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

1.将异核多重共振能力集成到临床成像仪中，发展了高灵敏度的~(13)C核磁共振方法。原始的磁共振成像系统没有在硬件上进行修改，但在软件中插入了触发脉冲，以与合并的RF系统同步。2.利用~1H和~(13)&gt；C之间的异核多量子相干，结合梯度选择脉冲，获得了高灵敏度。通过多量子相干的自旋系统中的信号强度受到多量子态的快速弛豫的影响。因此，通过优化选择梯度脉冲的形状和持续时间来获得对结果的最高灵敏度。3.用~1H检测~(13)&gt；C核磁共振法对活体器官注射的葡萄糖进行了无创性示踪。血糖在30分钟内达到最高值，然后迅速下降，而葡萄糖代谢产生的谷氨酰胺/谷氨酸在1小时内达到最高水平，并维持在较高水平2小时以上。4.用~(13)P和~(13)C核磁共振波谱对肝脏代谢功能进行了无创性分析，发现葡萄糖作为糖原的蓄积以及丙氨酸对谷氨酰胺、谷氨酸和葡萄糖的代谢反应与ATP水平有关，也与糖异生和糖的生成有关。5.在构建的系统的易操作性以及代谢反应自动分析软件的开发方面将进一步完善，有助于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.