Nardone Valerio, Reginelli Alfonso, Grassi Roberta, Vacca Giovanna, Giacobbe Giuliana, Angrisani Antonio, Clemente Alfredo, Danti Ginevra, Correale Pierpaolo, Carbone Salvatore Francesco, Pirtoli Luigi, Bianchi Lorenzo, Vanzulli Angelo, Guida Cesare, Grassi Roberto, Cappabianca Salvatore
Department of Precision Medicine, University of Campania "L. Vanvitelli", 80138 Naples, Italy.
Italian Society of Medical and Interventional Radiology (SIRM), SIRM Foundation, 20122 Milan, Italy.
Cancers (Basel). 2022 Jun 18;14(12):3004. doi: 10.3390/cancers14123004.
We performed a pilot study to evaluate the use of MRI delta texture analysis (D-TA) as a methodological item able to predict the frequency of complete pathological responses and, consequently, the outcome of patients with locally advanced rectal cancer addressed to neoadjuvant chemoradiotherapy (C-RT) and subsequently, to radical surgery. In particular, we carried out a retrospective analysis including 100 patients with locally advanced rectal adenocarcinoma who received C-RT and then radical surgery in three different oncological institutions between January 2013 and December 2019. Our experimental design was focused on the evaluation of the gross tumor volume (GTV) at baseline and after C-RT by means of MRI, which was contoured on T2, DWI, and ADC sequences. Multiple texture parameters were extracted by using a LifeX Software, while D-TA was calculated as percentage of variations in the two time points. Both univariate and multivariate analysis (logistic regression) were, therefore, carried out in order to correlate the above-mentioned TA parameters with the frequency of pathological responses in the examined patients' population focusing on the detection of complete pathological response (pCR, with no viable cancer cells: TRG 1) as main statistical endpoint. ROC curves were performed on three different datasets considering that on the 21 patients, only 21% achieved an actual pCR. In our training dataset series, pCR frequency significantly correlated with ADC GLCM-Entropy only, when univariate and binary logistic analysis were performed (AUC for pCR was 0.87). A confirmative binary logistic regression analysis was then repeated in the two remaining validation datasets (AUC for pCR was 0.92 and 0.88, respectively). Overall, these results support the hypothesis that D-TA may have a significant predictive value in detecting the occurrence of pCR in our patient series. If confirmed in prospective and multicenter trials, these results may have a critical role in the selection of patients with locally advanced rectal cancer who may benefit form radical surgery after neoadjuvant chemoradiotherapy.
我们进行了一项初步研究，以评估磁共振成像（MRI）增量纹理分析（D-TA）作为一种方法学项目的应用，该方法能够预测完全病理缓解的频率，进而预测接受新辅助放化疗（C-RT）并随后接受根治性手术的局部晚期直肠癌患者的预后。具体而言，我们进行了一项回顾性分析，纳入了100例局部晚期直肠腺癌患者，这些患者于2013年1月至2019年12月期间在三个不同的肿瘤机构接受了C-RT，随后接受了根治性手术。我们的实验设计重点是通过MRI评估基线时和C-RT后的大体肿瘤体积（GTV），并在T2、扩散加权成像（DWI）和表观扩散系数（ADC）序列上勾勒出其轮廓。使用LifeX软件提取多个纹理参数，而D-TA计算为两个时间点的变化百分比。因此，进行了单变量和多变量分析（逻辑回归），以便将上述纹理分析参数与所检查患者群体中的病理反应频率相关联，重点是将完全病理缓解（pCR，无存活癌细胞：肿瘤退缩分级1级）的检测作为主要统计终点。考虑到在21例患者中只有21%实现了实际的pCR，对三个不同的数据集进行了ROC曲线分析。在我们的训练数据集系列中，进行单变量和二元逻辑分析时发现，pCR频率仅与ADC灰度共生矩阵熵显著相关（pCR的AUC为0.87）。然后在其余两个验证数据集中重复进行了验证性二元逻辑回归分析（pCR的AUC分别为0.92和0.88）。总体而言，这些结果支持了这样的假设，即D-TA在检测我们患者系列中pCR的发生方面可能具有显著的预测价值。如果在前瞻性多中心试验中得到证实，这些结果可能在选择局部晚期直肠癌患者方面发挥关键作用，这些患者可能从新辅助放化疗后的根治性手术中获益。
