Technical feasibility of radiomics signature analyses for improving detection of occult tonsillar cancer

Diagnosis of occult palatine tonsil squamous cell carcinoma (SCC) using conventional magnetic resonance imaging (MRI) is difficult in patients with cervical nodal metastasis from an unknown primary site at presentation. We aimed to establish a radiomics approach based on MRI features extracted from the volume of interest in these patients. An Elastic Net model was developed to differentiate between normal palatine tonsils and occult palatine tonsil SCC. The diagnostic performances of the model with radiomics features extracted from T1-weighted image (WI), T2WI, contrast-enhanced T1WI, and an apparent diffusion coefficient (ADC) map had area under the receiver operating characteristic (AUROC) curve values of 0.831, 0.840, 0.781, and 0.807, respectively, for differential diagnosis. The model with features from the ADC alone showed the highest sensitivity of 90.0%, while the model with features from T1WI + T2WI + contrast-enhanced T1WI showed the highest AUROC of 0.853. The added sensitivity of the radiomics feature analysis were 34.6% over that of conventional MRI to detect occult palatine tonsil SCC. Therefore, we concluded that adding radiomics feature analysis to MRI may improve the detection sensitivity for occult palatine tonsil SCC in patients with a cervical nodal metastasis from cancer of an unknown primary site.