SEOM clinical guideline of diagnosis and management of low-grade glioma (2017)

Differential Diagnosis of Early-Stage Atypical Primary Central Nervous System Lymphoma and Low-Grade Glioma Using Magnetic Resonance Imaging-Based Radiomics

BACKGROUND

Different from typical primary central nervous system lymphoma (PCNSL), early-stage atypical PCNSL usually presents as patchy signal abnormalities without evident mass effect or significant contrast enhancement and is prone to confusion with low-grade glioma (LGG). This study aims to develop a magnetic resonance imaging (MRI)-based radiomics model to differentiate early-stage atypical PCNSL from LGG.

METHODS

Two cohorts consisting of early-stage atypical PCNSL patients, as well as LGG patients with similar radiological manifestations, were retrospectively recruited from West China Hospital of Sichuan University (PCNSL = 75; LGG = 138) and Chengdu Shangjin Nanfu Hospital (PCNSL = 35; LGG = 72) to serve as the training set and external validation set, respectively. Within the training set, there were additional early-stage atypical lesions from 19 typical or advanced-stage PCNSL patients included as a supplement. MRI-based radiomics models were developed and validated based on these 2 cohorts.

RESULTS

Nine radiomic features were selected as significant features, most of which are wavelet radiomic features. The best radiomics model achieved an area under the curve of 0.929 (0.901-0.957) and an accuracy of 91.6% on the independent external validation set. The inclusion of 19 additional PCNSL patients improved the model's performance.

CONCLUSIONS

The MRI-based radiomics model can accurately differentiate early-stage atypical PCNSL from LGG with similar radiological manifestations, allowing early-stage atypical PCNSL patients to receive timely and appropriate radiotherapy or chemotherapy while avoiding unnecessary surgical resection.

Completely non-invasive prediction of IDH mutation status based on preoperative native CT images

The isocitrate dehydrogenase (IDH) mutation status is one of the most important markers according to the 2021 WHO classification of CNS tumors. Preoperatively, this information is usually obtained based on invasive biopsies, contrast-enhanced MR images or PET images generated using radioactive tracers. However, the completely non-invasive determination of IDH mutation status using routinely acquired preoperative native CT images has hardly been investigated to date. In our study, we show that radiomics-based machine learning allows to determine IDH mutation status based on preoperative native CT images both with very high accuracy and completely non-invasively. Based on independent test data, we are able to correctly identify 91.1% of cases with an IDH mutation. Our final model, containing only six features, exhibits a high area under the curve of 0.847 and an excellent area under the precision-recall curve of 0.945. In the future, such models may be used for a completely non-invasive prediction of important genetic markers, potentially allowing treating physicians to reduce the number of biopsies and speed up further treatment planning.

Retinal Microstructural Changes Reflecting Treatment-Associated Cognitive Dysfunction in Patients with Lower-Grade Gliomas

Purpose

To determine whether microstructural retinal changes, tumor features, and apolipoprotein E (APOE) ε4 polymorphism are correlated with clinically detectable treatment-associated cognitive dysfunction (TACD) in patients with lower-grade gliomas.

Design

Cohort study.

Participants and Controls

Sixteen patients with lower-grade glioma at a United States academic ophthalmology department between January 2021 and November 2023. Normal controls were recruited from convenient sampling.

Methods

Montreal Cognitive Assessment (MoCA) scores and retinal changes were assessed in 6-month intervals. Apolipoprotein E genotyping was performed, and tumor details were recorded. Partial least-squares discriminant (PLSD) model was established to evaluate the association between TACD with APOE genotype, ophthalmic, and tumor features.

Main Outcome Measures

The main outcome measure was cognitive status as measured by the MoCA score and analyzed in relation to ophthalmic measurements, tumor features, and APOE genotype.

Results

Median time to first eye examination was 34 months (2-266) from tumor diagnosis and 23 months (0-246) from radiation. Nine patients (56%) had abnormal cognition (MoCA <26/30). Montreal Cognitive Assessment scores were significantly worse in patients with temporal (22 ± 7.2) than frontal lobe tumors (26 ± 3.1, P = 0.02) and those with oligodendrogliomas (22 ± 4.1) than astrocytomas (26 ± 3.6, = 0.02). Patients with TACD had significant radial peripapillary capillary density loss (45% ± 4.6) compared with those with normal cognition (49% ± 2.6, P = 0.02). A PLSD model correlated MoCA scores with retinal nerve fiber thickness, intraocular pressure, foveal avascular zone, best-corrected visual acuity, months since first diagnosis, and tumor pathology (oligodendroglioma or not). Using these features, the model identified patients with TACD with 77% accuracy. Apolipoprotein E genotyping showed: 2 ε2/ε3 (13%), 10 ε3/ε3 (63%), and 1 ε3/ε4 (6%).

