Brain Cancer

Efficient Diagnosis of Spatiotemporal Evolution and Driving Factors of Surface Ozone Pollution Episodes: An Application in Jiangsu Province, China.

Severe ozone (O3) pollution is a major challenge for air quality improvement in China, primarily due to its spatiotemporal heterogeneity and nonlinear formation regimes. Here, we developed a novel framework to illustrate the spatiotemporal evolution of pollution episodes and to identify their recurrent driver modes and formation sensitivities in Jiangsu Province during the warm season from 2020 to...

MRI-based gross tumor volume delineation in high-grade glioma using a deep convolutional neural network.

OBJECTIVE: In brain radiotherapy, accurate target volume delineation is a key step in treatment planning. However, manual contour delineation can be time-consuming, labor-intensive, and subject to inter-physician variability. Therefore, this study aimed to develop a deep learning (DL)-assisted, MRI-based auto-contouring model for gross tumor volume (GTV) delineation in radiotherapy for high-grade ...

Radiolysis in drug discovery: molecular modification, repurposing, and mechanistic insights.

INTRODUCTION: In drug discovery, exploring novel chemical space and elucidating precise molecular mechanisms are essential for successful lead identif...

Integrative transcriptomics, machine learning, and molecular docking derive a DAM-like macrophage signature for risk stratification and therapeutic nomination in glioblastoma.

Glioblastoma presents a significant challenge for drug development due to its complex immunosuppressive microenvironment. Identifying candidate therap...

Towards clinically reliable AI: comparative evaluation of CNN, transformer, and hybrid architectures for meningioma detection and segmentation.

Accurate and clinically reliable meningioma detection from brain MRI remains a critical challenge, requiring not only high predictive performance but ...

Comparative outcomes of proton and photon therapy in the management of malignant peripheral nerve sheath tumors.

BACKGROUND: Malignant Peripheral Nerve Sheath Tumors (MPNSTs) are aggressive sarcomas often arising in the spine, characterized by high metastatic pot...

Advanced Deep Learning Architectures in MRI-Based Brain Tumor Classification: A Systematic Review Focused on Meningiomas.

Deep learning (DL) is increasingly applied to automate brain tumor classification from magnetic resonance imaging (MRI), yet meaningful clinical deplo...

LKCAU-Net: A Large Kernel Coordinated Attention U-Net for Breast Tumors Segmentation in Ultrasound Images.

Breast cancer remains a significant health concern for women worldwide. Ultrasound imaging is widely adopted for screening due to its non-invasive and...

GAN-Augmented Radiomics and Machine Learning for Post-Therapy GBM Progression Assessment.

OBJECTIVE: Differentiating true progression (TP) from pseudoprogression (PsP) in post-therapy of glioblastoma multiforme (GBM) remains a critical chal...

Image sharpening improves the visibility of reference points on low-dose lateral cephalometric radiographs: a phantom study.

This phantom study aimed to determine whether a novel non-artificial intelligence image-sharpening approach improves the visibility of reference point...

From tumor-centric to ecosystem-based hypotheses in brain tumor research and care: Proceedings from The second Brain Tumor Meeting by the Sea organized by Julie Gavard and Eric Chevet, held in St Malo (France), 23-25 March 2026.

Brain tumors remain among the most lethal cancers, largely due to their remarkable heterogeneity, plasticity, and resistance to therapy. The second Br...

Intraoperative technological advances and new frontiers in precision glioma surgery.

BACKGROUND: Diffuse gliomas remain among the most surgically challenging tumors, characterized by their infiltrative nature, proximity to eloquent bra...

Advances in CT and MRI for Yttrium-90 Radioembolization of Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: Transarterial radioembolization (TARE) is increasingly used for patients with hepatocellular carcinoma (HCC) across Barcelon...

End-to-end 2.5D multisequence-multichannel fusion model for preoperative survival prediction in glioma: a retrospective study.

Gliomas are the most common primary malignant tumors of the central nervous system and show marked imaging heterogeneity, making accurate preoperative...

TREM2 in glioma: Reprogramming the immune microenvironment from mechanistic understanding to clinical translation (Review).

The poor prognosis of high‑grade gliomas, such as glioblastoma, is largely driven by a notably immunosuppressive tumor microenvironment (TME), wherein...

Enhancing decision-making in surgery for a large temporocorneal meningioma through an explainable human-AI collaboration: a case report.

BACKGROUND: Meningiomas, particularly large temporocorneal meningiomas, pose significant surgical challenges due to their proximity to critical brain ...

Deep learning based two-way feature depiction model for brain tumor detection.

Brain tumors are one of the most fatal disorders that cause one of the highest mortalities in the world. Gliomas are the most common primary brain tum...

Optimisation of radiation dose and image quality in paediatric chest and abdominal CT examinations: A systematic review.

INTRODUCTION: Computed tomography (CT) is indispensable for the rapid evaluation of paediatric chest and abdominal pathology, yet it delivers relative...

BEAMSTER: Brain mEtAstases segMentation for STEreotactic Radiotherapy, A Retrospective MRI Dataset with Expert Segmentations.

We present a retrospective dataset of contrast-enhanced T1-weighted magnetic resonance imaging scans from 140 patients with brain metastases who under...

The Big Data Science Center at the Shanghai Synchrotron Radiation Facility: the architecture of the superfacility.

In the context of the global big data deluge, concerted efforts are being made to address the challenges faced by large scientific facilities. These e...