Diagnosis Of Glioma Research Articles

Preoperative Grading of Brain Gliomas Using 3D-ResNet18 Based on Multimodal MRI and Attention Mechanism

In response to the prevalent challenge of imprecise preoperative glioma grading prediction, a multimodal Magnetic Resonance Imaging (MRI) image with attention mechanism prediction model based on Residual Network (ResNet) is proposed for accurate prediction. To achieve this, publicly accessible datasets from BraTS 2019 and BraTS 2020 were employed. MRI images across three modalities underwent preprocessing, cropping, and subsequent stacking to generate comprehensive multimodal representations. Meanwhile, An Efficient Channel Attention (ECA) mechanism based on 3D data (3D-ECA) is proposed and introduced to reduce the problem of slow network convergence and overfitting. Notably, experiments demonstrate that the 3D-ECA attention mechanism added to the model improves the network training speed and the classification accuracy of the model, and the classification accuracy reached 88.1%, with an impressive area under the subject working characteristic curve of 0.918. Therefore, the 3D-ResNet18 deep learning model, incorporating multimodal MRI and 3D-ECA attention mechanisms, demonstrates high accuracy and robustness in distinguishing between high-grade and low-grade gliomas. Thus, showcasing significant clinical potential for glioma classification and diagnosis.

Research progress on function and mechanism of long non-coding RNA in glioma.

This review aimed to comprehensively summarize the role of long non-coding RNA (lncRNA) in gliomas, the most common malignant tumors in the central nervous system, and explore their potential clinical applications. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, a systematic search using the PubMed database was conducted forty studies met the inclusion and exclusion criteria and were analyzed for type of intervention, the study's design, participants' demographics, and outcomes, including attrition. Gliomas, originating within the central nervous system, account for 40-45% of intracranial tumors. Despite advances in neurosurgical techniques, precise radiotherapy, and chemotherapy, the prognosis for glioma patients remains suboptimal. The review highlights the crucial regulatory role of lncRNA in gliomas. Differential expression of various lncRNAs, such as INHEG, SATB2-AS1, PSMB8-AS1, LINC01018, and SPRY4-IT1, has been observed in gliomas, suggesting their involvement in promoting or inhibiting tumorigenesis. Additionally, lncRNAs play roles in glioma characteristics such as proliferation, invasion, migration, angiogenesis, and the presence of glioma stem cells. The potential clinical applications of lncRNA in gliomas involve their association with tumor grading, diameter, metastasis, and family history. This review emphasizes the importance of understanding the molecular mechanisms involving lncRNA in gliomas. The identification of specific lncRNAs associated with gliomas provides potential molecular markers for diagnosis, differentiation, treatment, and prognosis evaluation. Further research is needed to uncover additional key lncRNAs and their underlying mechanisms, ultimately contributing to the improvement of glioma diagnosis and treatment.

Low-grade glioma of the temporal lobe and tumor-related epilepsy in children.

Low-grade glioma is the most common brain tumor among children and adolescents. When these tumors arise in the temporal lobe, patients frequently present with seizures that are poorly controlled with antiepileptic drugs. Here we summarize the clinical features, pathophysiology, preoperative evaluation, surgical treatment, and outcomes of pediatric patients with low-grade gliomas in the temporal lobe. We reviewed the literature on pediatric low-grade gliomas in the temporal lobe, focusing on cohort studies and systematic reviews that described surgical treatment strategies and reported both oncologic and epilepsy outcomes. The differential diagnoses of pediatric low-grade gliomas in the temporal lobe include ganglioglioma, dysembryoplastic neuroepithelial tumor, desmoplastic infantile ganglioglioma, papillary glioneuronal tumor, pilocytic astrocytoma, pleomorphic xanthoastrocytoma, angiocentric glioma, and polymorphous low-grade neuroepithelial tumor of the young. There is no consensus on the optimal surgical approach for these tumors: lesionectomy alone, or extended lesionectomy with anterior temporal lobectomy, with or without removal of mesial temporal structures. Gross total resection and shorter preoperative duration of epilepsy are strongly associated with favorable seizure outcomes, defined as Engel Class I or Class II, approaching 90% in most series. The risk of surgical complications ranges from 4 to 17%, outweighing the lifetime risks of medically refractory epilepsy. Pediatric patients with temporal low-grade glioma and tumor-related epilepsy are best managed by a multidisciplinary epilepsy surgery team. Early and appropriate surgery leads to prolonged survival and a greater likelihood of seizure freedom, improving their overall quality of life.

