Radiology

Multimodal artificial intelligence in prostate cancer: integrating multiparametric MRI with clinicopathological, molecular, and functional imaging data.

Multimodal artificial intelligence (AI) is reshaping prostate cancer imaging by moving beyond MRI-only algorithms toward models that integrate multiparametric MRI (mpMRI) with clinical variables, pathology, genomics, ultrasound, and prostate-specific membrane antigen (PSMA) positron emission tomography (PET). This review summarizes the deep-learning architectures, fusion strategies, representative...

PRECISE v2 in active surveillance prostate MRI: toward a structured lexicon for longitudinal interpretation.

Active surveillance increasingly incorporates prostate MRI for longitudinal assessment of lesion stability or progression, yet terminology for serial interpretation remains less standardized than in the diagnostic setting. PRECISE version 2 (v2) provides an updated framework for evaluating interval MRI change during active surveillance, incorporating lesion-level and technical descriptors, stable ...

AI-Assisted Tumor Boundary Delineation via Targeted Ultrasmall Iron Oxide Nanoprobe for High-Contrast HER2-Positive Tumor Imaging.

Breast cancer continues to be a leading cause of cancer-related mortality in women globally, where precise diagnosis and clear tumor demarcation are c...

Artificial intelligence applications in radiology: the new frontier in interstitial lung diseases.

BACKGROUND: Interstitial lung disease (ILD) comprises a heterogeneous group of disorders with diverse clinical behaviors, for which early diagnosis, a...

Fetal brain MRI analysis: Towards clinical translation and impact.

While slice-to-volume registration and super-resolution reconstruction laid the foundation for motion-corrected 3D T2-weighted fetal brain magnetic re...

Radiologic, Pathologic, and Deep Learning Predictors of Response to Immune Checkpoint Blockade in Renal Cell Carcinoma Patients Undergoing Post-Treatment Nephrectomy.

Response assessment of primary kidney tumors in the consolidation cytoreductive and neoadjuvant settings offers a unique opportunity to inform postope...

Deep Learning-guided Late-Phase Dynamic Frame Prediction for Accelerated Patlak Analysis in 18F-FDG-PET Brain Imaging.

PURPOSE: Dynamic 18F-FDG-PET enables the quantitative assessment of cerebral glucose metabolism but requires prolonged acquisition times, which pose c...

Artificial Intelligence Optimizes Efficiency and Sonographer Workflow in Routine Adult Transthoracic Echocardiography: A Mixed-Methods Time-Motion Study.

Integrating multimodality CT-MRI deep learning with clinical-radiological features for preoperative hepatocellular carcinoma grading: a multicenter study.

OBJECTIVE: To develop and externally validate an integrated model that combines multimodality CT-MRI deep learning with clinical and radiological feat...

MSCT-Trans: A Multi-scale Convolutional Neural Network Token Transformer for Interpretable Ultrasound Image Classification.

Automated ultrasound image classification is increasingly important for clinical decision support in breast, thyroid and fetal screening. However, dep...

Deep Learning-Based Automated Segmentation of the Suprascapular Nerve and Adjacent Structures in Dynamic Supraclavicular Ultrasound.

OBJECTIVE: The suprascapular nerve (SSN) provides major motor and sensory innervation to the shoulder. Its accurate identification on ultrasound is ch...

Multiparametric MRI Habitat Imaging for Preoperative Assessment of Ki-67 Proliferation Index in Meningiomas: A Multicenter Study.

BACKGROUND: Preoperative assessment of meningioma proliferative activity relies on the postoperative Ki-67. Habitat imaging captures proliferative var...

Intramuscular Fat Assessed by AI-Assisted Muscle Ultrasound: Association With Cardiometabolic Risk Factors and Diabetic Nephropathy in Diabetes Mellitus.

AIMS: Intramuscular fat (IMF) is increasingly recognized as a marker of ectopic adiposity and adverse cardiometabolic outcomes. Artificial intelligenc...

Robotic Ultrasound Imaging: A Comprehensive Review of Historical Evolution, Current State-of-the-Art, and Future Perspectives.

Ultrasound imaging is an indispensable diagnostic tool, yet its profound reliance on operator expertise inherently restricts its reproducibility and g...

Biomarkers in facioscapulohumeral muscular dystrophy.

PURPOSE OF REVIEW: Facioscapulohumeral muscular dystrophy is one of the most frequent myopathies. Its clinical presentation and genetic background are...

Beyond robotics: a systematic review of technology integration in direct anterior approach total hip arthroplasty.

Technology-assisted implant positioning has emerged as a strategy to improve component placement accuracy in total hip arthroplasty (THA). However, th...

MRI-Based Deep Learning Guides Multi-Omics Discovery of NBPF4 as a Therapeutic Target for Breast Cancer Lymph Node Metastasis.

Deep learning models are increasingly used to analyze medical images, but their "black box" nature makes it hard to understand the underlying biology ...

3D U-net for volumetric segmentation of spinal cord MRI in degenerative disorders.

The correct identification of spinal cord structures in magnetic resonance imaging (MRI) plays a vital role in identifying degenerative spondyloarthro...

Development and validation of an automated MRI-based pipeline for temporal classification of intracerebral hemorrhage using U-Net segmentation and machine learning.

This study aimed to develop and validate an automated magnetic resonance imaging (MRI)-based pipeline for temporal classification of intracerebral hem...

Dual geometry-inspired structural modeling for neuroendocrine tumor segmentation in endoscopic ultrasound.

PURPOSE: The increasing incidence of lower gastrointestinal neuroendocrine tumors (NETs) necessitates improved methods for early and accurate detectio...