School of Mechanical, Electrical & Information Engineering, Shandong University, Weihai, China.
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education), Department of Radiology, Peking University Cancer Hospital & Institute, Beijing, China.
Radiother Oncol. 2019 Mar;132:100-108. doi: 10.1016/j.radonc.2018.11.007. Epub 2018 Dec 21.
Locally advanced rectal cancer (LARC) patients showing pathological good response (pGR) of down-staging to ypT0-1N0 after neoadjuvant chemoradiotherapy (nCRT) may receive organ-preserving treatment instead of total mesorectal excision (TME). In the current study, quantitative analysis of diffusion weighted imaging (DWI) is conducted to predict pGR patients in order to provide decision support for organ-preserving strategies.
222 LARC patients receiving nCRT and TME are enrolled from Beijing Cancer Hospital and allocated into training (152) and validation (70) set. Three pGR prediction models are constructed in the training set, including DWI prediction model based on quantitative DWI features, clinical prediction model based on clinical characteristics, and combined prediction model integrating DWI and clinical predictors. Prediction performances are assessed by area under receiver operating characteristic curve (AUC), classification accuracy (ACC), positive and negative predictive values (PPV and NPV).
The DWI (AUC = 0.866, ACC = 91.43%) and combined (AUC = 0.890, ACC = 90%) prediction model obtains good prediction performance in the independent validation set. Nevertheless, the clinical prediction model performs worse than the other two models (AUC = 0.631, ACC = 75.71% in validation set). Calibration analysis indicates that the pGR probability predicted by the combined prediction model is close to perfect prediction. Decision curve analysis reveals that the LARC patients will acquire clinical benefit if receiving organ-preserving strategy according to combined prediction model.
Combination of quantitative DWI analysis and clinical characteristics holds great potential in identifying the pGR patients and providing decision support for organ-preserving strategies after nCRT treatment.
接受新辅助放化疗（nCRT）后降期达到ypT0-1N0 的局部晚期直肠癌（LARC）患者病理完全缓解（pGR），可选择保肛治疗而非全直肠系膜切除术（TME）。本研究旨在通过定量分析扩散加权成像（DWI）来预测 pGR 患者，为保肛治疗策略提供决策支持。
回顾性分析 2016 年 1 月至 2019 年 6 月于北京肿瘤医院接受 nCRT 联合 TME 治疗的 222 例 LARC 患者的临床资料。根据是否达到 pGR 将患者分为训练集（152 例）和验证集（70 例）。基于 DWI 定量特征、临床特征和 DWI 与临床特征联合构建 pGR 预测模型，采用受试者工作特征曲线（ROC）下面积（AUC）、准确率（ACC）、阳性预测值（PPV）、阴性预测值（NPV）评价模型预测效能。
在独立验证集，DWI 预测模型（AUC=0.866，ACC=91.43%）和联合预测模型（AUC=0.890，ACC=90%）具有良好的预测效能，而临床预测模型的预测效能（AUC=0.631，ACC=75.71%）较差。校准分析显示联合预测模型预测 pGR 的概率接近完美预测。决策曲线分析显示，LARC 患者若根据联合预测模型选择保肛治疗策略可获得临床获益。
定量 DWI 分析与临床特征相结合可用于识别 pGR 患者，为 nCRT 治疗后保肛治疗策略提供决策支持。