The Role of Peripheral Inflammatory Markers and Coagulation Factors in Patients with Central Nervous System (CNS) Immune Disease and Glioma

Gliomas are associated with high rates of disability and mortality, and currently, there is a lack of specific and sensitive biomarkers for diagnosis. The ideal biomarkers should be detected early through noninvasive methods. Our research aims to develop a rapid, convenient, noninvasive diagnostic method for gliomas, as well as for grading and differentiation. We retrospectively collected data from patients who underwent surgery for glioma, trigeminal neuralgia/hemifacial spasmschwannoma, and those diagnosed with multiple sclerosis at our institution from January 2018 to December 2020. Inflammatory markers and coagulation factor levels were collected on admission, and neutrophil count (NLR), (WBC count minus neutrophil count) / lymphocyte count, platelet count / lymphocyte count, lymphocyte count / monocyte count, and albumin count [g/L]+total lymphocyte count× 5 were calculated for patients. Analyze the significance of biomarkers in the diagnosis and grading of gliomas, the diagnosis of MS, and the differential diagnosis of them. We evaluated 155 healthy individuals, 64trigeminal neuralgia/hemifacial spasm patients, 47 MS patients, 316 schwannoma patients, and 814 with glioma patients. Compared with healthy controls and MS group, the preoperative levels of NLR, (WBC count minus neutrophil count) / lymphocyte count, D-dimer, Fibrinogen, Antithrobin, and Factor VIII of glioma patients were significantly higher in glioma patients and positively correlated with the grade of glioma. Conversely, 0020 lymphocyte count / Monocyte count and albumin count [g/L]+total lymphocyte count× 5 were significantly lower and negatively correlated with glioma grading. ROC curves confirmed that for the diagnosis of glioma, NLR showed a maximum area under the curve value of 0.8616 (0.8322-0.8910), followed by D-dimer and Antithrombin, with area under the curve values of 0.8205 (0.7601-0.8809) and 0.8455 (0.8153-0.8758), respectively. NLR and d-dimer also showed great sensitivity in the diagnosis of MS and differential diagnosis with gliomas. Our study demonstrated that multiple inflammatory markers and coagulation factors could be utilized as biomarkers for the glioma diagnosis, grading, and differential diagnosis of MS. Furthermore, the combination of these markers exhibited high sensitivity and specificity.

Quantification of attenuation and speckle features from endoscopic OCT images for the diagnosis of human brain glioma

Application of optical coherence tomography (OCT) in neurosurgery mostly includes the discrimination between intact and malignant tissues aimed at the detection of brain tumor margins. For particular tissue types, the existing approaches demonstrate low performance, which stimulates the further research for their improvement. The analysis of speckle patterns of brain OCT images is proposed to be taken into account for the discrimination between human brain glioma tissue and intact cortex and white matter. The speckle properties provide additional information of tissue structure, which could help to increase the efficiency of tissue differentiation. The wavelet analysis of OCT speckle patterns was applied to extract the power of local brightness fluctuations in speckle and its standard deviation. The speckle properties are analysed together with attenuation ones using a set of ex vivo brain tissue samples, including glioma of different grades. Various combinations of these features are considered to perform linear discriminant analysis for tissue differentiation. The results reveal that it is reasonable to include the local brightness fluctuations at first two wavelet decomposition levels in the analysis of OCT brain images aimed at neurosurgical diagnosis.

THOC6 is a novel biomarker of glioma and a target of anti-glioma drugs: An analysis based on bioinformatics and molecular docking.

