Pretreatment MR-based radiomics nomogram as potential imaging biomarker for individualized assessment of perineural inva
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Pretreatment MR‑based radiomics nomogram as potential imaging biomarker for individualized assessment of perineural invasion status in rectal cancer Jiayou Chen1 · Ying Chen1 · Dechun Zheng1 · Peipei Pang2 · Hejun Zhang3 · Xiang Zheng1 · Jiang Liao1 Received: 6 June 2020 / Revised: 8 August 2020 / Accepted: 15 August 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Purpose To investigate whether pretreatment magnetic resonance (MR)-based radiomics nomogram can individualize prediction of perineural invasion (PNI) status in rectal cancer (RC). Material and methods A total of 122 RC patients with pathologically confirmed were classified as training cohort (n = 87) and test cohort (n = 35). 180 radiomics features were extracted from all lesions based on oblique axial T 2WI TSE images. The dimensionality reduction and feature selection in training cohort were realized by the maximum relevance minimum redundancy (mRMR) algorithm and the least absolute shrinkage and selection operator (LASSO) regression model. A predictive model combining radiomics features and clinical risk factors (pathological N stage, pathological LVI status) was established by multivariate logistic regression analysis. The performance of the model was assessed based on its receiver operating characteristic (ROC) curve, nomogram, and calibration. Results The developed radiomics nomogram that integrated the radiomics signature and clinical risk factors could provide discrimination in the training and test cohorts. The accuracy and the area under the curve (AUC) for assessing PNI status were 0.82, 0.86, respectively, in the training cohort, while they were 0.71 and 0.85 in the test cohort. The goodness-of-fit of the nomogram was evaluated using the Hosmer–Lemeshow test (p = 0.52 in training cohort and p = 0.24 in test cohort). Decision curve analysis (DCA) showed that the radiomics nomogram was clinically useful. Conclusion The developed radiomics nomogram might be helpful in the individualized assessment PNI status in patients with RC. This stratification of RC patients according to their PNI status may provide the basis for individualized adjuvant therapy, especially for stage II patients. Keywords Rectal cancer · Peripheral nerve · Radiomics · Nomogram · Magnetic resonance imaging Abbreviations AUC Area under curve CI Confidence interval Electronic supplementary material The online version of this article (https://doi.org/10.1007/s00261-020-02710-4) contains supplementary material, which is available to authorized users. * Jiayou Chen [email protected] 1
Department of Radiology, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, Fuzhou 350014, Fujian, China
2
GE Healthcare (China), Hangzhou, China
3
Department of Pathology, Fujian Cancer Hospital & Fujian Medical University Cancer Hospital, Fuzhou 350014, Fujian, China
RC Rectal cancer LVI Lymphovascular invasion PNI Perineural invasion MR Magnetic resonance RLM Run-length matrix GLCM Gray-level co-oc
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