Conclusions

Retinal microstructural changes may serve as biomarkers for TACD in patients with lower-grade gliomas. Temporal lobe tumors and oligodendrogliomas may increase susceptibility to TACD. Utilization of retinal markers may enhance TACD diagnosis, progression monitoring, and inform management of lower-grade patients with glioma. A larger study with serial eye examinations is warranted to evaluate the role of APOE ε4 and develop a predictive model.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

2023 Beijing Health Data Science Summit

The 5th annual Beijing Health Data Science Summit, organized by the National Institute of Health Data Science at Peking University, recently concluded with resounding success. This year, the summit aimed to foster collaboration among researchers, practitioners, and stakeholders in the field of health data science to advance the use of data for better health outcomes. One significant highlight of this year's summit was the introduction of the Abstract Competition, organized by Health Data Science, a Science Partner Journal, which focused on the use of cutting-edge data science methodologies, particularly the application of artificial intelligence in the healthcare scenarios. The competition provided a platform for researchers to showcase their groundbreaking work and innovations. In total, the summit received 61 abstract submissions. Following a rigorous evaluation process by the Abstract Review Committee, eight exceptional abstracts were selected to compete in the final round and give presentations in the Abstract Competition. The winners of the Abstract Competition are as follows:•First Prize: "Interpretable Machine Learning for Predicting Outcomes of Childhood Kawasaki Disease: Electronic Health Record Analysis" presented by researchers from the Chinese Academy of Medical Sciences, Peking Union Medical College, and Chongqing Medical University (presenter Yifan Duan).•Second Prize: "Survival Disparities among Mobility Patterns of Patients with Cancer: A Population-Based Study" presented by a team from Peking University (presenter Fengyu Wen).•Third Prize: "Deep Learning-Based Real-Time Predictive Model for the Development of Acute Stroke" presented by researchers from Beijing Tiantan Hospital (presenter Lan Lan). We extend our heartfelt gratitude to the esteemed panel of judges whose expertise and dedication ensured the fairness and quality of the competition. The judging panel included Jiebo Luo from the University of Rochester (chair), Shenda Hong from Peking University, Xiaozhong Liu from Worcester Polytechnic Institute, Liu Yang from Hong Kong Baptist University, Ma Jianzhu from Tsinghua University, Ting Ma from Harbin Institute of Technology, and Jian Tang from Mila-Quebec Artificial Intelligence Institute. We wish to convey our deep appreciation to Zixuan He and Haoyang Hong for their invaluable assistance in the meticulous planning and execution of the event. As the 2023 Beijing Health Data Science Summit comes to a close, we look forward to welcoming all participants to join us in 2024. Together, we will continue to advance the frontiers of health data science and work toward a healthier future for all.

Brain Tumor Imaging without Gadolinium-based Contrast Agents: Feasible or Fantasy?

Gadolinium-based contrast agents (GBCAs) form the cornerstone of current primary brain tumor MRI protocols at all stages of the patient journey. Though an imperfect measure of tumor grade, GBCAs are repeatedly used for diagnosis and monitoring. In practice, however, radiologists will encounter situations where GBCA injection is not needed or of doubtful benefit. Reducing GBCA administration could improve the patient burden of (repeated) imaging (especially in vulnerable patient groups, such as children), minimize risks of putative side effects, and benefit costs, logistics, and the environmental footprint. On the basis of the current literature, imaging strategies to reduce GBCA exposure for pediatric and adult patients with primary brain tumors will be reviewed. Early postoperative MRI and fixed-interval imaging of gliomas are examples of GBCA exposure with uncertain survival benefits. Half-dose GBCAs for gliomas and T2-weighted imaging alone for meningiomas are among options to reduce GBCA use. While most imaging guidelines recommend using GBCAs at all stages of diagnosis and treatment, non-contrast-enhanced sequences, such as the arterial spin labeling, have shown a great potential. Artificial intelligence methods to generate synthetic postcontrast images from decreased-dose or non-GBCA scans have shown promise to replace GBCA-dependent approaches. This review is focused on pediatric and adult gliomas and meningiomas. Special attention is paid to the quality and real-life applicability of the reviewed literature.

Assessing the methodological strengths and limitations of the Spanish Society of Medical Oncology (SEOM) guidelines: a critical appraisal using AGREE II and AGREE-REX tool

BACKGROUND

The Spanish Society of Medical Oncology (SEOM) has provided open-access guidelines for cancer since 2014. However, no independent assessment of their quality has been conducted to date. This study aimed to critically evaluate the quality of SEOM guidelines on cancer treatment.

METHODS

Appraisal of Guidelines for Research and Evaluation II (AGREE II) and AGREE-REX tool was used to evaluate the qualities of the guidelines.

RESULTS

We assessed 33 guidelines, with 84.8% rated as "high quality". The highest median standardized scores (96.3) were observed in the domain "clarity of presentation", whereas "applicability" was distinctively low (31.4), with only one guideline scoring above 60%. SEOM guidelines did not include the views and preferences of the target population, nor did specify updating methods.

CONCLUSIONS

Although developed with acceptable methodological rigor, SEOM guidelines could be improved in the future, particularly in terms of clinical applicability and patient perspectives.