Glioma is a typical malignant tumor of the nervous system. It is of great significance to identify new biomarkers for accurate diagnosis of glioma. In this context, THOC6 has been studied as a highly diagnostic prognostic biomarker, which contributes to improve the dilemma in diagnosing gliomas. We used online databases and a variety of statistical methods, such as Wilcoxon rank sum test, Dunn test and t test. We analyzed the mutation, location and expression profile of THOC6, revealing the network of THOC6 interaction with disease. Wilcoxon rank sum test showed that THOC6 is highly expressed in gliomas (P < 0.001). Dunn test, Wilcoxon rank sum test and t test showed that THOC6 expression was correlated with multiple clinical features. Logistic regression analysis further confirmed that THOC6 gene expression was a categorical dependent variable related to clinical features of poor prognosis. Kaplan-Meier survival analysis showed that the overall survival (OS) of glioma patients with high expression of THOC6 was poor (P < 0.001). Both univariate (P < 0.001) and multivariate (P = 0.04) Cox analysis confirmed that THOC6 gene expression was an independent risk factor for OS in patients with glioma. ROC curve analysis showed that THOC6 had a high diagnostic value in glioma (AUC = 0.915). Based on this, we constructed a nomogram to predict patient survival. Enrichment analysis showed that THOC6 expression was associated with multiple signal pathways. Immuno-infiltration analysis showed that the expression of THOC6 in glioma was closely related to the infiltration level of multiple immune cells. Molecular docking results showed that THOC6 might be the target of anti-glioma drugs. THOC6 is a novel diagnostic factor and prognostic biomarker of glioma.

Efficacy of Operative Ultrasonography Plus Neuronavigation for Brain Glioma Surgery: 2 – Year Single Center Experience in a Developing Country

Background: preoperative MRI data has been the gold standard for the diagnosis and therapy of malignant gliomas for decades, and operative ultrasonography for the management of patients with neurological pathologies that require surgical treatment has been also used for many years as it provides additional image guidance for surgical procedure to neuronavigation techniques. The main objective of this study is to find out if the use of operative ultrasonography in glioma surgery could give greater benefit in the total resection of brain gliomas and how improvement influences the degree of neoplastic resection on the survival of patients. Methods: prospective case-control study that was performed at the ISSEMyM Licenciado Arturo Montiel Rojas Medical Center, of patients with a histopathological diagnosis of cerebral glioma treated by the neurosurgery service in the period between January 2018 and December 2020. Results: Thirty - two patients were included, with 13 patients (40.6%) with grade IV astrocytoma. Operative USG + NNV was used in 17 patients and a subtotal or total resection was achieved in 75% of the patients, with a significantly lower postoperative volumetry in patients operated on by NNV + USG (5.6mm3 + 2.5), compared to NNV alone (8mm3 + 2.8) However, these results did not affect tumor-free time, which was comparable between both groups. Conclusions: Surgical treatment of brain gliomas with USG + NNV has a good degree of tumor resection compared to those treated with NNV only, but the main factor affecting survival is the hystophatological grade of the tumor.

Classifying Glioma via Liquid Biopsy: Progress toward an Unmet Clinical Need.

The diagnosis and classification of glioma by liquid biopsy represent a critical unmet need in neuro-oncology. A recent study demonstrates targeted next-generation sequencing of cell-free DNA from cerebrospinal fluid as an evolving option for liquid biopsy in patients with glioma. See related article by Iser et al., p. 2974.

Biomimetic Nanocomposites for Glioma Imaging and Therapy.

Glioma, the most common primary brain tumor, is highly invasive and grows rapidly. As such, the survival of glioma patients is relatively short, highlighting the vital importance of timely diagnosis and treatment of glioma. However, the blood brain barrier (BBB) and the non-targeting delivery systems of contrast agents and drugs greatly hinder the effective glioma imaging and therapy. Fortunately, in recent years, investigators have constructed various biomimetic delivery platforms utilizing the exceptional advantages of biomimetic nanocomposites, such as immune evasion, homologous targeting ability, and BBB penetrating ability, to achieve efficient and precise delivery of substances to glioma sites for improved diagnosis and treatment. In this concept, we present the application of these biomimetic nanocomposites in fluorescence imaging (FI), magnetic resonance imaging (MRI), and multi-modal imaging, as well as in chemotherapy, phototherapy, and combined therapy for glioma. Lastly, we provide our perspective on this research field.

2-Hydroxyglutarate as an MR spectroscopic predictor of an IDH mutation in gliomas.

