Merits of 18F-FDG PET/CT metabolic tumor volume for prediction of occult axillary lymph node metastasis in luminal early breast cancer patients with clinical and radiologically negative axilla.

Background: To see if pre-treatment ¹⁸F-FDG PET/CT metabolic tumor volume (MTV) might predict occult axillary lymph node metastases (ALNM) in luminal early breast cancer (BC) with negative axilla on clinical examination, radiological studies, and conventional ¹⁸F-FDG PET/CT interpretation. Methods: Out of 330 consecutive patients with early BC who were referred for preoperative staging, only 110 female patients with luminal early BC who had biopsy-proven axillary lymph node (ALN) status and negative axilla on clinical examination, radiological studies, and conventional ¹⁸F-FDG PET/CT interpretation, were eligible for analysis. Maximum standardized uptake value (SUVmax), SUVmean, MTV, total lesion glycolysis (TLG), and clinicopathological features were determined. Via ROC analysis, we determined the optimal cutoff values for SUVmax, SUVmean, MTV, and TLG of the primary tumor to predict ALNM. Univariate and multivariate regression analyses were performed to identify the most potent PET metabolic parameters to predict ALNM. Results: Pathologic ALNM was identified in 29.1% of cases; 40.6% of them had lymphovascular invasion (LVI) compared to 9% of the ALN-negative group (P < 0.0001). The median MTV of tumors with ALNM was significantly higher than that of the ALN-negative group (P = 0.049). The best cutoff value of MTV was > 4.83. In univariate analysis, MTV (P = 0.005) and LVI (P < 0.0001) were significantly associated with ALNM, and in multivariate analysis, both MTV (P = 0.002) and LVI (P < 0.0001) were confirmed to be independent predictors for ALNM. Conclusions: In early luminal BC with clinically and radiologically negative axilla, including negative conventional interpretation of PET/CT, the inclusion of MTV has an added value in predicting ALNM. [ABSTRACT FROM AUTHOR]