Nardone Valerio, Reginelli Alfonso, Scala Fernando, Carbone Salvatore Francesco, Mazzei Maria Antonietta, Sebaste Lucio, Carfagno Tommaso, Battaglia Giuseppe, Pastina Pierpaolo, Correale Pierpaolo, Tini Paolo, Pellino Gianluca, Cappabianca Salvatore, Pirtoli Luigi
Istituto Toscano Tumori, Florence, Italy.
Unit of Radiation Oncology, University Hospital of Siena, Siena, Italy.
Gastroenterol Res Pract. 2019 Jan 17;2019:8505798. doi: 10.1155/2019/8505798. eCollection 2019.
We hypothesized that texture analysis (TA) from the preoperative MRI can predict early disease progression (ePD), defined as the percentage of patients who relapsed or showed distant metastasis within three months from the radical surgery, in patients with locally advanced rectal cancer (LARC, stage II and III, AJCC) undergoing neoadjuvant chemoradiotherapy (C-RT).
This retrospective monoinstitutional cohort study included 49 consecutive patients in total with a newly diagnosed rectal cancer. All the patients underwent baseline abdominal MRI and CT scan of the chest and abdomen to exclude distant metastasis before C-RT. Texture parameters were extracted from MRI performed before C-RT (T1, DWI, and ADC sequences) using LifeX Software, a dedicated software for extracting texture parameters from radiological imaging. We divided the cohort in a training set of 34 patients and a validation set of 15 patients, and we tested the data sets for homogeneity, considering the clinical variables. Then we performed univariate and multivariate analysis, and a ROC curve was also generated.
Thirteen patients (26.5%) showed an ePD, three of whom with lung metastases and ten with liver relapse. The model was validated based on the prediction accuracy calculated in a previously unseen set of 15 patients. The prediction accuracy of the generated model was 82% (AUC = 0.853) in the training and 80% (AUC = 0.833) in the validation cohort. The only significant features at multivariate analysis was DWI GLCM Correlation (OR: 0.239, < 0.001).
Our results suggest that TA could be useful to identify patients that may develop early progression.
我们假设，对于接受新辅助放化疗（C-RT）的局部晚期直肠癌（LARC，美国癌症联合委员会[AJCC]分期为II期和III期）患者，术前MRI纹理分析（TA）能够预测早期疾病进展（ePD），其定义为根治性手术后三个月内复发或出现远处转移的患者百分比。
这项回顾性单机构队列研究共纳入49例新诊断的直肠癌患者。所有患者在接受C-RT前均接受了基线腹部MRI以及胸部和腹部CT扫描以排除远处转移。使用LifeX软件从C-RT前进行的MRI（T1、DWI和ADC序列）中提取纹理参数，该软件是一种专门用于从放射影像中提取纹理参数的软件。我们将队列分为一个包含34例患者的训练集和一个包含15例患者的验证集，并考虑临床变量对数据集进行同质性检验。然后我们进行了单因素和多因素分析，还生成了ROC曲线。
13例患者（26.5%）出现了ePD，其中3例有肺转移，10例有肝复发。该模型基于在一组之前未见过的15例患者中计算出的预测准确性进行验证。所生成模型在训练队列中的预测准确性为82%（AUC = 0.853），在验证队列中的预测准确性为80%（AUC = 0.833）。多因素分析中唯一显著的特征是DWI灰度共生矩阵相关性（OR：0.239，P < 0.001）。
我们的结果表明，TA可能有助于识别可能发生早期进展的患者。
