Acoustics and Ionising Radiation Team, National Physical Laboratory, Teddington, TW11 0LW, UK.
Department of Medical Physics and Biomedical Engineering, University College London, London, WC1E 6BT, UK.
Med Phys. 2017 Jun;44(6):2332-2344. doi: 10.1002/mp.12215. Epub 2017 Apr 21.
Dual-energy CT (DECT) promises improvements in estimating stopping power ratios (SPRs) for proton therapy treatment planning. Although several comparable mathematical formalisms have been proposed in literature, the optimal techniques to characterize human tissue SPRs with DECT in a clinical environment are not fully established. The aim of this work is to compare the most robust DECT methods against conventional single-energy CT (SECT) in conditions reproducing a clinical environment, where CT artifacts and noise play a major role on the accuracy of these techniques.
Available DECT tissue characterization methods are investigated and their ability to predict SPRs is compared in three contexts: (a) a theoretical environment using the XCOM cross section database; (b) experimental data using a dual-source CT scanner on a calibration phantom; (c) simulations of a virtual humanoid phantom with the ImaSim software. The latter comparison accounts for uncertainties caused by CT artifacts and noise, but leaves aside other sources of uncertainties such as CT grid size and the I-values. To evaluate the clinical impact, a beam range calculation model is used to predict errors from the probability distribution functions determined with ImaSim simulations. Range errors caused by SPR errors in soft tissues and bones are investigated.
Range error estimations demonstrate that DECT has the potential of reducing proton beam range uncertainties by 0.4% in soft tissues using low noise levels of 12 and 8 HU in DECT, corresponding to 7 HU in SECT. For range uncertainties caused by the transport of protons through bones, the reduction in range uncertainties for the same levels of noise is found to be up to 0.6 to 1.1 mm for bone thicknesses ranging from 1 to 5 cm, respectively. We also show that for double the amount noise, i.e., 14 HU in SECT and 24 and 16 HU for DECT, the advantages of DECT in soft tissues are lost over SECT. In bones however, the reduction in range uncertainties is found to be between 0.5 and 0.9 mm for bone thicknesses ranging from 1 to 5 cm, respectively.
DECT has a clear potential to improve proton beam range predictions over SECT in proton therapy. However, in the current state high levels of noise remain problematic for DECT characterization methods and do not allow getting the full benefits of this technology. Future work should focus on adapting DECT methods to noise and investigate methods based on raw-data to reduce CT artifacts.
双能 CT（DECT）有望改善质子治疗计划中对阻止能力比（SPR）的估计。尽管文献中提出了几种可比较的数学形式，但在临床环境中用 DECT 对人体组织 SPR 进行特征描述的最佳技术尚未完全确定。本研究的目的是在 CT 伪影和噪声对这些技术的准确性有重大影响的临床环境条件下，比较最稳健的 DECT 方法与传统的单能量 CT（SECT）。
研究了现有的 DECT 组织特征描述方法，并在三种情况下比较了它们预测 SPR 的能力：（a）使用 XCOM 截面数据库的理论环境；（b）使用双源 CT 扫描仪在校准体模上的实验数据；（c）使用 ImaSim 软件对虚拟人形体模进行模拟。后一种比较考虑了由 CT 伪影和噪声引起的不确定性，但排除了 CT 网格大小和 I 值等其他不确定性源。为了评估临床影响，使用射束范围计算模型来预测从 ImaSim 模拟确定的概率分布函数中得出的误差。研究了软组织和骨骼中 SPR 误差引起的射程误差。
射程误差估计表明，在 DECT 中使用低噪声水平（分别为 12 和 8 HU）时，DECT 有可能将软组织中的质子射束范围不确定性降低 0.4%，而在 SECT 中则为 7 HU。对于质子穿过骨骼传输引起的射程不确定性，对于相同噪声水平，对于厚度为 1 至 5 cm 的骨骼，射程不确定性的降低幅度分别为 0.6 至 1.1 mm。我们还表明，对于噪声增加一倍，即 SECT 中的 14 HU 和 DECT 中的 24 和 16 HU，在软组织中 DECT 的优势相对于 SECT 而言将会丧失。然而，在骨骼中，对于厚度为 1 至 5 cm 的骨骼，射程不确定性的降低幅度分别为 0.5 至 0.9 mm。
DECT 有望在质子治疗中比 SECT 更能改善质子射束范围预测。然而，在当前状态下，高水平的噪声仍然是 DECT 特征描述方法的一个问题，并且无法充分利用这项技术。未来的工作应集中于使 DECT 方法适应噪声，并研究基于原始数据的方法以减少 CT 伪影。
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