identify the pre-treatment radiologic features by Magnetic Resonance Imaging (MRI) associated with subsequent treatment options in patients with glioma. Study included 220 previously untreated adult patients from two institutions (94 + 126 patients) with a histopathologically confirmed diagnosis of glioma after surgery. Using a blind, cross-institutional and randomized setup, four expert neuroradiologists recorded radiologic features, suggested glioma grade and corresponding confidence. The radiologic features were scored using the Visually AcceSAble Rembrandt Images (VASARI) standard. Results were retrospectively compared to patient treatment outcomes. Our findings show that patients receiving a biopsy or a subtotal resection were more likely to have a tumor with pathological MRI-signal (by T2-weighted Fluid-Attenuated Inversion Recovery) crossing the midline (Hazard Ratio; HR = 1.30 [1.21–1.87], P < 0.001), and those receiving a biopsy sampling more often had multifocal lesions (HR = 1.30 [1.16–1.64], P < 0.001). For low-grade gliomas (N = 50), low observer confidence in the radiographic readings was associated with less chance of a total resection (P = 0.002) and correlated with the use of a more comprehensive adjuvant treatment protocol (Spearman = 0.48, P < 0.001). This study may serve as a guide to the treating physician by identifying the key radiologic determinants most likely to influence the treatment decision-making process.

DGCR8/ZFAT-AS1 Promotes CDX2 Transcription in a PRC2 Complex-Dependent Manner to Facilitate the Malignant Biological Behavior of Glioma Cells

Studies have found that RNA-binding proteins (RBPs) and long non-coding RNAs (lncRNAs) are dysregulated and play an important regulatory role in the development of tumors. Based on The Cancer Genome Atlas (TCGA) database, our findings from experiments, and the evidence of previous studies, we screened DiGeorge syndrome critical region gene 8 (DGCR8), ZFAT antisense RNA 1 (ZFAT-AS1), and caudal type homeobox 2 (CDX2) as research candidates. In the present study, DGCR8 and CDX2 were highly expressed and ZFAT-AS1 was markedly downregulated in glioma tissues and cells. DGCR8 or CDX2 knockdown or ZFAT-AS1 overexpression suppressed glioma cell proliferation, migration, and invasion and facilitated apoptosis. DGCR8 might decrease ZFAT-AS1 expression by attenuating its stability in a manner of inducing its cleavage. Importantly, ZFAT-AS1 could inhibit CDX2 transcription by mediating the methylation of histone H3 on lysine 27 (H3K27me3) modification induced by PRC2 in the CDX2 promoter region. In addition, CDX2 transcriptionally activated DGCR8 expression by binding to its promoter regions, forming a positive feedback loop of DGCR8/ZFAT-AS1/CDX2. In conclusion, DGCR8/ZFAT-AS1 promotes CDX2 transcription in a PRC2 complex-dependent manner to facilitate the malignant biological behavior of glioma cells.

Accelerated whole-brain perfusion imaging using a simultaneous multislice spin-echo and gradient-echo sequence with joint virtual coil reconstruction

PURPOSE

Dynamic susceptibility contrast imaging requires high temporal sampling, which poses limits on achievable spatial coverage and resolution. Additionally, more encoding-intensive multi-echo acquisitions for quantitative imaging are desired to mitigate contrast leakage effects, which further limits spatial encoding. We present an accelerated sequence that provides whole-brain coverage at an improved spatio-temporal resolution, to allow for dynamic quantitative R2 and R2 * mapping during contrast-enhanced imaging.

METHODS

A multi-echo spin and gradient-echo sequence was implemented with simultaneous multislice acquisition. Complementary k-space sampling between repetitions and joint virtual coil reconstruction were used along with a dynamic phase-matching technique to achieve high-quality reconstruction at 9-fold acceleration, which enabled 2 × 2 × 5 mm whole-brain imaging at TR of 1.5 to 1.7 seconds. The multi-echo images from this sequence were fit to achieve quantitative R2 and R2 * maps for each repetition, and subsequently used to find perfusion measures including cerebral blood flow and cerebral blood volume.

RESULTS

Images reconstructed using joint virtual coil show improved image quality and g-factor compared with conventional reconstruction methods, resulting in improved quantitative maps with a 9-fold acceleration factor and whole-brain coverage during the dynamic perfusion acquisition.

CONCLUSION

The method presented shows the advantage of using a joint virtual coil-GRAPPA reconstruction to allow for high acceleration factors while maintaining reliable image quality for quantitative perfusion mapping, with the potential to improve tumor diagnostics and monitoring.

Increased Antiangiogenic Effect by Blocking CCL2-dependent Macrophages in a Rodent Glioblastoma Model: Correlation Study with Dynamic Susceptibility Contrast Perfusion MRI

When glioblastoma multiforme (GBM) is treated with anti-vascular endothelial growth factor (VEGF) agents, it commonly exhibits tumor progression due to the development of resistance, which results in a dismal survival rate. GBM tumors contain a large number of monocytes/macrophages, which have been shown to be resistant to the effects of bevacizumab. It has been reported that tumor-associated macrophages (TAMs) promote resistance to bevacizumab treatment. Therefore, it is important to target TAMs in the GBM microenvironment. TAMs, which depend on chemokine ligand 2 (CCL2) for differentiation and survival, induce the expression of proangiogenic factors such as VEGF. Dynamic susceptibility contrast (DSC)-MR imaging is an advanced technique that provides information on tumor blood volume and can potentially predict the response to several treatments, including anti-angiogenic agents such as bevacizumab, in human GBM. In this study, we used a CCL2 inhibitor, mNOX-E36, to suppress the recruitment of TAMs in a CCL2-expressing rat GBM model and investigated the effect of combination therapy with bevacizumab using DSC-MR imaging. We demonstrated that the inhibition of CCL2 blocked macrophage recruitment and angiogenesis, which resulted in decreased tumor volume and blood volume in CCL2-expressing GBM in a rat model. Our results provide direct evidence that CCL2 expression can increase the resistance to bevacizumab, which can be assessed noninvasively with the DSC-MR imaging technique. This study shows that the suppression of CCL2 can play an important role in increasing the efficacy of anti-angiogenic treatment in GBM by inhibiting the recruitment of CCL2-dependent macrophages.