Kamal Rose, Thaper Deepak, Singh Gaganpreet, Sharma Shambhavi, Oinam Arun Singh, Kumar Vivek
Department of Radiation Oncology, Amrita Institute of Medical Sciences and Research Centre, Faridabad, Haryana, India.
Department of Radiation Oncology, Institute of Liver and Biliary Sciences, New Delhi, India.
J Med Phys. 2024 Apr-Jun;49(2):232-239. doi: 10.4103/jmp.jmp_176_23. Epub 2024 Jun 25.
The purpose of this study was to develop a predictive model to evaluate pretreatment patient-specific quality assurance (QA) based on treatment planning parameters for stereotactic body radiation therapy (SBRT) for liver carcinoma.
We retrospectively selected 180 cases of liver SBRT treated using the volumetric modulated arc therapy technique. Numerous parameters defining the plan complexity were calculated from the DICOM-RP (Radiotherapy Plan) file using an in-house program developed in MATLAB. Patient-specific QA was performed with global gamma evaluation criteria of 2%/2 mm and 3%/3 mm in a relative mode using the Octavius two-dimensional detector array. Various statistical tests and multivariate predictive models were evaluated.
The leaf speed (MI) and planning target volume size showed the highest correlation with the gamma criteria of 2%/2 mm and 3%/3 mm ( < 0.05). Degree of modulation (DoM), MCS, leaf speed (MI), and gantry speed (MI) were predictors of global gamma pass rate (GPR) for 2%/2 mm (G22), whereas DoM, MCS, leaf speed (MI) and robust decision making were predictors of the global GPR criterion of 3%/3 mm (G33). The variance inflation factor values of all predictors were <2, indicating that the data were not associated with each other. For the G22 prediction, the sensitivity and specificity of the model were 75.0% and 75.0%, respectively, whereas, for G33 prediction, the sensitivity and specificity of the model were 74.9% and 85.7%%, respectively.
The model was potentially beneficial as an easy alternative to pretreatment QA in predicting the uncertainty in plan deliverability at the planning stage and could help reduce resources in busy clinics.
本研究的目的是开发一种预测模型，以基于肝癌立体定向体部放射治疗（SBRT）的治疗计划参数评估治疗前患者特异性质量保证（QA）。
我们回顾性选择了180例采用容积调强弧形治疗技术治疗的肝脏SBRT病例。使用在MATLAB中开发的内部程序从DICOM-RP（放射治疗计划）文件中计算出众多定义计划复杂性的参数。使用Octavius二维探测器阵列，以相对模式下2%/2 mm和3%/3 mm的全局伽马评估标准进行患者特异性QA。评估了各种统计测试和多变量预测模型。
叶片速度（MI）和计划靶体积大小与2%/2 mm和3%/3 mm的伽马标准显示出最高相关性（<0.05）。调制度（DoM）、MCS、叶片速度（MI）和机架速度（MI）是2%/2 mm（G22）全局伽马通过率（GPR）的预测因子，而DoM、MCS、叶片速度（MI）和稳健决策是3%/3 mm（G33）全局GPR标准的预测因子。所有预测因子的方差膨胀因子值均<2，表明数据之间不存在关联。对于G22预测，模型的敏感性和特异性分别为75.0%和75.0%，而对于G33预测，模型的敏感性和特异性分别为74.9%和85.7%。
该模型在预测计划实施阶段计划可交付性的不确定性方面，作为治疗前QA的一种简便替代方法可能有益，并有助于繁忙诊所减少资源消耗。