Low grade gliomas guide-lines elaborated by the tumor section of Spanish Society of Neurosurgery

Adult low-grade gliomas (Low Grade Gliomas, LGG) are tumors that originate from the glial cells of the brain and whose management involves great controversy, starting from the diagnosis, to the treatment and subsequent follow-up. For this reason, the Tumor Group of the Spanish Society of Neurosurgery (GT-SENEC) has held a consensus meeting, in which the most relevant neurosurgical issues have been discussed, reaching recommendations based on the best scientific evidence. In order to obtain the maximum benefit from these treatments, an individualised assessment of each patient should be made by a multidisciplinary team. Experts in each LGG treatment field have briefly described it based in their experience and the reviewed of the literature. Each area has been summarized and focused on the best published evidence. LGG have been surrounded by treatment controversy, although during the last years more accurate data has been published in order to reach treatment consensus. Neurosurgeons must know treatment options, indications and risks to participate actively in the decision making and to offer the best surgical treatment in every case.

Benign and Malignant Tumors of the Pineal Region

Pineal region tumors fall into five broad categories: benign pineal region tumors, glial tumors, papillary tumors, pineal parenchymal tumors, and germ cell tumors. Genetic and transcriptional studies have identified key chromosomal alterations in germinomas (RUNDC3A, ASAH1, LPL) and in pineocytomas/pineoblastomas (DROSHA/DICER1, RB1). Pineal region tumors generally present with symptoms of hydrocephalus including nausea, vomiting, papilledema, and the classical Parinaud's triad of upgaze paralysis, convergence-retraction nystagmus, and light-near pupillary dissociation. Workup requires neuroimaging and tissue diagnosis via biopsy. In germinoma cases, diagnosis may be made based on serum or CSF studies for alpha-fetoprotein or beta-HCG making the preferred treatment radiosurgery, thereby preventing the need for unnecessary surgeries. Treatment generally involves three steps: CSF diversion in cases of hydrocephalus, biopsy through endoscopic or stereotactic methods, and open surgical resection. Multiple surgical approaches are possible for approach to the pineal region. The original approach to the pineal region was the interhemispheric transcallosal first described by Dandy. The most common approach is the supracerebellar infratentorial approach as it utilizes a natural anatomic corridor for access to the pineal region. The paramedian or lateral supracerebellar infratentorial approach is another improvement that uses a similar anatomic corridor but allows for preservation of midline bridging veins; this minimizes the chance for brainstem or cerebellar venous infarction. Determination of the optimal approach relies on tumor characteristics, namely location of deep venous structures to the tumor along with the lateral eccentricity of the tumor. The immediate post-operative period is important as hemorrhage or swelling can cause obstructive hydrocephalus and lead to rapid deterioration. Adjuvant therapy, whether chemotherapy or radiation, is based on tumor pathology. Improvements within pineal surgery will require improved technology for access to the pineal region along with targeted therapies that can effectively treat and prevent recurrence of malignant pineal region tumors.

Benign Glioma

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

Predictors of tumor progression of low-grade glioma in adult patients within 5 years follow-up after surgery

Background

Glioma originates from glial cells in the brain and is the most common primary intracranial tumor. This study intends to use a retrospective analysis to explore the factors that can predict tumor progression in adult low-grade gliomas, namely WHO II grade patients, within 5 years after surgery.

Methods

Patients with WHO grade II glioma who were surgically treated in our hospital from February 2011 to May 2017 were included. According to the inclusion and exclusion criteria, 252 patients were included in the final analysis. According to the results of the 5-year follow-up (including survival and imaging review results), patients were divided into progression-free group and progression group. Univariate and multivariate analysis were conducted to investigate the related factors of tumor progression during the 5-year follow-up.

Results

The results of the 5-year follow-up showed that 111 (44.0%) cases had no progress (progression free group, PFG), 141 (56.0%) cases had progress (progression group, PG), of which 43 (30.5%) cases were operated again, 37 cases (26.2%) received non-surgical treatments. There were 26 (10.3%) all-cause deaths, and 21 (8.3%) tumor-related deaths. Univariate and multivariate analysis showed that age >45 years old (OR = 1.35, 95% CI, 1.07-3.19, P = 0.027), partial tumor resection (OR = 1.66, 95% CI, 1.15-3.64, P = 0.031), tumor diameter >3 cm (OR = 1.52, 95% CI, 1.14-4.06, P = 0.017) and no radiotherapy (OR = 1.37, 95% CI, 1.12-2.44, P = 0.039) were independent predictors of the progression of tumor during the 5-year follow-up period.

Conclusion

Age >45 years old, partial tumor resection, tumor diameter >3 cm, no radiotherapy are predictors for tumor progression for glioma patients after surgery.

