Development and External Validation of an MRI-Based Radiomics Nomogram for Pretreatment Prediction for Early Relapse in Osteosarcoma: A Retrospective Multicenter Study

Abstract

Background: To develop and externally validate an MR-based radiomics nomogram from retrospective multicenter datasets for pretreatment prediction of early relapse (≤1 year) in osteosarcoma after surgical resection. Methods: This multicenter study retrospectively enrolled 93 patients (training cohort: 62 patients from four hospitals; validation cohort: 31 patients from two hospitals) with clinicopathologically confirmed osteosarcoma who received neoadjuvant chemotherapy and surgical resection at six hospitals between January 2009 and October 2017. Radiomics feature was extracted from contrast-enhanced fat-suppressed T1-weighted (CE FS T1-w) images. A radiomics signature was constructed with least absolute shrinkage and selection operator (LASSO) regression. The radiomics nomogram that incorporated the radiomics signature and subjective MRI-assessed risk factors was developed to predict early relapse with a multivariate logistic regression model in the training cohort and validated in the external validation cohort. The performance of the nomogram was assessed by its discrimination, calibration, and clinical usefulness. Findings: The radiomics nomogram, which incorporated a radiomics signature (consisted of six selected features) and subjective MRI-assessed risk factors (joint invasion and perivascular involvement) from the multicenter datasets, achieved good discrimination in the training cohort (C-index: 0.907, 95% CI: 0.838-0.977) and external validation cohort (C-index: 0.811, 95% CI: 0.653-0.970), and good calibration. Decision curve analysis suggested that the combined nomogram was clinically useful. Interpretation: The proposed MRI-based radiomics nomogram could provide a nonvasive tool to develop a model for pretreatment prediction of early relapse in osteosarcoma, which has potential to lead to improvement of personalized pretreatment management of osteosarcoma. Funding: This research is supported by the National Key Research and Development Program of China (No. 2017YFC1309100), the National Natural Science Foundation of China (Grant Nos. 81871510, 81771912). Declaration of Interest: No competing interest exists. Ethical Approval: This multicentric study was approved by the ethics committee of every participating hospital and was conducted in accordance with the Declaration of Helsinki.