Frontiers in Oncology (Mar 2023)

Clinical features combined with ultrasound-based radiomics nomogram for discrimination between benign and malignant lesions in ultrasound suspected supraclavicular lymphadenectasis

  • Jieli Luo,
  • Jieli Luo,
  • Peile Jin,
  • Peile Jin,
  • Jifan Chen,
  • Jifan Chen,
  • Yajun Chen,
  • Yajun Chen,
  • Fuqiang Qiu,
  • Fuqiang Qiu,
  • Tingting Wang,
  • Tingting Wang,
  • Ying Zhang,
  • Ying Zhang,
  • Huili Pan,
  • Huili Pan,
  • Yurong Hong,
  • Yurong Hong,
  • Pintong Huang,
  • Pintong Huang,
  • Pintong Huang

DOI
https://doi.org/10.3389/fonc.2023.1048205
Journal volume & issue
Vol. 13

Abstract

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BackgroundConventional ultrasound (CUS) is the first choice for discrimination benign and malignant lymphadenectasis in supraclavicular lymph nodes (SCLNs), which is important for the further treatment. Radiomics provide more comprehensive and richer information than radiographic images, which are imperceptible to human eyes.ObjectiveThis study aimed to explore the clinical value of CUS-based radiomics analysis in preoperative differentiation of malignant from benign lymphadenectasis in CUS suspected SCLNs.MethodsThe characteristics of CUS images of 189 SCLNs were retrospectively analyzed, including 139 pathologically confirmed benign SCLNs and 50 malignant SCLNs. The data were randomly divided (7:3) into a training set (n=131) and a validation set (n=58). A total of 744 radiomics features were extracted from CUS images, radiomics score (Rad-score) built were using least absolute shrinkage and selection operator (LASSO) logistic regression. Rad-score model, CUS model, radiomics-CUS (Rad-score + CUS) model, clinic-radiomics (Clin + Rad-score) model, and combined CUS-clinic-radiomics (Clin + CUS + Rad-score) model were built using logistic regression. Diagnostic accuracy was assessed by receiver operating characteristic (ROC) curve analysis.ResultsA total of 20 radiomics features were selected from 744 radiomics features and calculated to construct Rad-score. The AUCs of Rad-score model, CUS model, Clin + Rad-score model, Rad-score + CUS model, and Clin + CUS + Rad-score model were 0.80, 0.72, 0.85, 0.83, 0.86 in the training set and 0.77, 0.80, 0.82, 0.81, 0.85 in the validation set. There was no statistical significance among the AUC of all models in the training and validation set. The calibration curve also indicated the good predictive performance of the proposed nomogram.ConclusionsThe Rad-score model, derived from supraclavicular ultrasound images, showed good predictive effect in differentiating benign from malignant lesions in patients with suspected supraclavicular lymphadenectasis.

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