Economic implications of the modern treatment paradigm of glioblastoma: an analysis of global cost estimates and their utility for cost assessment

Pharmaceutical equivalent 5-aminolevulinic acid fluorescence guided resection of central nervous system tumors: feasibility, safeness and cost-benefit considerations

PURPOSE

5-aminolevulinic acid (5-ALA) fluorescence-guided resection (FGR) has been an essential tool in the 'standard of care' of malignant gliomas. Over the last two decades, its indications have been extended to other neoplasms, such as metastases and meningiomas. However, its availability and cost-benefit still pose a challenge for widespread use. The present article reports a retrospective series of 707 cases of central nervous system (CNS) tumors submitted to FGR with pharmacological equivalent 5-ALA and discusses financial implications, feasibility and safeness.

METHODS

From December 2015 to February 2024, a retrospective single institution series of 707 cases of 5-ALA FGR were analyzed. Age, gender, 5-ALA dosage, intraoperative fluorescence finding, diagnosis and adverse effects were recorded. Financial impact in the surgical treatment cost were also reported.

RESULTS

there was an additional cost estimated in $300 dollars for each case, increasing from 2,37 to 3,28% of the total hospitalization cost. There were 19 (2,69%) cases of asymptomatic photosensitive reaction and 2 (0,28%) cases of photosensitive reaction requiring symptomatic treatment. 1 (0,14%) patient had a cutaneous rash sustained for up to 10 days. No other complications related to the method were evident. In 3 (0,42%) cases of patients with intracranial hypertension, there was vomiting after administration.

CONCLUSION

FGR with pharmacological equivalent 5-ALA can be considered safe and efficient and incorporates a small increase in hospital expenses. It constitutes a reliable solution in avoiding prohibitive costs worldwide, especially in countries where commercial 5-ALA is unavailable.

A tale of two tumors: differential, but detrimental, effects of glioblastoma extracellular vesicles (EVs) on normal human brain cells

Glioblastomas (GBMs) are dreadful brain tumors with abysmal survival outcomes. GBM EVs dramatically affect normal brain cells (largely astrocytes) constituting the tumor microenvironment (TME). EVs from different patient-derived GBM spheroids induced differential transcriptomic, secretomic, and proteomic effects on cultured astrocytes/brain tissue slices as GBM EV recipients. The net outcome of brain cell differential changes nonetheless converges on increased tumorigenicity. GBM spheroids and brain slices were derived from neurosurgical patient tissues following informed consent. Astrocytes were commercially obtained. EVs were isolated from conditioned culture media by ultrafiltration, ultraconcentration, and ultracentrifugation. EVs were characterized by nanoparticle tracking analysis, electron microscopy, biochemical markers, and proteomics. Astrocytes/brain tissues were treated with GBM EVs before downstream analyses. EVs from different GBMs induced brain cells to alter secretomes with pro-inflammatory or TME-modifying (proteolytic) effects. Astrocyte responses ranged from anti-viral gene/protein expression and cytokine release to altered extracellular signal-regulated protein kinase (ERK1/2) signaling pathways, and conditioned media from EV-treated cells increased GBM cell proliferation. Thus, astrocytes/brain slices treated with different GBM EVs underwent non-identical changes in various 'omics readouts and other assays, indicating "personalized" tumor-specific GBM EV effects on the TME. This raises concern regarding reliance on "model" systems as a sole basis for translational direction. Nonetheless, net downstream impacts from differential cellular and TME effects still led to increased tumorigenic capacities for the different GBMs.

Neurooncological Rehabilitation in Diffuse Gliomas

BACKGROUND

With the further advancement of surgical technology and modern tumor-targeted treatment strategies, longer survival rates can be achieved in diffuse gliomas. Pre- and post-therapeutic physical and cognitive deficits are frequently associated with gliomas. The clinical impact of physical therapy and rehabilitation on neurooncological disorders has not been analyzed consecutively. This study investigates the clinical effect of rehabilitation in patients with diffuse gliomas.

