Radiology

Comparative Performance of Multimodal Large Language Models in Grayscale Ultrasound-Based Classification of Thyroid Nodules.

BACKGROUND: Multimodal large language models (LLMs) are increasingly being explored for medical image analysis, but their relative performance in thyroid ultrasound remains unclear. OBJECTIVE: This study aimed to compare six publicly available multimodal LLMs for grayscale ultrasound-based classification of thyroid nodules. METHODS: This prospective cross-sectional study included 178 patients with...

Machine Learning-Based Discrimination of Treatment-Resistant Schizophrenia Using Structural Brain Imaging: A Multi-Site Proof-of-Concept Study.

BACKGROUND: Treatment-resistant schizophrenia (TRS) affects 20-30% of individuals with schizophrenia, with persistent symptoms, functional impairment, and reduced quality of life. Clinical identification remains dependent on sequential antipsychotic trials despite reported structural brain differences between TRS and treatment-responsive schizophrenia (TxR). This study evaluated whether structural...

Autonomous Vascular Access Devices: Current Solutions and Future Challenges.

INTRODUCTION: Central venous cannulation is essential for life-saving interventions including resuscitation of critically ill patients, hemodynamic mo...

Super-resolution MRI and 2.5D deep learning for intratumoral-peritumoral radiomics in preoperative prediction of rectal cancer perineural invasion.

OBJECTIVES: Preoperative prediction of perineural invasion (PNI) in rectal cancer (RC) is challenging due to limited MRI resolution and the neglect of...

MRI Evaluation of Axial Spondyloarthritis: From Early Diagnosis to Therapeutic Response Assessment.

Magnetic resonance imaging (MRI) has reshaped the evaluation of axial spondyloarthritis (axSpA), which comprises radiographic axSpA (historically anky...

FusionNetX: A Deep Feature Fusion Model Leveraging MRI and Deep Learning for Enhanced Brain Tumor Detection.

Brain tumors are considered one of the deadliest diseases in the world, and misdiagnosing them puts patients' lives in danger and lowers the survival ...

Image Quality of 1.5 T MRI Using Dual-Type Deep Learning Reconstruction for Pancreatic Cystic Lesions: An Exploratory Comparison With Conventional 3 T MRI Without Deep Learning Reconstruction.

BACKGROUND: Dual-type deep learning reconstruction (DLR) may improve the pancreatic MRI image quality; however, the effects of different DLR strengths...

Unsupervised Dynamic MRI Reconstruction via Low-Rank Patch-Based Tensor Functions with Implicit Neural Representation.

Dynamic MRI suffers from limited spatiotemporal resolution due to long acquisition times. Undersam pling k-space can accelerate imaging, but it poses ...

Local Deployment of Open-Weight Language Models in Dermatology: Viewpoint on Privacy, Equity, and Practical Implementation.

Generative AI, particularly large language models (LLMs), is reshaping clinical workflows in dermatology. However, cloud-based commercial models pose ...

Comparative evaluation of feature-selection strategies for machine learning-based histological grading of breast cancer using tumor and fibroglandular-tissue DCE-MRI features.

BACKGROUND: Nottingham histological grading is central to breast cancer prognosis and treatment planning, but conventional pathological assessment is ...

Machine learning-based analysis of average glandular dose in mammography: The role of breast density.

INTRODUCTION: Average glandular dose (Dg) is the primary metric for assessing radiation risk in screening mammography. Although Dg analysis is commonl...

A physics-informed decomposition network for carbon ion radiotherapy dose monitoring: a proof-of-concept study.

In-beam positron emission tomography (PET) provides a promising strategy for dose monitoring in carbon ion radiotherapy (CIRT), but accurate dose pred...

Bile extracellular vesicles for early cholangiocarcinoma detection in primary sclerosing cholangitis.

BACKGROUND & AIMS: Cholangiocarcinoma (CCA) is a major complication of primary sclerosing cholangitis (PSC), with a 20-year incidence of ∼15%. Early d...

Multimodal Transformer Fusion of Clinical Information, Medical Text, and Pituitary MRI 2.5D Deep Learning Features for Differentiating Growth Hormone Deficiency and Idiopathic Short Stature.

RATIONALE AND OBJECTIVES: To develop a non-invasive, efficient and accurate auxiliary tool for the precise differential diagnosis between pediatric gr...

Single-shot T2-Weighted Turbo Spin-echo Imaging of the Liver Improves Lesion Characterization Compared with Free-breathing Acquisition.

RATIONALE AND OBJECTIVES: T2-weighted imaging is essential for liver magnetic resonance imaging (MRI), but conventional free-breathing turbo spin-echo...

Prognostic value of automated CT body composition in hepatocellular carcinoma: a volumetric versus single-slice comparison.

BACKGROUNDS/AIMS: To compare the prognostic value of fully automated volumetric versus single-slice computed tomography (CT)-derived body composition ...

Radiomics-guided multimodal MRI fusion framework for non-enhanced glioblastoma noninvasive identification.

This study aimed to develop and externally validate a radiomics-based machine learning framework for the noninvasive differentiation of non-enhanced g...

Computed Tomographic Angiography-Based Radiomics Predicted Stroke Recurrence in Patients With Symptomatic Intracranial Atherosclerotic Stenosis.

BACKGROUND: The aim of the current study was to investigate the predictive values of computed tomographic angiography-derived radiomics features (RFs)...

Opportunistic Screening of Carotid Atherosclerosis and Cardiovascular Mortality Risk Using Chest Radiographs: A Comparative Study of Foundation Models.

BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of death, but population-level screening for atherosclerosis often depends on special...

Systematic Review on Noncomputed Tomography-Based Technologies for Prehospital Stroke Diagnosis.

Effects of stroke therapies area highly time dependent but onset-to-treatment times for recanalizing treatment are mostly beyond optimal time windows....