Abstract
Background: To investigate whether the radiomics signature (Rad-score) of DCE-MRI images obtained in triple-negative breast cancer (TNBC) patients before neoadjuvant chemotherapy (NAC) is associated with disease-free survival (DFS). Develop and validate an intuitive nomogram based on radiomics signatures, MRI findings, and clinicopathological variables to predict DFS. Methods: Patients (n = 150) from two hospitals who received NAC from August 2011 to May 2017 were diagnosed with TNBC by pathological biopsy, and follow-up through May 2020 was retrospectively analysed. Patients from one hospital (n = 109) were used as the training group, and patients from the other hospital (n = 41) were used as the validation group. ROIs were drawn on 1.5 T MRI T1W enhancement images of the whole volume of the tumour obtained with a 3D slicer. Radiomics signatures predicting DFS were identified, optimal cut-off value for Rad-score was determined, and the associations between DFS and radiomics signatures, MRI findings, and clinicopathological variables were analysed. A nomogram was developed and validated for individualized DFS estimation. Results: The median follow-up time was 53.5 months, and 45 of 150 (30.0%) patients experienced recurrence and metastasis. The optimum cut-off value of the Rad-score was 0.2528, which stratified patients into high- and low-risk groups for DFS in the training group (p<0.001) and was validated in the external validation group. Multivariate analysis identified three independent indicators: multifocal/centric disease status, pCR status, and Rad-score. A nomogram based on these factors showed discriminatory ability, the C-index of the model was 0.834 (95% CI, 0.761–0.907) and 0.868 (95% CI, 0.787–949) in the training and the validation groups, respectively, which is better than clinicoradiological nomogram(training group: C-index = 0.726, 95% CI = 0.709–0.743; validation group: C-index = 0.774,95% CI = 0.743–0.805). Conclusion: The Rad-score derived from preoperative MRI features is an independent biomarker for DFS prediction in patients with TNBC to NAC, and the combined radiomics nomogram improved individualized DFS estimation.
Highlights
Triple-negative breast cancer (TNBC) is a clinical challenge because of its invasive nature, high risk of distant metastasis, and poor prognosis
Except for the clinical stage, pre-neoadjuvant chemotherapy (NAC) N stage and pathological complete response (pCR) status, there were no differences between the training and validation groups
We demonstrated the prognostic value of multiphase CE-MRI radiomics features for patients with TNBC treated with NAC
Summary
Triple-negative breast cancer (TNBC) is a clinical challenge because of its invasive nature, high risk of distant metastasis, and poor prognosis. PCR alone is not enough to predict the long-term recurrence-free survival rate of patients with TNBC, and an efficient prognostic biomarker is urgently needed to help stratify patients and create treatment guidelines. The radiomics nomogram provided a promising prediction of neoadjuvant chemotherapy efficacy in breast cancer patients based on pretreatment MRI images (Bian et al, 2020; Chen et al, 2020). Another study reported that the radiomics signature(Rad-score) could be used for DFS prediction in HER-2-positive invasive breast cancer treated with NAC, and the radiomicsclinicoradiologic-based nomogram may potentially be useful for personalized treatment strategies (Li et al, 2020). To investigate whether the radiomics signature (Rad-score) of DCE-MRI images obtained in triple-negative breast cancer (TNBC) patients before neoadjuvant chemotherapy (NAC) is associated with disease-free survival (DFS). Develop and validate an intuitive nomogram based on radiomics signatures, MRI findings, and clinicopathological variables to predict DFS
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