METHODS

Patients with surgically and radio-/oncologically treated diffuse gliomas were recruited into this study. They were admitted to an inpatient program for three weeks. The patients underwent physical and occupational therapy, exercise programs, and psychooncological support. The outcome measures included motor strength, mobility, neuropsychological deficits, and tumor localization-dependent symptoms for the statistical determination and comparison of the respective Eastern Cooperative Oncology Group (ECOG) scores on admission and discharge by a two-tailed t-test.

RESULTS

A total of 25 patients (f/m: 11/14) with diffuse gliomas were recruited into the program. Four patients (16%) had CNS WHO grade 2, seven patients (28%) had grade 3, and 14 patients (56%) had grade 4 tumors. Major improvement in motor, cognitive, and functions of the daily activities was achieved in the examined population. Major improvement in motor, cognitive, and neurological functions of the daily activities screened in the admission of all patients was achieved. The comparison of the ECOG scores determined on admission and on discharge showed a statistical significance derived from the undertaken t-test with a p-value <0.05.

CONCLUSION

We herein show that a clearly defined inpatient rehabilitation protocol significantly enables the improvement of the quality of life of patients with diffuse gliomas. The effectiveness of the exercise program and psychooncological assistance was confirmed by the course of patient-reported functions. Based on the limited number of our patient collective, multicenter studies with broader patient sizes should be performed to confirm our significant results.

High costs, low quality of life, reduced survival, and room for improving treatment: an analysis of burden and unmet needs in glioma

Gliomas are a group of heterogeneous tumors that account for substantial morbidity, mortality, and costs to patients and healthcare systems globally. Survival varies considerably by grade, histology, biomarkers, and genetic alterations such as IDH mutations and MGMT promoter methylation, and treatment, but is poor for some grades and histologies, with many patients with glioblastoma surviving less than a year from diagnosis. The present review provides an introduction to glioma, including its classification, epidemiology, economic and humanistic burden, as well as treatment options. Another focus is on treatment recommendations for IDH-mutant astrocytoma, IDH-mutant oligodendroglioma, and glioblastoma, which were synthesized from recent guidelines. While recommendations are nuanced and reflect the complexity of the disease, maximum safe resection is typically the first step in treatment, followed by radiotherapy and/or chemotherapy using temozolomide or procarbazine, lomustine, and vincristine. Immunotherapies and targeted therapies currently have only a limited role due to disappointing clinical trial results, including in recurrent glioblastoma, for which the nitrosourea lomustine remains the de facto standard of care. The lack of treatment options is compounded by frequently suboptimal clinical practice, in which patients do not receive adequate therapy after resection, including delayed, shortened, or discontinued radiotherapy and chemotherapy courses due to treatment side effects. These unmet needs will require significant efforts to address, including a continued search for novel treatment options, increased awareness of clinical guidelines, improved toxicity management for chemotherapy, and the generation of additional and more robust clinical and health economic evidence.

Intraoperative ultrasound for surgical resection of high-grade glioma and glioblastoma: a meta-analysis of 732 patients

PURPOSE

Here, we conducted a meta-analysis to explore the use of intraoperative ultrasound (iUS)-guided resection in patients diagnosed with high-grade glioma (HGG) or glioblastoma (GBM). Our aim was to determine whether iUS improves clinical outcomes compared to conventional neuronavigation (CNN).

METHODS

Databases were searched until April 21, 2023 for randomized controlled trials (RCTs) and observational cohort studies that compared surgical outcomes for patients with HGG or GBM with the use of either iUS in addition to standard approach or CNN. The primary outcome was overall survival (OS). Secondary outcomes include volumetric extent of resection (EOR), gross total resection (GTR), and progression-free survival (PFS). Outcomes were analyzed by determining pooled relative risk ratios (RR), mean difference (MD), and standardized mean difference (SMD) using random-effects model.

RESULTS

Of the initial 867 articles, only 7 articles specifically met the inclusion criteria (1 RCT and 6 retrospective cohorts). The analysis included 732 patients. Compared to CNN, the use of iUS was associated with higher OS (SMD = 0.26,95%CI=[0.12,0.39]) and GTR (RR = 2.02; 95% CI=[1.31,3.1]) for both HGG and GBM. There was no significant difference in PFS or EOR.

