Tambas Makbule, van der Laan Hans P, Rutgers Wouter, van den Hoek Johanna G M, Oldehinkel Edwin, Meijer Tineke W H, van der Schaaf Arjen, Scandurra Daniel, Free Jeffrey, Both Stefan, Steenbakkers Roel J H M, Langendijk Johannes A
University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, the Netherlands.
University of Groningen, University Medical Center Groningen, Department of Radiation Oncology, Groningen, the Netherlands.
Radiother Oncol. 2021 Jul;160:61-68. doi: 10.1016/j.radonc.2021.04.012. Epub 2021 Apr 21.
In the Netherlands, head and neck cancer (HNC) patients are selected for proton therapy (PT) based on estimated normal tissue complication probability differences (ΔNTCP) between photons and protons, which requires a plan comparison (VMAT vs. IMPT). We aimed to develop tools to improve patient selection for plan comparisons.
This prospective study consisted of 141 consecutive patients in which a plan comparison was done. IMPT plans of patients not qualifying for PT were classified as 'redundant'. To prevent redundant IMPT planning, 5 methods that were primarily based on regression models were developed to predict IMPT D to OARs, by using data from VMAT plans and volumetric data from delineated targets and OARs. Then, actual and predicted plan comparison outcomes were compared. The endpoint was being selected for proton therapy.
Seventy out of 141 patients (49.6%) qualified for PT. Using the developed preselection tools, redundant IMPT planning could have been prevented in 49-68% of the remaining 71 patients not qualifying for PT (=specificity) when the sensitivity of all methods was fixed to 100%, i.e., no false negative cases (positive predictive value range: 57-68%, negative predictive value: 100%).
The advanced preselection tools, which uses volume and VMAT dose data, prevented labour intensive creation of IMPT plans in up to 68% of non-qualifying patients for PT. No patients qualifying for PT would have been incorrectly denied a plan comparison. This method contributes significantly to a more cost-effective model-based selection of HNC patients for PT.
在荷兰，头颈癌（HNC）患者基于光子和质子之间估计的正常组织并发症概率差异（ΔNTCP）被选作质子治疗（PT），这需要进行计划比较（容积调强放疗[VMAT]与调强质子治疗[IMPT]）。我们旨在开发工具以改善用于计划比较的患者选择。
这项前瞻性研究纳入了141例连续进行计划比较的患者。不符合质子治疗条件的患者的IMPT计划被归类为“冗余”。为防止冗余的IMPT计划制定，开发了5种主要基于回归模型的方法，通过使用VMAT计划的数据以及勾画靶区和危及器官的容积数据来预测IMPT对危及器官的剂量。然后，比较实际和预测的计划比较结果。终点是被选作质子治疗。
141例患者中有70例（49.6%）符合质子治疗条件。当所有方法的敏感性固定为100%，即无假阴性病例时（阳性预测值范围：57 - 68%，阴性预测值：100%），使用所开发的预选工具，在其余71例不符合质子治疗条件的患者中，49 - 68%的患者本可避免冗余的IMPT计划制定。
使用容积和VMAT剂量数据的先进预选工具，在高达68%不符合质子治疗条件的患者中避免了IMPT计划的高强度制定。没有符合质子治疗条件的患者会被错误地拒绝进行计划比较。该方法对基于模型的更具成本效益的头颈癌患者质子治疗选择做出了重大贡献。
