Abstract

PurposeTo investigate whether potential differences in staging between a traditional staging imaging algorithm and 18F-FDG PET/MR lead to a change in patient management in breast carcinoma and to compare the diagnostic accuracy between the traditional staging algorithm and 18F-FDG PET/MR for the TNM classification. MethodIn this prospective cohort study from two university hospitals 56 women with newly diagnosed, therapy-naive breast cancer and increased pre-test probability for distant metastases were included. All patients were examined by a traditional staging imaging algorithm (X-ray mammography, breast ultrasonography, chest plain radiography, bone scintigraphy, and ultrasonography of the liver and axillary fossa) and whole-body 18F-FDG PET/MR including dedicated 18F-FDG PET/MR breast examinations. Each patient was discussed two times in a separate tumor board session to determine a total of three therapy recommendations based on histopathological data of the primary tumor and (1) traditional algorithm only, (2) traditional algorithm and 18F-FDG PET/MR, and (3) 18F-FDG PET/MR only. Major changes in therapy recommendations and differences between the traditional staging algorithm and 18F-FDG PET/MR for the TNM classification were evaluated. ResultsStaging by 18F-FDG PET/MR led to a difference in treatment compared the traditional staging algorithm in 8/56 cases (14%). Therapy changes included therapy of the breast, locoregional nodes and systemic therapy. A trend to staging superiority was found for 18F-FDG PET/MRI without statistical significance (p = 0.3827). ConclusionIn conclusion, for breast cancer patients with elevated pre-test probability for distant metastases a change of the therapy regiment occurs in 14 % of patients when staged by 18F-FDG PET/MR and confirmed by histopathology compared to a traditional staging algorithm. In particular with regard to the amendment of the guideline further assessment of 18F-FDG-PET/MR in this setting is necessary to assess the true value of this modality.

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