CONCLUSION

The use of iUS in surgical resections for HGG and GBM can improve OS and GTR compared to CNN, but it did not affect PFS. These results suggest that iUS reduces mortality associated with HGG and GBM but not the risk of recurrence. These results can provide valuable cost-effective interventions for neurosurgeons in HGG and GBM surgery.

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.

Regulation of cancer stem cells and immunotherapy of glioblastoma (Review)

Glioblastoma (GB) is one of the most adverse diagnoses in oncology. Complex current treatment results in a median survival of 15 months. Resistance to treatment is associated with the presence of cancer stem cells (CSCs). The present review aimed to analyze the mechanisms of CSC plasticity, showing the particular role of β-catenin in regulating vital functions of CSCs, and to describe the molecular mechanisms of Wnt-independent increase of β-catenin levels, which is influenced by the local microenvironment of CSCs. The present review also analyzed the reasons for the low effectiveness of using medication in the regulation of CSCs, and proposed the development of immunotherapy scenarios with tumor cell vaccines, containing heterogenous cancer cells able of producing a multidirectional antineoplastic immune response. Additionally, the possibility of managing lymphopenia by transplanting hematopoietic stem cells from a healthy sibling and using clofazimine or other repurposed drugs that reduce β-catenin concentration in CSCs was discussed in the present study.

The Role of Progranulin (PGRN) in the Pathogenesis of Glioblastoma Multiforme

Glioblastoma multiforme (GBM) represents the most common and aggressive malignant form of brain tumour in adults and is characterized by an extremely poor prognosis with dismal survival rates. Currently, expanding concepts concerning the pathophysiology of GBM are inextricably linked with neuroinflammatory phenomena. On account of this fact, the identification of novel pathomechanisms targeting neuroinflammation seems to be crucial in terms of yielding successful individual therapeutic strategies. In recent years, the pleiotropic growth factor progranulin (PGRN) has attracted significant attention in the neuroscience and oncological community regarding its neuroimmunomodulatory and oncogenic functions. This review of the literature summarizes and updates contemporary knowledge about PGRN, its associated receptors and signalling pathway involvement in GBM pathogenesis, indicating possible cellular and molecular mechanisms with potential diagnostic, prognostic and therapeutic targets in order to yield successful individual therapeutic strategies. After a review of the literature, we found that there are possible PGRN-targeted therapeutic approaches for implementation in GBM treatment algorithms both in preclinical and future clinical studies. Furthermore, PGRN-targeted therapies exerted their highest efficacy in combination with other established chemotherapeutic agents, such as temozolomide. The results of the analysis suggested that the possible implementation of routine determinations of PGRN and its associated receptors in tumour tissue and biofluids could serve as a diagnostic and prognostic biomarker of GBM. Furthermore, promising preclinical applications of PGRN-related findings should be investigated in clinical studies in order to create new diagnostic and therapeutic algorithms for GBM treatment.

Protein structuromics: A new method for protein structure-function crosstalk in glioma

Glioma is a type of tumor that starts in the glial cells of the brain or spine. Since the 1800s, when the disease was first named, its survival rates have always been unsatisfactory. Despite great advances in molecular biology and traditional treatment methods, many questions regarding cancer occurrence and the underlying mechanism remain to be answered. In this study, we assessed the protein structural features of 20 oncogenes and 20 anti-oncogenes via protein structure and dynamic analysis methods and 3D structural and systematic analyses of the structure-function relationships of proteins. All of these results directly indicate that unfavorable group proteins show more complex structures than favorable group proteins. As the tumor cell microenvironment changes, the balance of oncogene-related and anti-oncogene-related proteins is disrupted, and most of the structures of the two groups of proteins will be disrupted. However, more unfavorable group proteins will maintain and refold to achieve their correct shape faster and perform their functions more quickly than favorable group proteins, and the former thus support cancer development. We hope that these analyses will help promote mechanistic research and the development of new treatments for glioma.

