Chen Li, Zhu Wenchao, Zhang Wei, Chen Engeng, Zhou Wei
Department of Colorectal Surgery, School of Medicine, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China.
Department of Radiology, School of Medicine, Sir Run Run Shaw Hospital, Zhejiang University, Hangzhou, China.
Langenbecks Arch Surg. 2024 Jul 17;409(1):218. doi: 10.1007/s00423-024-03416-7.
To predict severe inflammatory response after neoadjuvant radiochemotherapy in locally advanced rectal cancer (RC) patients using magnetic resonance imaging (MRI) radiomics models.
This retrospective study included patients who underwent radical surgery for RC cancer after neoadjuvant radiochemotherapy between July 2017 and December 2019 at XXX Hospital. MRI radiomics features were extracted from T2WI images before (pre-nRCT-RF) and after (post-nRCT-RF) neoadjuvant radiochemotherapy, and the variation of radiomics features before and after neoadjuvant radiochemotherapy (delta-RF) were calculated. Eight, eight, and five most relevant features were identified for pre-nRCT-RF, post-nRCT-RF, and delta-RF, respectively.
Eighty-six patients were included and randomized 3:1 to the training and test set (n = 65 and n = 21, respectively). The prediction model based on delta-RF had areas under the curve (AUCs) of 0.80 and 0.85 in the training and test set, respectively. A higher rate of difficult operations was observed in patients with severe inflammation (65.5% vs. 42.9%, P = 0.045).
The prediction model based on MRI delta-RF may be a useful tool for predicting severe inflammatory response after neoadjuvant radiochemotherapy in locally advanced RC patients.
使用磁共振成像(MRI)影像组学模型预测局部晚期直肠癌(RC)患者新辅助放化疗后的严重炎症反应。
这项回顾性研究纳入了2017年7月至2019年12月期间在XXX医院接受新辅助放化疗后行RC根治性手术的患者。从新辅助放化疗前(nRCT-RF前)和后(nRCT-RF后)的T2WI图像中提取MRI影像组学特征,并计算新辅助放化疗前后影像组学特征的变化(delta-RF)。分别为nRCT-RF前、nRCT-RF后和delta-RF确定了8个、8个和5个最相关的特征。
纳入86例患者,按3:1随机分为训练组和测试组(分别为n = 65和n = 21)。基于delta-RF的预测模型在训练组和测试组中的曲线下面积(AUC)分别为0.80和0.85。严重炎症患者的困难手术率更高(65.5%对42.9%,P = 0.045)。
基于MRI delta-RF的预测模型可能是预测局部晚期RC患者新辅助放化疗后严重炎症反应的有用工具。