医学
接收机工作特性
置信区间
磁共振成像
放射科
逻辑回归
新辅助治疗
无线电技术
结直肠癌
特征选择
放化疗
有效扩散系数
内科学
核医学
癌症
人工智能
放射治疗
计算机科学
乳腺癌
作者
Lijuan Wan,Wenjing Peng,Shuangmei Zou,Feng Ye,Yayuan Geng,Han Ouyang,Xinming Zhao,Hongmei Zhang
标识
DOI:10.1016/j.acra.2020.10.026
摘要
To investigate the capability of delta-radiomics to predict pathological complete response (pCR) after neoadjuvant chemoradiotherapy (nCRT) in patients with locally advanced rectal cancer (LARC).This retrospective study enrolled 165 consecutive patients with LARC (training set, n = 116; test set, n = 49) who received nCRT before surgery. All patients underwent pre- and post-nCRT MRI examination from which radiomics features were extracted. A delta-radiomics feature was defined as the percentage change in a radiomics feature from pre- to post-nCRT MRI. A data reduction and feature selection process including the least absolute shrinkage and selection operator algorithm was performed for building T2-weighted imaging (T2WI) and diffusion-weighted imaging (DWI) delta-radiomics signature. Logistic regression was used to build a T2WI and DWI combined radiomics model. Receiver operating characteristic analysis was performed to assess diagnostic performance. Delong method was used to compare the performance of delta-radiomics model with that of magnetic resonance tumor regression grade (mrTRG).Twenty-seven of 165 patients (16.4%) achieved pCR. T2WI and DWI delta-radiomics signature, and the combined model showed good predictive performance for pCR. The combined model achieved the highest areas under the receiver operating characteristic curves of 0.91 (95% confidence interval: 0.85-0.98) and 0.91 (95% confidence interval: 0.83-0.99) in the training and test sets, respectively (significantly greater than those for mrTRG; training set, p < 0.001; test set, p = 0.04).MRI-based delta-radiomics can help predict pCR after nCRT in patients with LARC with better performance than mrTRG.
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