Palma Giuseppe, Monti Serena, Conson Manuel, Xu Ting, Hahn Stephen, Durante Marco, Mohan Radhe, Liao Zhongxing, Cella Laura
Institute of Biostructures and Bioimaging, National Research Council, Naples, Italy.
National Institute for Nuclear Physics, (INFN), Naples, Italy.
Front Oncol. 2020 Mar 17;10:344. doi: 10.3389/fonc.2020.00344. eCollection 2020.
Radiation therapy (RT) of thoracic cancers may cause severe radiation dermatitis (RD), which impacts on the quality of a patient's life. Aim of this study was to analyze the incidence of acute RD and develop normal tissue complication probability (NTCP) models for severe RD in thoracic cancer patients treated with Intensity-Modulated RT (IMRT) or Passive Scattering Proton Therapy (PSPT). We analyzed 166 Non-Small-Cell Lung Cancer (NSCLC) patients prospectively treated at a single institution with IMRT (103 patients) or PSPT (63 patients). All patients were treated to a prescribed dose of 60 to 74 Gy in conventional daily fractionation with concurrent chemotherapy. RD was scored according to CTCAE v3 scoring system. For each patient, the epidermis structure (skin) was automatically defined by an in house developed segmentation algorithm. The absolute dose-surface histogram (DSH) of the skin were extracted and normalized using the Body Surface Area (BSA) index as scaling factor. Patient and treatment-related characteristics were analyzed. The Lyman-Kutcher-Burman (LKB) NTCP model recast for DSH and the multivariable logistic model were adopted. Models were internally validated by Leave-One-Out method. Model performance was evaluated by the area under the receiver operator characteristic curve, and calibration plot parameters. Fifteen of 166 (9%) patients developed severe dermatitis (grade 3). RT technique did not impact RD incidence. Total gross tumor volume (GTV) size was the only non dosimetric variable significantly correlated with severe RD ( = 0.027). Multivariable logistic modeling resulted in a single variable model including , the relative skin surface receiving more than 20 Gy (OR = 31.4). The cut off for was 1.1% of the BSA. LKB model parameters were TD = 9.5 Gy, = 0.24, = 0.62. Both NTCP models showed comparably high prediction and calibration performances. Despite skin toxicity has long been considered a potential limiting factor in the clinical use of PSPT, no significant differences in RD incidence was found between RT modalities. Once externally validated, the availability of NTCP models for prediction of severe RD may advance treatment planning optimization.
胸段癌的放射治疗（RT）可能会导致严重的放射性皮炎（RD），这会影响患者的生活质量。本研究的目的是分析急性RD的发生率，并为接受调强放疗（IMRT）或被动散射质子治疗（PSPT）的胸段癌患者建立严重RD的正常组织并发症概率（NTCP）模型。我们前瞻性分析了在单一机构接受IMRT（103例患者）或PSPT（63例患者）治疗的166例非小细胞肺癌（NSCLC）患者。所有患者均接受常规每日分割剂量为60至74 Gy的治疗，并同步进行化疗。根据CTCAE v3评分系统对RD进行评分。对于每位患者，表皮结构（皮肤）由内部开发的分割算法自动定义。提取皮肤的绝对剂量-表面积直方图（DSH），并使用体表面积（BSA）指数作为缩放因子进行归一化。分析了患者和治疗相关特征。采用针对DSH重新构建的Lyman-Kutcher-Burman（LKB）NTCP模型和多变量逻辑模型。通过留一法对模型进行内部验证。通过受试者操作特征曲线下面积和校准图参数评估模型性能。166例患者中有15例（9%）发生严重皮炎（3级）。放疗技术对RD发生率没有影响。总大体肿瘤体积（GTV）大小是与严重RD显著相关的唯一非剂量学变量（P = 0.027）。多变量逻辑建模产生了一个单变量模型，包括接受超过20 Gy剂量的相对皮肤表面积（OR = 31.4）。该相对皮肤表面积的截断值为BSA的1.1%。LKB模型参数为TD = 9.5 Gy，n = 0.24，m = 0.62。两种NTCP模型均显示出相当高的预测和校准性能。尽管长期以来皮肤毒性一直被认为是PSPT临床应用中的一个潜在限制因素，但在放疗方式之间未发现RD发生率有显著差异。一旦经过外部验证，用于预测严重RD的NTCP模型的可用性可能会推动治疗计划的优化。
