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

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. 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. 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. 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.

Yao Y ，Jin X ，Peng T ，Song P ，Ye Y ，Song L ，Li H ，An P ... -  《World Journal of Surgical Oncology》

Prediction of Prognosis of Tongue Squamous Cell Carcinoma Based on Clinical MR Imaging Data Modeling.

Liu J ，Song L ，Zhou J ，Yu M ，Hu Y ，Zhang J ，Song P ，Ye Y ，Wang J ，Feng G ，Guo H ，An P ... -  《-》

[Establishment and verification of a prognostic nomogram for survival of tongue squamous cell carcinoma patients who underwent cervical dissection].

Su J ，Wang X ，Sun Z 《-》

A Prognostic Model Based on Clinicopathological Features and Inflammation- and Nutrition-Related Indicators Predicts Overall Survival in Surgical Patients With Tongue Squamous Cell Carcinoma.

Wei LF ，Huang XC ，Lin YW ，Luo Y ，Ding TY ，Liu CT ，Chu LY ，Xu YW ，Peng YH ，Guo HP ... -  《-》

An MRI-based radiomics-clinical nomogram for the overall survival prediction in patients with hypopharyngeal squamous cell carcinoma: a multi-cohort study.

To explore whether radiomics features extracted from pre-treatment magnetic resonance imaging (MRI) can predict the overall survival (OS) in patients with hypopharyngeal squamous cell carcinoma. A total of 190 patients with hypopharyngeal squamous cell carcinoma were eligibly enrolled from two institutions. Radiomics features were extracted from contrast-enhanced axial T1-weighted (CE-T1WI) sequence. The least absolute shrinkage selection operator (LASSO) algorithm was applied to establish a radiomics score correlated with OS. Multivariate logistic regression analysis was applied to determine the independent risk factors, which was combined with radiomics score to build the final radiomics nomogram. A radiomics score with 6 CE-T1WI features for OS prediction was constructed and validated; its integration with specific clinicopathologic factors (N stage) showed a better prediction performance in the training, internal validation, and external validation cohorts (C-index 0.78, 0.75, and 0.75). Calibration curves determined a good agreement between the predicted and actual overall survival. The radiomics-clinical nomogram and radiomics score might be non-invasive and reliable methods for the risk stratification in patients with hypopharyngeal squamous cell carcinoma. • An MRI-based radiomics model was constructed to evaluate of OS in patients with hypopharyngeal squamous cell carcinoma. • A radiomics-clinical nomogram that combined radiomics features and clinical characteristics was established. • Multi-cohort study validated the predictive performance of the radiomics-clinical nomogram to stratify patients with high risk in clinical practice.

Chen J ，Lu S ，Mao Y ，Tan L ，Li G ，Gao Y ，Tan P ，Huang D ，Zhang X ，Qiu Y ，Liu Y ... -  《-》