Longarino Friderike K, Kowalewski Antonia, Tessonnier Thomas, Mein Stewart, Ackermann Benjamin, Debus Jürgen, Mairani Andrea, Stiller Wolfram
Clinical Cooperation Unit Radiation Oncology, German Cancer Research Center (DKFZ), Heidelberg, Germany.
Department of Radiation Oncology, Heidelberg University Hospital, Heidelberg, Germany.
Front Oncol. 2022 Apr 20;12:853495. doi: 10.3389/fonc.2022.853495. eCollection 2022.
In particle therapy treatment planning, dose calculation is conducted using patient-specific maps of tissue ion stopping power ratio (SPR) to predict beam ranges. Improving patient-specific SPR prediction is therefore essential for accurate dose calculation. In this study, we investigated the use of the Spectral CT 7500, a second-generation dual-layer spectral computed tomography (DLCT) system, as an alternative to conventional single-energy CT (SECT) for patient-specific SPR prediction. This dual-energy CT (DECT)-based method allows for the direct prediction of SPR from quantitative measurements of relative electron density and effective atomic number using the Bethe equation, whereas the conventional SECT-based method consists of indirect image data-based prediction through the conversion of calibrated CT numbers to SPR. The performance of the Spectral CT 7500 in particle therapy treatment planning was characterized by conducting a thorough analysis of its SPR prediction accuracy for both tissue-equivalent materials and common non-tissue implant materials. In both instances, DLCT was found to reduce uncertainty in SPR predictions compared to SECT. Mean deviations of 0.7% and 1.6% from measured SPR values were found for DLCT- and SECT-based predictions, respectively, in tissue-equivalent materials. Furthermore, end-to-end analyses of DLCT-based treatment planning were performed for proton, helium, and carbon ion therapies with anthropomorphic head and pelvic phantoms. 3D gamma analysis was performed with ionization chamber array measurements as the reference. DLCT-predicted dose distributions revealed higher passing rates compared to SECT-predicted dose distributions. In the DLCT-based treatment plans, measured distal-edge evaluation layers were within 1 mm of their predicted positions, demonstrating the accuracy of DLCT-based particle range prediction. This study demonstrated that the use of the Spectral CT 7500 in particle therapy treatment planning may lead to better agreement between planned and delivered dose compared to current clinical SECT systems.
在粒子治疗计划中，剂量计算是通过使用患者特定的组织离子阻止本领比（SPR）图谱来预测射束射程进行的。因此，改进患者特定的SPR预测对于准确的剂量计算至关重要。在本研究中，我们研究了使用第二代双层光谱计算机断层扫描（DLCT）系统Spectral CT 7500，作为传统单能CT（SECT）在患者特定SPR预测方面的替代方法。这种基于双能CT（DECT）的方法允许通过使用贝特方程从相对电子密度和有效原子序数的定量测量直接预测SPR，而传统的基于SECT的方法则是通过将校准后的CT值转换为SPR进行基于间接图像数据的预测。通过对Spectral CT 7500在粒子治疗计划中对组织等效材料和常见非组织植入材料的SPR预测准确性进行全面分析，表征了其性能。在这两种情况下，与SECT相比，DLCT都能降低SPR预测的不确定性。在组织等效材料中，基于DLCT和SECT的预测与测量的SPR值的平均偏差分别为0.7%和1.6%。此外，还使用拟人化头部和盆腔体模对基于DLCT的质子、氦离子和碳离子治疗计划进行了端到端分析。以电离室阵列测量为参考进行了三维伽马分析。与SECT预测的剂量分布相比，DLCT预测的剂量分布显示出更高的通过率。在基于DLCT的治疗计划中，测量的远端边缘评估层在其预测位置的1毫米范围内，证明了基于DLCT的粒子射程预测的准确性。本研究表明，与当前临床SECT系统相比，在粒子治疗计划中使用Spectral CT 7500可能会使计划剂量与实际 delivered 剂量之间的一致性更好。 （原文中“delivered”疑为“delivered”，已按正确理解翻译）
