Radiology

A machine learning-based risk prediction framework for atypical hyperplasia and endometrial cancer in postmenopausal women.

BACKGROUND: This study aimed to develop and internally validate a machine learning-based model for predicting endometrial malignancy, defined as atypical hyperplasia or endometrial cancer (AH/EC), in postmenopausal women, integrating routinely available clinical, ultrasound, and laboratory features to support individualized diagnostic triage and potentially reduce unnecessary invasive diagnostic p...

CAR Practice Guidelines on Breast Imaging and Interventions: Mammography and Digital Breast Tomosynthesis.

This guideline presents Part I of the Canadian Association of Radiologists (CAR) Practice Guidelines on Breast Imaging and Intervention and focuses on mammography and digital breast tomosynthesis (DBT). Developed by the CAR Breast Imaging Working Group, this guideline provides updated, evidence-based recommendations for screening and diagnostic mammography, reflecting advances in digital imaging, ...

Synthetic phase image modulated by two-dimensional sinusoidal profile based on magnitude image using for magnetic resonance imaging reconstruction.

BACKGROUND: Magnetic resonance imaging (MRI) is a complex-valued technique incorporating magnitude and phase information, with phase images critical f...

Recent Updates on Endobronchial Ultrasound-Guided Transbronchial Needle Aspiration and Its Clinical Implications.

Endobronchial ultrasound-guided transbronchial needle aspiration (EBUS-TBNA) is the standard minimally invasive modality for mediastinal staging in no...

Artificial intelligence potential in ovarian endometriosis imaging: a comparative meta-analysis of transvaginal ultrasound-based AI models and human readers.

PURPOSE: Transvaginal ultrasound (TVUS) is widely used for diagnosing ovarian endometriosis but remains limited by significant operator dependency. Th...

Beyond target lesions: Prognostic value of longitudinal AI-derived whole-body [1⁸F]FDG PET/CT metrics in metastatic melanoma.

PURPOSE: To investigate the prognostic value of an artificial intelligence (AI)-based semi-automated tool for longitudinal whole-body quantification o...

Beyond the Coronaries: Utility of Extra-Coronary Calcification for Cardiovascular Risk Assessment in Women.

PURPOSE OF REVIEW: Globally, cardiovascular disease (CVD) is the leading cause of mortality in women. Traditional risk calculators underestimate ather...

Integrative advances in biomarker-driven prostate cancer management from genomic discovery to precision oncology.

Prostate cancer (PCa) is the second most common malignancy in men worldwide, with rising mortality linked to late-stage diagnoses. While current diagn...

FA-SedLoRA: scene-driven fine-tuning and style disentanglement for domain-generalized cardiac MRI segmentation.

The advent of deep learning has significantly advanced the state of the art in cardiac magnetic resonance (CMR) image segmentation. However, most mode...

Assessment of pre-trained deep learning models in the detection of metal artifacts in axial cone beam tomography slices.

OBJECTIVES: This study aimed to evaluate the performance of three pre-trained deep learning models (ResNet50, MobileNetV2, and EfficientNetB0) in the ...

[Emerging classifications of cardiometabolic risk in obesity].

Obesity, historically defined by body mass index and waist circumference, is a major risk factor for cardiometabolic complications; however, these ind...

Diagnostic Performance of General Practitioners in Carotid Plaque Detection Using AI-Enhanced Point-of-Care Ultrasound After Systematic Training.

PURPOSE: While point-of-care ultrasound (POCUS) has been integrated into daily practice by general practitioners (GPs) in some countries, there is a p...

The Impact of Artificial Intelligence on Radiology Specialty Preferences Among Canadian Medical Students and Residents.

RATIONALE AND OBJECTIVES: Artificial intelligence (AI) is playing an increasingly significant role in radiology While prior studies examined medical s...

Synthetic computed tomography of the head from magnetic resonance imaging based on latent diffusion model.

RATIONALE AND OBJECTIVES: Magnetic resonance imaging (MRI) is widely used in head scans. However, MRI lacks electron density information, which is inh...

Advanced Quantitative CT for Coronary Artery Disease: Integrating Stenosis-, Plaque Quantification, and FFR-CT.

Coronary artery disease (CAD) continues to be a leading cause of death globally. Radiological evaluation of CAD generally consists of stenosis detecti...

Automatic Localization and Classification of Crohn's Disease Activity in Computed Tomography Enterography Images Using Deep Learning.

Rapid and accurate localization and activity grading of Crohn's disease (CD) lesions on computed tomography enterography (CTE) images enhance the diag...

Aleatoric uncertainty in accelerated prostate MRI reconstruction: echo-train dropout versus Gaussian noise Monte Carlo sampling.

PURPOSE: Although undersampling combined with deep learning (DL)-based reconstruction shortens MRI acquisition, it increases the chance of inaccuracie...

Overdiagnosis in renal cancer: the hidden consequence of modern imaging.

The global burden of renal cell carcinoma (RCC) has risen substantially over the past three decades, while mortality rates have remained largely stabl...

A visual analysis of the research dynamics of biomarkers for lung cancer screening.

BACKGROUND: Non-invasive biomarkers offer potential to improve risk stratification and early diagnosis of lung cancer, complementing low-dose computed...

Development and evaluation of AI model with deep learning for segmentation of extraocular muscles in thyroid eye disease.

PURPOSE: To develop and evaluate an AI model for the segmentation of extraocular muscles (EOMs) using Magnetic Resonance Imaging (MRI). DESIGN: Single...