Monitoring bone and soft-tissue tumors after carbon-ion radiotherapy using 18F-FDG positron emission tomography: a retrospective cohort study
نویسندگان
چکیده
BACKGROUND The results of treatment for malignant bone and soft-tissue tumors arising from the deep trunk and pelvis are still not acceptable due to the relatively high recurrence and low overall survival rates. Recently, carbon ion radiotherapy (CIRT) was applied for several malignancies, including bone and soft-tissue sarcomas, and provided favorable results. However, it has been unclear what modalities should be used for evaluating the response and for the follow-up of these patients. Here, we analyzed the methods used to predict local recurrence and to find local failures or metastases. METHODS We analyzed 37 patients with bone and soft-tissue tumors who received CIRT at our institute. The patients were examined with FDG positron emission tomography (PET) and enhanced MRI before and three months after CIRT. The pre-treatment maximum standardized uptake value (SUVmax), and that three months after treatment, the difference between the pre- and post-CIRT SUVmax, the ratio of the post- to pre-SUVmax in FDG-PET and the size of the tumors were evaluated as predictors for local recurrence. FDG-PET and enhanced MRI were used to detect local recurrence. RESULTS Local recurrence appeared in 10 cases after CIRT. Nine of the 10 lesions (90.0 %) were detected with FDG-PET, while enhanced MRI detected just 50.0 % of the recurrences. One case of local recurrence, in which the lesion was negative on FDG-PET, was detected using enhanced MRI. A receiver operating characteristic curve analysis showed that neither the SUVmax on FDG-PET nor the tumor size before or three months after CIRT could be used to predict local recurrence. CONCLUSIONS The combination of FDG-PET and enhanced MRI is recommended to detect local recurrence for patients with sarcomas who have received CIRT; however, no parameters obtained during the examinations performed before and three months after CIRT accurately predicted the development of local recurrence.
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