The mutated enzyme isocitrate dehydrogenase (IDH) 1 and 2 has been detected in various tumor entities such as gliomas and can convert α-ketoglutarate into the oncometabolite 2-hydroxyglutarate (2-HG). This neuro-oncologically significant metabolic product can be detected by MR spectroscopy and is therefore suitable for noninvasive glioma classification and therapy monitoring.This paper provides an up-to-date overview of the methodology and relevance of 1H-MR spectroscopy (MRS) in the oncological primary and follow-up diagnosis of gliomas. The possibilities and limitations of this MR spectroscopic examination are evaluated on the basis of the available literature.By detecting 2-HG, MRS can in principle offer a noninvasive alternative to immunohistological analysis thus avoiding surgical intervention in some cases. However, in addition to an adapted and optimized examination protocol, the individual measurement conditions in the examination region are of decisive importance. Due to the inherently small signal of 2-HG, unfavorable measurement conditions can influence the reliability of detection. · MR spectroscopy enables the non-invasive detection of 2-hydroxyglutarate.. · The measurement of this metabolite allows the detection of an IDH mutation in gliomas.. · The choice of MR examination method is particularly important.. · Detection reliability is influenced by glioma size, necrotic tissue and the existing measurement conditions.. · Bauer J, Raum HN, Kugel H et al. 2-Hydroxyglutarate as an MR spectroscopic predictor of an IDH mutation in gliomas. Fortschr Röntgenstr 2024; DOI 10.1055/a-2285-4923.

Development of a hydrogen peroxide fluorescent probe for the rapid discrimination of IDH1 mutant gliomas from the wild-type

Isocitrate dehydrogenase (IDH) mutations are common in gliomas, and recent studies have suggested that these mutants have distinct microenvironments characterized by higher levels of reactive oxygen species (ROS) and a higher pH. The identification of IDH mutants is important for the diagnosis, individualized treatment, and clinical prognosis of gliomas. Sanger sequencing and immunohistochemistry are the standard methods for IDH mutation detection. As the mutations have several types, the detection of multiple gene sites and proteins are required, which means high cost and tedious operations. The high levels of ROS observed in mutIDH gliomas have not been used for mutIDH detection. Fluorescent probe-based detection techniques have emerged as a prevalent method to detect diverse analytes in living systems due to their distinctive benefits of simple operation, high sensitivity and selectivity, fast response, and real-time applicability. In the present study, we report the rapid discrimination of mutIDH1 from wild-type gliomas using the novel fluorescent probe BOD-G that varies in its fluorescence response to different levels of H2O2. BOD-G exhibits high sensitivity and selectivity in its turn-on response to H2O2, and its performance improves as the pH increases. The probe exhibits a much stronger fluorescence in IDH1 mutant U87 cells than in wild-type U87MG cells after 5 min. Importantly, BOD-G displays a bright fluorescence when exposed to fresh mutIDH1 human glioma specimens after 15 min but not with wild-type samples. Thus, BOD-G can be used to discriminate mutIDH1 from wild-type human glioma specimens rapidly by simple fluorescent imaging.

Diagnosis of Glioma, Menigioma and Pituitary brain tumor using MRI images recognition by Deep learning in Python

Medical image processing is a very difficult and new field. One thing they do in this field is analyze pictures of people's brains to look for signs of tumors. They use a special computer program to help with this. This paper talks about a new way to use the program to find brain cancer early by looking at the texture of the tumor. This paper explains how we can find and understand brain tumors using special pictures called MRI scans. We use computer programs to help us do this. First, we find the tumor, then we separate it from the rest of the brain, and finally we measure how big it is. We can also figure out how serious the tumor is by looking at different kinds of tumors. To make it easier for people to use, we made a special program in a computer language called COLAB for python codes about using CNN network for deep learning. We tested this program on 8 patients and learned a lot about their tumors.

Comparison of MRI findings of hypothalamic-optic chiasmatic gliomas and craniopharyngiomas.

