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

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 < 0.001), hot pot consumption (P < 0.001), Radscore 1 (P = 0.01), and Radscore 2 (P < 0.001) were independent factors affecting TSCC-OS. The same result was validated by the XGBoost algorithm. The nomogram based on the aforementioned factors exhibited good discrimination (C-index 0.86/0.81) and calibration (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.