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MRI-based delta-radiomics are predictive of pathological complete response after neoadjuvant chemoradiotherapy in locally advanced rectal cancer

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
出处
期刊:Academic Radiology [Elsevier BV]
卷期号:28: S95-S104 被引量:62
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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