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Erschienen in:
21.04.2017 | Breast Oncology
Predictive Value of 18F-FDG PET/CT for Axillary Lymph Node Metastasis in Invasive Ductal Breast Cancer
Erschienen in: Annals of Surgical Oncology | Ausgabe 8/2017
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Background
This study assessed whether primary tumor maximum standardized uptake value (pSUVmax) measured by 18F-fluoro-2-deoxy-d-glucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) could improve the prediction of axillary lymph node (ALN) metastasis in invasive ductal breast cancer (IDC).
Methods
In this study, 128 IDC patients who underwent pretreatment 18F-FDG PET/CT and surgical resection of primary tumor with sentinel lymph node biopsy, ALN dissection, or both were analyzed. All the patients were classified as five molecular subtypes. The optimal cutoff values of pSUVmax for all the patients and each molecular subtype for the prediction of ALN metastasis were determined using receiver operating characteristic (ROC) analysis. Furthermore, the prognostic accuracy of ALN metastasis was assessed using c-statistics.
Results
The findings showed ALN metastasis in 52 patients (40.6%). The 18F-FDG PET/CT procedure had a sensitivity of 48.1% and a specificity of 94.7% for ALN metastasis. In the ROC analysis of pSUVmax for ALN metastasis, the optimal cutoff value was 3.9 for all the patients, 2.8 for the luminal A subtype, 3.3 for the luminal B (human epidermal growth factor receptor 2 [HER2]-negative) subtype, 5.3 for the luminal B (HER2-positive) subtype, 12.7 for the HER2-positive subtype, and 11.5 for the triple-negative subtype. A predictive ALN metastasis model using nodal 18F-FDG uptake finding gave a c-statistic of 0.714, and a model combination of nodal 18F-FDG uptake finding with pSUVmax of all the patients gave a c-statistic of 0.736 (P = 0.3926). However, the combination of nodal the 18F-FDG uptake finding with the pSUVmax of each molecular subtype gave a c-statistic of 0.791 (P = 0.0047).
Conclusions
Combining the pSUVmax of each molecular subtype with the nodal 18F-FDG uptake finding can improve the prediction of ALN metastasis in IDC.