对比度(视觉)
磁共振成像
计算机科学
模式
高对比度
领域(数学)
核磁共振
材料科学
医学物理学
纳米技术
人工智能
放射科
医学
物理
光学
数学
社会科学
社会学
纯数学
作者
Abhinandan Banerjee,Barbara Błasiak,Armita Dash,Bogusław Tomanek,Frank C. J. M. van Veggel,Simon Trudel
摘要
There is a need for non-invasive diagnostic tools to detect and monitor the occurrence of diseases. Ideally, this can be done without resorting to ionizing radiation, especially when multiple rounds of imaging are required. Magnetic resonance imaging (MRI), a form of three-dimensional nuclear magnetic resonance, has become a common tool of choice for diagnosticians. Due to the low contrast difference between healthy and diseased tissue, contrast agents—magnetic species administered to the patient prior to imaging—are routinely used for contrast improvement. High-field (B0 ≥ 4.7 T, 1H Larmor frequency ≥ 200 MHz) MRI offers advantages in terms of better signal-to-noise ratio, as well as improved spectral resolution for certain applications. New contrast agents are being developed for high-field MRI, the topic of this review. After discussing the purpose of contrast agents and the advantages and potential issues of high-field MRI, we discuss recent developments in the field of contrast agent design, synthesis, and applications, citing examples of high-field MRI-ready molecular contrast agents, as well as nanoparticulate contrast agents based on various inorganic materials (e.g., coordination polymers, transition metal oxides, or lanthanide halides). We will discuss how certain aspects (composition, shape, ligands) affect the contrasting abilities of these agents. Finally, we highlight recent developments in the promising field of multifunctional probes, wherein multiple imaging and/or therapeutic modalities are combined in a single species. As high-field MRI becomes more commonplace in the clinical setting, such new contrast agents are needed to provide optimized imaging. This will facilitate the clinician's task in resolving pathologies for more efficient diagnosis and patient treatment.
科研通智能强力驱动
Strongly Powered by AbleSci AI