biostudies-literature00480Unknown12Xia BScience and Technology Commission of Shanghai MunicipalityShanghai Shenkang Hospital Development CenterNational Natural Science Foundation of China<b>Background:</b> 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. <b>Methods:</b> Patients (<i>n</i> = 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 (<i>n</i> = 109) were used as the training group, and patients from the other hospital (<i>n</i> = 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. <b>Results:</b> 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 (<i>p</i><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). <b>Conclusion:</b> 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.Frontiers in genetics783513https://www.ebi.ac.uk/biostudies/studies/S-EPMC8632946biostudies-literatureA Combined Nomogram Model to Predict Disease-free Survival in Triple-Negative Breast Cancer Patients With Neoadjuvant Chemotherapy.PMC8632946Liu YQian ZShao ZGu YZhou SYou CXia BWang HWang ZXiao QChai W48falseA Combined Nomogram Model to Predict Disease-free Survival in Triple-Negative Breast Cancer Patients With Neoadjuvant Chemotherapy.<b>Background:</b> 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. <b>Methods:</b> Patients (<i>n</i> = 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 (<i>n</i> = 109) were used as the training group, and patients from the other hospital (<i>n</i> = 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. <b>Results:</b> 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 (<i>p</i><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). <b>Conclusion:</b> 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.2021-01-01T00:00:00Z20212024-02-15T21:07:29.129Z2022-02-11T13:53:27.875ZS-EPMC86329463486827310.3389/fgene.2021.783513