BACKGROUND: To establish the most effective and safe pre-transcatheter aortic valve implantation (TAVI) CT angiography (CTA) protocol by comparing two approaches in terms of image quality, radiation and contrast dose.
The prediction and management of sudden cardiac death risk continue to pose significant challenges in cardiovascular care despite advances in therapies over the last two decades. Late gadolinium enhancement (LGE) on cardiac magnetic resonance-a marke...
Purpose To improve the generalizability of pathologic complete response prediction following neoadjuvant chemotherapy using deep learning-based retrospective pharmacokinetic quantification of early treatment dynamic contrast-enhanced MRI. Materials a...
OBJECTIVE: To develop a dynamic contrast-enhanced ultrasound (CEUS)-based method for segmenting tumor perfusion subregions, quantifying tumor heterogeneity, and constructing models for distinguishing benign from malignant breast tumors.
RATIONALE AND OBJECTIVES: The aim of this study was to evaluate image quality for contrast-enhanced (CE) neck MRI with a deep learning-reconstructed VIBE sequence with acceleration factors (AF) 4 (DL4-VIBE) and 6 (DL6-VIBE).
PURPOSE: To develop and validate interpretable machine learning models for differentiating glioblastoma (GB) from solitary brain metastasis (SBM) using radiomics features from contrast-enhanced T1-weighted MRI (CE-T1WI), and to compare the impact of ...
High-resolution magnetic resonance angiography (∼ 50 μm MRA) data plays a critical role in the accurate diagnosis of various vascular disorders. However, it is very challenging to acquire, and it is susceptible to artifacts and noise which limits its...
RATIONALE AND OBJECTIVES: Radiogenomics holds promise in identifying molecular alterations in nonsmall cell lung cancer (NSCLC) using imaging features. Previously, we developed a radiogenomics model to predict epidermal growth factor receptor (EGFR) ...
PURPOSE: To develop a multiparametric breast MRI radiomics and deep learning-based multimodal model for predicting preoperative Ki-67 expression status in breast cancer, with the potential to advance individualized treatment and precision medicine fo...
PURPOSE: The purpose of this study is to perform image registration and averaging of multiple free-breathing single-shot cardiac images, where the individual images may have a low signal-to-noise ratio (SNR).
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