AIMC Topic: Contrast Media

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Enabling AI-Generated Content for Gadolinium-Free Contrast-Enhanced Breast Magnetic Resonance Imaging.

Journal of magnetic resonance imaging : JMRI Jul 25, 2024
BACKGROUND: There is increasing interest in utilizing AI-generated content for gadolinium-free contrast-enhanced breast MRI.
Imaging, Three-Dimensional Image Processing, Computer-Assisted Contrast Media Magnetic Resonance Imaging Humans Breast Artificial Intelligence Image Interpretation, Computer-Assisted Algorithms Gadolinium Retrospective Studies Image Enhancement Aged Female Diffusion Magnetic Resonance Imaging Adult Reproducibility of Results Sensitivity and Specificity Breast Neoplasms Middle Aged
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Utility of Thin-slice Fat-suppressed Single-shot T2-weighted MR Imaging with Deep Learning Image Reconstruction as a Protocol for Evaluating the Pancreas.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Jul 21, 2024
PURPOSE: To compare the utility of thin-slice fat-suppressed single-shot T2-weighted imaging (T2WI) with deep learning image reconstruction (DLIR) and conventional fast spin-echo T2WI with DLIR for evaluating pancreatic protocol.
Retrospective Studies Female Aged Aged, 80 and over Adipose Tissue Humans Male Middle Aged Pancreas Pancreatic Neoplasms Deep Learning Signal-To-Noise Ratio Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Gadolinium DTPA Contrast Media Magnetic Resonance Imaging
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Deep learning-based 3D quantitative total tumor burden predicts early recurrence of BCLC A and B HCC after resection.

European radiology Jul 19, 2024
OBJECTIVES: This study aimed to evaluate the potential of deep learning (DL)-assisted automated three-dimensional quantitative tumor burden at MRI to predict postoperative early recurrence (ER) of hepatocellular carcinoma (HCC).
Magnetic Resonance Imaging Predictive Value of Tests Neoplasm Recurrence, Local Tumor Burden Hepatectomy Deep Learning Prognosis Liver Neoplasms Retrospective Studies Aged Humans Carcinoma, Hepatocellular Female Male Imaging, Three-Dimensional Middle Aged Contrast Media
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Fully automated segmentation and volumetric measurement of ocular adnexal lymphoma by deep learning-based self-configuring nnU-net on multi-sequence MRI: a multi-center study.

Neuroradiology Jul 17, 2024
PURPOSE: To evaluate nnU-net's performance in automatically segmenting and volumetrically measuring ocular adnexal lymphoma (OAL) on multi-sequence MRI.
Humans Eye Neoplasms Retrospective Studies Female Aged Aged, 80 and over Adult Sensitivity and Specificity Male Middle Aged Deep Learning Lymphoma Contrast Media Magnetic Resonance Imaging Image Interpretation, Computer-Assisted
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Preoperative Contrast-Enhanced CT-Based Deep Learning Radiomics Model for Distinguishing Retroperitoneal Lipomas and Well‑Differentiated Liposarcomas.

Academic radiology Jul 14, 2024
RATIONALE AND OBJECTIVES: To assess the efficacy of a preoperative contrast-enhanced CT (CECT)-based deep learning radiomics nomogram (DLRN) for predicting murine double minute 2 (MDM2) gene amplification as a means of distinguishing between retroper...
Lipoma Adult Humans Liposarcoma Radiomics Retrospective Studies Nomograms Retroperitoneal Neoplasms Male Tomography, X-Ray Computed Contrast Media Preoperative Care Middle Aged Female Diagnosis, Differential Deep Learning Aged
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Low energy virtual monochromatic CT with deep learning image reconstruction to improve delineation of endoleaks.

Clinical radiology Jul 9, 2024
AIM: This study aimed to investigate the utility of low-energy virtual monochromatic imaging (VMI) combined with deep-learning image reconstruction (DLIR) in improving the delineation of endoleaks (ELs) after endovascular aortic repair (EVAR) in cont...
Radiographic Image Interpretation, Computer-Assisted Aged, 80 and over Humans Endovascular Procedures Male Retrospective Studies Endoleak Deep Learning Tomography, X-Ray Computed Radiography, Dual-Energy Scanned Projection Contrast Media Female Aortic Aneurysm, Abdominal Aged
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Deep learning-based segmentation of left ventricular myocardium on dynamic contrast-enhanced MRI: a comprehensive evaluation across temporal frames.

International journal of computer assisted radiology and surgery Jul 4, 2024
PURPOSE: Cardiac perfusion MRI is vital for disease diagnosis, treatment planning, and risk stratification, with anomalies serving as markers of underlying ischemic pathologies. AI-assisted methods and tools enable accurate and efficient left ventric...
Magnetic Resonance Imaging Heart Ventricles Adult Humans Male Retrospective Studies Middle Aged Female Deep Learning Aged Contrast Media
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Characterizing Sentinel Lymph Node Status in Breast Cancer Patients Using a Deep-Learning Model Compared With Radiologists' Analysis of Grayscale Ultrasound and Lymphosonography.

Ultrasound quarterly Jul 3, 2024
The objective of the study was to use a deep learning model to differentiate between benign and malignant sentinel lymph nodes (SLNs) in patients with breast cancer compared to radiologists' assessments.Seventy-nine women with breast cancer were enro...
Breast Sentinel Lymph Node Sentinel Lymph Node Biopsy Ultrasonography Lymphatic Metastasis Contrast Media Radiologists Ultrasonography, Mammary Humans Female Reproducibility of Results Aged Adult Breast Neoplasms Middle Aged Deep Learning
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Prospective Deployment of Deep Learning Reconstruction Facilitates Highly Accelerated Upper Abdominal MRI.

Academic radiology Jul 2, 2024
RATIONALE AND OBJECTIVES: To compare a conventional T1 volumetric interpolated breath-hold examination (VIBE) with SPectral Attenuated Inversion Recovery (SPAIR) fat saturation and a deep learning (DL)-reconstructed accelerated VIBE sequence with SPA...
Image Interpretation, Computer-Assisted Signal-To-Noise Ratio Organometallic Compounds Humans Breath Holding Prospective Studies Female Aged Middle Aged Male Deep Learning Abdomen Contrast Media Magnetic Resonance Imaging
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A comparative analysis of deep learning and hybrid iterative reconstruction algorithms with contrast-enhancement-boost post-processing on the image quality of indirect computed tomography venography of the lower extremities.

BMC medical imaging Jul 1, 2024
PURPOSE: To examine whether there is a significant difference in image quality between the deep learning reconstruction (DLR [AiCE, Advanced Intelligent Clear-IQ Engine]) and hybrid iterative reconstruction (HIR [AIDR 3D, adaptive iterative dose redu...
Humans Algorithms Adult Male Middle Aged Deep Learning Venous Thrombosis Contrast Media Retrospective Studies Tomography, X-Ray Computed Female Aged Aged, 80 and over Radiographic Image Enhancement Lower Extremity Phlebography Radiographic Image Interpretation, Computer-Assisted Femoral Vein Radiation Dosage Varicose Veins Vena Cava, Inferior Popliteal Vein Computed Tomography Angiography
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