Differential diagnosis of hypothalamic-optic chiasmatic gliomas (HOCGs) and craniopharyngiomas on magnetic resonance imaging (MRI) can be quite challenging. To compare the MRI features of HOCGs and cranipharyngiomas. Patients diagnosed with HOCG or craniopharyngioma in histopathological evaluation between 2012 and 2022 and who underwent preoperative contrast-enhanced brain MRI were included. Various MRI features were retrospectively evaluated for each lesion: T2-weighted imaging and fluid attenuation inversion recovery hyperintensity, calcification, cystic change, T1-weighted (T1W) imaging hyperintensity of the cystic component, hemorrhage, involvement of sellar, suprasellar or other adjacent structures, lobulated appearance, presence of hydrocephalus, and contrast enhancement pattern. Apparent diffusion coefficient (ADC) values were also evaluated and compared. Among 38 patients included, 13 (34%) had HOCG and 25 (66%) had craniopharyngioma. Craniopharyngiomas had a significantly higher rate of cystic changes, calcification, and T1W imaging hyperintensity of the cystic component than HOCGs (P <0.05). Of HOCGs, 92% had chiasm involvement, 23% had optic nerve involvement, and 31% had brain stem involvement. On the other hand, chiasm involvement was observed in 8% of craniopharyngiomas, but none had optic nerve and/or brain stem involvement (P <0.05). While 62% (8/13) of HOCGs had diffuse homogeneous enhancement, 80% (20/25) of craniopharyngiomas had a diffuse heterogeneous enhancement pattern. Mean ADC values were significantly higher in craniopharyngiomas compared to HOCGs (2.1 vs. 1.6 ×10-3mm2/s, P <0.05). Although some neuroimaging findings may overlap, features such as presence of cyst and calcification, brain stem and optic pathway involvement, different enhancement patterns, and ADC values may be helpful in the differential diagnosis of HOCGs and craniopharyngiomas.

Design, Synthesis, and Evaluation of [18F]BIBD-300 as a Positron Emission Tomography Tracer for Poly(ADP-Ribose) Polymerase-1.

Compounds 8a-j were designed to adjust the mode of interaction and lipophilicity of FTT by scaffold hopping and changing the length of the alkoxy groups. Compounds 8a, 8d, 8g, and BIBD-300 were screened for high-affinity PARP-1 through enzyme inhibition assays and are worthy of further evaluation. PET imaging of MCF-7 subcutaneous tumors with moderate expression of PARP-1 showed that compared to [18F]FTT, [18F]8a, [18F]8d, and [18F]8g exhibited greater nonspecific uptake, a lower target-to-nontarget ratio, and severe defluorination, while [18F]BIBD-300 exhibited lower nonspecific uptake and a greater target-to-nontarget ratio. PET imaging of 22Rv1 subcutaneous tumors, which highly express PARP-1, confirmed that the uptake of [18F]BIBD-300 in normal organs, such as the liver, muscle, and bone, was lower than that of [18F]FTT, and the ratio of tumor-to-muscle and tumor-to-liver [18F]BIBD-300 was greater than that of [18F]FTT. The biodistribution results in mice with MCF-7 and 22Rv1 subcutaneous tumors further validated the results of PET imaging. Unlike [18F]FTT, which mainly relies on hepatobiliary clearance, [18F]BIBD-300, which has lower lipophilicity, undergoes a partial shift from hepatobiliary to renal clearance, providing the possibility for [18F]BIBD-300 to indicate liver cancer. The difference in the PET imaging results for [18F]FTT, [18F]BIBD-300, and [18F]8j in 22Rv1 mice and the corresponding molecular docking results further confirmed that subtle structural modifications in lipophilicity greatly optimize the properties of the tracer. Cell uptake experiments also demonstrated that [18F]BIBD-300 has a high affinity for PARP-1. Metabolized and unmetabolized [18F]FTT and [18F]BIBD-300 were detected in the brain, indicating that they could not accurately quantify the amount of PARP-1 in the brain. However, PET imaging of glioma showed that both [18F]FTT and [18F]BIBD-300 could accurately localize both in situ to C6 and U87MG tumors. Based on its potential advantages in the diagnosis of breast cancer, prostate cancer, and glioma, as well as liver cancer, [18F]BIBD-300 is a new option for an excellent PARP-1 tracer.

LncRNA NDUFA6-DT: A Comprehensive Analysis of a Potential LncRNA Biomarker and Its Regulatory Mechanisms in Gliomas.

