Synthetic MRI and diffusion-weighted imaging for differentiating nasopharyngeal lymphoma from nasopharyngeal carcinoma: combination with morphological features

Abstract

Objectives To investigate the feasibility of synthetic MRI (syMRI), diffusion-weighted imaging (DWI) and their combination with morphological features for differentiating nasopharyngeal lymphoma (NPL) from nasopharyngeal carcinoma (NPC). Methods Sixty-nine patients with nasopharyngeal tumors (NPL, n = 22; NPC, n = 47) who underwent syMRI and DWI were retrospectively enrolled between October 2020 and May 2022. syMRI and DWI quantitative parameters (T1, T2, PD, ADC), and morphological features were obtained. Diagnostic performance was assessed by independent sample t-test, chi-square test, logistic regression analysis, receiver operating characteristic curve (ROC), and DeLong test. Results NPL has significantly lower T2, PD, and ADC values compared to NPC (all P < 0.05), whereas no significant difference was found in T1 value between these two entities (P > 0.05). The morphological features of tumor type, skull-base involvement, Waldeyer ring involvement, and lymph nodes involvement region were significantly different between NPL and NPC (all P < 0.05). The syMRI (T2+PD) model has better diagnostic efficacy, with AUC, sensitivity, specificity, and accuracy of 0.875, 77.27%, 89.36%, and 85.51%. Compared with syMRI model, syMRI+Morph (PD+Waldeyer ring involvement+lymph nodes involvement region), syMRI+DWI (T2+PD+ADC), and syMRI+DWI+Morph (PD+ADC+skull base involvement+Waldeyer ring involvement) models can further improve the diagnostic efficiency (all P < 0.05). Furthermore, syMRI+DWI+Morph model has excellent diagnostic performance, with AUC, sensitivity, specificity, and accuracy of 0.986, 95.47%, 97.87%, and 97.10%, respectively. Conclusion syMRI and DWI quantitative parameters were helpful in discriminating NPL from NPC. syMRI+DWI+Morph model has the excellent diagnostic efficiency in differentiating these two entities. Advances in knowledge syMRI+DWI+morphological feature method can differentiate NPL from NPC with excellent diagnostic performance.