AIMC Topic: Contrast Media

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Predictive Value of Neutrophil Gelatinase-Associated Lipocalin for Contrast-Induced Acute Kidney Injury After Cardiac Catheterization: A Meta-analysis.

The Canadian journal of cardiology Sep 30, 2015
BACKGROUND: Neutrophil gelatinase-associated lipocalin (NGAL) accumulates in cortical tubules in acute kidney injury (AKI) patients, with its levels associated with serum creatinine. However, the predictive value of NGAL level for contrast-induced ac...
Humans Time Factors Biomarkers Contrast Media Acute Kidney Injury Sensitivity and Specificity Predictive Value of Tests Lipocalin-2 Cardiac Catheterization
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Myocardial Fractional Flow Reserve Measurement Using Contrast Media as a First-Line Assessment of Coronary Lesions in Current Practice.

The Canadian journal of cardiology Sep 25, 2015
BACKGROUND: Fractional flow reserve (FFR) measurement requires adenosine injection. However, adenosine can induce conductive and rhythmic complications, or be contraindicated in some patients. Contrast-induced hyperemia could provide a simple first-l...
Coronary Angiography Humans Patient Selection Fractional Flow Reserve, Myocardial Prospective Studies Risk Factors Risk Assessment Female Adenosine France Aged Reproducibility of Results Body Mass Index Sensitivity and Specificity Triiodobenzoic Acids Contrast Media Male Coronary Stenosis Predictive Value of Tests Middle Aged
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Support vector machine classification of brain metastasis and radiation necrosis based on texture analysis in MRI.

Journal of magnetic resonance imaging : JMRI Apr 10, 2015
PURPOSE: To develop a classification model using texture features and support vector machine in contrast-enhanced T1-weighted images to differentiate between brain metastasis and radiation necrosis.
Diagnosis, Differential Retrospective Studies Area Under Curve Female Image Enhancement Reproducibility of Results Radiation Injuries Brain Neoplasms Middle Aged Necrosis Male Support Vector Machine Contrast Media Magnetic Resonance Imaging Humans Brain
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A generic support vector machine model for preoperative glioma survival associations.

Radiology Dec 8, 2014
PURPOSE: To develop a generic support vector machine (SVM) model by using magnetic resonance (MR) imaging-based blood volume distribution data for preoperative glioma survival associations and to prospectively evaluate the diagnostic effectiveness of...
Humans Retrospective Studies Female Aged Aged, 80 and over Adult Brain Neoplasms Male Middle Aged Magnetic Resonance Imaging Adolescent Survival Analysis Glioma Image Interpretation, Computer-Assisted Support Vector Machine Contrast Media
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Denoising of high-resolution 3D UTE-MR angiogram data using lightweight and efficient convolutional neural networks.

Magnetic resonance imaging Sep 1, 2025
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...
Algorithms Convolutional Neural Networks Imaging, Three-Dimensional Image Processing, Computer-Assisted Contrast Media Artifacts Signal-To-Noise Ratio Magnetic Resonance Angiography Humans Phantoms, Imaging Neural Networks, Computer
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Study on predicting breast cancer Ki-67 expression using a combination of radiomics and deep learning based on multiparametric MRI.

Magnetic resonance imaging Sep 1, 2025
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...
Multiparametric Magnetic Resonance Imaging ROC Curve Image Processing, Computer-Assisted Contrast Media Magnetic Resonance Imaging Predictive Value of Tests Breast Image Interpretation, Computer-Assisted Ki-67 Antigen Humans Diffusion Magnetic Resonance Imaging Sensitivity and Specificity Female Breast Neoplasms Reproducibility of Results Radiomics Aged Middle Aged Adult Deep Learning
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Deep learning reconstruction for T2-weighted and contrast-enhanced T1-weighted magnetic resonance enterography imaging in patients with Crohn's disease: Assessment of image quality and clinical utility.

Clinical imaging Aug 1, 2025
PURPOSE: To investigate the image quality of deep learning-reconstructed T2-weighted half-Fourier single-shot turbo spin echo (DL T2 HASTE) and contrast-enhanced T1-weighted volumetric interpolated breath-hold examination (DL T1 VIBE) of magnetic res...
Humans Retrospective Studies Female Reproducibility of Results Crohn Disease Image Interpretation, Computer-Assisted Middle Aged Deep Learning Adolescent Contrast Media Magnetic Resonance Imaging Aged Young Adult Adult Male
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Discriminating Clear Cell From Non-Clear Cell Renal Cell Carcinoma: A Machine Learning Approach Using Contrast-enhanced Ultrasound Radiomics.

Ultrasound in medicine & biology Aug 1, 2025
OBJECTIVE: The aim of this investigation is to assess the clinical usefulness of a machine learning model using contrast-enhanced ultrasound (CEUS) radiomics in discriminating clear cell renal cell carcinoma (ccRCC) from non-ccRCC.
Kidney Contrast Media Diagnosis, Differential Image Interpretation, Computer-Assisted Kidney Neoplasms Radiomics Male Middle Aged Ultrasonography Retrospective Studies Humans Image Enhancement Female Machine Learning Carcinoma, Renal Cell Aged Aged, 80 and over Adult
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Renal Transplant Survival Prediction From Unsupervised Deep Learning-Based Radiomics on Early Dynamic Contrast-Enhanced MRI.

Academic radiology Aug 1, 2025
RATIONALE AND OBJECTIVES: End-stage renal disease is characterized by an irreversible decline in kidney function. Despite a risk of chronic dysfunction of the transplanted kidney, renal transplantation is considered the most effective solution among ...
Female Adult Radiomics Male Middle Aged Humans Kidney Transplantation Retrospective Studies Kidney Failure, Chronic Deep Learning Graft Survival Contrast Media Magnetic Resonance Imaging Unsupervised Machine Learning
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Contrast-enhanced image synthesis using latent diffusion model for precise online tumor delineation in MRI-guided adaptive radiotherapy for brain metastases.

Physics in medicine and biology Jul 3, 2025
Magnetic resonance imaging-guided adaptive radiotherapy (MRIgART) is a promising technique for long-course radiotherapy of large-volume brain metastasis (BM), due to the capacity to track tumor changes throughout treatment course. Contrast-enhanced T...
Image Processing, Computer-Assisted Contrast Media Magnetic Resonance Imaging Diffusion Radiotherapy, Image-Guided Humans Brain Neoplasms Deep Learning
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