Radiology

Lifespan Pancreas Morphology for Control Versus Type 2 Diabetes Using AI on Largescale Clinical Imaging.

Understanding how pancreas size and shape change with normal aging is critical for establishing a baseline to detect deviations in type 2 diabetes and other pancreatic disease. We measure pancreas size and shape using morphological measurements from early development through aging (ages 0-90). Our goals are to (1) identify reliable clinical imaging modalities for artificial intelligence (AI) based...

Interpretable Artificial Intelligence in Assisting Treatment Response Prediction for Locally Advanced Rectal Cancer After Neoadjuvant Chemoradiotherapy: A Prospective, Multicenter, Human-Model Interaction Study.

PURPOSE: Preoperative assessment of pathologic complete response (pCR) to neoadjuvant therapy is an urgent need for anorectal preservation in patients with locally advanced rectal cancer (LARC). Artificial intelligence assistance remains challenging due to a lack of prospective validation and reliable interpretability. METHODS AND MATERIALS: Eligible patients with LARC were retrospectively collect...

First trimester prediction of gestational diabetes mellitus by machine learning in twin pregnancies.

INTRODUCTION: We aimed to develop a machine learning model for first-trimester prediction of gestational diabetes mellitus (GDM) in twin pregnancies u...

The Diagnosis and Treatment Technology of Port-Wine Stain, and the Prospect of Future Treatment.

Port-wine stain (PWS) is a congenital capillary malformation with a 0.3-0.5% prevalence. This article reviews key techniques and advancements in the d...

Artificial intelligence in lung scintigraphy.

Lung scintigraphy is a common nuclear medicine procedure for evaluating pulmonary perfusion and ventilation, particularly in the diagnosis of pulmonar...

[Potential of imaging in the clinical routine : Focus on cardiovascular MRI].

Cardiac magnetic resonance imaging (CMR) provides decisive advantages, particularly in coronary heart disease, myocarditis and cardiomyopathy. It accu...

Clinical prediction of aortic arch anatomy to guide stroke CT angiography protocols: A machine learning study.

BackgroundThe aortic arch (AA) influences catheter navigation during endovascular treatment (EVT) for acute ischemic stroke. Whether routine inclusion...

Quantifying Innovation in Stroke: Large Language Model Bibliometric Analysis.

BACKGROUND: Thrombolysis and mechanical thrombectomy represent the most successful stroke innovations over the last 30 years. Quantifying innovation i...

Adaptive geometric-attention multi-task framework with knowledge distillation for aortic dissection detection in non-contrast CT.

Aortic dissection (AD) is a life-threatening cardiovascular emergency. Non-contrast-enhanced CT (NCE-CT) could provide timely AD screening with fewer ...

Preoperative Neuroimaging Markers, Clinical Severity Measures, and Shunt Characteristics for Predicting Shunt Revision in Idiopathic Intracranial Hypertension: An Explainable Machine-Learning Study.

BACKGROUND AND PURPOSE: Surgical shunt placement is a common treatment for idiopathic intracranial hypertension (IIH) but is hampered by high revision...

Role of MRI radiomics in deep learning-based prediction of intestinal diseases.

BACKGROUND: Magnetic resonance imaging (MRI) is widely used for the diagnosis, evaluation, and follow-up of intestinal diseases. With advances in arti...

Customized CNN Architectures Outperform Pre-Trained Models in Differentiating Normal Brain Tissues, Glioma, Meningioma, and Pituitary Tumors.

Early and accurate detection of brain tumors is essential for improving treatment outcomes and patient survival. While pre-trained deep learning model...

FetCAT: Cross-attention fusion of transformer-CNN architecture for fetal brain plane classification with explainability using motion-degraded MRI.

Fetal brain magnetic resonance imaging (MRI) has been recognized as a vital diagnostic tool for identifying neurological anomalies during pregnancy. A...

MCDNet: Morphological-conditional dual-view fusion for 3D tubular structure segmentation.

Accurate segmentation of 3D tubular structures in medical images is critical for clinical diagnosis and interventional planning. Although deep learnin...

A Guided Sampling Enhanced Rapidly-Exploring Random Tree Path Planning Algorithm for Robot-Assisted Flexible Needle Insertion.

Percutaneous puncture techniques have been widely adopted across various domains of modern clinical interventional therapy due to their high diagnosti...

Early management of acute heart failure.

PURPOSE OF REVIEW: Acute heart failure (AHF) is a frequent, high-risk emergency department presentation in which early diagnostic and therapeutic deci...

Systemic Microvasculature Frailty: Brain frailty score predicts contrast-associated acute kidney injury after thrombectomy for stroke.

BACKGROUND: Contrast-associated acute kidney injury (CA-AKI) is a frequent complication after mechanical thrombectomy (MT). Cerebral small vessel dise...

Radiomics-based classification and inference of subtypes and stages in social anxiety disorder using resting-state functional images.

BACKGROUND: This study aimed to leverage advanced radiomics analysis of resting-state functional magnetic resonance imaging (rs-fMRI) data to investig...

Evaluation of an Artificial Intelligence Defined Lung Nodule Malignancy Score in Incidental Pulmonary Nodules: The CREATE Study.

OBJECTIVE: To evaluate the effectiveness of the artificial intelligence-based qXR lung nodule malignancy score (qXR-LNMS) in detecting high-risk incid...

Multimodal imaging of acquired aortic diseases: clinical efficacy, comparative analysis, and future perspectives.

Aortic diseases, particularly acute aortic syndromes (AAS) and aortic aneurysms (AA), represent critical cardiovascular conditions with high mortality...