Molecular Characterization of IDH Wild-type Diffuse Astrocytomas: The Potential of cIMPACT-NOW Guidelines

IDH wild-type (wt) grade 2/3 astrocytomas are a heterogenous group of tumors with disparate clinical and molecular profiles. cIMPACT-NOW recommendations incorporated in the new 2021 World Health Organization (WHO) Classification of Central Nervous System (CNS) Tumors urge minimal molecular criteria to identify a subset that has an aggressive clinical course similar to IDH -wt glioblastomas (GBMs). This paper describes the use of a panel of molecular markers to reclassify IDH -wt grade 2/3 diffuse astrocytic gliomas (DAGs) and study median overall survival concerning for to IDH -wt GBMs in the Indian cohort. IDH -wt astrocytic gliomas (grades 2, 3, and 4) confirmed by IDHR132H immunohistochemistry and IDH1/2 gene sequencing, 1p/19q non-codeleted with no H3F3A mutations were included. TERT promoter mutation by Sanger sequencing, epidermal growth factor receptor amplification, and whole chromosome 7 gain and chromosome 10 loss by fluorescence in situ hybridization was assessed and findings correlated with clinical and demographic profiles. The molecular profile of 53 IDH -wt DAGs (grade 2: 31, grade 3: 22) was analyzed. Eleven cases (grade 2: 8, grade 3: 3) (20.75%) were reclassified as IDH -wt GBMs, WHO grade 4 ( TERT promoter mutation in 17%, epidermal growth factor receptor amplification in 5.5%, and whole chromosome 7 gain and chromosome 10 loss in 2%). Molecular GBMs were predominantly frontal (54.5%) with a mean age of 36 years and median overall survival equivalent to IDH -wt GBMs (18 vs. 19 mo; P =0.235). Among grade 2/3 DAGs not harboring these alterations, significantly better survival was observed for grade 2 versus grade 3 DAGs (25 vs. 16 mo; P =0.002). Through the incorporation of a panel of molecular markers, a subset of IDH -wt grade 2 DAGs can be stratified into molecular grade 4 tumors with prognostic and therapeutic implications. However, IDH -wt grade 3 DAGs behave like GBMs irrespective of molecular profile.

A Single-Center, Randomized, Double-Blind Study of 94 Patients Undergoing Surgery for Cerebral Glioma to Compare Postoperative Thromboprophylaxis with and without Rivaroxaban

Background

Venous thrombosis (VTE) is a common adverse event among inpatients, which can cause pulmonary embolism, and greatly increases mortality. The effects of rivaroxaban in patients undergoing brain glioma surgery have still not been explored. This single-center study of 94 patients undergoing surgery for cerebral glioma aimed to compare postoperative thromboprophylaxis with and without rivaroxaban.

Material/Methods

We designed a randomized, controlled, double-blind study to evaluate the effect of rivaroxaban on 94 patients undergoing brain glioma surgery. These patients were divided into a rivaroxaban group (administered at 10 mg per day from admission to discharge) and a placebo group. The primary study endpoint was incidence of VTE at discharge. The secondary endpoints included safety outcomes of major bleeding, allergy, or VTE-related death.

Results

A total of 94 patients were enrolled in the study: 47 in the rivaroxaban group and 47 in the placebo group. Baseline characteristics of participants were well-matched in both groups. A significant reduction was found in the incidence of VTE in the rivaroxaban treatment group versus the placebo group (1/47 vs 10/47 patients, P=0.008). The rate of major bleeding events was quite low in both group (1/47 vs 1/47 patients). One patient in the placebo group died due to a pulmonary embolism and intractable concomitant underlying diseases.

Conclusions

Our results indicate that treatment with rivaroxaban is a safe and effective thromboprophylaxis treatment in patients undergoing surgery for malignant cerebral glioma.

What matters for people with brain cancer? Selecting clinical quality indicators for an Australian Brain Cancer Registry

BACKGROUND

The goal of a clinical quality registry is to deliver immediate gains in survival and quality of life by delivering timely feedback to practitioners, thereby ensuring every patient receives the best existing treatment. We are developing an Australian Brain Cancer Registry (ABCR) to identify, describe, and measure the impact of the variation and gaps in brain cancer care from the time of diagnosis to the end of life.

METHODS

To determine a set of clinical quality indicators (CQIs) for the ABCR, a database and internet search were used to identify relevant guidelines, which were then assessed for quality using the AGREE II Global Rating Scale. Potential indicators were extracted from 21 clinical guidelines, ranked using a modified Delphi process completed in 2 rounds by a panel of experts and other stakeholders, and refined by a multidisciplinary Working Group.

RESULTS

Nineteen key quality reporting domains were chosen, specified by 57 CQIs detailing the specific inclusion and outcome characteristics to be reported.

CONCLUSION

The selected CQIs will form the basis for the ABCR, provide a framework for achievable data collection, and specify best practices for patients and health care providers, with a view to improving care for brain cancer patients. To our knowledge, the systematic and comprehensive approach we have taken is a world first in selecting the reporting specifications for a brain cancer clinical registry.

Dynamic susceptibility contrast and diffusion-weighted MRI in posterior fossa pilocytic astrocytoma and medulloblastoma

BACKGROUND AND PURPOSE

The utility of perfusion MRI in distinguishing between pilocytic astrocytoma (PA) and medulloblastoma (MB) is unclear. This study aimed to evaluate the diagnostic and prognostic performance of dynamic susceptibility contrast (DSC)-MRI parameters and apparent diffusion coefficient (ADC) values between PA and MB.

