scholarly journals Gadobenate dimeglumine-enhanced magnetic resonance imaging of intracranial metastases: Effect of dose on lesion detection and delineation

2001 ◽  
Vol 14 (5) ◽  
pp. 525-539 ◽  
Author(s):  
G�nther Schneider ◽  
Miles A. Kirchin ◽  
Gianpaolo Pirovano ◽  
Cesare Colosimo ◽  
Jordi Ruscalleda ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Gadobenate Dimeglumine ◽  
Lesion Detection ◽  
Resonance Imaging ◽  
Intracranial Metastases

A Pictorial Review of Hepatobiliary Magnetic Resonance Imaging with Hepatocyte-Specific Contrast Agents: Uses, Findings, and Pitfalls of Gadoxetate Disodium and Gadobenate Dimeglumine

2017 ◽  
Vol 68 (3) ◽  
pp. 293-307 ◽  
Author(s):  
Elena P. Scali ◽  
Triona Walshe ◽  
Hina Arif Tiwari ◽  
Alison C. Harris ◽  
Silvia D. Chang
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Contrast Agents ◽  
The United States ◽  
Gadobenate Dimeglumine ◽  
Lesion Detection ◽  
Focal Liver Lesions ◽  
Gadoxetate Disodium ◽  
Resonance Imaging ◽  
Pictorial Review

Magnetic resonance imaging (MRI) has a well-established role as a highly specific and accurate modality for characterizing benign and malignant focal liver lesions. In particular, contrast-enhanced MRI using hepatocyte-specific contrast agents (HSCAs) improves lesion detection and characterization compared to other imaging modalities and MRI techniques. In this pictorial review, the mechanism of action of gadolinium-based MRI contrast agents, with a focus on HSCAs, is described. The clinical indications, protocols, and emerging uses of the 2 commercially available combined contrast agents available in the United States, gadoxetate disodium and gadobenate dimeglumine, are discussed. The MRI features of these agents are compared with examples of focal hepatic masses, many of which have been obtained within the same patient therefore allowing direct lesion comparison. Finally, the pitfalls in the use of combined contrast agents in liver MRI are highlighted.

scholarly journals A Gadolinium(III) Complex Based on the Thymine Nucleobase with Properties Suitable for Magnetic Resonance Imaging

2021 ◽  
Vol 22 (9) ◽  
pp. 4586
Author(s):  
Marta Orts-Arroyo ◽  
Amadeo Ten-Esteve ◽  
Sonia Ginés-Cárdenas ◽  
Isabel Castro ◽  
Luis Martí-Bonmatí ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Mr Imaging ◽  
Lesion Detection ◽  
Resonance Imaging ◽  
X Ray Diffraction ◽  
Functional Images ◽  
High Relaxivity ◽  
Contrast Enhanced ◽  
Phantom Studies

The paramagnetic gadolinium(III) ion is used as contrast agent in magnetic resonance (MR) imaging to improve the lesion detection and characterization. It generates a signal by changing the relaxivity of protons from associated water molecules and creates a clearer physical distinction between the molecule and the surrounding tissues. New gadolinium-based contrast agents displaying larger relaxivity values and specifically targeted might provide higher resolution and better functional images. We have synthesized the gadolinium(III) complex of formula [Gd(thy)2(H2O)6](ClO4)3·2H2O (1) [thy = 5-methyl-1H-pyrimidine-2,4-dione or thymine], which is the first reported compound based on gadolinium and thymine nucleobase. 1 has been characterized through UV-vis, IR, SEM-EDAX, and single-crystal X-ray diffraction techniques, and its magnetic and relaxometric properties have been investigated by means of SQUID magnetometer and MR imaging phantom studies, respectively. On the basis of its high relaxivity values, this gadolinium(III) complex can be considered a suitable candidate for contrast-enhanced magnetic resonance imaging.

Prostate Magnetic Resonance Imaging: Lesion Detection and Local Staging

2019 ◽  
Vol 70 (1) ◽  
pp. 451-459 ◽  
Author(s):  
Baris Turkbey ◽  
Peter L. Choyke
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Lesion Detection ◽  
Lower Sensitivity ◽  
Resonance Imaging ◽  
Prostate Mri ◽  
Local Staging ◽  
Clinically Significant ◽  
Magnetic Resonance Imaging Mri ◽  
Indolent Disease

Dramatic changes in the use of prostate magnetic resonance imaging (MRI) have occurred in the last decade. The recognition that MRI detects and localizes cancers with reasonable accuracy led to the development of directed biopsies. These image-guided biopsies have a higher sensitivity for clinically significant cancers and a lower sensitivity for indolent disease. Prospective trials provide level 1 evidence supporting the use of prostate MRI. For local staging, while the specificity of prostate MRI is high, its sensitivity is lacking for microscopic extraprostatic extension. Computer-aided diagnosis of prostate MRI promises to bring the diagnostic power of MRI to nonexpert readers and thus further integrate MRI into the diagnostic workup.

scholarly journals Automated Detection and Segmentation of Nonmass-Enhancing Breast Tumors with Dynamic Contrast-Enhanced Magnetic Resonance Imaging

2018 ◽  
Vol 2018 ◽  
pp. 1-11 ◽  
Author(s):  
Ignacio Alvarez Illan ◽  
Javier Ramirez ◽  
J. M. Gorriz ◽  
Maria Adele Marino ◽  
Daly Avendano ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
False Positive Rate ◽  
Lesion Detection ◽  
Support Vector ◽  
Breast Cancer Patients ◽  
Resonance Imaging ◽  
Dce Mri ◽  
Dynamic Contrast Enhanced ◽  
Contrast Enhanced

Nonmass-enhancing (NME) lesions constitute a diagnostic challenge in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) of the breast. Computer-aided diagnosis (CAD) systems provide physicians with advanced tools for analysis, assessment, and evaluation that have a significant impact on the diagnostic performance. Here, we propose a new approach to address the challenge of NME lesion detection and segmentation, taking advantage of independent component analysis (ICA) to extract data-driven dynamic lesion characterizations. A set of independent sources was obtained from the DCE-MRI dataset of breast cancer patients, and the dynamic behavior of the different tissues was described by multiple dynamic curves, together with a set of eigenimages describing the scores for each voxel. A new test image is projected onto the independent source space using the unmixing matrix, and each voxel is classified by a support vector machine (SVM) that has already been trained with manually delineated data. A solution to the high false-positive rate problem is proposed by controlling the SVM hyperplane location, outperforming previously published approaches.

scholarly journals Validation of computational lesion detection methods in magnetic resonance imaging–negative, focal epilepsy

Epilepsia ◽  
2020 ◽  
Vol 61 (4) ◽  
pp. 828-830
Author(s):  
Baris Kanber ◽  
John S. Duncan ◽  
Roman Rodionov ◽  
Fahmida Amin Chowdhury ◽  
Gavin P. Winston
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Focal Epilepsy ◽  
Lesion Detection ◽  
Detection Methods ◽  
Resonance Imaging
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