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  • Title: Identifying Associations between DCE-MRI Radiomic Features and Expression Heterogeneity of Hallmark Pathways in Breast Cancer: A Multi-Center Radiogenomic Study.
    Author: Ming W, Zhu Y, Li F, Bai Y, Gu W, Liu Y, Sun X, Liu X, Liu H.
    Journal: Genes (Basel); 2022 Dec 22; 14(1):. PubMed ID: 36672769.
    Abstract:
    BACKGROUND: To investigate the relationship between dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomic features and the expression activity of hallmark pathways and to develop prediction models of pathway-level heterogeneity for breast cancer (BC) patients. METHODS: Two radiogenomic cohorts were analyzed (n = 246). Tumor regions were segmented semiautomatically, and 174 imaging features were extracted. Gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to identify significant imaging-pathway associations. Random forest regression was used to predict pathway enrichment scores. Five-fold cross-validation and grid search were used to determine the optimal preprocessing operation and hyperparameters. RESULTS: We identified 43 pathways, and 101 radiomic features were significantly related in the discovery cohort (p-value < 0.05). The imaging features of the tumor shape and mid-to-late post-contrast stages showed more transcriptional connections. Ten pathways relevant to functions such as cell cycle showed a high correlation with imaging in both cohorts. The prediction model for the mTORC1 signaling pathway achieved the best performance with the mean absolute errors (MAEs) of 27.29 and 28.61% in internal and external test sets, respectively. CONCLUSIONS: The DCE-MRI features were associated with hallmark activities and may improve individualized medicine for BC by noninvasively predicting pathway-level heterogeneity.
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