AIMC Topic: Contrast Media

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Denoising Diffusion Probabilistic Model to Simulate Contrast-enhanced spinal MRI of Spinal Tumors: A Multi-Center Study.

Academic radiology Feb 28, 2025
RATIONALE AND OBJECTIVES: To generate virtual T1 contrast-enhanced (T1CE) sequences from plain spinal MRI sequences using the denoising diffusion probabilistic model (DDPM) and to compare its performance against one baseline model pix2pix and three a...
Algorithms Computer Simulation Female Reproducibility of Results Aged Humans Spinal Neoplasms Image Enhancement Signal-To-Noise Ratio Diffusion Magnetic Resonance Imaging Contrast Media Magnetic Resonance Imaging Models, Statistical Image Interpretation, Computer-Assisted Artifacts Adult Sensitivity and Specificity Male Middle Aged
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Prediction of contrast-associated acute kidney injury with machine-learning in patients undergoing contrast-enhanced computed tomography in emergency department.

Scientific reports Feb 27, 2025
Radiocontrast media is a major cause of nephrotoxic acute kidney injury(AKI). Contrast-enhanced CT(CE-CT) is commonly performed in emergency departments(ED). Predicting individualized risks of contrast-associated AKI(CA-AKI) in ED patients is challen...
Adult Acute Kidney Injury Male Humans Emergency Service, Hospital Female Middle Aged Machine Learning Risk Factors Creatinine Contrast Media Retrospective Studies Aged Tomography, X-Ray Computed
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RAE-Net: a multi-modal neural network based on feature fusion and evidential deep learning algorithm in predicting breast cancer subtypes on DCE-MRI.

Biomedical physics & engineering express Feb 25, 2025
Accurate identification of molecular subtypes in breast cancer is critical for personalized treatment. This study introduces a novel neural network model, RAE-Net, based on Multimodal Feature Fusion (MFF) and the Evidential Deep Learning Algorithm (E...
Adult Breast Neoplasms Middle Aged Deep Learning Image Processing, Computer-Assisted Algorithms Female Reproducibility of Results Aged Contrast Media Magnetic Resonance Imaging Dynamic Contrast Enhanced Magnetic Resonance Imaging Humans Neural Networks, Computer
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[MP-MRI in the evaluation of non-operative treatment response, for residual and recurrent tumor detection in head and neck cancer].

Magyar onkologia Feb 23, 2025
As non-surgical therapies gain acceptance in head and neck tumors, the importance of imaging has increased. New therapeutic methods (in radiation therapy, targeted biological therapy, immunotherapy) need better tumor characterization and prognostic i...
Multiparametric Magnetic Resonance Imaging Neoplasm Staging Neoplasm Recurrence, Local Neoplasm, Residual Diffusion Magnetic Resonance Imaging Humans Treatment Outcome Head and Neck Neoplasms Contrast Media Magnetic Resonance Imaging
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Multimodal deep learning fusion of ultrafast-DCE MRI and clinical information for breast lesion classification.

Computers in biology and medicine Feb 19, 2025
BACKGROUND: Breast cancer is the most common cancer worldwide, and magnetic resonance imaging (MRI) constitutes a very sensitive technique for invasive cancer detection. When reviewing breast MRI examination, clinical radiologists rely on multimodal ...
Breast Image Interpretation, Computer-Assisted Middle Aged Retrospective Studies Deep Learning Female Humans Contrast Media Aged Magnetic Resonance Imaging Adult Breast Neoplasms
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Deep Learning-Based Signal Amplification of T1-Weighted Single-Dose Images Improves Metastasis Detection in Brain MRI.

Investigative radiology Feb 18, 2025
OBJECTIVES: Double-dose contrast-enhanced brain imaging improves tumor delineation and detection of occult metastases but is limited by concerns about gadolinium-based contrast agents' effects on patients and the environment. The purpose of this stud...
Humans Prospective Studies Female Aged Deep Learning Contrast Media Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Image Enhancement Sensitivity and Specificity Brain Neoplasms Male Middle Aged
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Machine learning model based on preoperative contrast-enhanced CT and clinical features to predict perineural invasion in gallbladder carcinoma patients.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology Feb 16, 2025
BACKGROUND: Perineural invasion (PNI) is an independent prognostic risk factor for gallbladder carcinoma (GBC). However, there is currently no reliable method for the preoperative noninvasive prediction of PNI.
Adult Tomography, X-Ray Computed Neoplasm Staging Male Female Peripheral Nerves Humans Middle Aged Risk Factors Gallbladder Neoplasms Machine Learning Contrast Media Aged Retrospective Studies Neoplasm Invasiveness
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Artificial intelligence can extract important features for diagnosing axillary lymph node metastasis in early breast cancer using contrast-enhanced ultrasonography.

Scientific reports Feb 15, 2025
Contrast-enhanced ultrasound (CEUS) plays a pivotal role in the diagnosis of primary breast cancer and in axillary lymph node (ALN) metastasis. However, the imaging features that are clinically crucial for lymph node metastasis have not been fully el...
Retrospective Studies Female Aged Adult Breast Neoplasms Middle Aged Lymphatic Metastasis Ultrasonography Contrast Media ROC Curve Axilla Lymph Nodes Humans Artificial Intelligence
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A Bi-modal Temporal Segmentation Network for Automated Segmentation of Focal Liver Lesions in Dynamic Contrast-enhanced Ultrasound.

Ultrasound in medicine & biology Feb 14, 2025
OBJECTIVE: To develop and validate an automated deep learning-based model for focal liver lesion (FLL) segmentation in a dynamic contrast-enhanced ultrasound (CEUS) video.
Middle Aged Deep Learning Ultrasonography Liver Neoplasms Contrast Media Liver Retrospective Studies Image Interpretation, Computer-Assisted Female Image Enhancement Aged Humans Adult Male
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Artificial Intelligence Model for Detection of Colorectal Cancer on Routine Abdominopelvic CT Examinations: A Training and External-Testing Study.

AJR. American journal of roentgenology Feb 12, 2025
Radiologists are prone to missing some colorectal cancers (CRCs) on routine abdominopelvic CT examinations that are in fact detectable on the images. The purpose of this study was to develop an artificial intelligence (AI) model to detect CRC on ro...
Colorectal Neoplasms Male Middle Aged Contrast Media Pelvis Radiographic Image Interpretation, Computer-Assisted Radiography, Abdominal Aged Aged, 80 and over Adult Sensitivity and Specificity Artificial Intelligence Retrospective Studies Tomography, X-Ray Computed Female Humans
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