METHODS

Between January 2012 and August 2021, 49 (median, 7 years [range, 1-28 years]; 28 females) and 35 (median, 8 years [1-24 years]; 12 females) patients with pathologically confirmed PA and MB, respectively, were included. The normalized relative cerebral blood volume and flow (nrCBV and nrCBF) and mean and minimal normalized ADC (nADCmean and nADCmin) values were calculated using volume-of-interest analyses. Diagnostic performance and Pearson's correlation with progression-free survival were also evaluated.

RESULTS

The MB group showed a significantly higher nrCBV and nrCBF (nrCBV: 1.69 [0.93-4.23] vs. 0.95 [range, 0.37-2.28], p = .0032; nrCBF: 1.62 [0.93-3.16] vs. 1.07 [0.46-2.26], p = .0084) and significantly lower nADCmean and nADCmin (nADCmean: 0.97 [0.70-1.68] vs. 2.21 [1.44-2.80], p < .001; nADCmin: 0.50 [0.19-0.89] vs. 1.42 [0.89-2.20], p < .001) than the PA group. All parameters exhibited good diagnostic ability (accuracy >0.80) with nADCmin achieving the highest score (accuracy = 1). A moderate correlation was found between nADCmean and progression-free survival for MB (r = 0.44, p = .0084).

CONCLUSIONS

DSC-MRI parameters and ADC values were useful for distinguishing between PA and MB. A lower ADC indicated an unfavorable MB prognosis, but the DSC-MRI parameters did not correlate with progression-free survival in either group.

Online database for brain cancer-implicated genes: exploring the subtype-specific mechanisms of brain cancer

Background

Brain cancer is one of the eight most common cancers occurring in people aged 40+ and is the fifth-leading cause of cancer-related deaths for males aged 40–59. Accurate subtype identification is crucial for precise therapeutic treatment, which largely depends on understanding the biological pathways and regulatory mechanisms associated with different brain cancer subtypes. Unfortunately, the subtype-implicated genes that have been identified are scattered in thousands of published studies. So, systematic literature curation and cross-validation could provide a solid base for comparative genetic studies about major subtypes.

Results

Here, we constructed a literature-based brain cancer gene database (BCGene). In the current release, we have a collection of 1421 unique human genes gathered through an extensive manual examination of over 6000 PubMed abstracts. We comprehensively annotated those curated genes to facilitate biological pathway identification, cancer genomic comparison, and differential expression analysis in various anatomical brain regions. By curating cancer subtypes from the literature, our database provides a basis for exploring the common and unique genetic mechanisms among 40 brain cancer subtypes. By further prioritizing the relative importance of those curated genes in the development of brain cancer, we identified 33 top-ranked genes with evidence mentioned only once in the literature, which were significantly associated with survival rates in a combined dataset of 2997 brain cancer cases.

Conclusion

BCGene provides a useful tool for exploring the genetic mechanisms of and gene priorities in brain cancer. BCGene is freely available to academic users at http://soft.bioinfo-minzhao.org/bcgene/.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07793-x.

Genomic Prognosticators and Extent of Resection in Molecularly Subtyped World Health Organization Grade II and III Gliomas-A Single-Institution, Nine-Year Data

BACKGROUND

World Health Organization (WHO) grade II and III isocitrate dehydrogenase wild-type (IDH-wt) gliomas are often treated as WHO grade IV glioblastomas. However, cumulative evidence indicates that IDH mutation status alone is insufficient in predicting survival. The current study examines molecular and clinical markers to further prognostically stratify WHO grade II and III gliomas, in particular, IDH-wt.

METHODS

A single institution's records were retrospectively reviewed for molecularly stratified WHO grade II and grade III gliomas over a 9-year period (2010-2019). Clinical data, IDH1/IDH2 status, EGFR amplification, and other molecular markers were recorded and correlated to the study outcomes. These outcomes were defined as progression-free survival (PFS), overall survival (OS), and time to malignant progression (TtMP).

RESULTS

A total of 167 and 42 WHO grade II and III gliomas, respectively, were identified, totaling 209 cases with 157 IDH1/2 mutated and 52 IDH-wt tumors. The presence of IDH1/2 mutation was associated with longer OS (P < 0.0001) and PFS (P < 0.0001) but not with TtMP (P = 0.314). Lack of EGFR amplification, younger age, and greater extent of resection (EOR) (≥80%) were identified as independent, favorable OS prognostic factors. In the IDH-wt cohort, multivariate analysis indicated that older age (P = 0.003) and lesser EOR (<80%) (P = 0.007) are associated with worse OS. In addition, EGFR amplification showed a trend toward shorter OS in the IDH-wt cohort (P = 0.073).

CONCLUSIONS

IDH1/2 mutation favors longer OS and PFS but does not protect from malignant progression. Lack of EGFR amplification, younger age and greater EOR are favorable OS prognosticators. In the IDH-wt cohort, older age and lesser EOR were linked to worse OS.