A retrospective analysis of practical benefits and caveats of the new WHO 2021 central nervous system tumor classification scheme in low-resource settings: "A perspective from low- and middle-income countries"

The revised classification of tumors of the central nervous system (CNS) by the World Health Organization (WHO) in 2021 was hailed as a major advance and improvement in the management of brain tumor patients. However, the increased reliance on sophisticated technology and molecular analysis posed a major challenge to healthcare systems in low- and middle-income countries. A few recent publications have drawn attention to the issue of the applicability of the new CNS WHO 2021 worldwide, but the exuberant enthusiasm observed in high-income countries seems to have stifled such a concern. In this study, we present data on the practical utility of the changes that occurred in CNS WHO 2021 in four institutions with limited resources. Our findings demonstrate no major alterations in patient management in low resource settings and significant added financial impact. While there is no doubt that the revised classification provides greater insight into tumor biology and molecular/genetic features of CNS tumors, its practical benefit and applicability in the majority of cases worldwide are limited, and attempts to improve its utility in low resource settings are warranted.

Characterization of tumor microenvironment in glioblastoma multiforme identifies ITGB2 as a key immune and stromal related regulator in glial cell types

Glioblastoma multiforme (GBM) is the most aggressive form of brain tumor characterized by inter and intra-tumor heterogeneity and complex tumor microenvironment. To uncover the molecular targets in this milieu, we systematically identified immune and stromal interactions at the glial cell type level that leverages on RNA-sequencing data of GBM patients from The Cancer Genome Atlas. The perturbed genes between the high vs low immune and stromal scored patients were subjected to weighted gene co-expression network analysis to identify the glial cell type specific networks in immune and stromal infiltrated patients. The intramodular connectivity analysis identified the highly connected genes in each module. Combining it with univariable and multivariable prognostic analysis revealed common vital gene ITGB2, between the immune and stromal infiltrated patients enriched in microglia and newly formed oligodendrocytes. We found following unique hub genes in immune infiltrated patients; COL6A3 (microglia), ITGAM (oligodendrocyte precursor cells), TNFSF9 (microglia), and in stromal infiltrated patients, SERPINE1 (microglia) and THBS1 (newly formed oligodendrocytes, oligodendrocyte precursor cells). To validate these hub genes, we used external GBM patient single cell RNA-sequencing dataset and this identified ITGB2 to be significantly enriched in microglia, newly formed oligodendrocytes, T-cells, macrophages and adipocyte cell types in both immune and stromal datasets. The tumor infiltration analysis of ITGB2 showed that it is correlated with myeloid dendritic cells, macrophages, monocytes, neutrophils, B-cells, fibroblasts and adipocytes. Overall, the systematic screening of tumor microenvironment components at glial cell types uncovered ITGB2 as a potential target in primary GBM.

Uncertainty quantification and attention-aware fusion guided multi-modal MR brain tumor segmentation

Brain tumor is one of the most aggressive cancers in the world, accurate brain tumor segmentation plays a critical role in clinical diagnosis and treatment planning. Although deep learning models have presented remarkable success in medical segmentation, they can only obtain the segmentation map without capturing the segmentation uncertainty. To achieve accurate and safe clinical results, it is necessary to produce extra uncertainty maps to assist the subsequent segmentation revision. To this end, we propose to exploit the uncertainty quantification in the deep learning model and apply it to multi-modal brain tumor segmentation. In addition, we develop an effective attention-aware multi-modal fusion method to learn the complimentary feature information from the multiple MR modalities. First, a multi-encoder-based 3D U-Net is proposed to obtain the initial segmentation results. Then, an estimated Bayesian model is presented to measure the uncertainty of the initial segmentation results. Finally, the obtained uncertainty maps are integrated into a deep learning-based segmentation network, serving as an additional constraint information to further refine the segmentation results. The proposed network is evaluated on publicly available BraTS 2018 and BraTS 2019 datasets. The experimental results demonstrate that the proposed method outperforms the previous state-of-the-art methods on Dice score, Hausdorff distance and Sensitivity metrics. Furthermore, the proposed components could be easily applied to other network architectures and other computer vision fields.

