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Purpose: Desmoid tumor (DT) is a rare monoclonal, fibroblastic proliferation characterized by a variable and often unpredictable clinical course. Initial active surveillance is recommended by current guideline, and surgery is one of the main therapies for DT. Predicting the prognosis and outcome of active surveillance for intra-abdominal DT is pressing issue., Methods: The study included eighteen patients with intra-abdominal DT. Metabolic tumor volume (MTV), total lesion glycolysis (TLG), and maximum standardized uptake value (SUVmax) were measured. We analyzed their relationship with the outcome of active surveillance, as well as clinical, prognostic, and pathological data., Results: The MTV and TLG of recurrent DT were significantly higher than those of non-recurrent DT (P < 0.001 and P = 0.00, respectively). The ROC curve suggested that the appropriate cutoff values for distinguishing recurrent DT from non-recurrent DT were 760.8 for MTV (sensitivity = 1, specificity = 0.857 and AUC = 0.929), and 1318.4 for TLG (sensitivity = 1, specificity = 0.786, and AUC = 0.911). The cutoff values of MTV and TLG significantly correlated with PFS using the Kaplan-Meier method (P = 0.002 and P = 0.007, respectively). MTV and TLG could distinguish DTs with subsequent progression from stable ones (P = 0.004 and P = 0.004, respectively). The ROC curve suggested that the appropriate cutoff values for distinguishing DTs with subsequent progression from stable ones were 197.1 for MTV (sensitivity = 0.9, specificity = 1, and AUC = 0.900), and 445.45 for TLG (sensitivity = 0.9, specificity = 1, and AUC = 0.900)., Conclusion: Volume-based 18 F-FDG-PET can predict prognosis of intra-abdominal DT. MTV and TLG can predict the outcome of active surveillance for intra-abdominal DT. MTV and TLG can potentially be predictors of surgical risk and difficulty., (© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Purpose: To evaluate the potential role of MR findings and DWI parameters in predicting small regional lymph nodes metastases (with short-axis diameter < 10 mm) in pancreatic ductal adenocarcinomas (PDACs)., Methods: A total of 127 patients, 82 in training group and 45 in testing group, with histopathologically diagnosed PDACs who underwent pancreatectomy were retrospectively analyzed. PDACs were divided into two groups of positive and negative lymph node metastases (LNM) based on the pathological results. Pancreatic cancer characteristics, short axis of largest lymph node, and DWI parameters of PDACs were evaluated., Results: Univariate and multivariate analyses showed that extrapancreatic distance of tumor invasion, short-axis diameter of the largest lymph node, and mean diffusivity of tumor were independently associated with small LNM in patients with PDACs. The combining MRI diagnostic model yielded AUCs of 0.836 and 0.873, and accuracies of 81.7% and 80% in the training and testing groups. The AUC of the MRI model for predicting LNM was higher than that of subjective MRI diagnosis in the training group (rater 1, P = 0.01; rater 2, 0.008) and in a testing group (rater 1, P = 0.036; rater 2, 0.024). Comparing the subjective diagnosis, the error rate of the MRI model was decreased. The defined LNM-positive group by the MRI model showed significantly inferior overall survival compared to the negative group (P = 0.006)., Conclusions: The MRI model showed excellent performance for individualized and noninvasive prediction of small regional LNM in PDACs. It may be used to identify PDACs with small LNM and contribute to determining an appropriate treatment strategy for PDACs., (© 2021. The Author(s).)