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Prediction of Individual Lymph Node Metastatic Status in Esophageal Squamous Cell Carcinoma Using Routine Computed Tomography Imaging: Comparison of Size-Based Measurements and Radiomics-Based Models

  • Thoracic Oncology
  • Published:
Annals of Surgical Oncology Aims and scope Submit manuscript

Abstract

Background

Lymph node status is vital for prognosis and treatment decisions for esophageal squamous cell carcinoma (ESCC). This study aimed to construct and evaluate an optimal radiomics-based method for a more accurate evaluation of individual regional lymph node status in ESCC and to compare it with traditional size-based measurements.

Methods

The study consecutively collected 3225 regional lymph nodes from 530 ESCC patients receiving upfront surgery from January 2011 to October 2015. Computed tomography (CT) scans for individual lymph nodes were analyzed. The study evaluated the predictive performance of machine-learning models trained on features extracted from two-dimensional (2D) and three-dimensional (3D) radiomics by different contouring methods. Robust and important radiomics features were selected, and classification models were further established and validated.

Results

The lymph node metastasis rate was 13.2% (427/3225). The average short-axis diameter was 6.4 mm for benign lymph nodes and 7.9 mm for metastatic lymph nodes. The division of lymph node stations into five regions according to anatomic lymph node drainage (cervical, upper mediastinal, middle mediastinal, lower mediastinal, and abdominal regions) improved the predictive performance. The 2D radiomics method showed optimal diagnostic results, with more efficient segmentation of nodal lesions. In the test set, this optimal model achieved an area under the receiver operating characteristic curve of 0.841–0.891, an accuracy of 84.2–94.7%, a sensitivity of 65.7–83.3%, and a specificity of 84.4–96.7%.

Conclusions

The 2D radiomics-based models noninvasively predicted the metastatic status of an individual lymph node in ESCC and outperformed the conventional size-based measurement. The 2D radiomics-based model could be incorporated into the current clinical workflow to enable better decision-making for treatment strategies.

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Acknowledgment

This work was supported by the National Natural Science Foundation of China (Grant Nos. 81402003 and 81972614).

Author information

Author notes

  1. Chenyi Xie and Yihuai Hu have contributed equally as first authors.

  2. Varut Vardhanabhuti and Hong Yang have contributed equally as senior authors.

Authors and Affiliations

  1. Department of Thoracic Surgery, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Esophageal Cancer Institute, Sun Yat-sen University Cancer Center, Guangzhou, China

    Yihuai Hu MD, PhD, Jianhua Fu MD, PhD & Hong Yang MD, PhD

  2. Department of Radiology, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China

    Chenyi Xie MD, PhD

  3. Department of Thoracic Surgery, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China

    Yihuai Hu MD, PhD

  4. Department of Diagnostic Radiology, Li Ka Shing Faculty of Medicine, University of Hong Kong, Pok Fu Lam, Hong Kong SAR, China

    Chenyi Xie MD, PhD & Varut Vardhanabhuti FRCR, PhD

  5. Department of Radiology, Sun Yat-sen University Cancer Center, Guangzhou, China

    Lujun Han MD, PhD

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Correspondence to Varut Vardhanabhuti FRCR, PhD or Hong Yang MD, PhD.

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Xie, C., Hu, Y., Han, L. et al. Prediction of Individual Lymph Node Metastatic Status in Esophageal Squamous Cell Carcinoma Using Routine Computed Tomography Imaging: Comparison of Size-Based Measurements and Radiomics-Based Models. Ann Surg Oncol 29, 8117–8126 (2022). https://doi.org/10.1245/s10434-022-12207-7

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