A literature survey of MR-based brain tumor segmentation with missing modalities

Multimodal MR brain tumor segmentation is one of the hottest issues in the community of medical image processing. However, acquiring the complete set of MR modalities is not always possible in clinical practice, due to the acquisition protocols, image corruption, scanner availability, scanning cost or allergies to certain contrast materials. The missing information can cause some restraints to brain tumor diagnosis, monitoring, treatment planning and prognosis. Thus, it is highly desirable to develop brain tumor segmentation methods to address the missing modalities problem. Based on the recent advancements, in this review, we provide a detailed analysis of the missing modality issue in MR-based brain tumor segmentation. First, we briefly introduce the biomedical background concerning brain tumor, MR imaging techniques, and the current challenges in brain tumor segmentation. Then, we provide a taxonomy of the state-of-the-art methods with five categories, namely, image synthesis-based method, latent feature space-based model, multi-source correlation-based method, knowledge distillation-based method, and domain adaptation-based method. In addition, the principles, architectures, benefits and limitations are elaborated in each method. Following that, the corresponding datasets and widely used evaluation metrics are described. Finally, we analyze the current challenges and provide a prospect for future development trends. This review aims to provide readers with a thorough knowledge of the recent contributions in the field of brain tumor segmentation with missing modalities and suggest potential future directions.

Reduced time to imaging, length of stay, and hospital charges following implementation of a novel postoperative pathway for craniotomy

OBJECTIVE

The authors created a postoperative postanesthesia care unit (PACU) pathway to bypass routine intensive care unit (ICU) admissions of patients undergoing routine craniotomies, to improve ICU resource utilization and reduce overall hospital costs and lengths of stay while maintaining quality of care and patient satisfaction. In the present study, the authors evaluated this novel PACU-to-floor clinical pathway for a subset of patients undergoing craniotomy with a case time under 5 hours and blood loss under 500 ml.

METHODS

A single-institution retrospective cohort study was performed to compare 202 patients enrolled in the PACU-to-floor pathway and 193 historical controls who would have met pathway inclusion criteria. The pathway cohort consisted of all adult supratentorial brain tumor cases from the second half of January 2021 to the end of January 2022 that met the study inclusion criteria. Control cases were selected from the beginning of January 2020 to halfway through January 2021. The authors also discuss common themes of similar previously published pathways and the logistical and clinical barriers overcome for successful PACU pathway implementation.

RESULTS

Pathway enrollees had a median age of 61 years (IQR 49-69 years) and 53% were female. Age, sex, pathology, and American Society of Anesthesiologists physical status distributions were similar between pathway and control patients (p > 0.05). Most of the pathway cases (96%) were performed on weekdays, and 31% had start times before noon. Nineteen percent of pathway patients had 30-day readmissions, most frequently for headache (16%) and syncope (10%), whereas 18% of control patients had 30-day readmissions (p = 0.897). The average time to MRI was 6 hours faster for pathway patients (p < 0.001) and the time to inpatient physical therapy and/or occupational therapy evaluation was 4.1 hours faster (p = 0.046). The average total length of stay was 0.7 days shorter for pathway patients (p = 0.02). A home discharge occurred in 86% of pathway cases compared to 81% of controls (p = 0.225). The average total hospitalization charges were $13,448 lower for pathway patients, representing a 7.4% decrease (p = 0.0012, adjusted model). Seven pathway cases were escalated to the ICU postoperatively because of attending physician preference (2 cases), agitation (1 case), and new postoperative neurological deficits (4 cases), resulting in a 96.5% rate of successful discharge from the pathway. In bypassing the ICU, critical care resource utilization was improved by releasing 0.95 ICU days per patient, or 185 ICU days across the cohort.

CONCLUSIONS

The featured PACU-to-floor pathway reduces the stay of postoperative craniotomy patients and does not increase the risk of early hospital readmission.

Personalised therapeutic approaches to glioblastoma: A systematic review

Introduction

Glioblastoma is the most common and malignant primary brain tumour with median survival of 14.6 months. Personalised medicine aims to improve survival by targeting individualised patient characteristics. However, a major limitation has been application of targeted therapies in a non-personalised manner without biomarker enrichment. This has risked therapies being discounted without fair and rigorous evaluation. The objective was therefore to synthesise the current evidence on survival efficacy of personalised therapies in glioblastoma.

