Korean Journal of Radiology

The Korean Society of Radiology (대한영상의학회)
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Prediction of Residual Axillary Nodal Metastasis Following Neoadjuvant Chemotherapy for Breast Cancer: Radiomics Analysis Based on Chest Computed Tomography

  • Hyo-jae Lee (Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School) ;
  • Anh-Tien Nguyen (Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School) ;
  • Myung Won Song (Department of Radiology, Chonnam National University Hwasun Hospital, Chonnam National University Medical School) ;
  • Jong Eun Lee (Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School) ;
  • Seol Bin Park (Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School) ;
  • Won Gi Jeong (Department of Radiology, Chonnam National University Hwasun Hospital, Chonnam National University Medical School) ;
  • Min Ho Park (Department of Surgery, Chonnam National University Hwasun Hospital, Chonnam National University Medical School) ;
  • Ji Shin Lee (Department of Pathology, Chonnam National University Hwasun Hospital, Chonnam National University Medical School) ;
  • Ilwoo Park (Department of Radiology, Chonnam National University Hospital, Chonnam National University Medical School) ;
  • Hyo Soon Lim (Department of Radiology, Chonnam National University Hwasun Hospital, Chonnam National University Medical School)
  • Received : 2022.10.18
  • Accepted : 2023.04.30
  • Published : 2023.06.01
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Abstract

Objective: To evaluate the diagnostic performance of chest computed tomography (CT)-based qualitative and radiomics models for predicting residual axillary nodal metastasis after neoadjuvant chemotherapy (NAC) for patients with clinically node-positive breast cancer. Materials and Methods: This retrospective study included 226 women (mean age, 51.4 years) with clinically node-positive breast cancer treated with NAC followed by surgery between January 2015 and July 2021. Patients were randomly divided into the training and test sets (4:1 ratio). The following predictive models were built: a qualitative CT feature model using logistic regression based on qualitative imaging features of axillary nodes from the pooled data obtained using the visual interpretations of three radiologists; three radiomics models using radiomics features from three (intranodal, perinodal, and combined) different regions of interest (ROIs) delineated on pre-NAC CT and post-NAC CT using a gradient-boosting classifier; and fusion models integrating clinicopathologic factors with the qualitative CT feature model (referred to as clinical-qualitative CT feature models) or with the combined ROI radiomics model (referred to as clinical-radiomics models). The area under the curve (AUC) was used to assess and compare the model performance. Results: Clinical N stage, biological subtype, and primary tumor response indicated by imaging were associated with residual nodal metastasis during the multivariable analysis (all P < 0.05). The AUCs of the qualitative CT feature model and radiomics models (intranodal, perinodal, and combined ROI models) according to post-NAC CT were 0.642, 0.812, 0.762, and 0.832, respectively. The AUCs of the clinical-qualitative CT feature model and clinical-radiomics model according to post-NAC CT were 0.740 and 0.866, respectively. Conclusion: CT-based predictive models showed good diagnostic performance for predicting residual nodal metastasis after NAC. Quantitative radiomics analysis may provide a higher level of performance than qualitative CT features models. Larger multicenter studies should be conducted to confirm their performance.

Keywords

Acknowledgement

We appreciate the statistical consultation and analyses of Cho-Hee Hwang, MPH of the Regional Cardiocerebrovascular Center in Chonnam National University Hospital.

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