Application of First-Order Feature Analysis of DWI-ADC in Rare Malignant Mesenchymal Tumours of the Maxillofacial Region

Objective: To research the first-order features of magnetic resonance (MR) diffusion-weighted imaging (DWI)-apparent diffusion coefficient (ADC) in maxillofacial malignant mesenchymal tumours. Methods: : Eight patients that the patients' diagnoses were confirmed by pathology, and the clinical and imaging data were determined to be accurate. The patients were all examined by 1.5T MR imaging (MRI). Results: : PyRadiomics were used to extract radiomics imaging features. The ADC mean and ADC median of sarcoma tissues were 42.2689 and 42.7275, respectively, significantly higher than those in lymphoma tissues (ADC mean (-61.3343) and ADC median (-70.2335)). Conclusion: While the statistical difference is not significant, it is consistent with the outcome of the manual measurement of the ADC mean value of the most significant cross-section of five cases of lymphoma. Development of tumour volume based on the ADC parameter map of DWI demonstrates that the first-order ADC radiomics features analysis can provide new imaging markers for the differentiation of maxillofacial sarcoma and lymphoma. Therefore, first-order ADC features of ADC kurt combined ADC skew may improve the diagnosis level.