AIMC Topic: Glioblastoma

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Regional-aware and sequence-informed multi-decoder network for robust brain glioma segmentation in multi-parametric MRI.

Computers in biology and medicine
Accurate segmentation of glioblastoma subregions from multi-parametric MRI is essential for diagnosis, surgical planning, and treatment monitoring in neuro-oncology. However, effective delineation of surrounding non-enhancing FLAIR hyperintensity, no...

Radiomics-based quantification of tumor infiltration in the non-enhancing peritumoral region on postoperative MRI is associated with survival in glioblastoma.

Scientific reports
Glioblastoma is characterized by diffuse infiltration, making accurate detection of residual disease essential for improving prognostication and guiding treatment. This study evaluates whether the volume of predicted infiltration, generated by a mach...

Enhancing lipid nanoparticles-mediated RNA delivery to glioblastoma via targeted strategies.

Journal of controlled release : official journal of the Controlled Release Society
Glioblastoma (GBM) is an aggressive central nervous system (CNS) malignancy with a poor prognosis and limited responses to conventional therapies. RNA-based therapeutics, with their gene-targeting specificity, present a promising avenue for GBM treat...

scSpecies: enhancement of network architecture alignment in comparative single-cell studies.

Genome biology
Animals can provide meaningful context for human single-cell data. To transfer information between species, we propose a deep learning approach that pre-trains a conditional variational autoencoder on animal data and transfers its final encoder layer...

Machine learning-enhanced discovery of a basement membrane-related gene signature in glioblastoma via single-cell and Spatial transcriptomics.

Journal of translational medicine
BACKGROUND: The complex invasiveness and heterogeneity of glioblastoma multiforme (GBM) hinder the complete eradication of the tumor. The invasion of the basement membrane (BM) occurs before the spread to the meninges and the metastasis of glioma cel...

Non-invasive identification of mesenchymal glioblastoma using quantitative radiomic features from advanced diffusion MRI: a preclinical-to-clinical transfer learning strategy.

European radiology experimental
BACKGROUND: Glioblastoma (GBM) is no longer regarded as a single disease, as distinct molecular subgroups exist, with the mesenchymal (MES) having the worst prognosis. As such, there is a critical need for noninvasive methods to determine GBM molecul...

Interpretable radiomics-based machine learning model for differentiating glioblastoma from primary central nervous system lymphoma using contrast-enhanced T1-weighted imaging.

Scientific reports
This study aimed to develop and validate an interpretable radiomics-based machine learning model using contrast-enhanced T1-weighted imaging (CE-T1WI) to differentiate glioblastoma (GB) from primary central nervous system lymphoma (PCNSL), while comp...

Spatial-reprogramming derived GPNMB macrophages interact with COL6A3 fibroblasts to enhance vascular fibrosis in glioblastoma.

Genome medicine
BACKGROUND: Neoadjuvant therapy plays an important role in the treatment of glioblastoma (GBM), but a considerable proportion of patients remain unresponsive to the combination of immune checkpoint blockade (ICB) and antiangiogenic therapy. Understan...

Evaluation of (Z)-endoxifen as a potential therapy for glioblastoma multiforme through computational and experimental analyses.

Scientific reports
(Z)-endoxifen (endoxifen) is the active metabolite of tamoxifen. Endoxifen is a potent antiestrogen that binds and blocks estrogen receptor alpha (ERα) and estrogen receptor beta (ERβ). Early-phase clinical trials have shown that endoxifen has promis...

Survival risk stratification of 2021 WHO glioblastoma by MRI radiomics and biological exploration.

BMC cancer
BACKGROUND: There is variability in overall survival among 2021 World Health Organization isocitrate dehydrogenase wild type glioblastoma (IDH-wt GBM) patients. The aim of the study was to develop a combined model for stratifying survival risk in IDH...