Predictive value of 18F-FDG PET/CT multi-metabolic parameters and tumor metabolic heterogeneity in the prognosis of gastric cancer.

OBJECTIVE: We aimed to investigate the predictive value of pre-treatment 18F-FDG PET/CT multi-metabolic parameters and tumor metabolic heterogeneity for gastric cancer prognosis. METHODS: Seventy-one patients with gastric cancer were included. All patients underwent 18F-FDG PET/CT whole-body scans prior to treatment and had pathologically confirmed gastric adenocarcinomas. Each metabolic parameter, including SUVmax, SUVmean, MTV, and TLG, was collected from the primary lesions of gastric cancer in all patients, and the slope of the linear regression between the MTV corresponding to different SUVmax thresholds (40% × SUVmax, 80% × SUVmax) of the primary lesions was calculated. The absolute value of the slope was regarded as the metabolic heterogeneity of the primary lesions, expressed as the heterogeneity index HI-1, and the coefficient of variance of the SUVmean of the primary lesions was regarded as HI-2. Patient prognosis was assessed by PFS and OS, and a nomogram of the prognostic prediction model was constructed, after which the clinical utility of the model was assessed using DCA. RESULTS: A total of 71 patients with gastric cancer, including 57 (80.3%) males and 14 (19.7%) females, had a mean age of 61 ± 10 years; disease progression occurred in 27 (38.0%) patients and death occurred in 24 (33.8%) patients. Multivariate Cox regression analysis showed that HI-1 alone was a common independent risk factor for PFS (HR: 1.183; 95% CI: 1.010-1.387, P < 0.05) and OS (HR: 1.214; 95% CI: 1.016-1.450, P < 0.05) in patients with gastric cancer. A nomogram created based on the results of Cox regression analysis increased the net clinical benefit for patients. Considering disease progression as a positive event, patients were divided into low-, intermediate-, and high-risk groups, and Kaplan-Meier survival analysis showed that there were significant differences in PFS among the three groups. When death was considered a positive event and patients were included in the low- and high-risk groups, there were significant differences in OS between the two groups. CONCLUSION: The heterogeneity index HI-1 of primary gastric cancer lesions is an independent risk factor for patient prognosis. A nomogram of prognostic prediction models constructed for each independent factor can increase the net clinical benefit and stratify the risk level of patients, providing a reference for guiding individualized patient treatment.

[Correlations of 18F-FDG PET/CT Metabolic Parameters and Metabolic Heterogeneity with Human Epidermal Growth Factor Receptor 2 Expression in Patients with Gastric Cancer].

Objective To investigate the value of 18F-FDG PET/CT metabolic parameters and metabolic heterogeneity for predicting the expression of human epidermal growth factor receptor 2 (HER2) in patients with gastric cancer. Methods A total of 45 patients with gastric cancer confirmed by surgical pathology between September 2016 and May 2021 were enrolled in this study.All the patients underwent 18F-FDG PET/CT examination before surgery.The maximum standardized uptake value (SUVmax),metabolic tumor volume (MTV),and total lesion glycolysis (TLG) of primary gastric cancer were measured,and the linear regression slope of MTV corresponding to different SUVmax thresholds (40% SUVmax and 80% SUVmax) was calculated.The absolute value of the slope was deemed to represent the metabolic heterogeneity of primary gastric cancer,termed the heterogeneity index (HI).Univariate and multivariate Logistic regression analyses were conducted to evaluate the correlations of 18F-FDG PET/CT metabolic parameters and HI with HER2 expression. Results The 45 patients included 10 with positive HER2 expression and 35 with negative result.The MTV (P=0.043) and HI (P=0.048) were lower in the patients with positive HER2 expression than in the patients with negative HER2 expression.The MTV and HI had the optimal thresholds of 12.10 cm3 and 3.71,respectively,which respectively showed the accuracy of 62.2% and 57.8% for predicting HER2 expression.The univariate Logistic regression showed that the tumor differentiation degree,MTV,and HI were correlated with HER2 expression,while the multivariate Logistic regression showed that only the tumor differentiation degree (OR=20.130,95%CI=1.843-219.860,P=0.014) was an independent predictor for HER2 expression.A further stratified analysis of the tumor differentiation degree showed that HER2 expression only varied among different MTV threshold groups in patients with moderately/well differentiated gastric cancer (P=0.031). Conclusions MTV and HI were associated with HER2 expression in gastric cancer,whereas neither played an independent predictive role.Therefore,these factors should be combined with clinicopathological characteristics of patients to jointly guide treatment decisions.

