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Significance of PET-CT for Detecting Occult Lymph Node Metastasis and Affecting Prognosis in Early-Stage Tongue Squamous Cell Carcinoma

Guo Zhao, Jianli Sun, Kai Ba, Yunxiang Zhang

2020Frontiers in Oncology16 citationsDOIOpen Access PDF

Abstract

Objective: We aimed to clarify the significance of PET-CT for detecting occult lymph node metastasis and affecting prognosis in early-stage tongue squamous cell carcinoma (SCC). Methods: Patients with surgically treated primary cT1-2N0 tongue SCC who agreed to undergo a preoperative PET-CT scan were prospectively enrolled. The primary study outcomes were occult neck lymph node metastasis and locoregional control (LRC). The Kaplan-Meier method was used to analyze the LRC rate, and then the factors that were significant in the Kaplan-Meier method were assessed in the Cox model to determine the independent factors. Results: A total of 135 patients were included, and the median maximum standardized uptake value (SUV max) of the primary tumor was 9.0. When analyzing the PET-CT results, 18 patients were recognized as having neck lymph node metastasis, and 12 patients were proven to have pathologic lymph nodes. A total of 117 patients did not have neck lymph node metastasis reported by PET-CT, and 5 patients were proven to have pathologic lymph nodes. The sensitivity and specificity of PET-CT for predicting occult metastasis were 70.6% and 94.9%, respectively. In patients with an SUV max ≤9.0, the 5-year LRC rate was 95%; in patients with an SUV max >9.0, the 5-year LRC rate was 85%, and the difference was significant. Further Cox model analyses confirmed the independence of the SUV max for predicting LRC. Conclusion: PET-CT has a high specificity for predicting occult lymph node metastasis, and an SUV max >9.0 is significantly associated with worse LRC in cT1-2N0 tongue SCC.

Topics & Concepts

MedicineOccultStage (stratigraphy)Lymph nodeMetastasisRadiologyLymphTonguePrimary tumorCarcinomaNuclear medicineOncologyPathologyCancerInternal medicineAlternative medicinePaleontologyBiologyHead and Neck Cancer StudiesCancer Diagnosis and TreatmentRadiomics and Machine Learning in Medical Imaging