Colen R, Zinn PO. MRI-Based Radiomics and Radiogenomics in the Management of Low-Grade Gliomas: Evaluating the Evidence for a Paradigm Shift

Low-grade gliomas (LGGs) are tumors that affect mostly adults. These neoplasms are comprised mainly of oligodendrogliomas and diffuse astrocytomas. LGGs remain vexing to current management and therapeutic modalities although they exhibit more favorable survival rates compared with high-grade gliomas (HGGs). The specific genetic subtypes that these tumors exhibit result in variable clinical courses and the need to involve multidisciplinary teams of neurologists, epileptologists, neurooncologists and neurosurgeons. Currently, the diagnosis of an LGG pivots mainly around the preliminary radiological findings and the subsequent definitive surgical diagnosis (via surgical sampling). The introduction of radiomics as a high throughput quantitative imaging technique that allows for improved diagnostic, prognostic and predictive indices has created more interest for such techniques in cancer research and especially in neurooncology (MRI-based classification of LGGs, predicting Isocitrate dehydrogenase (IDH) and Telomerase reverse transcriptase (TERT) promoter mutations and predicting LGG associated seizures). Radiogenomics refers to the linkage of imaging findings with the tumor/tissue genomics. Numerous applications of radiomics and radiogenomics have been described in the clinical context and management of LGGs. In this review, we describe the recently published studies discussing the potential application of radiomics and radiogenomics in LGGs. We also highlight the potential pitfalls of the above-mentioned high throughput computerized techniques and, most excitingly, explore the use of machine learning artificial intelligence technologies as standalone and adjunct imaging tools en route to enhance a personalized MRI-based tumor diagnosis and management plan design.

Neural Stem Cell-Based Therapies and Glioblastoma Management: Current Evidence and Clinical Challenges

Gliomas, which account for nearly a quarter of all primary CNS tumors, present significant contemporary therapeutic challenges, particularly the highest-grade variant (glioblastoma multiforme), which has an especially poor prognosis. These difficulties are due to the tumor's aggressiveness and the adverse effects of radio/chemotherapy on the brain. Stem cell therapy is an exciting area of research being explored for several medical issues. Neural stem cells, normally present in the subventricular zone and the hippocampus, preferentially migrate to tumor masses. Thus, they have two main advantages: They can minimize the side effects associated with systemic radio/chemotherapy while simultaneously maximizing drug delivery to the tumor site. Another feature of stem cell therapy is the variety of treatment approaches it allows. Stem cells can be genetically engineered into expressing a wide variety of immunomodulatory substances that can inhibit tumor growth. They can also be used as delivery vehicles for oncolytic viral vectors, which can then be used to combat the tumorous mass. An alternative approach would be to combine stem cells with prodrugs, which can subsequently convert them into the active form upon migration to the tumor mass. As with any therapeutic modality still in its infancy, much of the research regarding their use is primarily based upon knowledge gained from animal studies, and a number of ongoing clinical trials are currently investigating their effectiveness in humans. The aim of this review is to highlight the current state of stem cell therapy in the treatment of gliomas, exploring the different mechanistic approaches, clinical applicability, and the existing limitations.

Radiomics for prediction of survival in lower-grade gliomas-it's time to move beyond the crystal ball

• Radiomics might help predict survival of patients with lower-grade gliomas.

• Several different models using different radiomics features have been proposed with only little overlap in included features.

• Prospective trials and validation studies are needed to establish which models offer clinical benefit and which do not.

MRS as an Aid to Diagnose Malignant Transformation in Low-Grade Gliomas with Increasing Contrast Enhancement

BACKGROUND AND PURPOSE

Increased contrast enhancement has been used as a marker of malignant transformation in low-grade gliomas. This marker has been found to have limited accuracy because many low-grade gliomas with increased contrast enhancement remain grade II. We aimed to investigate whether MR spectroscopy can contribute to the diagnosis of malignant transformation in low-grade gliomas with increased contrast enhancement.

MATERIALS AND METHODS

Patients with low-grade gliomas who had contemporaneous MR spectroscopy and histopathology for tumor regions with increased contrast enhancement between 2004 and 2015 were retrospectively reviewed. Clinical data collected were sex and age, Karnofsky Performance Scale, histologic subtypes, isocitrate dehydrogenase 1 mutation status, disease duration, adjuvant therapy, and post-radiation therapy duration. Imaging data collected were contrast-enhancement size, whole-tumor size, MR spectroscopy metabolite ratios, and tumor grades of regions with increased contrast enhancement. Diagnostic values of these factors on malignant transformation of low-grade gliomas were statistically analyzed.

RESULTS

A total of 86 patients with 96 MR spectroscopy studies were included. Tumor grades associated with increased contrast enhancement were grade II (n = 42), grade III (n = 27), and grade IV (n = 27). On multivariate analysis, the NAA/Cho ratio was the only significant factor (P < .001; OR, 7.1; 95% CI, 3.2-16.1) diagnostic of malignant transformation. With 0.222 as the cutoff value, the sensitivity, specificity, and accuracy of NAA/Cho for diagnosing malignant transformation were 94.4%, 83.3%, and 89.6%, respectively.

CONCLUSIONS

MR spectroscopy complements conventional MR imaging in the diagnosis of malignant transformation in a subgroup of low-grade gliomas with increased contrast enhancement.

