Radiology

Evolution of Facial Assessment in Aesthetic Medicine: 3D Imaging, Digital Analysis, and Patient-Reported Outcomes.

BACKGROUND: Facial assessment is central to treatment planning and outcome evaluation. Traditional approaches, including visual inspection, manual anthropometry, and classical esthetic proportions, are limited by inter-observer variability and challenges in accounting for cultural and demographic diversity. Recent advances in digital imaging and computational analysis now enable more objective, re...

A Systematic Review and Meta-analysis of Two-Dimensional Breast Ultrasound Radiomics: Implications for Lesion Characterization and Diagnostic Accuracy.

Radiomics applied to two-dimensional breast ultrasound has emerged as a potential noninvasive approach for differentiating benign from malignant breast lesions; however, its diagnostic accuracy and methodological reliability remain uncertain. This PRISMA-DTA-compliant systematic review and meta-analysis (PROSPERO CRD420251149769) synthesized evidence from observational studies published between 20...

Domain Generalization Mitigates Scanner-Induced Domain Shift in Medical Imaging.

Deep learning models for medical image analysis often fail in clinical deployment due to domain shift from varied acquisition hardware and protocols. ...

Deep Learning-Based Automated Reports for Breast Density Assessment in Mammography Images.

Breast density is a key factor in mammographic screening, as high-density tissue increases cancer risk and can obscure lesions, reducing diagnostic se...

Radiologist Detection of Deficiencies in LLM-Generated Patient Communications About Radiology Reports: A Multi-Reader Study.

Patients increasingly use large language models (LLMs) to interpret radiology reports, yet the reliability of radiologist oversight in detecting error...

Advanced Deep Learning Architectures in MRI-Based Brain Tumor Classification: A Systematic Review Focused on Meningiomas.

Deep learning (DL) is increasingly applied to automate brain tumor classification from magnetic resonance imaging (MRI), yet meaningful clinical deplo...

Cross-Center Online Generalization Algorithm with Unadversarial Consistency for Fetal Heart Ultrasound View Recognition.

Fetal congenital heart disease (FCHD) remains a leading cause of infant mortality globally, yet the clinical deployment of deep learning models for au...

MRI Radiomics for Preoperative Microvascular Invasion Stratification in Hepatocellular Carcinoma: Comparative Analysis of Intratumoral, Peritumoral, and Combined Intratumoral-Peritumoral Approaches-A Systematic Review and Meta-analysis.

Microvascular invasion (MVI) represents a critical prognostic determinant in hepatocellular carcinoma (HCC), yet preoperative prediction remains chall...

Pilot feasibility study of deep learning-based detection of malignant liver lesions in intraoperative ultrasound imaging.

BACKGROUND: Intraoperative ultrasound plays a central role in hepatobiliary surgery for the detection of liver lesions, but image interpretation is ch...

Deep learning-based automatic identification model of main pancreatic duct in intraoperative ultrasonography.

BACKGROUND: Pancreatic enucleation (PE) preserves parenchyma in benign/low-grade malignant pancreatic tumors but risks postoperative pancreatic fistul...

Predicting sentinel lymph node metastasis in breast cancer using an interpretable machine learning approach based on multi-domain clinical features.

BACKGROUND: Accurate identification of sentinel lymph node (SLN) status is essential for surgical and adjuvant therapy decisions in breast cancer. Alt...

Vessel Wall Imaging in 1.5 T MRI Using Deep Learning Reconstruction: Prospective Evaluation of Interchangeability With Standard 3 T MRI.

OBJECTIVES: Vessel wall magnetic resonance imaging is important in the diagnosis of intracranial vascular diseases. Until now, adequate clinical imple...

DeepKneeXR: YOLOv8 multi-label X-rays detection of knee abnormalities from sports injury with clinical explainability.

BACKGROUND: Soft-tissue knee abnormalities are common, yet first-line radiography provides limited soft-tissue contrast, whereas MRI or arthroscopy is...

Early detection of severe fetal growth restriction using multimodal deep learning based on ultrasound and prenatal biomarkers.

OBJECTIVE: To develop and evaluate a multimodal deep learning model that integrates first- and second-trimester ultrasound images with first-trimester...

A multimodal deep learning classifier for prediction of HER2-low expression in triple-negative breast cancer.

BACKGROUND: Triple-negative breast cancer (TNBC) is an aggressive molecular subtype. With the new definition of HER2-low status and the availability o...

Comparative evaluation of automated MRI-based brain volumetry software for estimating cognitive domains in early Alzheimer's disease.

BACKGROUND: Brain volumetry software is widely accepted for assessment in Alzheimer's disease. However, direct comparisons for software-specific predi...

Automated detection of lumbar disc herniation at L4-L5 and L5-S1 levels on sagittal MRI using a YOLO-based deep learning model.

OBJECTIVE: To conduct a preliminary single-center feasibility study of a YOLO-based deep-learning model for automated detection of lumbar disc herniat...

LKCAU-Net: A Large Kernel Coordinated Attention U-Net for Breast Tumors Segmentation in Ultrasound Images.

Breast cancer remains a significant health concern for women worldwide. Ultrasound imaging is widely adopted for screening due to its non-invasive and...

GAN-Augmented Radiomics and Machine Learning for Post-Therapy GBM Progression Assessment.

OBJECTIVE: Differentiating true progression (TP) from pseudoprogression (PsP) in post-therapy of glioblastoma multiforme (GBM) remains a critical chal...

Artificial Intelligence in Fascial Ultrasound: A Structured Narrative Review and Evidence Map From Segmentation to Translational Requirements.

Artificial intelligence is increasingly used in ultrasound imaging, but its role in fascial ultrasound remains unclear. This structured narrative revi...