Radiology

Esketamine multi-omic biomarker evaluation in major depressive disorder (EMBER-MDD): concept, objectives and methodologies of a non-clinical investigator-initiated study.

Treatment resistance (TR) in major depressive disorder (MDD) affects a substantial minority of patients and is hard to recognize early, delaying intensified care. The Esketamine multi-omic biomarker evaluation in MDD (EMBER-MDD) is a non-interventional, investigator-initiated, in-vitro study within the EU Psych-STRATA programme, analyzing biospecimens collected in the randomized INTENSIFY study an...

Deep learning and machine learning in image-based hepatocellular carcinoma detection: a systematic review and meta-analysis.

BACKGROUND: Early detection and management are essential in hepatocellular carcinoma (HCC) care. Artificial intelligence (AI) is enhancing the precision and efficiency of diagnostic imaging for liver tumor assessment. OBJECTIVE: This study aimed to characterize the diagnostic performance of AI algorithms for detecting HCC via systematic review and meta-analysis. METHODS: A systematic literature se...

Precision Exercise for Breast Cancer-Related Outcomes: Towards Personalised Training Based on Tumour, Treatment and Patient Characteristics.

Exercise is a promising strategy associated with improved cancer-related outcomes through multiple biological mechanisms. However, current exercise gu...

Physiology-guided Self-supervised Learning for Simultaneous Dual-Tracer PET Separation.

Simultaneous dual-tracer PET provides more comprehensive information for clinical diagnosis than standard PET imaging, but separating the hybrid dual-...

Linking retinal sampling in neural encoding models to temporal profiles of visual processing in humans.

Retinotopic tuning of neural populations is a key organizing principle of human visual cortex. However, state-of-the-art models that predict neural re...

Beyond the tumor: Recurrence-prone radiomics for prognostication in negative PSMA PET/CT scans of prostate cancer.

Prostate-specific membrane antigen (PSMA) PET/CT is routinely used to restage prostate cancer (PCa) in patients with biochemical recurrence (BCR), yet...

Lung ultrasound in interstitial lung disease: from bedside screening to prognostic integration and AI-assisted standardization.

Interstitial lung diseases (ILDs) require early recognition and longitudinal assessment, yet repeated high-resolution computed tomography (HRCT) is of...

Automated deep learning-based retinoschisis and detachment volume measurement in pathological myopia with posterior scleral contraction.

PURPOSE: This study developed an automated deep learning-based system to quantify retinoschisis and detachment volume (RDV) in pathological myopia (PM...

Region-Specific Evaluation of Plaque Segmentation in Cross-sectional Projections of Carotid Ultrasound Images Using Deep Learning Models in a Sub-clinical Atherosclerosis Cohort.

OBJECTIVE: Detection of atherosclerotic plaque in the carotid arteries is essential for early cardiovascular risk assessment. While B-mode ultrasound ...

[Before the examination: digital check-in].

BACKGROUND: The check-in before imaging is an often underestimated but clinically critical step in the radiological patient journey. In computed tomog...

Hybrid deep learning framework for cardiovascular risk prediction in post-COVID-19 patients.

Cardiovascular complications associated with Post-COVID-19 Patients remain difficult to identify at early stages due to heterogeneous physiological ma...

AI-driven model for early failure prediction after HIFU integrating immediate post-ablation ultrasound and clinical data.

PURPOSE: High-Intensity Focused Ultrasound (HIFU) is an emerging focal therapy for localized prostate cancer, offering an alternative to radical prost...

Clinical artificial intelligence (AI) in Japan: Regulatory pathways, domain-specific evidence, and its data infrastructure from an international perspective.

Artificial intelligence (AI) has advanced rapidly across clinical domains, generating both a growing evidence base and dedicated regulatory frameworks...

FedFound: a federated foundation model for lifespan brain morphological connectome analysis.

The brain morphological connectome derived from structural MRI reflects inter-regional morphological relationships, providing a powerful representatio...

Prediction modeling in transdiagnostic risk: results from the PROCAN study.

Identifying biomarkers for serious mental illnesses (SMI) has significant implications for early intervention and prevention. The current study uses m...

Magnetic resonance imaging-based Alzheimer's disease detection using an EfficientNet-CMSACCN framework.

Alzheimer's Disease (AD) is a degenerative neurological condition characterized by memory loss, cognitive deterioration, and brain tissue shrinkage. D...

Secondary prevention of recurrent ischemic stroke: from guidelines to precision medicine.

Recurrent ischemic stroke remains a major global health challenge, accounting for substantial disability and mortality despite advances in acute manag...

Proteomic signatures as biomarkers of atherosclerosis burden.

AIMS: Atherosclerosis is currently evaluated by imaging, but scalable circulating biomarkers to detect its presence and quantify overall burden are la...

Artificial intelligence in the imaging diagnosis of gallbladder and bile duct stones: a systematic review.

BACKGROUND: Gallbladder and bile duct stones (cholelithiasis and choledocholithiasis) represent a major global health burden. Conventional imaging mod...

Comparative study of radiomics features between ASL and DSC perfusion-weighted imaging in distinguishing radiation-induced brain injury from glioma recurrence.

OBJECTIVE: To compare the radiomics features of pseudocontinuous arterial spin labeling (ASL) and dynamic susceptibility contrast (DSC) perfusion-weig...