Radiology

Beyond the Cuff: Deep Learning-Based Analysis of Handheld Doppler Signals to Detect Masked Peripheral Ischemia in Diabetic Patients with Normal Ankle-Brachial Index.

OBJECTIVE: The Ankle-Brachial Index (ABI) remains the primary screening tool for Peripheral Arterial Disease (PAD). However, its diagnostic performance is severely compromised in patients with diabetes mellitus due to medial arterial calcification (MAC), leading to falsely normal or elevated results. We aimed to evaluate the efficacy of a smartphone-based Deep Learning (DL) model analyzing handhel...

Quantitative Impact of T1 Subtraction Maps on Enhancing Component Delineation and Measured Volumes in Minimally Enhancing Pediatric Brain Tumors.

BACKGROUND AND PURPOSE: The delineation of contrast enhancement in pediatric brain tumors is crucial for effective surgical and treatment planning, as well as for monitoring treatment response per Response Assessment in Pediatric Neuro-Oncology (RAPNO) guidelines. Accurate delineation of enhancement is also important in ground truth generation for training automated deep learning models. However, ...

Multimodal PET/CT-based PD-L1 status prediction in lung cancer via semi-supervised and unsupervised deep learning.

Deep learning (DL) techniques have been applied in lung cancer screening, assessing drug effectiveness, and enhancing prognosis prediction. Within thi...

Reduced environmental impact in body CT imaging with deep learning reconstruction: experience of a high-volume tertiary referral center.

PURPOSE: To evaluate the environmental impact associated with CT scanners equipped with deep-learning-based image reconstruction (DLIR) compared with ...

Consensus on the use of artificial intelligence in the management and measurement of vestibular schwannomas: A protocol for a modified delphi consensus.

INTRODUCTION: The assessment of vestibular schwannomas (VS) requires a standardized approach as growth is a key element in defining treatment strategy...

Traditional learning meets adaptive learning: the present and future of education in nonoperating room anesthesia.

PURPOSE OF REVIEW: Nonoperating room anesthesia (NORA) and continuing education in this setting are both in a state of change. Procedures performed ou...

Vestibular cortex-related effective connectivity signatures: characterization and differentiation of vestibular migraine patients via magnetic resonance imaging and machine learning.

BACKGROUND: Neuroimaging studies of vestibular migraine (VM) have revealed abnormal functional connectivity in the central vestibular system. However,...

CT-based automatic segmentation of key CSF regions for detecting disproportionately enlarged subarachnoid space hydrocephalus.

BACKGROUND: Disproportionately enlarged subarachnoid space hydrocephalus (DESH) is a characteristic neuroimaging feature of idiopathic normal pressure...

Bibliometric analysis of research hotspots in coronary artery CT fractional flow reserve for diagnosing myocardial ischemia in coronary artery disease.

OBJECTIVE: This study aimed to conduct a comprehensive bibliometric analysis to map the global research landscape, identify evolving hotspots, and for...

Outer nuclear layer thinning as an in vivo biomarker for discriminating probable FTLD-tau from probable FTLD-TDP with PET-supported subtyping.

BACKGROUND AND OBJECTIVES: Outer nuclear layer (ONL) thinning has been identified in frontotemporal lobar degeneration (FTLD); however, its utility fo...

Artificial intelligence for detection and segmentation of accessory root canals in endodontic imaging: A systematic review.

Accessory root canal anatomy, including second mesiobuccal (MB2) and middle mesial canals (MMC), is difficult to identify and may compromise endodonti...

Hybrid Physics-Driven Deep Learning for Enhanced Ultrasound Image Quality and Speckle Noise Suppression.

Ultrasound imaging is widely used in clinical practice due to its non-invasive, real-time, and cost-effective nature. However, speckle noise often deg...

A Multi-Task Segmentation and Classification Network Based on Ultrasound Images for Predicting the Grading of Ascites in the Abdominal Cavity.

Abdominal trauma with bleeding is a leading cause of post-traumatic death, and detecting free fluid in the abdomen or hemoperitoneum can provide criti...

Coronary computed tomography angiography to guide percutaneous coronary intervention: proceedings from the 1st CCTA-guided PCI summit in the United States.

Coronary computed tomography angiography (CCTA) can be used beyond diagnostic purposes to support the preprocedural planning of percutaneous coronary ...

Artificial Intelligence-Driven MRI for Cervical Nodal Metastasis Detection in Oral Squamous Cell Carcinoma: A Hierarchical Meta-Analysis of Diagnostic Accuracy.

BACKGROUND: Artificial intelligence (AI) applied to magnetic resonance imaging (MRI) may improve detection of cervical lymph node metastases in oral s...

Accuracy of Key Sonographic Markers for Juxta-Articular Fractures: A Prospective Study Using Explainable Machine Learning.

OBJECTIVES: To systematically evaluate sonographic features of long bone juxta-articular fractures and identify key diagnostic predictors using machin...

From Magnetic Resonance Imaging Radiomics to the Prediction of Regional Nodal Metastasis in Laryngeal Cancer.

OBJECTIVE: To investigate the potential of magnetic resonance imaging (MRI) radiomics-based machine learning (ML) models in predicting local lymph nod...

Noninvasive Electrophysiological Biomarkers of Olfactory Responses Across Cognitive States in Alzheimer Dementia: Cross-Sectional Study.

BACKGROUND: Alzheimer disease (AD) is characterized by progressive cognitive decline, with olfactory dysfunction emerging among its earliest symptoms....

APASA: adaptive selection of informative peritumoral regions for improved automated cancer lesion analysis.

Precise cancer lesion analysis in medical imaging critically depends on the accurate definition of regions of interest (ROIs), which directly influenc...

Applying ensemble machine learning techniques to MRI scans to predict Alzheimer's disease.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia globally. Early prediction, prior to the onset ...