IADI U1254, INSERM and Université de Lorraine, Nancy, France.
Siemens Healthcare SAS, Saint Denis, France.
Sci Rep. 2024 Jul 12;14(1):16109. doi: 10.1038/s41598-024-67014-9.
This work was inspired by the observation that a majority of MR-electrical properties tomography studies are based on direct comparisons with ex vivo measurements carried out on post-mortem samples in the 90's. As a result, the in vivo conductivity values obtained from MRI in the megahertz range in different types of tissues (brain, liver, tumors, muscles, etc.) found in the literature may not correspond to their ex vivo equivalent, which still serves as a reference for electromagnetic modelling. This study aims to pave the way for improving current databases since the definition of personalized electromagnetic models (e.g. for Specific Absorption Rate estimation) would benefit from better estimation. Seventeen healthy volunteers underwent MRI of both brain and thorax/abdomen using a three-dimensional ultrashort echo-time (UTE) sequence. We estimated conductivity (S/m) in several classes of macroscopic tissue using a customized reconstruction method from complex UTE images, and give general statistics for each of these regions (mean-median-standard deviation). These values are used to find possible correlations with biological parameters such as age, sex, body mass index and/or fat volume fraction, using linear regression analysis. In short, the collected in vivo values show significant deviations from the ex vivo values in conventional databases, and we show significant relationships with the latter parameters in certain organs for the first time, e.g. a decrease in brain conductivity with age.
这项工作的灵感来自于这样一种观察,即大多数磁共振电特性层析成像研究都是基于与 90 年代在死后样本上进行的离体测量的直接比较。因此,文献中从不同类型的组织(大脑、肝脏、肿瘤、肌肉等)在兆赫兹范围内的 MRI 获得的体内电导率值可能与它们的离体等效值不对应,而离体等效值仍然是电磁建模的参考。本研究旨在为改进当前数据库铺平道路,因为个性化电磁模型的定义(例如用于特定吸收率估计)将受益于更好的估计。17 名健康志愿者使用三维超短回波时间(UTE)序列进行大脑和胸部/腹部的 MRI 检查。我们使用来自复杂 UTE 图像的自定义重建方法来估计几种宏观组织的电导率(S/m),并给出这些区域的一般统计信息(平均值-中位数-标准差)。使用线性回归分析,这些值用于寻找与生物参数(如年龄、性别、体重指数和/或脂肪体积分数)的可能相关性。总之,与传统数据库中的离体值相比,所采集的体内值存在显著偏差,并且我们首次在某些器官中显示出与后者参数的显著关系,例如大脑电导率随年龄的降低。