AIMC Topic: Contrast Media

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Using interpretable rule-learning artificial intelligence to optimally differentiate adrenal pheochromocytomas from adenomas with CT radiomics.

Abdominal radiology (New York) Mar 26, 2025
PURPOSE: To identify interpretable CT-based radiomics features that can differentiate adrenal pheochromocytomas from adenomas.
Pheochromocytoma Adult Radiomics Male Middle Aged Contrast Media Adenoma Diagnosis, Differential Adrenal Gland Neoplasms Radiographic Image Interpretation, Computer-Assisted Retrospective Studies Humans Tomography, X-Ray Computed Artificial Intelligence Female Machine Learning Aged
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A Novel Visual Model for Predicting Prognosis of Resected Hepatoblastoma: A Multicenter Study.

Academic radiology Mar 26, 2025
RATIONALE AND OBJECTIVES: This study aimed to evaluate the application of a contrast-enhanced CT-based visual model in predicting postoperative prognosis in patients with hepatoblastoma (HB).
Humans Prognosis Retrospective Studies Tomography, X-Ray Computed Female Male Liver Neoplasms Nomograms Contrast Media Hepatoblastoma Risk Assessment Infant Child, Preschool Child
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Preliminary phantom study of four-dimensional computed tomographic angiography for renal artery mapping: Low-tube voltage and low-contrast volume imaging with deep learning-based reconstruction.

Radiography (London, England : 1995) Mar 26, 2025
INTRODUCTION: A hybrid angio-CT system with 320-row detectors and deep learning-based reconstruction (DLR), provides additional imaging via 4D-CT angiography (CTA), potentially shortening procedure time and reducing DSA acquisitions, contrast media, ...
Computed Tomography Angiography Renal Artery Four-Dimensional Computed Tomography Feasibility Studies Radiation Dosage Humans Signal-To-Noise Ratio Deep Learning Phantoms, Imaging Contrast Media Radiographic Image Interpretation, Computer-Assisted
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Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery.

BMC medical imaging Mar 26, 2025
BACKGROUND AND PURPOSE: Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several DL algorithms focu...
Deep Learning Contrast Media Magnetic Resonance Imaging Radiosurgery Humans Aged Algorithms Brain Neoplasms Retrospective Studies Male Female Middle Aged
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Digital mammography with AI-based computer-aided diagnosis to predict neoadjuvant chemotherapy response in HER2-positive and triple-negative breast cancer patients: comparison with MRI.

European radiology Mar 25, 2025
OBJECTIVE: To investigate whether digital mammography (DM) with artificial intelligence-based computer-aided diagnosis (AI-CAD) predicts pathologic complete response (pCR) after neoadjuvant chemotherapy (NAC) in human epidermal growth factor receptor...
Contrast Media Magnetic Resonance Imaging Mammography Receptor, ErbB-2 Retrospective Studies Female Adult Breast Neoplasms Middle Aged Diagnosis, Computer-Assisted Triple Negative Breast Neoplasms Treatment Outcome Neoadjuvant Therapy Humans Artificial Intelligence
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Ovarian masses suggested for MRI examination: assessment of deep learning models based on non-contrast-enhanced MRI sequences for predicting malignancy.

Abdominal radiology (New York) Mar 21, 2025
PURPOSE: We aims to assessed and compare four deep learning(DL) models using non-contrast-enhanced magnetic resonance imaging(MRI) to differentiate benign from malignant ovarian tumors, considering diagnostic efficacy and associated development costs...
Aged Aged, 80 and over Adult Sensitivity and Specificity Middle Aged Humans Retrospective Studies Female Magnetic Resonance Imaging Diagnosis, Differential Ovarian Neoplasms Predictive Value of Tests Image Interpretation, Computer-Assisted Deep Learning Adolescent Child Contrast Media
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Multiple Instance Learning-Based Prediction of Blood-Brain Barrier Opening Outcomes Induced by Focused Ultrasound.

IEEE transactions on bio-medical engineering Mar 21, 2025
OBJECTIVE: Targeted blood-brain barrier (BBB) opening using focused ultrasound (FUS) and micro/nanobubbles is a promising method for brain drug delivery. This study aims to explore the feasibility of multiple instance learning (MIL) in accurate and f...
Machine Learning Signal Processing, Computer-Assisted Animals Blood-Brain Barrier Phospholipids Ultrasonography Drug Delivery Systems Microbubbles Mice Sulfur Hexafluoride Contrast Media Multiple-Instance Learning Algorithms
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Robust resolution improvement of 3D UTE-MR angiogram of normal vasculatures using super-resolution convolutional neural network.

Scientific reports Mar 18, 2025
Contrast-enhanced UTE-MRA provides detailed angiographic information but at the cost of prolonged scanning periods, which may impose moving artifacts and affect the promptness of diagnosis and treatment of time-sensitive diseases like stroke. This st...
Stroke Magnetic Resonance Angiography Neural Networks, Computer Animals Male Imaging, Three-Dimensional Deep Learning Convolutional Neural Networks Rats, Wistar Rats Contrast Media
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Diagnosis of moderate-to-severe hepatic steatosis using deep learning-based automated attenuation measurements on contrast-enhanced CT.

Abdominal radiology (New York) Mar 17, 2025
PURPOSE: To evaluate the utility of deep learning-based automated attenuation measurements on contrast-enhanced CT (CECT) for diagnosing moderate-to-severe hepatic steatosis (HS), using histology as reference standard.
Humans Retrospective Studies Tomography, X-Ray Computed Female Adult Deep Learning Fatty Liver Contrast Media Liver Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Male Middle Aged Severity of Illness Index Radiographic Image Enhancement
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Preoperative Assessment of Ki-67 Labeling Index in Pituitary Adenomas Using Delta-Radiomics Based on Dynamic Contrast-Enhanced MRI.

Journal of magnetic resonance imaging : JMRI Mar 17, 2025
BACKGROUND: Ki-67 labeling index (Ki-67 LI) is a proliferation marker that is correlated with aggressive behavior and prognosis of pituitary adenomas (PAs). Dynamic contrast-enhanced MRI (DCE-MRI) may potentially contribute to the preoperative assess...
Preoperative Care Ki-67 Antigen Contrast Media Magnetic Resonance Imaging Pituitary Neoplasms Adenoma Retrospective Studies Female Reproducibility of Results Aged Adult Radiomics Male Humans Middle Aged ROC Curve
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