18F-FDG PET/CT纹理分析预测局部晚期直肠癌新辅助放化疗疗效的价值

背景与目的：近年来，影像组学方法评价肿瘤异质性、早期预测肿瘤放化疗疗效及预后已显示出良好的应用前景。本研究利用18F-FDG PET/CT影像的纹理分析参数预测局部晚期直肠癌（locally advanced rectal cancer，LARC）新辅助放化疗后的病理反应。方法：回顾性纳入48例新诊断为T_3-4期和（或）N₊的LARC患者，所有患者在接受新辅助放化疗前均进行¹⁸F-FDG PET/CT基线检查（PET1），治疗结束后1周内进行第2次¹⁸F-FDG PET/CT检查（PET2），并于放化疗后6~8周行手术。PET图像再处理获得原发灶标准化最大摄取值（maximal standard uptake，SUV_max）、肿瘤代谢体积（metabolic tumor volume，MTV）和纹理分析参数，包括使用归一化共生矩阵计算的熵（entropy）、对比度参数（contrast）以及基于局部灰度差分矩阵计算的粗糙度参数（coarseness）。应用Kruskal-Wallis检验分析各参数与肿瘤退缩分级（grade of tumor regression，TRG）的相关性，并采用受试者工作特征曲线（receiver operator characteristic curve，ROC）曲线下面积（area under curve，AUC）对各参数的诊断效能进行评价。同时还利用支持向量机（support vector machine，SVM）方法分析了这些病例。结果：所有患者中，有病理反应20例（41.7%），无病理反应28例（58.3%）。基于PET2测得病理有反应组和无反应组的对比度参数2值分别为84.2±31.2和65.6±21.8，差异有统计学意义（P=0.038），AUC为0.677。两次PET/CT检查的SUV_max、MTV、熵、粗糙度参数及其变化和对比度参数1差异均无统计学意义。通过SVM方法利用PET1和PET2数据获得的灵敏度分别为25.0%和57.1%，特异度均为100.0%，有反应预测率均为100.0%，无反应预测率为53.9%和66.7%，总的预测准确率为60.0%和76.9%。结论：利用SVM方法和治疗后早期¹⁸F-FDG PET/CT检查图像contrast2值可以预测LARC新辅助放化疗后病理反应的结果。

The value of 18F-FDG PET/CT texture analysis in predicting neoadjuvant chemoradiotherapy of locally advanced rectal cancer

Background and purpose: In recent years, radiomics analysis has shown certain application value in evaluating tumor heterogeneity and predicting the early effect and prognosis after chemoradiotherapy. This study aimed to predict the pathological response after neoadjuvant chemoradiotherapy of locally advanced rectal cancer (LARC). Methods: Forty-eight patients diagnosed with T_3-4 and/or N₊ of LARC were retrospectively enrolled. All enrolled patients received baseline ¹⁸F-FDG PET/CT (PET1) before neoadjuvant chemoradiotherapy and the second ¹⁸F-FDG PET/CT (PET2) within 1 week after neoadjuvant chemoradiotherapy. The operation was performed 6-8 weeks after neoadjuvant chemoradiotherapy. PET/CT images were processed to obtain maximal standardized uptake value (SUV_max), metabolic tumor volume (MTV) and texture analysis parameters ［including the use of normalized cooccurrence matrix calculation of the entropy (entropy), contrast, and coarseness based on local gray difference roughness parameter matrix calculation (coarseness)］. Kruskal-Wallis test was used to analyze the correlation between tumor regression grade (TRG) and various parameters, and the area under curve (AUC) of the receiver operating characteristic (ROC) curve was used to evaluate the diagnostic efficacy of the parameters. The support vector machine (SVM) method was also used to analyze the enrolled cases. Results: Of all patients, 20 (41.7%) were responders and 28 (58.3%) were non-responders. The averages of contrast2 based on PET2 among responders and non-responders were 84.2±31.2 and 65.6±21.8 respectively (P=0.038), and the AUC was 0.677. The SUV_max, MTV, entropy, coarseness and their changes and contrast 1 did not show statistical significance. According to the SVM method, the sensitivities of PET1 and PET2 were 25.0% and 57.1% respectively, and the specificities were both 100.0%. Both of the predictive ratios of responders among PET1 and PET2 were 100.0%. The predictive ratios of non-responders among PET1 and PET2 were 53.9% and 66.7%, respectively. The prediction accuracy of PET1 and PET2 were 60.0% and 76.9%, respectively. Conclusion: Contrast 2 as one of the texture analysis parameters of early ¹⁸F-FDG PET/CT images and the SVM method can be used to predict the pathological response of LARC after neoadjuvant chemoradiotherapy.