Radiology

Fully automated volumetric assessment of tumor burden using artificial intelligence on 68Ga-PSMA-11 PET predicts survival after 177Lu-PSMA therapy in metastatic Castration-resistant prostate cancer.

PURPOSE: Despite the rapid development of artificial intelligence (AI)-powered automated segmentation tools for PET/CT imaging, their prognostic value in predicting survival outcomes remains inadequately assessed. Our objective was to explore the prognostic significance of tumor burden quantification derived from PSMA PET/CT using AI for metastatic castration-resistant prostate cancer (mCRPC) pati...

Real-world diagnostic performance of knee MRI protocols accelerated using simultaneous multi-slice acquisition and deep learning reconstruction.

OBJECTIVE: To assess whether accelerated knee MRI protocols using simultaneous multi-slice (SMS) and deep learning reconstruction (DLR) are non-inferior to a conventional parallel imaging protocol for detecting internal derangement injuries. METHODS: This retrospective cohort study included 1055 patients who underwent knee MRI followed by arthroscopy within 180 days. Patients were scanned using ei...

Utility of multimodal deep learning model to diagnose lymph node metastasis in esophageal cancer using computed tomography and positron emission tomography images.

PURPOSE: This study aimed to assess the performance of a deep learning model using multimodal imaging for detecting lymph node metastasis in esophagea...

Comprehensive deep learning-assisted multi-condition analysis of knee MRI studies improves resident radiologist performance.

OBJECTIVES: Developing a deep-learning model for automated multi-tissue, multi-condition knee MRI analysis and assessing its clinical potential. MATER...

Artificial intelligence in diagnostic imaging: collaborative asset or looming replacement?

Artificial intelligence (AI) is rapidly transforming diagnostic imaging, raising important questions about its role as a collaborative tool or a poten...

A Simplified and Data-Driven Lung Ultrasound Approach for Predicting Surfactant Need in Preterm Infants: A Pilot Study Using Machine Learning and Rule-Based Models.

OBJECTIVES: Six-region lung ultrasound (LUS) scores show good predictive value for predicting surfactant need in preterm infants but rely on a fixed t...

Real-Time Phase-Contrast Cardiovascular MRI Using a Deep Learning Reconstruction Network With Combined Dictionary Learning and CNN.

PURPOSE: This study aims to develop real-time phase-contrast (PC) cardiovascular MRI with low latency. METHODS: In this study, a framework using golde...

Comparisons of the reliability of airway measurements on cone beam computed tomography scans among human raters and a convolutional neural network.

OBJECTIVE: To evaluate the performance of commercially available AI tools in airway evaluation in clinical conditions. STUDY DESIGN: 100 anonymized co...

High-precision wavefield simulation and deep learning-based sound speed reconstruction for transcranial ultrasound imaging.

Transcranial ultrasound imaging plays an important role in the diagnosis of brain diseases and the monitoring of brain function. However, the quality ...

Clinical evaluation of deep learning-based CT-free PET reconstruction image: a dual-center study.

PURPOSE: Efforts to reduce the radiation burden of PET/CT have driven the increasing development of AI-based CT-less PET imaging techniques. However, ...

Prostate cancer and benign prostatic hyperplasia lesions segmentation using diffusion kurtosis imaging, T2*, and R2* mapping with U-Net++ algorithm.

This study aimed to propose a deep learning-based segmentation framework to delineate prostate lesions across multiple MRI acquisitions and derived pa...

CT-FFR: How a new technology could transform cardiovascular diagnostic imaging.

CT-based fractional flow reserve (CT-FFR) is a promising noninvasive method for the functional assessment of coronary stenosis. It expands the diagnos...

Cingulate atrophy as a shared structural basis for cognitive and functional brain impairments in GAD, PD, and OCD: Links to shared gene expression and treatment implications.

BACKGROUND: Structural brain deficits associated with generalized anxiety disorder (GAD), panic disorder (PD), and obsessive-compulsive disorder (OCD)...

Development and validation of a nomogram combining PI-RADS v2.1 and clinical indicators for the diagnosis of prostate cancer in patients with PSA ≤ 20 ng/mL.

PURPOSE: This investigation focused on developing a predictive clinical tool that combines biparametric MRI-derived PI-RADS v2.1 assessments with pati...

Radiomics-based IVIM-DWI for early noninvasive assessment of renal allograft dysfunction.

OBJECTIVE: To develop and rigorously validate radiomics-based predictive models using postoperative intravoxel incoherent motion diffusion-weighted im...

Artificial Intelligence in Abdominal MRI Diagnostics: Current Applications, Challenges, and Future Perspectives.

The increasing availability of large image data sets and technical advances in the field of information technology have also greatly advanced the use ...

Artificial Intelligence 3D Augmented Reality-guided Robotic Prostatectomy Versus Cognitive MRI Intervention: Results of the Prospective Randomized RIDERS Trial.

BACKGROUND AND OBJECTIVE: Three-dimensional (3D) augmented reality (AR) and artificial intelligence (AI) technologies have recently been introduced to...

Deep learning enhanced label-free cervical screening via stimulated Raman cytology.

Cervical cancer screening remains pivotal for early detection and effective disease management, yet conventional cytopathological methods relying on s...

Diagnostic performance of a coronary CT angiography-based deep learning model for the prediction of vessel-specific ischemia.

OBJECTIVES: Fractional flow reserve (FFR) and instantaneous wave-Free Ratio (iFR) pressure measurements during invasive coronary angiography (ICA) are...

Do patients with renal calculi exhibit viscerosomatic reflexes as evident on CT imaging?

CONTEXT: Experimental evidence supporting the existence of the viscerosomatic reflex highlights an involvement of multiple vertebral levels when renal...