Masilela Thongchai A M, D-Kondo Naoki, Shin Wook-Geun, Ortiz Ramon, Meyer Isaac, LaVerne Jay A, Faddegon Bruce, Schuemann Jan, Ramos-Méndez José
Department of Radiation Oncology, University of California San Francisco, San Francisco, CA 94115, United States of America.
Department of Radiation Oncology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, United States of America.
Phys Med Biol. 2025 May 16;70(10). doi: 10.1088/1361-6560/add4b9.
To develop a regression testing system for TOPAS-nBio: a wrapper of Geant4-DNA, and the radiobiological extension of TOPAS-a Monte Carlo code for the simulation of radiation transport. This regression testing system will be made publicly available on the TOPAS-nBio GitHub page.A set of seven regression tests were chosen to evaluate the suite of capabilities of TOPAS-nBio from both a physical and chemical point of view. Three different versions of the code were compared: TOPAS-nBio-v2.0 (the previous version), TOPAS-nBio-v3.0 (the current public release), and TOPAS-nBio-v4.0 (the current developer version, planned for future release). The main aspects compared for each test were the differences in execution times, variations from other versions of TOPAS-nBio, and agreement with measurements/in silico data.Execution times of nBio-v3.0 for all physics tests were faster than those of nBio-v2.0 due to the use of a new Geant4 version. Mean point-to-point differences between TOPAS-nBio versions across all tests fell largely within 5%. The exceptions were the radiolytic yields (values) ofH2andH2O2, which differed moderately (16% and 10% respectively) when going from nBio-v3.0 to nBio-v4.0. In all cases a good agreement with other experimental/simulated data was obtained.From a developer point of view, this regression testing system is essential as it allows a more rigorous reporting of the consequences of new version releases on quantities such as the LET orvalues of chemical species. Furthermore, it enables us to test 'pushes' made to the codebase by collaborators and contributors. From an end-user point of view, users of the software are now able to easily evaluate how changes in the source code, made for their specific application, would affect the results of known quantities.
为TOPAS-nBio开发一个回归测试系统:Geant4-DNA的一个包装器,以及TOPAS(一个用于模拟辐射传输的蒙特卡罗代码)的放射生物学扩展。这个回归测试系统将在TOPAS-nBio的GitHub页面上公开提供。选择了一组七个回归测试,从物理和化学角度评估TOPAS-nBio的功能套件。比较了代码的三个不同版本:TOPAS-nBio-v2.0(上一版本)、TOPAS-nBio-v3.0(当前公开发布版本)和TOPAS-nBio-v4.0(当前开发者版本,计划未来发布)。每个测试比较的主要方面是执行时间的差异、与TOPAS-nBio其他版本的差异以及与测量数据/计算机模拟数据的一致性。由于使用了新的Geant4版本,所有物理测试中nBio-v3.0的执行时间比nBio-v2.0快。所有测试中TOPAS-nBio版本之间的平均点对点差异大多在5%以内。例外情况是H2和H2O2的辐射分解产率(值),从nBio-v3.0到nBio-v4.0时分别有适度差异(分别为16%和10%)。在所有情况下,都与其他实验/模拟数据取得了良好的一致性。从开发者的角度来看,这个回归测试系统至关重要,因为它允许更严格地报告新版本发布对诸如LET或化学物种值等数量的影响。此外,它使我们能够测试合作者和贡献者对代码库所做 的“推送”。从最终用户的角度来看,该软件的用户现在能够轻松评估针对其特定应用对源代码所做的更改将如何影响已知数量的结果。