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Intratumoral and Peritumoral Radiomics Based on Functional Parametric Maps from Breast DCE‐MRI for Prediction of HER ‐2 and Ki‐67 Status
Author(s) -
Li Chunli,
Song Lirong,
Yin Jiandong
Publication year - 2021
Publication title -
journal of magnetic resonance imaging
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.563
H-Index - 160
eISSN - 1522-2586
pISSN - 1053-1807
DOI - 10.1002/jmri.27651
Subject(s) - medicine , receiver operating characteristic , intraclass correlation , breast mri , confidence interval , magnetic resonance imaging , breast cancer , reproducibility , logistic regression , nuclear medicine , radiomics , wilcoxon signed rank test , lasso (programming language) , effective diffusion coefficient , radiology , cancer , computer science , mathematics , mammography , statistics , mann–whitney u test , world wide web
Background Radiomics has been applied to breast magnetic resonance imaging (MRI) for gene status prediction. However, the features of peritumoral regions were not thoroughly investigated. Purpose 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. Study Type Retrospective. Population 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. Field Strength/Sequence 3. 0T , T 1 gradient echo. Assessment 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. Statistical Tests Wilcoxon rank‐sum test, minimum redundancy maximum relevance, LASSO, receiver operating characteristic curve (ROC) analysis, and DeLong test. Results 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). Data Conclusion 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. Level of Evidence : 3 Technical Efficacy Stage : 2