Radiology

Use of contrast-enhanced mammography for preoperative prediction of lymphovascular invasion status in invasive breast cancer.

BACKGROUND: To investigate the use of contrast-enhanced mammography (CEM) for preoperative prediction of lymphovascular invasion (LVI) status in invasive breast cancer. METHODS: A total of 243 female patients diagnosed with invasive breast cancer (median age: 49 years; range: 27-77 years) who received preoperative CEM examination in our hospital between September 2018 and February 2024 were retros...

[18F] PSMA-3Q PET/CT radiomics at 45% SUVmax threshold: predicting post-surgical ISUP grade ≥ 4 and extraprostatic extension for noninvasive stratification in prostate cancer management.

OBJECTIVE: To systematically evaluate radiomic features extracted from [18F] PSMA-3Q PET/CT using 40%, 45%, and 50% SUVmax thresholds for their ability to predict post-surgical International Society of Urological Pathology (psISUP) grading and extraprostatic extension (EPE) in prostate cancer and ultimately develop an optimal threshold-based predictive model. MATERIALS & METHODS: This retrospectiv...

No-reflow phenomenon during percutaneous coronary intervention: Contemporary insights into mechanisms, prediction, and management.

No-reflow phenomenon remains a common and prognostically adverse complication of percutaneous coronary intervention (PCI), characterized by impaired m...

Optimizing Military Teledermatology: A Controlled Interventional Study on the Impact of a Standardized Store-and-Forward Protocol.

Cascaded Deep Learning enables multimodal brain PET spatial normalization and quantification for Alzheimer's disease.

Semi-quantitative positron emission tomography (PET) analysis, particularly Centiloid and CenTauRz scaling, is essential for Alzheimer's disease (AD) ...

Cardiac magnetic resonance in patients with acute myocardial infarction: The added clinical value.

Cardiovascular magnetic resonance (CMR) has emerged as the reference noninvasive modality for a comprehensive assessment of myocardial injury followin...

Fully Automated Free-Breathing Cardiac MRI at 3T: A Prospective Randomized Study of Image Quality, Efficiency, and Workflow Burden.

BACKGROUND: Automation in cardiac magnetic resonance (CMR) scans holds the potential to improve examination efficiency and workflow consistency. Prosp...

Use of artificial intelligence in magnetic resonance imaging across the epileptic patient's journey: A meta-analysis of four clinical applications.

OBJECTIVE: The application of artificial intelligence/machine learning (AI/ML) to magnetic resonance imaging (MRI) promises to enhance and support cli...

Assessing and mitigating demographic bias in large language models for diagnostic radiology.

PURPOSE: Large language models (LLMs) are increasingly integrated into radiology workflows, but their demographic biases have not been evaluated in di...

Zero echo time MRI with deep learning reconstruction and chemical shift correction for detecting osteolytic myeloma lesions.

OBJECTIVE: We compared three magnetic resonance imaging (MRI) sequences-native zero echo time (ZTE), deep learning (DL)-chemical shift correction (CSC...

Whole anterior visual pathway segmentation from high-resolution MRI using artificial intelligence.

OBJECTIVE: Manual segmentation of the whole anterior visual pathway (aVP) from high-resolution magnetic resonance imaging (MRI) is time-consuming and ...

Infant Brain Age Estimation With T1w/T2w Ratio MRI: A Myelination-Aware Deep Learning Approach.

BACKGROUND: Brain age estimation provides a noninvasive MRI biomarker of neurodevelopment. In infancy, rapid regionally ordered myelination reflects b...

Application of Focused Ultrasound in Alzheimer's Disease: A Bibliometric Analysis.

OBJECTIVE: This study uses bibliometric analysis and knowledge mapping methods to systematically explore the emerging research frontiers and developme...

Artificial intelligence in prostate cancer imaging: A mini-review of current applications and future directions.

This mini-review synthesizes evidence from recent studies to provide an updated perspective on current applications, methodological challenges, and fu...

Hybrid learning: a combination of self-supervised and supervised learning for joint MRI reconstruction and denoising in low-field MRI.

Deep learning has demonstrated strong potential for MRI reconstruction. However, conventional supervised learning requires high-quality, high-SNR refe...

Hyperspectral Imaging for Breast-Conserving Surgery Margin Assessment: A Systematic Review.

CONTEXT.—: Breast-conserving surgery (BCS) offers comparable overall survival rates to mastectomy. However, 14% to 37% of cases require re-excision ow...

Deep Multi-Task Attention Network for Automated, Reproducible Quantification of Carotid Plaque Burden in Ultrasound Imaging.

Carotid atherosclerotic plaque burden is a well-established biomarker of cerebrovascular and cardiovascular risk, yet its quantitative assessment from...

Development of LRRC15-binding disulfide-constrained peptides for PET imaging of cancer-associated fibroblasts.

Leucine-rich-repeat-containing protein 15 (LRRC15) is selectively expressed on cancer-associated fibroblasts (CAFs) and constitutes a promising biomar...

Deep learning based on multiparametric MRI for differentiating benign from malignant PI-RADS 3 prostate lesions: a dual-center study.

To address the diagnostic challenge of indeterminate PI-RADS 3 prostate lesions, we developed a non-invasive deep learning radiomics model using multi...

Three-dimensional artificial intelligence-based computed tomography analysis of lower limb muscle volume and fatty degeneration in varus and valgus knee osteoarthritis: a single-center retrospective study.

BACKGROUND: Despite the high prevalence of knee osteoarthritis, the anatomical factors that characterize distinct deformity patterns remain unclear. T...