Gliomas are the most prevalent primary malignant tumors affecting the brain, with high recurrence and mortality rates. Accurate diagnoses and effective treatment challenges persist, emphasizing the need for identifying new biomarkers to guide clinical decisions. Long noncoding RNAs (lncRNAs) hold potential as diagnostic and therapeutic biomarkers in cancer. However, only a limited subset of lncRNAs in gliomas have been explored. Therefore, this study aims to identify lncRNA signatures applicable to patients with gliomas across all grades and explore their clinical significance and potential biological mechanisms. Data used in this study were obtained from TCGA, CGGA, and GEO datasets to identify key lncRNA signatures in gliomas through differential and survival analyses and machine learning algorithms. We examined their associations with the clinical characteristics, gene mutations, diagnosis, and prognosis of gliomas. Functional enrichment analysis was employed to elucidate the potential biological mechanisms associated with these significant lncRNA signatures. We explored competing endogenous RNA (ceRNA) regulatory networks. We found that NDUFA6-DT emerged as a significant lncRNA signature in gliomas, with reduced NDUFA6-DT expression associated with a worse prognosis in gliomas. Nomogram analysis incorporating NDUFA6-DT expression levels exhibited excellent prognostic and predictive capabilities. Functional annotation suggested that NDUFA6-DT might influence immunological responses and synaptic transmission, potentially modifying glioma initiation and progression. The associated ceRNA network revealed the possible presence of the NDUFA6-DT-miR-455-3p-YWHAH/YWHAG axis in low-grade glioma (LGG) and glioblastoma multiforme (GBM), regulating the PI3K-AKT signaling pathway and influencing glioma cell survival and apoptosis. We believe that NDUFA6-DT is a novel lncRNA linked to glioma diagnosis and prognosis, potentially becoming a pivotal biomarker for glioma.

Dual-space disentangled-multimodal network (DDM-net) for glioma diagnosis and prognosis with incomplete pathology and genomic data

Objective. Effective fusion of histology slides and molecular profiles from genomic data has shown great potential in the diagnosis and prognosis of gliomas. However, it remains challenging to explicitly utilize the consistent-complementary information among different modalities and create comprehensive representations of patients. Additionally, existing researches mainly focus on complete multi-modality data and usually fail to construct robust models for incomplete samples. Approach. In this paper, we propose a dual-space disentangled-multimodal network (DDM-net) for glioma diagnosis and prognosis. DDM-net disentangles the latent features generated by two separate variational autoencoders (VAEs) into common and specific components through a dual-space disentangled approach, facilitating the construction of comprehensive representations of patients. More importantly, DDM-net imputes the unavailable modality in the latent feature space, making it robust to incomplete samples. Main results. We evaluated our approach on the TCGA-GBMLGG dataset for glioma grading and survival analysis tasks. Experimental results demonstrate that the proposed method achieves superior performance compared to state-of-the-art methods, with a competitive AUC of 0.952 and a C-index of 0.768. Significance. The proposed model may help the clinical understanding of gliomas and can serve as an effective fusion model with multimodal data. Additionally, it is capable of handling incomplete samples, making it less constrained by clinical limitations.

UBA2 as a Prognostic Biomarker and Potential Therapeutic Target in Glioma.

Gliomas are characterized by aggressive behavior, leading to severe disability and high mortality. Ubiquitin-like modifier activating enzyme 2 (UBA2) is a subunit of the E1-activating enzyme involved in the SUMOylation (SUMO, small ubiquitin-related modifier) of numerous proteins. Although the abnormality of UBA2 is linked to the progression of various tumor types, the role of UBA2 in glioma is still unknown. A bioinformatic analysis using several public databases was conducted to examine the expression level, clinicopathological correlations, and prognostic significance of UBA2 in glioma. The correlation between UBA2 expression and drug sensitivity in cancers was also explored. Multiple cellular experiments were conducted to validate the role of UBA2 in glioma. Analysis of multiple databases and cellular experiments revealed that UBA2 was overexpressed in glioma tissues and cell lines, respectively. UBA2 expression in gliomas correlated with World Health Organization (WHO) grade, IDH gene status, 1p19q deletion, histological type, and immune cell infiltration in glioma. UBA2 expression in carcinomas also correlated with drug sensitivity. Kaplan-Meier analysis revealed that high expression of UBA2 predicted poorer survival in glioma patients. A nomogram model containing UBA2 expression was constructed for clinical practice. Knockdown of UBA2 was observed to suppress glioma cell progression and sensitize glioma cells to irradiation in vitro. Overall, this research showed that UBA2 might be involved not only in the development of glioma but also in the regulation of immunity, drug sensitivity, and radiosensitivity. Therefore, UBA2 may be a potential target for therapy and a candidate biomarker for glioma diagnosis and prognosis.

Heteroions Radii Matching Produced Intensely Luminescent Bismuth-Ag2S Nanocrystals for through-Skull NIR-II Imaging of Orthotopic Glioma.

