Brain Cancer

A modality-agnostic coronary artery habitat model for cardiac sparing in radiotherapy.

BACKGROUND: Emerging evidence suggests that the risk of cardiotoxicity increases with increased radiation dose to coronary arteries (CAs). However, robust tools to evaluate this increased burden for cancer patients are not available due to current limitations in imaging for radiotherapy treatment planning. PURPOSE: We have developed a novel, statistical methodology to define coronary artery "habit...

Accurate estimation of intravoxel incoherent motion parameters based on implicit neural representation.

BACKGROUND: Intravoxel incoherent motion (IVIM) diffusion-weighted imaging has important value in treatment response monitoring. However, traditional voxel-wise independent fitting methods are highly sensitive to noise and do not utilize spatial correlation, resulting in unstable parameter estimation. Although existing deep learning methods have shown improvements, they are still limited by local ...

Combined circulating tumor antigen model demonstrates additional prognostic value in first-line treatment of non-small cell lung cancer.

BACKGROUND: Circulating tumor antigens (ctA; tumor markers) are blood-based proteins that can offer prognostic value in non-small cell lung cancer (NS...

Beyond Radiation Exposure: Occupational Health Challenges Across the Modern Radiology Workforce.

Radiology occupational safety has historically centred on radiation protection. Although radiation safety remains essential, the digital transformatio...

Retraction notice to "UBTD2 protein molecules emerges as a key prognostic protein marker in glioma: Insights from integrated omics and machine learning analysis of GRM7, NCAPG, CEP55, and other biomarkers" [Int. J. Biol. Macromol. 310 (2025) 143473].

Uncertainty-Aware Risk Stratification in Pediatric Low-Grade Glioma Using Multimodal Data.

BACKGROUND AND PURPOSE: Risk stratification in pediatric low-grade glioma (pLGG) remains challenging due to biological and clinical heterogeneity. We ...

Deep learning-based multi-modality image conversion for evaluating dose calculation and position correction accuracy in image-guided radiation therapy.

Cone-beam CT (CBCT) is widely used in image-guided radiation therapy (IGRT). However, CBCT has limited image quality, which can reduce dose calculatio...

Time-dependent prognostic value of automated Ki67 assessment and its integration with molecular risk profiling in WHO grade 2 meningioma.

WHO grade 2 meningiomas exhibit highly heterogeneous clinical courses. While the Ki67 proliferation index is a standard biomarker, its prognostic util...

Tumour cell density quantified by artificial intelligence is associated with differential benefit from irinotecan-based chemo-radiotherapy in locally advanced rectal cancer: a post-hoc study of the phase 3 ARISTOTLE trial.

BACKGROUND: Tumour cells and tumour-associated stroma are key components of the tumour microenvironment, and their interaction impacts disease progres...

Artificial Intelligence for radiation protection in medical imaging and radiotherapy: A perspective from the AI Working Party of ICRP Committee 3.

PURPOSE: The increasing integration of Artificial Intelligence (AI) into clinical workflows for medical imaging and radiotherapy presents new opportun...

Radiation dose reduction in computed tomography perfusion of acute ischemic stroke patients using a denoising autoencoder.

BACKGROUND: Ischemic stroke results from the occlusion of a cerebral artery and is a leading cause of mortality and disability worldwide. Multimodal c...

Genetically predicted breastfeeding propensity and brain microstructural morphology: Insights from genome-wide association study summary statistics and neurogenomics.

BACKGROUND: Breastfeeding provides nutrients and bioactive components relevant to infant development, but observational associations with brain outcom...

E-DCNNBAE: design of a novel segmentation and classification approach for brain tumour prediction.

Context: Health plays an essential role in human life, particularly brain health, which supports vital system functions. Magnetic Resonance Imaging (M...

DEGRO consensus framework for undergraduate radiation therapy teaching in Germany: a white paper with integrated guidance on artificial intelligence in medical education.

BACKGROUND AND PURPOSE: Undergraduate medical education is increasingly competency-based, digital, and interprofessional in accordance with the Nation...

Reply to the Letter to the Editor: Deep learning network for predicting meningioma grade and Ki-67 expression: tumor location stratification.

Letter to the Editor: Deep learning network for predicting meningioma grade and Ki-67 expression: tumor location stratification.

MoESurv: A Zero-Sample and Transferable Survival Prediction Framework for Rare Cancers Using Mixture of Experts.

MOTIVATION: Accurate survival prediction is crucial for personalized cancer treatment but remains challenging for rare cancers due to limited data. Mo...

Impact of a silver filter with deep learning reconstruction on noncontrast abdominopelvic MDCT in terms of image quality, density values and radiation dose reduction.

INTRODUCTION: To assess how the use of a silver beam filtration with deep learning reconstruction (DLR) impacts the unenhanced abdominopelvic CT in te...

Validating the Utility of Super-Resolution for Downstream Tasks in Periapical Films.

INTRODUCTION AND AIMS: Periapical radiography is widely used in dental practice, but its diagnostic yield is often compromised by motion artefacts, se...

Feature integration of [18F]FDG PET brain imaging using deep learning for sensitive cognitive decline detection.

BACKGROUND: Distinguishing individuals with cognitive decline (CD), including early Alzheimer's disease, from cognitively normal (CN) individuals is e...