Development of highly sensitive ^<13>C MR system for simultaneous evaluation of brain and liver function in brain death

1.通过<13>将异核多重共振能力集成到临床成像仪中，开发了高灵敏度的~ 1C NMR方法。原始MR成像系统的硬件未进行修改，但是，在软件中插入了触发脉冲，以与集成的RF系统同步。2.利用^1H和^ C之间的异质核多量子相干性，结合梯度选择脉冲，已经实现了高灵敏度<13>。发现自旋系统通过多量子相干后的信号强度会受到多量子态快速弛豫的影响。因此，通过优化选择梯度脉冲的形状和持续时间，获得了对结果的最高灵敏度。3.用<13>~ 1H-检测~ 1C NMR方法对活体器官中注射的~ 1C标记葡萄糖进行了无创示踪<13>。葡萄糖在30 min内达到最高值，并迅速下降，而葡萄糖代谢产生的谷氨酰胺/谷氨酸在1 h内达到最高值，并在2 h后仍维持在较高水平。4.通过13 P和13 C NMR光谱法非侵入性地分析肝脏中的代谢功能<13><13>，发现葡萄糖作为糖原的积累和丙氨酸对诸如谷氨酰胺、谷氨酸和葡萄糖的代谢反应与ATP水平相关，并且还与糖原生成和糖原生成相关。5.本系统的进一步改进将使系统操作更加简便，并开发代谢反应自动分析软件，以帮助准确判断脑死亡患者的状态。

1.Highly sensitive ^<13>C NMR method has been developed by the integration of hetero-nuclear multiple resonance capability into a clinical imager. The original MR imaging system was not modified in the hardware, however, a trigger pulse was inserted in the software to synchronize with the incorporated RF system. 2.High sensitivity has been achieved by employing hetero-nuclear multiple quantum coherence between ^1H and ^<13>C in combination with gradient selection pulses. The signal intensity in the spin system passing through multiple quantum coherence was found to be influenced by the rapid relaxation in the multiple quantum state. Therefore, the highest sensitivity for the outcome was obtained with optimizing the shape and duration of the selection gradient pulses. 3. Injected glucose labeled by ^<13>C in living organs was traced non-invasively by ^1H-detected ^<13>C NMR method. Glucose reached to the highest level in 30 minitues and decreased rapidly, however, glutamine/glutamate derived from the metabolism of the glucose reached to the highest in 1 hour and stayd in a high level for two more hours. 4. Metabolic function in liver was analyzed non-invasively by ^<13>P and ^<13>C NMR spectroscopy and found that the accumulation of glucose as glycogen and metabolic reaction of alanine to such as glutamine, glutamate, and glucose was related to the level of ATP and also to gluconeogenesis and glycogenesis. 5. Further improvement will be made in the easier operation of the constructed system as well as the development of automatically analyzing software of the metabolic response which will help to accurately judge the state of the brain dead patients.