Pregnancy

MRI radiomics combined with clinical features for predicting initial dose in focused ultrasound ablation surgery for uterine fibroids.

OBJECTIVE: To develop and validate a radiomics-clinical model for individualized prediction of the initial treatment dose in focused ultrasound ablation surgery (FUAS) for uterine fibroids. METHODS: This retrospective study included 210 patients with solitary uterine fibroids who underwent FUAS and were randomly divided into training and testing cohorts (7:3). The outcome variable was defined as t...

A Two-Stage Hybrid Feature Selection and Ensemble Learning Framework With Explainable AI for Accurate PCOS Prediction.

BACKGROUND AND AIMS: Polycystic ovary syndrome (PCOS) is the most prevalent endocrine ailment impacting women of reproductive age, distinguished by ongoing imbalances of hormones that lead to the growth of various ovarian cysts alongside other health issues. Infrequent or delayed menstrual periods, and also frequently excessive amounts of androgen, a male hormone, are characteristics of women with...

Accurate differentiation of metastatic and ultrasound-atypical reactive hyperplastic lymph nodes using a fusion model integrating ultrasound radiomics and habitatomics: A multicenter study.

BACKGROUND: The significant sonographic overlap between metastatic and ultrasound-atypical reactive hyperplastic lymph nodes remains a challenge in su...

Machine Learning-Based First-Trimester Antenatal Risk Prediction for Adverse Maternal and Neonatal Outcomes: Multicenter Model Development Study.

BACKGROUND: Maternal outcomes remain inequitable worldwide. Severe morbidity persists, and current risk assessment tools are largely arbitrary, focusi...

A novel approach for liver steatosis assessment in ultrasound images using an adapted Vision-Language Foundation Model.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is among the most prevalent chronic liver diseases worldwide. B-mode ultrasound remai...

MicroRNAs as novel therapeutics against multidrug-resistant ESKAPE pathogens: mechanisms, challenges, and future directions.

BACKGROUND: Multidrug-resistant (MDR) ESKAPE pathogens, including Enterococcus faecium, S. aureus, Klebsiella pneumoniae, Acinetobacter baumannii, P. ...

tDCS synchronous robotic training on lower-limb with post-stroke hemiplegia: a comparative study between synchronous and sequential group.

BACKGROUND: This study was aimed to compare the effects of tDCS synchronized with robotic training(RT)and tDCS sequential followed by RT on lower-limb...

Automated Hand Flexor Tendon Thickness Measurement in Systemic Sclerosis.

OBJECTIVE: Systemic sclerosis (SSc) can affect flexor tendons, contributing to hand function problems and reduced quality of life. Tendon changes are ...

Precision Oncology via Radiotherapy-Triggered Drug Delivery: Mechanisms, Molecular Engineering, and Clinical Translation.

Radiotherapy-triggered drug delivery systems (RDDS) promise to integrate the spatial precision of ionizing radiation with controllable pharmacological...

Radiolabeled drug-delivery and controlled-release nanocarriers for arthritis: Clinical evidence, kinetic modeling, radiation-safety challenges, and precision nanotheranostics.

BACKGROUND: Arthritis comprises a heterogeneous group of inflammatory and degenerative joint disorders characterized by distinct pathological mechanis...

Multimodal Ultrasound-Based Decision Support for Bethesda IV Thyroid Nodules: Integration of Clinical, Radiomics, Deep Learning, and Topological Features.

To develop and internally validate a multimodal ultrasound-based decision support framework for benign-malignant risk stratification of Bethesda IV th...

Driving Drugs Deeper: Force-Driven Microneedle Systems for Active Therapy and Their Road Towards Clinical Implementation.

Transdermal delivery of macromolecules and biologics is constrained by the barrier function of skin. First-generation microneedle arrays address this ...

An unsupervised physics-informed neural deconvolution framework for ultrasound imaging.

Objective. Point spread function (PSF) and clutter noise are primary causes of ultrasound quality degradation. Physical deconvolution can reduce PSF e...

Ensuring pragmatic and equitable paths forward for hepatitis B virus infection eradication in Latin America.

INTRODUCTION: Latin America occupies a paradoxical position in hepatitis B virus (HBV) elimination: aggregate prevalence is low, yet the region remain...

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 multipa...

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...

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...

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...