Methods

Studies reporting a survival outcome in human adults with supratentorial glioblastoma were eligible. PRISMA guidelines were followed. MEDLINE, Embase, Scopus, Web of Science and the Cochrane Library were searched to 5th May 2022. Clinicaltrials.gov was searched to 25th May 2022. Reference lists were hand-searched. Duplicate title/abstract screening, data extraction and risk of bias assessments were conducted. A quantitative synthesis is presented.

Results

A total of 102 trials were included: 16 were randomised and 41 studied newly diagnosed patients. Of 5,527 included patients, 59.4% were male and mean age was 53.7 years. More than 20 types of personalised therapy were included: targeted molecular therapies were the most studied (33.3%, 34/102), followed by autologous dendritic cell vaccines (32.4%, 33/102) and autologous tumour vaccines (10.8%, 11/102). There was no consistent evidence for survival efficacy of any personalised therapy.

Conclusion

Personalised glioblastoma therapies remain of unproven survival benefit. Evidence is inconsistent with high risk of bias. Nonetheless, encouraging results in some trials provide reason for optimism. Future focus should address target-enriched trials, combination therapies, longitudinal biomarker monitoring and standardised reporting.

An economic study of neuro-oncological patients in a large developing country: a cost analysis

BACKGROUND

Neuro-oncological patients require specialized medical care. However, the data on the costs incurred for such specialized care in developing countries are currently lacking. These data are relevant for international cooperation.

OBJECTIVE

The present study aimed to estimate the direct cost of specialized care for an adult neuro-oncological patient with meningioma or glioma during hospitalization in the largest philanthropic hospital in Latin America.

METHODS

The present observational economic analysis describes the direct cost of care of neuro-oncological patients in Santa Casa de São Paulo, Brazil. Only adult patients with a common primary brain tumor were included.

RESULTS

Due to differences in the system records, the period analyzed for cost estimation was between December 2016 and December 2019. A group of patients with meningiomas and gliomas was analyzed. The estimated mean cost of neurosurgical hospitalization was US$4,166. The cost of the operating room and intensive care unit represented the largest proportion of the total cost. A total of 17.5% of patients had some type of infection, and 66.67% of these occurred in nonelective procedures. The mortality rate was 12.7% and 92.3% of all deaths occurred in emergency procedures.

CONCLUSIONS

Emergency surgeries were associated with an increased rate of infections and mortality. The findings of the present study could be used by policymakers for resource allocation and to perform economic analyses to establish the value of neurosurgery in achieving global health goals.

Cost Matrix of Molecular Pathology in Glioma-Towards AI-Driven Rational Molecular Testing and Precision Care for the Future

Gliomas are the most common and aggressive primary brain tumors. Gliomas carry a poor prognosis because of the tumor's resistance to radiation and chemotherapy leading to nearly universal recurrence. Recent advances in large-scale genomic research have allowed for the development of more targeted therapies to treat glioma. While precision medicine can target specific molecular features in glioma, targeted therapies are often not feasible due to the lack of actionable markers and the high cost of molecular testing. This review summarizes the clinically relevant molecular features in glioma and the current cost of care for glioma patients, focusing on the molecular markers and meaningful clinical features that are linked to clinical outcomes and have a realistic possibility of being measured, which is a promising direction for precision medicine using artificial intelligence approaches.

H2B gene family: A prognostic biomarker and correlates with immune infiltration in glioma

