18F-Choline PET/CT, MRI, and Software-Based Image Fusion Analysis in Patients With Primary Hyperparathyroidism

Purpose The aim of this study was to evaluate the diagnostic performance of F-18-choline PET and MRI in patients with primary hyperparathyroidism. Furthermore, the additional value of software-based PET/MRI scan fusion was analyzed. Patients and Methods This retrospective study includes 42 patients (38 women) with an age between 32.5 and 79.1 years. PET/CT scans were performed on a dedicated system after injection of 250 to 350 MBq F-18-choline. For the MRI examination, T1-weighted images of the cervical region were used. The image fusion was made by anatomical coregistration using an automated algorithm based on mutual information. Results A total of 46 lesions were discovered and histologically confirmed in 42 patients. Histopathological examination revealed 38 adenomas and 8 hyperplasias. This means that, in 4 of these 42 patients, 2 lesions per patient were discovered. PET/CT also detected 46 abnormal findings, but only 43 were correctly recognized, whereas the other 3 were false-positive (FP). Six lesions could not be detected correctly: 3 were FP and 3 false-negative, which resulted in a sensitivity of 93.5% and a specificity of 97.5%. The site-specific evaluation showed 18 true-positive enlarged parathyroid glands with MRI, but also produced 13 FP findings and failed to detect 28 lesions; the sensitivity and specificity are thus 39.1% and 89.3%, respectively. The difference in detection rate between F-18-choline PET/CT and MRI was statistically significant (P < 0.001). Conclusions F-18-choline PET/CT is clearly superior to MRI for localization diagnostics in primary hyperparathyroidism. Image fusion of both modalities can be helpful for more precise anatomical assignment.

Automated summary

The study evaluated the diagnostic performance of F-18-choline PET and MRI in patients with primary hyperparathyroidism, with additional analysis of software-based PET/MRI scan fusion. F-18-choline PET/CT showed superior performance in localization diagnostics compared to MRI, with image fusion of both modalities providing more precise anatomical assignment.