接收机工作特性
医学
无线电技术
组内相关
置信区间
乳腺癌
磁共振成像
核医学
再现性
逻辑回归
Lasso(编程语言)
威尔科克森符号秩检验
有效扩散系数
放射科
乳房磁振造影
内科学
癌症
计算机科学
数学
乳腺摄影术
统计
曼惠特尼U检验
万维网
作者
Chunli Li,Lirong Song,Jiandong Yin
摘要
Radiomics has been applied to breast magnetic resonance imaging (MRI) for gene status prediction. However, the features of peritumoral regions were not thoroughly investigated.To evaluate the use of intratumoral and peritumoral regions from functional parametric maps based on breast dynamic contrast-enhanced MRI (DCE-MRI) for prediction of HER-2 and Ki-67 status.Retrospective.A total of 351 female patients (average age, 51 years) with pathologically confirmed breast cancer were assigned to the training (n = 243) and validation (n = 108) cohorts.3.0T, T1 gradient echo.Radiomic features were extracted from intratumoral and peritumoral regions on six functional parametric maps calculated using time-intensity curves of DCE-MRI. The intraclass correlation coefficients (ICCs) were used to determine the reproducibility of feature extraction. Based on the intratumoral, peritumoral, and combined intra- and peritumoral regions, three radiomics signatures (RSs) were built using the least absolute shrinkage and selection operator (LASSO) logistic regression model, respectively.Wilcoxon rank-sum test, minimum redundancy maximum relevance, LASSO, receiver operating characteristic curve (ROC) analysis, and DeLong test.The intratumoral and peritumoral RSs for prediction of HER-2 and Ki-67 status achieved areas under the ROC (AUCs) of 0.683 (95% confidence interval [CI], 0.574-0.793) and 0.690 (95% CI, 0.577-0.804), and 0.714 (95% CI, 0.616-0.812) and 0.692 (95% CI, 0.590-0.794) in the validation cohort, respectively. The combined RSs yielded AUCs of 0.713 (95% CI, 0.604-0.823) and 0.749 (95% CI, 0.656-0.841), respectively. There were no significant differences in prediction performance among intratumoral, peritumoral, and combined RSs. Most (69.7%) of the features had good agreement (ICCs >0.8).Radiomic features of intratumoral and peritumoral regions on functional parametric maps based on breast DCE-MRI had the potential to identify HER-2 and Ki-67 status.3 Technical Efficacy Stage: 2.
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