Akademik Veri Yönetim Sistemi
European Journal of Nuclear Medicine and Molecular Imaging, 2026 (SCI-Expanded, Scopus)
Purpose: This study aims to assess the diagnostic performance of 18F-FDG PET/CT parameters for the preoperative prediction of axillary lymph node (ALN) metastasis in Luminal A-type breast cancer patients, and to investigate the net clinical benefit of combining visual analysis with quantitative metrics. Materials and methods: We retrospectively evaluated 279 treatment-naive female patients histopathologically diagnosed with Luminal A type breast cancer who underwent 18F-FDG PET/CT for staging and subsequent ALN sampling between January 2012 and December 2025. Both visual assessment and quantitative parameters—including maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor, as well as axillary SUVmax and the axilla-to-primary SUVmax ratio (SUVr)—were analyzed by two nuclear medicine specialists in consensus. Diagnostic performance was measured using ROC analysis and DeLong’s test. The incremental value of the models was evaluated through Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI), while clinical utility was determined via Decision Curve Analysis (DCA). Results: ALN metastasis was confirmed in 152 (54.5%) patients. All quantitative parameters were significantly higher in the metastatic group (p < 0.001). While expert-based visual analysis showed 84.6% accuracy, axillary SUVmax (AUC: 0.881, 95% CI: 0.841–0.920) significantly outperformed visual assessment (AUC: 0.851, p = 0.031). At a cutoff of 0.93, axillary SUVmax yielded 83.6% sensitivity and 79.5% specificity. The Combined Model, integrating visual and quantitative data, achieved the highest diagnostic power (AUC: 0.889) and was statistically superior to axillary SUVmax alone (p = 0.022). The incorporation of quantitative data correctly reclassified 29% (NRI) of metastatic patients initially reported as false negatives in visual analysis and improved overall discrimination by 41.4% (IDI). DCA revealed that the combined model offered a higher net clinical benefit than standard surgical approaches within a 20–90% risk threshold range. Conclusion: In Luminal A-type breast cancer, objective quantitative 18F-FDG PET/CT parameters and their derived multiparametric models significantly exceed the diagnostic limitations of conventional visual assessment. By providing high net clinical benefit in the surgical decision-making process, the proposed combined model has the potential to serve as a valuable personalized decision support tool for the management of high-risk patients and the de-escalation of invasive surgery in low-risk cohorts.