Apparent Diffusion Coefficient-Based Radiomic Nomogram in Sinonasal Squamous Cell Carcinoma: A Preliminary Study on Histological Grade Evaluation.

PURPOSE

The aim of the study was to develop and validate a nomogram model combining radiomic features and clinical characteristics to preoperatively differentiate between low- and high-grade sinonasal squamous cell carcinomas.

MATERIAL AND METHODS

A total of 174 patients who underwent diffusion-weighted imaging were included in this study. The patients were allocated to the training and testing cohorts randomly at a ratio of 6:4. The least absolute shrinkage and selection operator regression was applied for feature selection and radiomic signature (radscore) construction. Multivariable logistic regression analysis was applied to identify independent predictors. The performance of the model was evaluated using the area under the receiver operating characteristic curve (AUC), the calibration curve, decision curve analysis, and the clinical impact curve.

RESULTS

The radscore included 9 selected radiomic features. The radscore and clinical stage were independent predictors. The nomogram showed better performance (training cohort: AUC, 0.92; 95% confidence interval, 0.85-0.96; testing cohort: AUC, 0.91; 95% CI, 0.82-0.97) than either the radscore or the clinical stage in both the training and test cohorts ( P < 0.050). The nomogram demonstrated good calibration and clinical usefulness.

CONCLUSIONS

The apparent diffusion coefficient-based radiomic nomogram model could be useful in differentiating between low- and high-grade sinonasal squamous cell carcinomas.