ObjectiveLymph node metastasis (LNM) is not only one of the important factors affecting the prognosis of gastric cancer but also an important basis for treatment decisions. The purpose of this study was to investigate the value of the radiomics nomogram based on preoperative 18F-deoxyglucose (FDG) PET/CT primary lesions and clinical risk factors for predicting LNM in gastric cancer (GC).MethodsWe retrospectively analyzed radiomics features of preoperative 18F-FDG PET/CT images in 224 gastric cancer patients from two centers. The prediction model was developed in the training cohort (n = 134) and validated in the internal (n = 59) and external validation cohorts (n = 31). The least absolute shrinkage and selection operator (LASSO) regression was used to select features and build radiomics signatures. The radiomics feature score (Rad-score) was calculated and established a radiomics signature. Multivariate logistic regression analysis was used to screen independent risk factors for LNM. The minimum Akaike’s information criterion (AIC) was used to select the optimal model parameters to construct a radiomics nomogram. The performance of the nomogram was assessed with calibration, discrimination, and clinical usefulness.ResultsThere was no significant difference between the internal verification and external verification of the clinical data of patients (all p > 0.05). The areas under the curve (AUCs) (95% CI) for predicting LNM based on the 18F-FDG PET/CT radiomics signature in the training cohort, internal validation cohort, and external validation cohort were 0.792 (95% CI: 0.712–0.870), 0.803 (95% CI: 0.681–0.924), and 0.762 (95% CI: 0.579–0.945), respectively. Multivariate logistic regression showed that carbohydrate antigen (CA) 19-9 [OR (95% CI): 10.180 (1.267–81.831)], PET/CT diagnosis of LNM [OR (95% CI): 6.370 (2.256–17.984)], PET/CT Rad-score [OR (95% CI): 16.536 (5.506–49.660)] were independent influencing factors of LNM (all p < 0.05), and a radiomics nomogram was established based on those factors. The AUCs (95% CI) for predicting LNM were 0.861 (95% CI: 0.799–0.924), 0.889 (95% CI: 0.800–0.976), and 0.897 (95% CI: 0.683–0.948) in the training cohort, the internal validation cohort, and the external validation cohort, respectively. Decision curve analysis (DCA) indicated that the 18F-FDG PET/CT-based radiomics nomogram has good clinical utility.ConclusionsRadiomics nomogram based on the primary tumor of 18F-FDG PET/CT could facilitate the preoperative individualized prediction of LNM, which is helpful for risk stratification in GC patients.
Background Sublobar resection is suitable for peripheral cT1N0M0 non-small-cell lung cancer (NSCLC). The traditional PET-CT criterion (lymph node size ≥1.0 cm or SUV max ≥2.5) for predicting lymph nodes metastasis (LNM) has unsatisfactory performance.Objective We explore the clinical role of preoperative SUV max and the size of the primary lesions for predicting peripheral cT1 NSCLC LNM.
MethodsWe retrospectively analyzed 174 peripheral cT1 NSCLC patients underwent preoperative 18 F-FDG PET-CT and divided into the LNM and non-LNM group by pathology. We compared the differences of primary lesions' baseline characteristics between the two groups. The risk factors of LNM were determined by univariate and multivariate analysis, and we assessed the diagnostic efficacy with the area under the receiver operating characteristic curve (AUC), sensitivity, specificity, positive predictive value and negative predictive value (NPV).
ResultsOf the enrolled cases, the incidence of LNM was 24.7%. The preoperative SUV max >6.3 or size >2.3 cm of the primary lesions were independent risk factors of peripheral cT1 NSCLC LNM (ORs, 95% CIs were 6.18 (2.40-15.92) and 3.03 (1.35-6.81). The sensitivity, NPV of SUV max >6.3 or size >2.3 cm of the primary lesions were higher than the traditional PET-CT criterion for predicting LNM (100.0 vs. 86.0%, 100.0 vs. 89.7%). A Hosmer-Lemeshow test showed a goodness-of-fit (P = 0.479).
ConclusionsThe excellent sensitivity and NPV of preoperative of the SUV max >6.3 or size >2.3 cm of the primary lesions based on 18 F-FDG PET-CT might identify the patients at low-risk LNM in peripheral cT1 NSCLC. Nucl Med Commun 42: 1328
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