Brain Cancer

Measuring AI preparedness in health professions education: Evidence from a national survey of medical radiation science students and new graduates.

INTRODUCTION: Artificial intelligence (AI) in medical radiation science (MRS) is increasingly embedded in everyday clinical workflows. As AI systems assume more operational roles, questions arise not only about technical competence, but about professional judgement, ethical responsibility, and what it now means to be "ready for practice". This study benchmarks perceived AI preparedness among Austr...

TOPOS: target organ prediction on scout views for automated CT scan planning.

BACKGROUND: Overscanning is a common issue in CT planning, leading to unnecessary radiation exposure. PURPOSE: To develop a deep learning model to segment anatomical structures in scout views to optimize scan ranges and reduce radiation. MATERIALS AND METHODS: In this single-center retrospective study, 1146 patients undergoing CT between 2022 and 2025 were included. The model was trained on segmen...

Enhancing glioma progression prediction: Unsupervised clustering of whole-brain magnetic resonance spectroscopy data for surgical planning.

BACKGROUND: The inevitable progression of high-grade gliomas has prompted a need for data-backed identification of compromised tissue prior to detecti...

Identification of drug candidates against glioblastoma with machine learning and high-throughput screening of heterogeneous cellular models.

Glioblastoma multiforme (GBM) is an aggressive primary brain tumour that presents significant treatment challenges due to its complex pathology and he...

Deep learning for detection and automatic visualization of radiation-induced temporal lobe injury in nasopharyngeal carcinoma across endemic and non-endemic areas in China.

PURPOSE: Detection of radiation-induced temporal lobe injury (RTLI) at the earliest radiologically detectable stage is important for timely interventi...

The Integration of Artificial Intelligence in Radiation Medical Physics: Insights from an International Survey with Regional Variability.

BACKGROUND: Artificial intelligence (AI) is considered to be a leading technology in radiation medical physics, which has the potential for improving ...

Personalized machine learning-guided radiation dose escalation in newly diagnosed glioblastoma: prospective pilot study.

Glioblastoma is a highly aggressive primary brain tumor with near-universal recurrence despite maximal safe resection followed by standard chemoradiat...

Single-cell and deep learning identify hypoxia-responsive lncRNAs predicting outcomes in colorectal cancer.

Emerging evidence highlights hypoxia-responsive long non-coding RNAs (lncRNAs) as potential modulators in tumor biology. In this study, we explored th...

Radiomics model integrating MRI and ECV enhances prediction accuracy for progression in high-grade glioma.

Glioma is the most common primary brain tumor, with high-grade glioma (HGG) posing significant clinical challenges due to its poor survival outcomes. ...

The challenge of data scarcity and imbalanced classes in radiomics performance.

BACKGROUND AND OBJECTIVES: Radiomics-based machine learning models are increasingly used for clinical decision-making, yet their reliability is often ...

Application of a multimodal MRI model integrating radiomics and habitat features for predicting glioma pathology and prognosis.

BACKGROUND: Accurate grading and prognostic assessment of glioma requires integrating key molecular biomarkers, including IDH mutation status and the ...

Copper transporters promote the malignant progression of glioblastoma by regulating the immunosuppressive tumour microenvironment via the SLC31A1-WNT5A axis.

BACKGROUND: The prognosis for patients with glioblastoma (GBM) remains extremely poor, a challenge largely attributable to the complex nature of its m...

Integrative bioinformatics analysis unveils neuro-cancer crosstalk-related genes and establishes prognostic risk model in Glioblastoma.

Neuro-cancer crosstalk plays an important role in the development and progression of Glioblastoma (GBM), but its specific mechanisms remain incomplete...

Robot-assisted lumbar facet joint infiltration improves accuracy and reduces radiation exposure compared to the manual technique in a comparative phantom study.

Compact robotic systems offer new opportunities for spinal procedures outside the operating room, but their potential for small-scale interventions su...

Gliomas as network diseases: Neuron-tumor interactions, connectome disruption, and clinical implications.

BACKGROUND: Gliomas are increasingly understood as disorders of distributed brain networks rather than focal lesions confined within radiographic marg...

Improving confidence in MRI-based auto-segmentation via uncertainty assessment.

BACKGROUND AND PURPOSE: Accurate delineation of organs of interest (OOIs, also commonly referred to as organs at risk, OARs) is crucial for safe radio...

Artificial neural network analysis for oxytactic microbes in hybrid nanofluid with chemical reaction and thermal radiation.

The purpose of this investigation is to assess the outcome of Oxytactic microorganism in chemical reactive flow of TiO2 + GO/water based hybrid nanofl...

Precision theranostics in oncology: integrating antibody-drug conjugates, radioimmunotherapy, and immuno‑PET for adaptive cancer care.

The century-old vision of a "magic bullet" in oncology is being realized through the paradigm of precision theranostics, which formally integrates tar...

Single-cell profiling identifies a pro-tumoral VCAN positive macrophage subset and defines a prognostic signature in glioblastoma.

Glioblastoma (GBM), the most aggressive primary brain tumor, develops within a tumor microenvironment (TME) dominated by tumor-associated macrophages ...

Integrating ConvNeXt tiny and radiomics in a nomogram to differentiate true progression from pseudoprogression in glioma.

PURPOSE: Differentiating true progression (TP) from pseudoprogression (PsP) in glioma is challenging due to overlapping enhancement patterns on conven...