Development of a Nomogram With Alternative Splicing Signatures for Predicting the Prognosis of Glioblastoma: A Study Based on Large-Scale Sequencing Data

Purpose: Alternative splicing (AS) was reported to play a vital role in development and progression of glioblastoma (GBM), the most common and fatal brain tumor. Systematic analysis of survival-associated AS event profiles and prognostic prediction model based on multiple AS events in GBM was needed. Methods: Genome-wide AS and RNA sequencing profiles were generated in 152 patients with GBM in the cancer genome atlas (TCGA). Prognosis-associated AS events were screened by integrated Cox regression analysis to construct the prognostic risk score model in the training cohort (n = 101). The AS-based signature and clinicopathologic parameters were applied to construct a prognostic nomogram for 0.5-, 1-, and 3-year OS prediction. Finally, the regulatory networks between prognostic AS events and splicing factors (SFs) were constructed. Results: A total of 1,598 prognosis-related AS events from 1,183 source genes were determined. Eight prognostic risk score model based on integrated AS events and 7 AS types were established, respectively. Concordance index (C-index) and receiver operating characteristic (ROC) curve analysis demonstrated powerful ability in distinguishing patients' outcomes. Only Alternate Donor site (AD) and Exon Skip (ES) signature out of the eight types of AS signature were identified as independent prognostic factors for GBM, which was validated in the internal validation cohort. The nomogram with age, new event, pharmaceutical therapy, radiation therapy, AD signature and ES signature were constructed, with C-index of 0.892 (95% CI, 0.853-0.931; P = 5.13 × 10^-15). Calibration plots, ROC, and decision curve analysis suggested excellent predictive performance for the nomogram in both TCGA training cohort and validation cohort. Splicing network indicated distinguished correlations between prognostic AS events and SFs in GBM patients. Conclusions: AS-based prediction model could serve as a promising prognostic predictor and potential therapeutic target for GBM, facilitating better treatment strategies in clinical practice.

Blockade of Cell Volume Regulatory Protein NKCC1 Increases TMZ-Induced Glioma Apoptosis and Reduces Astrogliosis

Glioma is one of the most common primary malignant tumors of the central nervous system accounting for approximately 40% of all intracranial tumors. Temozolomide is a conventional chemotherapy drug for adjuvant treatment of patients with high-risk gliomas, including grade II to grade IV. Our bioinformatic analysis of The Cancer Genome Atlas and Chinese Glioma Genome Atlas datasets and immunoblotting assay show that SLC12A2 gene and its encoded Na+-K+-2Cl- cotransporter isoform 1 (NKCC1) protein are abundantly expressed in grade II-IV gliomas. NKCC1 regulates cell volume and intracellular Cl- concentration, which promotes glioma cell migration, resistance to temozolomide, and tumor-related epilepsy in experimental glioma models. Using mouse syngeneic glioma models with intracranial transplantation of two different glioma cell lines (GL26 and SB28), we show that NKCC1 protein in glioma tumor cells as well as in tumor-associated reactive astrocytes was significantly upregulated in response to temozolomide monotherapy. Combination therapy of temozolomide with the potent NKCC1 inhibitor bumetanide reduced tumor proliferation, potentiated the cytotoxic effects of temozolomide, decreased tumor-associated reactive astrogliosis, and restored astrocytic GLT-1 and GLAST glutamate transporter expression. The combinatorial therapy also led to suppressed tumor growth and prolonged survival of mice bearing GL26 glioma cells. Taken together, these results demonstrate that NKCC1 protein plays multifaceted roles in the pathogenesis of glioma tumors and presents as a therapeutic target for reducing temozolomide-mediated resistance and tumor-associated astrogliosis.

Deep Learning-Based Concurrent Brain Registration and Tumor Segmentation

Image registration and segmentation are the two most studied problems in medical image analysis. Deep learning algorithms have recently gained a lot of attention due to their success and state-of-the-art results in variety of problems and communities. In this paper, we propose a novel, efficient, and multi-task algorithm that addresses the problems of image registration and brain tumor segmentation jointly. Our method exploits the dependencies between these tasks through a natural coupling of their interdependencies during inference. In particular, the similarity constraints are relaxed within the tumor regions using an efficient and relatively simple formulation. We evaluated the performance of our formulation both quantitatively and qualitatively for registration and segmentation problems on two publicly available datasets (BraTS 2018 and OASIS 3), reporting competitive results with other recent state-of-the-art methods. Moreover, our proposed framework reports significant amelioration (p < 0.005) for the registration performance inside the tumor locations, providing a generic method that does not need any predefined conditions (e.g., absence of abnormalities) about the volumes to be registered. Our implementation is publicly available online at https://github.com/TheoEst/joint_registration_tumor_segmentation.

