摘要目的:应用定量磁敏感图（QSM）探讨健康人群深灰质核团的引流静脉氧饱和度（SvO 2）、铁含量及体积的潜在关系。 方法:该研究为横断面研究。前瞻性连续招募2019年6月至2023年12月天津市某社区的健康志愿者126名。其中男57名、女69名，年龄（48±15）岁。所有健康志愿者接受MRI检查，获得策略性采集的梯度回波（STAGE）图像，并通过后处理获得T 1加权增强图像、QSM图及其最大信号投影图。采用SPIN软件对QSM图像进行半自动化分割得到尾状核（CN）、壳核（PUT）、苍白球（GP）、丘脑（THU）、丘脑底核（STN）、黑质（SN）及红核（RN）的铁含量及体积。使用SPIN软件在QSM最大信号投影图像上手动勾画深灰质核团的引流静脉（透明隔静脉、丘脑纹状体静脉、大脑内静脉、基底静脉），测得静脉磁敏感值，最终计算获得SvO 2。采用偏相关分析探讨深灰质核团的引流静脉SvO 2、铁含量、体积与年龄间的相关性及深灰质核团的引流静脉SvO 2、铁含量及体积之间的相关性。采用中介效应分析深灰质核团的引流静脉SvO 2在铁含量及体积之间的潜在作用。 结果:丘脑纹状体静脉（ r=0.23， P=0.018）和基底静脉（ r=0.27， P=0.004）的SvO 2与年龄呈正相关。大脑内静脉的SvO 2与CN（ r=?0.25， P=0.042）和PUT（ r=?0.33， P<0.001）的铁含量呈负相关；基底静脉的SvO 2与STN（ r=?0.25， P=0.042）和SN（ r=?0.24， P=0.045）的铁含量呈负相关。CN（ r=0.46， P<0.001）、PUT（ r=0.20， P=0.027）、GP（ r=0.76， P<0.001）、STN（ r=0.87， P<0.001）、SN（ r=0.90， P<0.001）、RN（ r=0.79， P<0.001）的铁含量与体积呈正相关。中介分析表明，大脑内静脉SvO 2间接介导CN、PUT、GP及THU的铁含量及体积之间的相互作用。 结论:氧参与了深灰质核团的铁沉积过程；深灰质核团的体积具有个体差异，体积越大，其铁含量越多；大脑内静脉SvO 2介导深灰质核团的铁含量与体积之间的联系。

abstractsObjective:To investigate the relationship among iron content, volume and drainage venous oxygen saturation (SvO 2) in deep gray matter nuclei of healthy people using quantitative susceptibility mapping (QSM). Methods:The study was a cross-sectional study. A total of 126 healthy volunteers were prospectively enrolled in the community in Tianjin from June 2019 to December 2023, and 57 males and 69 females, aged 48±15 years. All healthy volunteers underwent MRI examinations to get STrategically Acquired Gradient Echo images, then it was post-processed to obtain T 1 weighted enhanced images, QSM maps and the maximum intensity projection images. In QSM maps, caudate nucleus (CN), putamen (PUT), globus pallidus (GP), thalamus (THU), subthalamic nucleus (STN), substantia nigra (SN) and red nucleus (RN) were semi-automatically segmented to calculate the iron content and volume using SPIN software. Four bilateral deep cerebral veins regions of interest, including septum pellucidum veins, thalamostriate veins, internal cerebral veins and basilar veins, were manually delineated on the maximum intensity projection images of QSM to obtain venous magnetic sensitivity. The venous magnetic sensitivity was calculated as SvO 2. To observe the age-related trend of SvO 2, iron content and volume, the partial correlation analysis was conducted. The relationships between iron content, volume and SvO 2 were explored using the partial correlation analysis. To explore the potential effects of SvO 2 between iron content and volume in deep gray matter, the mediation analysis was utilized. Results:The relationships between the SvO 2 of thalamostriate veins ( r=0.23, P=0.018), basilar veins ( r=0.27, P=0.004) and age were positive. The relationships between the SvO 2 of internal cerebral veins and the iron contents of CN ( r=?0.25, P=0.042) and PUT ( r=?0.33, P<0.001) were negative. The relationships between the SvO 2 of basilar veins and the iron contents of STN ( r=?0.25, P=0.042) and SN ( r=?0.24, P=0.045) were negative. The relationships between iron content and volume including CN ( r=0.46, P<0.001), PUT ( r=0.20, P=0.027), GP ( r=0.76, P<0.001), STN ( r=0.87, P<0.001), SN ( r=0.90, P<0.001), RN ( r=0.79, P<0.001) were positive. The mediation analysis showed that the SvO 2 of internal cerebral veins indirectly mediated the relationship between iron content and volume of CN, PUT, GP and THU. Conclusions:The process of iron deposition required the participation of oxygen in deep gray matter nuclei. Volume shows positive correlation with iron content in deep gray matter nuclei, with individual variations. The SvO 2 of internal cerebral veins mediate the relationship between iron content and volume of deep gray matter nuclei.