Radiology

Evaluation of AI-based segmentation and synthetic CT generation for MRI-only prostate radiotherapy planning.

BACKGROUND: There is an increasing use of magnetic resonance imaging (MRI) for segmentation of target volumes and organs at risk due to superior soft tissue contrast compared to computed tomography (CT). Conventional workflows require CT-MRI registration, introducing geometric uncertainty that can propagate to dose delivery. MRI-only radiotherapy, based on AI-generated synthetic CT (sCT) and segme...

Multitask learning for ultrasound image classification and segmentation of endometrium in the diagnosis of ectopic pregnancy.

OBJECTIVE: To develop an automated tool that performs classification and segmentation of endometrium for ectopic pregnancy diagnosis before gestational sac identification through ultrasound and serial β-hCG trends are established. MATERIALS AND METHODS: The dataset comprised 1673 transvaginal ultrasonography images from early normal pregnancy (n = 382), ectopic pregnancy (n = 422), complete aborti...

[Artificial intelligence in cardiovascular prevention: a strategic opportunity for risk prediction and early diagnosis].

Cardiovascular diseases remain the leading cause of mortality and morbidity worldwide, with substantial impact in Italy. Cardiovascular prevention is ...

Pulmonary ventilation images from planning CT images using deep learning on locally-advanced NSCLC patients.

BACKGROUND: Pulmonary ventilation imaging has become an increasingly important component in thoracic radiotherapy, as it is applied to functional avoi...

Artificial Intelligence-Estimated Intrapancreatic Fat and Its Relationship to Familial and Germline Pancreatic Cancer Risk.

BACKGROUND: Family history of pancreatic cancer (PC), pathogenic germline variants (PGVs), and increased intrapancreatic fat (IPF) are individually as...

Artificial Intelligence in Echocardiography for Acute Coronary Syndromes: Current Evidence and Integration With Electrocardiography and Biomarkers.

BACKGROUND: Early diagnosis of acute coronary syndromes (ACS) remains challenging because electrical, mechanical, and biochemical manifestations of my...

LENS: A mammography-specific hybrid CNN-Transformer with lesion-aware evidence modeling.

BACKGROUND: Artificial Intelligence (AI) models for mammography classification is prone to shortcut learning because diagnostically relevant evidence ...

AI-Assisted Sonography for the Diagnosis of Thyroid Nodules.

PURPOSE: To evaluate the diagnostic accuracy, clinical utility, and workflow integration of artificial intelligence (AI)-assisted sonography for the a...

Elevated endogenous glucagon-like peptide-1 as a novel Alzheimer's disease biomarker associated with neuroinflammation and Aβ pathology.

BACKGROUND: Alzheimer's disease (AD), a neurodegenerative disorder, is pathologically defined by the accumulation of amyloid-β (Aβ) plaques, hyperphos...

Artificial intelligence in emergency medicine: from algorithmic performance to real-world clinical integration - understanding the implementation gap.

BACKGROUND: Emergency departments (EDs) operate under time pressure, diagnostic uncertainty, and cognitive overload. Artificial intelligence (AI)-driv...

The diagnostic accuracy of left ventricular ejection fraction assessment between visual and artificial intelligence-based algorithms on bedside ultrasound.

BACKGROUND: Focused cardiac ultrasound (FoCUS) has become the standard of care for bedside assessments of cardiac function. With the integration of ar...

Performance of a deep learning-based convolutional neural network for quantification of outer retina atrophy compared with in vivo imaging and manual histologic scoring.

The efficacy of candidate drugs for neuroprotection is tested in rodent models of retinal atrophy where light-induced outer retinal atrophy (ORA) is q...

Takotsubo syndrome diagnosis: the biomarker-based BioTAK score.

BACKGROUND AND AIMS: Takotsubo syndrome (TTS) closely mimics acute coronary syndrome (ACS). Early differentiation remains challenging because diagnosi...

A Habitat Imaging-Based Radiomics and Deep Learning Fusion for Preoperative Prediction of Lymphovascular Invasion in Invasive Breast Cancer: A Multicenter Study.

BACKGROUND: Lymphovascular invasion (LVI) is a critical prognostic factor in invasive breast cancer; however, reliable preoperative prediction remains...

Noninvasive Classification of Advanced Liver Fibrosis Using Clinical Data and Non-Contrast MRI: Fusion of Clinical, Radiomic, and Deep Learning Models.

Noninvasive identification of advanced liver fibrosis (ALF), commonly defined as Scheuer stage S3 or higher, is important for the management of patien...

Acquisition Time-Specific Deep Learning-Guided Image Quality Restoration in Accelerated I-123 DaTSCAN Brain SPECT on a Ring-Shaped CZT-Based Camera.

Brain single-photon emission computed tomography (SPECT) imaging using I-123 DaTSCAN is an effective tool for the diagnosis and follow-up of Parkinson...

Deep-Learning-Based Denoising for Improved Phase Precision in Electron Holography of Electromagnetic Fields in Nanoscale Materials.

Electron holography is a powerful tool for the quantitative mapping of electric and magnetic fields at the nanoscale, with direct applications in semi...

Non-invasive differentiation of diffuse midline glioma and midline glioblastoma using DCE-MRI perfusion parameters and machine learning classification in pediatric and young adult patients.

PURPOSE: Diffuse midline glioma (DMG) and midline glioblastoma (mGBM) are aggressive WHO grade 4 tumors with comparable median survival of 12-18 month...

An integrative multi-project transcriptomic and structural prediction framework identifies candidate cold-responsive transcription factors in Medicago sativa.

Cold stress limits alfalfa (Medicago sativa) growth and persistence, but public transcriptomic datasets differ widely in genotype, tissue, treatment d...

High-resolution 3D micro-CT reveals an additional muscle layer in esophageal atresia.

BACKGROUND: Esophageal atresia (EA) is a congenital malformation intrinsically associated with esophageal dysmotility. Its etiology is poorly understo...