Objectives: The present study aims to compare the diagnostic efficacy of MR, 18F-FDG PET/CT, and 18F-FDG PET/MR for the local detection of early-stage extranodal natural killer/T-cell lymphoma, nasal type (ENKTL).
Patients and methods: Thirty-six patients with histologically proven early-stage ENKTL were enrolled from a phase 2 study (Cohort A). Eight nasopharyngeal anatomical regions from each patient were imaged using 18F-FDG PET/CT and MR. A further nine patients were prospectively enrolled from a multicenter, phase 3 study; these patients underwent 18F-FDG PET/CT and PET/MR after a single 18F-FDG injection (Cohort B). Region-based sensitivity and specificity were calculated. The standardized uptake values (SUV) obtained from PET/CT and PET/MR were compared, and the relationship between the SUV and apparent diffusion coefficients (ADC) of PET/MR were analyzed.
Results: In Cohort A, of the 288 anatomic regions, 86 demonstrated lymphoma involvement. All lesions were detected by 18F-FDG PET/CT, while only 70 were detected by MR. 18F-FDG PET/CT exhibited a higher sensitivity than MR (100% vs. 81.4%, χ2 = 17.641, P < 0.001) for local detection of malignancies. The specificity of 18F-FDG PET/CT and MR were 98.5 and 97.5%, respectively (χ2 = 0.510, P = 0.475). The accuracy of 18F-FDG PET/CT was 99.0% and the accuracy of MR was 92.7% (χ2 = 14.087, P < 0.001). In Cohort B, 72 anatomical regions were analyzed. PET/CT and PET/MR have a sensitivity of 100% and a specificity of 92.5%. The two methods were consistent (κ = 0.833, P < 0.001). There was a significant correlation between PET/MR SUVmax and PET/CT SUVmax (r = 0.711, P < 0.001), and SUVmean (r = 0.685, P < 0.001). No correlation was observed between the SUV and the ADC.
Conclusion: In early-stage ENKTL, nasopharyngeal MR showed a lower sensitivity and a similar specificity when compared with 18F-FDG PET/CT. PET/MR showed similar performance compared with PET/CT.
Keywords: 18F-FDG; MR; PET/CT; PET/MR; extranodal NK/T-cell lymphoma; nasal-type.
Copyright © 2020 Guo, Xu, Cheng, Lin, Zhong, Li, Huang, Ouyang, Yi, Chen, Lin, Shi, Zhao and Li.