Cardiovascular

A Dynamic Prognostic and Adaptive Treatment Framework for Advanced Biliary Tract Cancer.

BACKGROUND & AIMS: First-line immuno-chemotherapy is standard for advanced biliary tract cancer (BTC), but outcomes vary substantially, necessitating longitudinal monitoring and treatment adaptation. We aimed to develop models that dynamically update survival predictions using evolving clinical data to support real-time prognostic stratification. METHODS: We analysed patients with advanced BTC rec...

Impact of neoadjuvant chemotherapy on breast tissue density and its correlation with pathologic response: a retrospective artificial intelligence-enhanced radiological study.

OBJECTIVES: This study evaluates the impact of neoadjuvant chemotherapy (NAT) on breast tissue density and examines the correlation between density changes and pathological response, while also assessing inter-reader agreement among radiologists and artificial intelligence (AI) tools. METHODS: The study included 135 women with triple-negative and/or HER2+ invasive ductal breast cancer who underwen...

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, ro...

Knowledge-distilled diffusion models for improving cone-beam CT image quality with meta-learning under imbalanced data.

BACKGROUND: Adaptive radiation therapy (ART) relies on daily cone-beam CT (CBCT), yet its limited image quality hinders accurate dose calculation, par...

Recent advances in biomarkers, artificial intelligence, and targeted therapeutic strategies in breast cancer: Current progress and future perspectives.

Breast cancer is a complex and heterogeneous disease that remains a major global health challenge. Recent progress in molecular biology, artificial in...

Machine learning and cox model-based prediction of CDK4/6 inhibitor outcomes in HR+/HER2 - metastatic breast cancer: a multicenter real-world study.

BACKGROUND: Cyclin-dependent kinase 4/6 inhibitors (CDK4/6is) are standard therapy for HR+/HER2 - metastatic breast cancer (MBC), yet treatment outcom...

Self-interaction nanoparticle spectroscopy predicts high-concentration viscosity of therapeutic IgG1 antibodies.

Predicting high-concentration viscosity of monoclonal antibodies is crucial for their development as therapeutics for subcutaneous delivery, but tradi...

Emerging biomarkers in breast fibroadenoma: implications for differential diagnosis, malignant transformation, and precision medicine.

Fibroadenoma is the most common benign fibroepithelial lesion of the breast; it occurs most frequently in adolescents and women of reproductive age. W...

External validation of machine learning models predicting global longitudinal strain from conventional echocardiography in patients with cancer.

Global longitudinal strain (GLS) is a well-established prognostic marker for the early detection of cancer therapy-related cardiac dysfunction (CTRCD)...

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...

Impact of image reconstruction algorithms on histogram analysis of iodine concentration for assessing chemotherapy response in pancreatic ductal adenocarcinoma.

PURPOSE: To evaluate the impact of image reconstruction algorithms on histogram analysis of iodine concentration (IC) derived from dual-energy CT (DEC...

A hybrid ConvNeXt-ViT framework with differential evolution optimization for breast cancer classification.

Breast cancer, a leading cause of mortality among women worldwide, necessitates early detection through mammography. Yet, automated classification rem...

Using Machine Learning to Predict Breast Cancer-Related Lymphedema Following Axillary Lymph Node Dissection.

BACKGROUND: Breast cancer-related lymphedema (BCRL) is a common and debilitating sequela of axillary lymph node dissection (ALND). Although machine le...

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...

AI-Assisted Risk Stratification in Stage II Colorectal Cancer: Multi-Institutional Validation of Semantically-Enhanced Deep Learning.

BACKGROUND AND AIMS: Accurate risk stratification in stage II colorectal cancer is essential for treatment decision-making, as current guidelines reco...

Developing a Histology-Based Artificial Intelligence Biomarker to Predict Adjuvant Chemotherapy Benefit in Pancreatic Cancer.

PURPOSE: The choice of adjuvant chemotherapy in pancreatic ductal adenocarcinoma (PDAC) is mainly guided by patients' general condition. We hypothesiz...

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...