World Journal of Surgical Oncology (Aug 2024)

A novel nomogram for predicting overall survival in patients with tongue squamous cell carcinoma using clinical features and MRI radiomics data: a pilot study

  • Yongling Yao,
  • Xin Jin,
  • Tianfang Peng,
  • Ping Song,
  • Yingjian Ye,
  • Lina Song,
  • Huantian Li,
  • Peng An

DOI
https://doi.org/10.1186/s12957-024-03508-0
Journal volume & issue
Vol. 22, no. 1
pp. 1 – 13

Abstract

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Abstract Objective Tongue squamous cell carcinoma (TSCC) accounts for 43.4% of oral cancers in China and has a poor prognosis. This study aimed to explore whether radiomics features extracted from preoperative magnetic resonance imaging (MRI) could predict overall survival (OS) in patients with TSCC. Methods The clinical imaging data of 232 patients with pathologically confirmed TSCC at Xiangyang No. 1 People’s Hospital were retrospectively analyzed from February 2010 to October 2022. Based on 2–10 years of follow-up, patients were categorized into two groups: control (healthy survival, n = 148) and research (adverse events: recurrence or metastasis-related death, n = 84). A training and a test set were established using a 7:3 ratio and a time node. Radiomics features were extracted from axial T2-weighted imaging, contrast-enhanced T1-weighted imaging, and diffusion-weighted imaging (DWI) sequences. The corresponding radiomics scores were generated using the least absolute shrinkage and selection operator algorithm. Kaplan–Meier and multivariate Cox regression analyses were used to screen for independent factors affecting adverse events in patients with TSCC using clinical and pathological results. A novel nomogram was established to predict the probability of adverse events and OS in patients with TSCC. Results The incidence of adverse events within 2–10 years after surgery was 36.21%. Kaplan–Meier analysis revealed that hot pot consumption, betel nut chewing, platelet–lymphocyte ratio, drug use, neutrophil–lymphocyte ratio, Radscore, and other factors impacted TSCC survival. Multivariate Cox regression analysis revealed that the clinical stage (P 0.05) in the training and test sets, accurately predicting the risk of adverse events and survival. Conclusion The nomogram constructed using clinical data and MRI radiomics parameters may accurately predict TSCC-OS noninvasively, thereby assisting clinicians in promptly modifying treatment strategies to improve patient prognosis.

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