[Value of dual-layer spectral detector CT in preoperative prediction of lymph node metastasis of gastric cancer].

To investigate the value of dual-layer spectral detector CT(SDCT) in preoperative prediction of lymph node (LN) metastasis of gastric cancer. From January 2019 to January 2021, the clinical and imaging data of 130 gastric cancer patients(93 males and 37 females, aged from 37 to 84 years)confirmed by pathology in the Zhongshan hospital of Xiamen University were retrospectively collected. According to the status of lymph node metastasis, those patients were divided into metastatic LNs group (=104) and nonmetastatic LNs group (=26). The maximum diameter of gastric cancer on spectral CT images, CT Values of lesions in 40, 50, 60, 70. KeV monoenergetic image of arterial and Venous phase (CT, CT, CT, CT), iodine concentration (IC) and effective atomic number (Z) were measured, then the normalized IC(NIC) and spectral curve(K) value were calculated. The differences of each parameter derived from spectral CT between the two groups were compared, and a logistic regression model was constructed. The ROC curves and area under the curve (AUC) were conducted to evaluate the diagnostic performance of each parameter and Delong test was used to compare the difference of each AUC. Compared to nonmetastatic LNs group, metastatic LNs group had higher maximum diameter of tumor, CT, CT, CT, CT, IC, NIC, Zeff, and K values on venous phase (the representative parameter is Z: 8.4 (8.2, 8.5) vs 8.2 (8.1, 8.3)) (all <0.05). The proportion of patients with lower histology differentiated degree, higher T grade and positive carcino embryonic antigen (CEA)were higher than that in nonmetastatic LNs (the representative parameter was CEA: 34.6%(36/104) vs 7.7%(2/26) (all <0.05). The regression model constructed by CEA and Zeff had the highest predictive value in predicting metastatic LNs, with an AUC of 0.835(0.759-0.894), sensitivity and specificity of 83.65% and 73.08%, respectively. SDCT quantitative parameters on venous phase and CEA facilitate the accurate prediction of metastatic LNs in patients with gastric cancer, and the multi-parameter regression model has the highest diagnostic performance.