AIMC Topic: Gadolinium DTPA

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Convolutional neural network-automated hepatobiliary phase adequacy evaluation may optimize examination time.

European journal of radiology Jan 14, 2020
PURPOSE: To develop and evaluate the performance of a fully-automated convolutional neural network (CNN)-based algorithm to evaluate hepatobiliary phase (HBP) adequacy of gadoxetate disodium (EOB)-enhanced MRI. Secondarily, we explored the potential ...
Gadolinium DTPA Contrast Media Magnetic Resonance Imaging Liver Image Interpretation, Computer-Assisted Time Area Under Curve Workflow Efficiency ROC Curve Liver Neoplasms Adult Male Middle Aged Humans Neural Networks, Computer Female Aged Algorithms Retrospective Studies
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SANTIS: Sampling-Augmented Neural neTwork with Incoherent Structure for MR image reconstruction.

Magnetic resonance in medicine Jun 5, 2019
PURPOSE: To develop and evaluate a novel deep learning-based reconstruction framework called SANTIS (Sampling-Augmented Neural neTwork with Incoherent Structure) for efficient MR image reconstruction with improved robustness against sampling pattern ...
Gadolinium DTPA Magnetic Resonance Imaging Liver Humans Image Interpretation, Computer-Assisted Neural Networks, Computer Knee Contrast Media
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Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance.

The international journal of cardiovascular imaging Apr 13, 2017
We evaluated the image quality and diagnostic performance of late iodine enhancement computed tomography (LIE-CT) with knowledge-based iterative model reconstruction (IMR) for the detection of myocardial infarction (MI) in comparison with late gadoli...
Computed Tomography Angiography Humans Coronary Circulation Retrospective Studies Myocardial Perfusion Imaging Female Cardiac-Gated Imaging Techniques Electrocardiography Reproducibility of Results Iopamidol Predictive Value of Tests Aged Myocardial Infarction Contrast Media Gadolinium DTPA Myocardium Coronary Angiography Male Knowledge Bases Observer Variation Magnetic Resonance Imaging, Cine Radiographic Image Interpretation, Computer-Assisted Middle Aged Multidetector Computed Tomography Coronary Artery Disease
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Interactive Explainable Deep Learning Model for Hepatocellular Carcinoma Diagnosis at Gadoxetic Acid-enhanced MRI: A Retrospective, Multicenter, Diagnostic Study.

Radiology. Imaging cancer May 1, 2025
Purpose To develop an artificial intelligence (AI) model based on gadoxetic acid-enhanced MRI to assist radiologists in hepatocellular carcinoma (HCC) diagnosis. Materials and Methods This retrospective study included patients with focal liver lesion...
Male Middle Aged Retrospective Studies Deep Learning Female Liver Neoplasms Liver Humans Aged Image Interpretation, Computer-Assisted Adult Image Enhancement Sensitivity and Specificity Carcinoma, Hepatocellular Gadolinium DTPA Contrast Media Magnetic Resonance Imaging
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AI-augmented reconstruction provides improved image quality and enables shorter breath-holds in contrast-enhanced liver MRI.

European radiology experimental May 1, 2025
BACKGROUND: To compare liver image quality and lesion detection using an AI-augmented T1-weighted sequence on hepatobiliary-phase gadoxetate-enhanced magnetic resonance imaging (MRI).
Image Enhancement Breath Holding Gadolinium DTPA Middle Aged Aged Humans Contrast Media Liver Liver Neoplasms Adult Neural Networks, Computer Magnetic Resonance Imaging Image Processing, Computer-Assisted Image Interpretation, Computer-Assisted Male Female
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Deep Learning Radiopathomics Models Based on Contrast-enhanced MRI and Pathologic Imaging for Predicting Vessels Encapsulating Tumor Clusters and Prognosis in Hepatocellular Carcinoma.

Radiology. Imaging cancer Mar 1, 2025
Purpose To develop deep learning (DL) radiopathomics models based on contrast-enhanced MRI and pathologic imaging to predict vessels encapsulating tumor clusters (VETC) and survival in hepatocellular carcinoma (HCC). Materials and Methods In this ret...
Humans Prognosis Retrospective Studies Nomograms Contrast Media Magnetic Resonance Imaging Gadolinium DTPA Middle Aged Deep Learning Liver Neoplasms Female Carcinoma, Hepatocellular Aged Male
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Gd-EOB-DTPA-enhanced MRI Image Characteristics and Radiomics Characteristics Combined with Machine Learning for Assessment of Functional Liver Reserve.

Current medical imaging Jan 1, 2024
OBJECTIVE: To investigate the feasibility of image characteristics and radiomics combined with machine learning based on Gd-EOB-DTPA-enhanced MRI for functional liver reserve assessment in cirrhotic patients.
Retrospective Studies Radiomics Liver Cirrhosis Contrast Media Humans Machine Learning Gadolinium DTPA Magnetic Resonance Imaging Liver Feasibility Studies
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