Heteroions doped Ag2S nanocrystals (NCs) exhibiting enhanced near-infrared-II emission (NIR-II) hold great promise for glioma diagnosis. Nevertheless, current doped Ag2S NCs paradoxically improved properties via toxic dopants, and the blood-brain barrier (BBB) constitutes another challenge for orthotopic glioma imaging. Thus, it is urgent to develop biofriendly high-bright Ag2S NCs with active BBB-penetration for glioma-targeted imaging. Herein, bismuth (Bi) was screened to obtain Bi-Ag2S NCs with high absolute PLQY (∼13.3%) for its matched ionic-radius (1.03 Å) with Ag+. The Bi-Ag2S NCs exhibited a higher luminance and deeper penetration (5-6 mm) than clinical indocyanine green. Upon conjugation with lactoferrin, the NCs acquired BBB-crossing and glioma-targeting abilities. Time-dependent NIR-II-imaging demonstrated their effective accumulation in glioma with skull/scalp intact after intravenous injection. Moreover, the toxic-metal-free NCs exhibited negligible toxicity and great biocompatibility. The success of leveraging the ion-radii comparison may unlock the full potential of doped-Ag2S NCs in bioimaging and inspire the development of various doped NIR-II NCs.

An update on susceptibility-weighted imaging in brain gliomas.

Susceptibility-weighted imaging (SWI) has become a standard component of most brain MRI protocols. While traditionally used for detecting and characterising brain hemorrhages typically associated with stroke or trauma, SWI has also shown promising results in glioma assessment. Numerous studies have highlighted SWI's role in differentiating gliomas from other brain lesions, such as primary central nervous system lymphomas or metastases. Additionally, SWI aids radiologists in non-invasively grading gliomas and predicting their phenotypic profiles. Various researchers have suggested incorporating SWI as an adjunct sequence for predicting treatment response and for post-treatment monitoring. A significant focus of these studies is on the detection of intratumoural susceptibility signals (ITSSs) in gliomas, which are indicative of microhemorrhages and vessels within the tumour. The quantity, distribution, and characteristics of these ITSSs can provide radiologists with more precise information for evaluating and characterising gliomas. Furthermore, the potential benefits and added value of performing SWI after the administration of gadolinium-based contrast agents (GBCAs) have been explored. This review offers a comprehensive, educational, and practical overview of the potential applications and future directions of SWI in the context of glioma assessment. CLINICAL RELEVANCE STATEMENT: SWI has proven effective in evaluating gliomas, especially through assessing intratumoural susceptibility signal changes, and is becoming a promising, easily integrated tool in MRI protocols for both pre- and post-treatment assessments. KEY POINTS: • Susceptibility-weighted imaging is the most sensitive sequence for detecting blood and calcium inside brain lesions. • This sequence, acquired with and without gadolinium, helps with glioma diagnosis, characterisation, and grading through the detection of intratumoural susceptibility signals. • There are ongoing challenges that must be faced to clarify the role of susceptibility-weighted imaging for glioma assessment.

Quantifying H&E staining results, grading and predicting IDH mutation status of gliomas using hybrid multi-dimensional MRI.

To assess the performance of hybrid multi-dimensional magnetic resonance imaging (HM-MRI) in quantifying hematoxylin and eosin (H&E) staining results, grading and predicting isocitrate dehydrogenase (IDH) mutation status of gliomas. Included were 71 glioma patients (mean age, 50.17 ± 13.38years; 35 men). HM-MRI images were collected at five different echo times (80-200ms) with seven b-values (0-3000s/mm2). A modified three-compartment model with very-slow, slow and fast diffusion components was applied to calculate HM-MRI metrics, including fractions, diffusion coefficients and T2 values of each component. Pearson correlation analysis was performed between HM-MRI derived fractions and H&E staining derived percentages. HM-MRI metrics were compared between high-grade and low-grade gliomas, and between IDH-wild and IDH-mutant gliomas. Using receiver operational characteristic (ROC) analysis, the diagnostic performance of HM-MRI in grading and genotyping was compared with mono-exponential models. HM-MRI metrics FDvery-slow and FDslow demonstrated a significant correlation with the H&E staining results (p < .05). Besides, FDvery-slow showed the highest area under ROC curve (AUC = 0.854) for grading, while Dslow showed the highest AUC (0.845) for genotyping. Furthermore, a combination of HM-MRI metrics FDvery-slow and T2Dslow improved the diagnostic performance for grading (AUC = 0.876). HM-MRI can aid in non-invasive diagnosis of gliomas.