Magnetic Resonance Imaging, Contrast Agents, and Neurological Clearance
This community focuses on the development and application of magnetic resonance imaging (MRI) techniques, with a specific emphasis on contrast-enhanced methods, diffusion-weighted imaging, and the assessment of brain clearance mechanisms.
The research is dominated by the design and evaluation of gadolinium-based contrast agents and their use in dynamic contrast-enhanced MRI. A significant portion of the work involves diffusion tensor imaging and the study of the glymphatic system, including cerebrospinal fluid dynamics and perivascular space analysis. Clinical applications span the diagnosis and monitoring of breast, prostate, and rectal cancers, as well as hepatocellular carcinoma. Recent methodological advances include the integration of deep learning for automated image analysis and the quantification of liver fat and brain inflammation. The work frequently compares different MRI sequences to improve diagnostic accuracy and assess disease progression in both oncological and neurological contexts.
The largest share of the community's output is found in gadolinium research, accounting for 19.9% of all gadolinium research, and 12,568 papers here. Other elements with notable presence include iodine, gold, and manganese, though their shares of total element research are significantly smaller.
The community comprises 53,238 papers, with the highest publication volumes in the Journal of Magnetic Resonance Imaging, Magnetic Resonance Imaging, and Magnetic Resonance in Medicine.
Recent work continues to focus on the glymphatic system and brain clearance mechanisms, including studies on aquaporin-4 dysfunction and neurovascular dynamics. Additional recent papers address the application of deep learning for stroke detection and the quantification of liver fat in fatty liver disease.