Development and validation of a nomogram with an autophagy-related gene signature for predicting survival in patients with glioblastoma

Glioblastoma (GBM) is the most common brain tumor with significant morbidity and mortality. Autophagy plays a vital role in GBM development and progression. We aimed to establish an autophagy-related multigene expression signature for individualized prognosis prediction in patients with GBM. Differentially expressed autophagy-related genes (DE-ATGs) in GBM and normal samples were screened using TCGA. Univariate and multivariate Cox regression analyses were performed on DE-ATGs to identify the optimal prognosis-related genes. Consequently, NRG1 (HR=1.142, P=0.008), ITGA3 (HR=1.149, P=0.043), and MAP1LC3A (HR=1.308, P=0.014) were selected to establish the prognostic risk score model and validated in the CGGA validation cohort. GSEA revealed that these genes were mainly enriched in cancer- and autophagy-related KEGG pathways. Kaplan-Meier survival analysis demonstrated that patients with high risk scores had significantly poorer overall survival (OS, log-rank P= 6.955×10^-5). The autophagy signature was identified as an independent prognostic factor. Finally, a prognostic nomogram including the autophagy signature, age, pharmacotherapy, radiotherapy, and IDH mutation status was constructed, and TCGA/CGGA-based calibration plots indicated its excellent predictive performance. The autophagy-related three-gene risk score model could be a prognostic biomarker and suggest therapeutic targets for GBM. The prognostic nomogram could assist individualized survival prediction and improve treatment strategies.

More than hemifacial spasm? A case of unilateral facial spasms with systematic review of red flags

Unilateral facial spasms (UFS) are frequently caused by hemifacial spasm (HFS), a disorder that usually results from vascular loop compression at the root exit zone of the facial nerve. However, UFS can also be a manifestation of other conditions, including brainstem tumours or demyelination, post-Bell's synkinesis, lesions of the facial nerve in the Faloppio canal and the parotid gland, dystonia, epilepsy, psychogenic conditions, tics and hemimasticatory spasm. In this report, we present a case of UFS, not due to HFS, highlighting clinical red flags for an alternative diagnosis. In addition, a systematic review was conducted to provide a comprehensive summary of UFS differential diagnoses with a list of red flags to assist neurologists in the evaluation of patients with UFS.

A Mistaken Diagnosis of Secondary Glioblastoma as Parasitosis

Background: Glioblastoma is a malignant brain tumor with poor prognosis requiring early diagnosis. Secondary glioblastoma refers to cases that progressed from low-grade glioma. Evidence shows that timely resection correlates with increased survival.

Case presentation: We describe a case of a patient with secondary glioblastoma who was mistakenly diagnosed with Angiostrongylus cantonensis infection until 7 years after disease onset. The patient presented with non-specific clinical manifestations at disease onset. A conventional magnetic resonance imaging (MRI) in the primary survey provided insufficient information, and thus failed to identify the malignancy. During follow-up, unfortunately, clinicians were misled by the patient's raw food diet, a positive serum parasite antibody and a result of low glucose metabolism on Fluorodeoxyglucose-positron emission tomography-computed tomography (FDG-PET-CT). The patient was diagnosed with parasitosis. However, his condition kept getting worse under antiparasitic treatment. Preoperative magnetic resonance spectroscopy (MRS) and diffusion tensor imaging (DTI) failed to reverse the mistaken impression. Final diagnosis was confirmed until intraoperative and postoperative pathological findings indicated glioblastoma.

Conclusion: We ascribe the incorrect diagnosis to insufficient understanding on imaging manifestations of brain neoplasm as well as clinical features of parasitosis. Thus, we review the MRI, FDG-PET-CT, MRS, and DTI data of this case according to the timeline, refer to relevant studies, and point out the pitfalls. With a long course of slowly progressing, this was a rare case of secondary glioblastoma with the absence of isocitrate dehydrogenase 1 (IDH1) gene mutation.

Integrated systems-genetic analyses reveal a network target for delaying glioma progression

Objective

To identify a convergent, multitarget proliferation characteristic for astrocytoma transformation that could be targeted for therapy discovery.

Methods

Using an integrated functional genomics approach, we prioritized networks associated with astrocytoma progression using the following criteria: differential co‐expression between grade II and grade III IDH1‐mutated and 1p/19q euploid astrocytomas, preferential enrichment for genetic risk to cancer, association with patient survival and sample‐level genomic features. Drugs targeting the identified multitarget network characteristic for astrocytoma transformation were computationally predicted using drug transcriptional perturbation data and validated using primary human astrocytoma cells.

Results

A single network, M2, consisting of 177 genes, was associated with glioma progression on the basis of the above criteria. Functionally, M2 encoded physically interacting proteins regulating cell cycle processes and analysis of genome‐wide gene‐regulatory interactions using mutual information and DNA–protein interactions revealed the known regulators of cell cycle processes FoxM1, B‐Myb, and E2F2 as key regulators of M2. These results suggest functional disruption of M2 via gene mutation or altered expression as a convergent pathway regulating astrocytoma transformation. By considering M2 as a multitarget drug target regulating astrocytoma transformation, we identified several drugs that are predicted to restore M2 expression in anaplastic astrocytoma toward its low‐grade profile and of these, we validated the known antiproliferative drug resveratrol as down‐regulating multiple nodes of M2 including at nanomolar concentrations achievable in human cerebrospinal fluid by oral dosing.

Interpretation

Our results identify M2 as a multitarget network characteristic for astrocytoma progression and encourage M2‐based drug screening to identify new compounds for preventing glioma transformation.