Evaluation of the efficacy of 18F-FDG PET-CT combined with CT in detecting lymph node metastasis in liver cancer - Yu, Jun; Tan, Xing-guo; Li, Fang (Frontiers in Oncology, 2025)
BackgroundThis study aims to evaluate the diagnostic efficacy of 18F-FDG PET-CT imaging and enhanced abdominal CT scans for the preoperative detection of lymph node metastasis in liver cancer.MethodsWe sought to compare the diagnostic performance of 18F-FDG PET-CT with that of CT and to determine the optimal predictive thresholds for lymph node metastasis, based on the maximum standardized uptake value (SUVmax) and the nodal short-axis diameter.ResultsThe diagnostic efficacy of 18F-FDG PET-CT, including sensitivity, specificity, and accuracy, was significantly higher than that of CT, with statistically significant differences (P < 0.05). Both the short diameter of lymph nodes and the SUVmax in the lymph node metastasis group were both greater than those in the non-metastasis group, with statistically significant differences (P < 0.05). The CT parameter of lymph node short diameter and the 18F-FDG PET-CT parameter of SUVmax were identified as independent predictors of lymph node metastasis in liver cancer and demonstrated a significant positive correlation (P < 0.001). The area under the receiver operating characteristic curve (ROC) for combined detection was 0.938, with a sensitivity of 92.3%, specificity of 85.3%, and accuracy of 88.3% for diagnosing regional lymph node metastasis in liver cancer. The efficacy of combined detection for diagnosing regional lymph node metastasis in liver cancer was superior to that of individual tests (P < 0.05), providing valuable clinical guidance for staging, treatment, and prognosis of liver cancer.ConclusionThe application of the optimal threshold values can further enhance the diagnostic accuracy of 18F-FDG PET-CT in detecting regional lymph node metastasis. The proposed criteria for lymph node metastasis were an SUVmax greater than 2.25 or a short diameter exceeding 8.5 mm. This information may assist in the formulation and optimisation of treatment plans for patients with liver cancer.