A Novel Validated Recurrence Stratification System Based on 18F-FDG PET/CT Radiomics to Guide Surveillance After Resection of Pancreatic Cancer.
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ABSTRACT: objective
Despite the heterogeneous biology of pancreatic cancer, similar surveillance schemas have been used. Identifying the high recurrence risk population and conducting prompt intervention may improve prognosis and prolong overall survival.Methods
One hundred fifty-six resectable pancreatic cancer patients who had undergone 18F-FDG PET/CT from January 2013 to December 2018 were retrospectively reviewed. The patients were categorized into a training cohort (n = 109) and a validation cohort (n = 47). LIFEx software was used to extract radiomic features from PET/CT. The risk stratification system was based on predictive factors for recurrence, and the index of prediction accuracy was used to reflect both the discrimination and calibration.Results
Overall, seven risk factors comprising the rad-score and clinical variables that were significantly correlated with relapse were incorporated into the final risk stratification system. The 1-year recurrence-free survival differed significantly among the low-, intermediate-, and high-risk groups (85.5, 24.0, and 9.1%, respectively; p < 0.0001). The C-index of the risk stratification system in the development cohort was 0.890 (95% CI, 0.835-0.945).Conclusion
The 18F-FDG PET/CT-based radiomic features and clinicopathological factors demonstrated good performance in predicting recurrence after pancreatectomy in pancreatic cancer patients, providing a strong recommendation for an adequate adjuvant therapy course in all patients. The high-risk recurrence population should proceed with closer follow-up in a clinical setting.
SUBMITTER: Wei M
PROVIDER: S-EPMC8149949 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Objective: The purpose of this study was to explore the value of 18F-FDG PET/CT in monitoring the disease activity and predicting the prognosis of the Adult-onset Still's disease (AOSD). Methods: We retrospectively analyzed the electronic medical records of 45 AOSD patients who underwent 18F-FDG PET/CT in the Second Xiangya Hospital. PET/CT imaging and clinical information were retrospectively reviewed and analyzed. 18F-FDG uptake was assessed by measuring standard uptake value (SUV) in the spleen, liver, bone marrow, and lymph nodes. The spleen-to-liver ratio of the SUVmax (SLRmax) and SUVmean (SLRmean), the bone-to-liver ratio of the SUVmax (BLRmax), and SUVmean (BLRmean), and the lymph nodes-to-liver ratio of the SUVmax (LyLRmax) were calculated. Clinical and laboratory information were collected and evaluated for association with metabolic parameters of 18F-FDG PET/CT. The influencing factors for recurrence within 1 year were analyzed to determine whether 18F-FDG PET/CT can predict the prognosis of AOSD patients. Results: Elevated 18F-FDG uptake could be observed in bone marrow, spleen, and lymph nodes of AOSD patients. Correlation analysis between 18F-FDG uptake of organs and laboratory examinations showed that SLRmean positively correlated with LDH, AST, ferritin, and the systemic score (r = 0.572, 0.353, 0.586, and 0.424, P < 0.05). The SLRmean had the highest correlation with ferritin (r = 0586, P < 0.001). All metabolic parameters in spleen, including SUVmax, SUVmean, SLRmax, and SLRmean, are positively correlated with LDH level (r = 0.405, 0.539, 0.481, and 0.572, P < 0.05). Bone marrow SUVmax, BLRmax, and BLRmean were correlated with C-reactive protein (CRP) level (r = 0.395, 0.437, and 0.469, P < 0.05). Analysis of the influencing factors of recurrence within 1 year showed that the spleen SUVmax, spleen SUVmean, SLRmax, SLRmean, ferritin, and the systemic score of the recurrence group was significantly higher than the non-recurrence group (P < 0.05). The SLRmean cutoff of 1.66 with a sensitivity of 72.7% and specificity of 80.0% had the highest performance in predicting recurrence. Conclusion: The glucose metabolism of the liver, spleen, and bone marrow of AOSD patients were correlated with laboratory inflammatory indicators and system score, suggesting that 18F-FDG PET/CT could be applied to evaluate disease activity. Moreover, spleen 18F-FDG uptake may be a potential biomarker for predicting clinical prognosis of AOSD patients.
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Project description:ObjectivesTo investigate the development and validation of a radiomics nomogram based on PET/CT for guiding personalized targeted therapy in patients with lung adenocarcinoma mutation(s) in the EGFR gene.MethodsA cohort of 109 (77/32 in training/validation cohort) consecutive lung adenocarcinoma patients with an EGFR mutation was enrolled in this study. A total of 1672 radiomic features were extracted from PET and CT images, respectively. The least absolute shrinkage and selection operator (LASSO) Cox regression was used to select the radiomic features and construct the radiomics nomogram for the estimation of overall survival (OS), which was then assessed with respect to calibration and clinical usefulness. Patients with an EGFR mutation were divided into high- and low- risk groups according to their nomogram score. The treatment strategy for high- and low-risk groups was analyzed using Kaplan-Meier analysis and a log-rank test.ResultsThe C-index of the radiomics nomogram for the prediction of OS in lung adenocarcinoma in patients with an EGFR mutation was 0.840 and 0.803 in the training and validation cohorts, respectively. Distant metastasis [(Hazard ratio, HR),1.80], metabolic tumor volume (MTV, HR, 1.62), and rad score (HR, 17.23) were the independent risk factors for patients with an EGFR mutation. The calibration curve showed that the predicted survival time was remarkably close to the actual time. Decision curve analysis demonstrated that the radiomics nomogram was clinically useful. Targeted therapy for patients with high-risk EGFR mutations attained a greater benefit than other therapies (p < 0.0001), whereas the prognoses of the two therapies were similar in the low-risk group (p = 0.85).ConclusionsDevelopment and validation of a radiomics nomogram based on PET/CT radiomic features combined with clinicopathological factors may guide targeted therapy for patients with lung adenocarcinoma with EGFR mutations. This is conducive to the advancement of precision medicine.
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