Predictive value of multiple metabolic and heterogeneity parameters of 18F-FDG PET/CT for EGFR mutations in non-small cell lung cancer.

OBJECTIVES: To explore the value of multiple metabolic and heterogeneity parameters of 2-deoxy-2-[fluorine-18] fluoro-D-glucose positron emission tomography/computed tomography (18F-FDG PET/CT) in predicting epidermal growth factor receptor gene (EGFR) mutations in non-small cell lung cancer (NSCLC). MATERIALS AND METHODS: A retrospective analysis was performed by reviewing 98 patients with NSCLC who underwent EGFR mutation testing and 18F-FDG PET/CT examination in our hospital between March 2016 and March 2021. Patients were divided into an EGFR-mutant group and a wild-type group. A multivariate logistic regression analysis was performed to screen and construct a prediction model. The diagnostic performance of the model was evaluated using a receiver-operating characteristic (ROC) curve. RESULTS: The study found that EGFR mutations were more likely to occur in women, non-smokers, and patients with peripheral lesions, shorter maximum tumor diameter, adenocarcinoma, and T1 stage cancer. Low maximum standardized uptake value (SUVmax), mean standardized uptake value (SUVmean), metabolic tumor volume, total lesion glycolysis, and high coefficient of variation (COV) were significantly correlated with EGFR mutations, and the area under the ROC curve (AUC) was 0.622, 0.638, 0.679, 0.687, and 0.672, respectively. Multivariate logistic regression analysis indicated that non-smokers (odds ratio (OR) = 0.109, P = 0.014), peripheral lesions (OR = 6.917, P = 0.022), low SUVmax (≤ 7.85, OR = 5.471, P = 0.001), SUVmean (≤ 5.34, OR = 0.044, P = 0.000), and high COV (≥ 106.08, OR = 0.996, P = 0.045) were independent predictors of EGFR mutations. The AUC of the prediction model established by combining the above factors was 0.926; the diagnostic efficiency was significantly higher than that of a single parameter. CONCLUSION: Among the metabolic and heterogeneity parameters of 18F-FDG PET/CT, low SUVmax, SUVmean, and high COV were significantly associated with EGFR mutations, and the predictive value of EGFR mutations could be enhanced when combined with clinicopathological features.

Multiple metabolic parameters and visual assessment of 18F-FDG uptake heterogeneity of PET/CT in advanced gastric cancer and primary gastric lymphoma.

PURPOSE: Advanced gastric cancer (AGC) and primary gastric lymphoma (PGL) are the two most common malignant tumors of the stomach. Conventional imaging examinations have difficulty distinguishing the two. This study explored the values of multiple parameters and visual assessment of 18F-fluorodeoxyglucose(18F-FDG) uptake heterogeneity of positron emission tomography/computed tomography(PET/CT) for differentiating between AGC and PGL. METHODS: This retrospective study included 70 AGC and 26 PGL patients, all of whom had undergone 18F-FDG PET/CT before treatment. We analyzed the differences between AGC and PGL in the distribution of metastatic lesions and multiple metabolic parameters, including the maximum standardized uptake value (SUVmax), SUVmax/maximal thickness(THKmax), metabolic tumor volume and total lesion glycolysis (TLG). In addition, 18F-FDG uptake heterogeneity was visually assessed using a visual scoring method and a method of measuring SUVmax differences (SUVmax-d). RESULTS: The most common metastasis of AGC patients were liver, bone, peritoneal and proximal lymph nodes; PGL patients had fewer peritoneal metastases and lymph node metastasis could appeared to be "skip metastasis." The metabolic parameters-SUVmax, SUVmax/THKmax and TLG-were higher in patients who had PGL, especially in diffuse large B-cell lymphoma (DLBCL). In the visual assessment of 18F-FDG uptake heterogeneity, the measurements of SUVmax-d in PGL were significantly higher than in AGC. Receiver operating characteristics curve analysis suggested that SUVmax has the highest comprehensive diagnostic efficiency due to having the highest value of area under the curve and the highest accuracy (77.2%). CONCLUSION: 18F-FDG PET/CT had a high diagnostic efficiency for discrimination of AGC and PGL, especially between DLBCL and other pathological subtypes. Visual assessment used to evaluate 18F-FDG uptake heterogeneity could help to distinguish the two types of tumors. In addition, our innovative method of measuring the heterogeneity of 18F-FDG uptake-namely, SUVmax-d-could contribute to identification of the two tumor types and should have its significance clarified by future studies.