Radiology

Data-driven thresholds for standardized classification of severe Alzheimer's disease neuropathology using digital neuropathology.

Alzheimer's disease neuropathological changes (ADNC)-operationalized with semi-quantitative parameters-represent the consensus-based gold standard for diagnostic evaluation of disease severity. Although useful, ADNC diagnostic frameworks have limitations, particularly in advanced disease stages where pathological severity varies widely within a given diagnostic category. Further, some individuals ...

AI-assisted versus fully automated volumetry for hemorrhage quantification in spontaneous ICH with ventricular extension: A multi-center study.

BACKGROUND: Spontaneous intracerebral hemorrhage (sICH) with intraventricular hemorrhage (IVH) extension is a neurological emergency associated with high mortality, where separate quantification of intraparenchymal hemorrhage (IPH) and IVH volumes is essential for risk stratification and treatment decisions. While commercial artificial intelligence (AI) tools increasingly promise to automate this ...

Waste-to-sensor upcycling of polyethylene terephthalate over Ag/Zr-MOF photocatalyst for microplastic degradation and AI-assisted heavy metal detection.

This study aims to develop an integrated waste to sensor platform that couples photocatalytic PET depolymerization with on stream quantification of co...

Brain PET in the era of anti-amyloid-β antibody therapy for Alzheimer disease.

Here the current and emerging roles of brain positron emission tomography (PET) in Alzheimer's disease (AD) in the era of anti-amyloid-β antibody ther...

Radiomics and artificial intelligence in pancreatic cyst characterization: future or fiction?

Pancreatic cystic lesions (PCLs) are increasingly detected due to the widespread use of cross-sectional imaging and represent a significant diagnostic...

Image Quality Assessment of the External Carotid Artery and Its Branches on Ultra-High-Resolution Head and Neck Computed Tomography Angiography Using a High-Resolution 0.25-mm Detector and Deep Learning Reconstruction.

BACKGROUND AND PURPOSE: Deep learning reconstruction can improve image quality of CTA, but its benefit for visualizing small-caliber external carotid ...

Combined radiomics, PI-RADS, and clinical model improve significant prostate cancer prediction and guide biopsy decision.

OBJECTIVES: The aim of this study was to develop and validate an MRI radiomics-based predictive model to discriminate significant prostate cancer (sPC...

A frontotemporal dementia-like phenotype in schizophrenia: links to striatal dopamine and iron accumulation.

Some schizophrenia patients share characteristics with behavioral variant frontotemporal dementia (bvFTD) including gray matter volume (GMV) similarit...

Enhancing genomic prediction for key production traits in chickens through ultrasound phenotyping and multi-model comparative analysis.

BACKGROUND: Growth performance and carcass traits are economically vital in poultry breeding. In Wenchang chickens, reducing excessive abdominal fat r...

Association of MRI-Visible Perivascular Spaces With Longitudinal Cognitive Decline Over a Decade.

BACKGROUND AND OBJECTIVES: Cerebral small vessel disease (SVD) is the most common vascular contributor to dementia. SVD markers often coexist, contrib...

From structural complexity to causal representation: A dynamic fractal-attention framework for fine-grained ovarian tumor classification in ultrasound.

Accurate fine-grained classification of ovarian tumors from ultrasound images remains challenging due to speckle noise, boundary ambiguity, structural...

External Validation of the PIPRA Model for Postoperative Delirium Prediction in a Japanese ICU Cohort: Integrating AI-Based Risk Assessment into Perioperative Care.

BACKGROUND: Postoperative delirium (POD) is a prevalent and serious complication in older surgical patients, linked to prolonged hospitalization, high...

High-Throughput Imaging Cytometry paired with Artificial Intelligence Identifies Ultra-Rare Sperm in Men previously Diagnosed with Clinical Azoospermia.

OBJECTIVE: To determine whether a novel diagnostic platform which pairs high-throughput imaging cytometry with Artificial Intelligence (AI) assisted i...

DUSTrack: Semi-automated point tracking in ultrasound videos.

UNLABELLED: Ultrasound technology enables safe, non-invasive imaging of dynamic tissue behavior, making it a valuable tool in medicine, biomechanics, ...

A Novel Breast Arterial Calcification Age-Based Percentile Nomogram for the Incremental Prediction of Incidental Cardiovascular Events.

BACKGROUND: Breast arterial calcification (BAC) detected on routine mammography is an emerging marker of cardiovascular risk in women. However, substa...

MRDT-GAN: generative adversarial network with multi-scale residual dense transformer generator for low-dose CT denoising.

Objective.Low-dose computed tomography (LDCT) reduces radiation exposure but introduces noise and artifacts that degrade diagnostic quality. Existing ...

Machine Learning-Based Magnetocardiography Model Aids in Diagnosing Non-ST-Segment Elevation Acute Coronary Syndrome in Acute Chest Pain.

BACKGROUND: Non-ST-segment elevation acute coronary syndrome (NSTE-ACS) is a leading cause of acute chest pain in clinical practice. Magnetocardiograp...

Generalizable spinal cord multiple sclerosis lesion segmentation across MRI contrasts, protocols, and centers.

BACKGROUND/OBJECTIVES: Characterizing spinal cord multiple sclerosis (MS) lesions in MRI is critical for diagnosis, monitoring, and treatment evaluati...

Real-time planar angiographic cerebral perfusion imaging.

PURPOSE: Digital Subtraction Angiography (DSA) is an X-ray-based imaging modality intimately related to minimally invasive procedures in interventiona...

Deep learning-based multimodal radiopathomics for preoperative prediction of lymph node metastasis in papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) exhibits a high incidence and a strong propensity for lymph node metastasis (LNM). Accurate preoperative assessment ...