Department of Radiological Technology, School of Health Sciences, Faculty of Medicine, Niigata University, Niigata, Japan.
Med Phys. 2023 Sep;50(9):5671-5681. doi: 10.1002/mp.16353. Epub 2023 Mar 23.
In-situ range verification of particle therapy based on the detection of secondary emitted radiation requires highly accurate assignment of elemental concentrations (particularly carbon and oxygen) in the human body.
A method for quantitatively predicting carbon and oxygen concentrations in human soft tissues is proposed. This method relies on an empirical one-to-one correspondence between the mass fraction and water content (WC), which is a measurable tissue quantity based on magnetic resonance (MR) imaging (referred to as "MRWC-based method").
A numerical analysis of the MRWC-based method was performed for 47 standard human soft tissues tabulated in the literature as objects of interest with unknown mass fractions of the four main elements-C, O, H, and N. Thereafter, the method was evaluated in terms of the mass-fraction quantification accuracy by comparing it with the gold-standard CT-based method developed by Schneider et al. The MRWC-based method was also applied to the MR imaging data of a virtual head phantom obtained from a three-dimensional MRI-simulated brain database.
The predicted mass fractions in a range of human soft tissues were in better agreement with the reference values than those predicted by the CT-based method. The mean absolute errors of the predicted mass% values for the overall standard soft tissues could be reduced from 4.8 percentage points (pp) (CT-based) to 0.5 pp (MRWC-based) for carbon and from 5.2 pp (CT-based) to 0.4 pp (MRWC-based) for oxygen. The application to the simulated MRI data confirmed the capability of the sufficient recognition of the boundaries between the white matter and gray matter in the brain that could not be realized by the CT-based method. Thus, the MRWC-based method exhibits superior performance in the prediction of carbon and oxygen concentrations in soft tissues.
This study is limited to a proof-of-concept scope but demonstrates the feasibility of the MRWC-based method for the generation of elemental images of human soft tissues from MRI-derived water-content images.
基于次级发射辐射检测的粒子治疗的原位范围验证需要高度准确地分配人体中的元素浓度（特别是碳和氧）。
提出了一种定量预测人体软组织中碳和氧浓度的方法。该方法依赖于质量分数与水含量（WC）之间的经验一一对应关系，WC 是一种基于磁共振（MR）成像（称为“基于 MRWC 的方法”）可测量的组织量。
对文献中列出的 47 种标准人体软组织进行了基于 MRWC 的方法的数值分析，这些软组织的四个主要元素（C、O、H 和 N）的质量分数未知。然后，通过与 Schneider 等人开发的金标准 CT 基于方法进行比较，评估了该方法在质量分数定量精度方面的表现。还将基于 MRWC 的方法应用于从三维 MRI 模拟脑数据库获得的虚拟头部体模的 MR 成像数据。
在所研究的人体软组织范围内，预测的质量分数与参考值更吻合，优于 CT 基于方法的预测结果。对于所有标准软组织，整体预测质量%值的平均绝对误差可以从 CT 基于方法的 4.8 个百分点（pp）降低到基于 MRWC 的方法的 0.5 pp，对于碳可以从 CT 基于方法的 5.2 pp 降低到基于 MRWC 的方法的 0.4 pp。对模拟 MRI 数据的应用证实了该方法能够充分识别大脑白质和灰质之间的边界，而 CT 基于方法无法实现这一点。因此，基于 MRWC 的方法在预测软组织中的碳和氧浓度方面表现出优异的性能。
本研究仅限于概念验证范围，但证明了基于 MRWC 的方法从 MRI 衍生的水含量图像生成人体软组织元素图像的可行性。
