Su Ting-Shi, Li Li-Qing, Liang Shi-Xiong, Xiang Bang-De, Li Jian-Xu, Ye Jia-Zhou, Li Le-Qun
Department of Radiation Oncology, Guangxi Medical University Cancer Hospital, Nanning, China.
Department of Hepatobiliary Surgery, Guangxi Medical University Cancer Hospital, Nanning, China.
Front Oncol. 2021 Aug 26;11:680303. doi: 10.3389/fonc.2021.680303. eCollection 2021.
In this study, we designed a new (Su'S) target area delineation to protect the normal liver during liver regeneration and prospectively evaluate liver regeneration after radiotherapy, as well as to explore the clinical factors of liver regeneration and established a model and nomogram.
Thirty patients treated with preoperative downstaging radiotherapy were prospectively included in the training cohort, and 21 patients treated with postoperative adjuvant radiotherapy were included in the validation cohort. The cut-off points of each optimal predictor were obtained using receiver-operating characteristic analysis. A model and nomogram for liver regeneration after radiotherapy were developed and validated.
After radiotherapy, 12 (40%) and 13 (61.9%) patients in the training and validation cohorts experienced liver regeneration, respectively. The risk stratification model based on the cutoffs of standard residual liver volume spared from at least 20 Gy (SVs20 = 303.4 mL/m) and alanine aminotransferase (ALT=43 u/L) was able to effectively discriminate the probability of liver regeneration. The model and nomogram of liver regeneration based on SVs20 and ALT showed good prediction performance (AUC=0.759) in the training cohort and performed well (AUC=0.808) in the validation cohort.
SVs20 and ALT were optimal predictors of liver regeneration. This model may be beneficial to the constraints of the normal liver outside the radiotherapy-targeted areas.
在本研究中，我们设计了一种新的（苏式）靶区划定方法，以在肝再生期间保护正常肝脏，并前瞻性评估放疗后的肝再生情况，同时探索肝再生的临床因素，并建立了一个模型和列线图。
前瞻性纳入30例接受术前降期放疗的患者作为训练队列，21例接受术后辅助放疗的患者作为验证队列。使用受试者操作特征分析获得每个最佳预测指标的截断点。开发并验证了放疗后肝再生的模型和列线图。
放疗后，训练队列和验证队列中分别有12例（40%）和13例（61.9%）患者出现肝再生。基于至少20 Gy未受照射的标准残余肝体积（SVs20 = 303.4 mL/m）和丙氨酸氨基转移酶（ALT = 43 u/L）截断点的风险分层模型能够有效区分肝再生的概率。基于SVs20和ALT的肝再生模型和列线图在训练队列中显示出良好的预测性能（AUC = 0.759），在验证队列中表现也良好（AUC = 0.808）。
SVs20和ALT是肝再生的最佳预测指标。该模型可能有助于放疗靶区外正常肝脏的保护。
