Abstract
The purpose of this preliminary study was to evaluate the differences in Magnetic Resonance Imaging (MRI)-based radiomics analysis between cerebellopontine angle neurinomas and schwannomas originating from other locations in the neck spaces. Twenty-six patients with available MRI exams and head and neck schwannomas were included. Lesions were manually segmented on the precontrast and postcontrast T1 sequences. The radiomics features were extracted by using PyRadiomics software, and a total of 120 radiomics features were obtained from each segmented tumor volume. An operator-independent hybrid descriptive‐inferential method was adopted for the selection and reduction of the features, while discriminant analysis was used to construct the predictive model. On precontrast T1 images, the original_glcm_InverseVariance demonstrated a good performance with an area under the receiver operating characteristic (AUROC) of 0.756 (95% C.I. 0.532–0.979; p = 0.026). On postcontrast T1 images, the original_glcm_Idmn provided a good diagnostic performance with an AUROC of 0.779 (95% C.I. 0.572–0.987; p = 0.014). In conclusion, this preliminary analysis showed statistically significant differences in radiomics features between cerebellopontine angle neurinomas and schwannomas of other locations in the neck spaces.
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Cutaia, G. et al. (2022). Radiomics Analyses of Schwannomas in the Head and Neck: A Preliminary Analysis. In: Mazzeo, P.L., Frontoni, E., Sclaroff, S., Distante, C. (eds) Image Analysis and Processing. ICIAP 2022 Workshops. ICIAP 2022. Lecture Notes in Computer Science, vol 13373. Springer, Cham. https://doi.org/10.1007/978-3-031-13321-3_28
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