The current prognosis of glioma is unfavorable and effective treatments remain limited. However, bioinformatics has created new opportunities for improving glioma treatment. Research indicates that H2B is involved in the pathological process of cancer. Thus, this study conducted bioinformatic analyses of the H2B gene family to evaluate whether these genes can play a role in predicting prognosis and are associated with immune infiltration. High expression of H2B genes was observed in cholangiocarcinoma, esophageal carcinoma, glioblastoma multiforme (GBM), head and neck squamous cell carcinoma, and other cancers. In addition, a rise in H2B gene expression was correlated with an increase in glioma grade. In the Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA) database and multiple datasets from the Gene Expression Omnibus (GEO), high expression of H2B gene family members predicted poor prognosis of a variety of tumors including glioma. In particular, high H2BC5, H2BC9, H2BC11, and H2BC21 expression was associated with poor glioma prognosis. H2BC9, H2BC11, and H2BC12 expression were also positively correlated with both immune and stromal scores. Enrichment analysis indicated that H2B family genes may be involved in the pathological process of glioma using various pathways including the cell cycle and immune response. H2B-specific siRNAs were used to verify the role of H2BC5, H2BC9, H2BC11, and H2BC21 expression on cell cycle distribution. In summary, H2BC5, H2BC9, H2BC11, and H2BC21 were independent prognostic indicators of glioma, and H2BC9 and H2BC11 may correlate with tumor immunity.

An artificial intelligence framework and its bias for brain tumor segmentation: A narrative review

BACKGROUND

Artificial intelligence (AI) has become a prominent technique for medical diagnosis and represents an essential role in detecting brain tumors. Although AI-based models are widely used in brain lesion segmentation (BLS), understanding their effectiveness is challenging due to their complexity and diversity. Several reviews on brain tumor segmentation are available, but none of them describe a link between the threats due to risk-of-bias (RoB) in AI and its architectures. In our review, we focused on linking RoB and different AI-based architectural Cluster in popular DL framework. Further, due to variance in these designs and input data types in medical imaging, it is necessary to present a narrative review considering all facets of BLS.

APPROACH

The proposed study uses a PRISMA strategy based on 75 relevant studies found by searching PubMed, Scopus, and Google Scholar. Based on the architectural evolution, DL studies were subsequently categorized into four classes: convolutional neural network (CNN)-based, encoder-decoder (ED)-based, transfer learning (TL)-based, and hybrid DL (HDL)-based architectures. These studies were then analyzed considering 32 AI attributes, with clusters including AI architecture, imaging modalities, hyper-parameters, performance evaluation metrics, and clinical evaluation. Then, after these studies were scored for all attributes, a composite score was computed, normalized, and ranked. Thereafter, a bias cutoff (AP(ai)Bias 1.0, AtheroPoint, Roseville, CA, USA) was established to detect low-, moderate- and high-bias studies.

CONCLUSION

The four classes of architectures, from best-to worst-performing, are TL > ED > CNN > HDL. ED-based models had the lowest AI bias for BLS. This study presents a set of three primary and six secondary recommendations for lowering the RoB.

Neuroscience20 (BRAIN20, SPINE20, and MENTAL20) Health Initiative: A Global Consortium Addressing the Human and Economic Burden of Brain, Spine, and Mental Disorders Through Neurotech Innovations and Policies

Neurological disorders significantly impact the world's economy due to their often chronic and life-threatening nature afflicting individuals which, in turn, creates a global disease burden. The Group of Twenty (G20) member nations, which represent the largest economies globally, should come together to formulate a plan on how to overcome this burden. The Neuroscience-20 (N20) initiative of the Society for Brain Mapping and Therapeutics (SBMT) is at the vanguard of this global collaboration to comprehensively raise awareness about brain, spine, and mental disorders worldwide. This paper aims to provide a comprehensive review of the various brain initiatives worldwide and highlight the need for cooperation and recommend ways to bring down costs associated with the discovery and treatment of neurological disorders. Our systematic search revealed that the cost of neurological and psychiatric disorders to the world economy by 2030 is roughly $16T. The cost to the economy of the United States is $1.5T annually and growing given the impact of COVID-19. We also discovered there is a shortfall of effective collaboration between nations and a lack of resources in developing countries. Current statistical analyses on the cost of neurological disorders to the world economy strongly suggest that there is a great need for investment in neurotechnology and innovation or fast-tracking therapeutics and diagnostics to curb these costs. During the current COVID-19 pandemic, SBMT, through this paper, intends to showcase the importance of worldwide collaborations to reduce the population's economic and health burden, specifically regarding neurological/brain, spine, and mental disorders.