ArticleEuropean radiology2022
Prediction of recurrence after surgery based on preoperative MRI features in patients with pancreatic neuroendocrine tumors.
Article in European radiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed, 11 citations in OpenAlex.
- MRI-based risk stratification for predicting overall survival in pancreatic ductal adenocarcinoma.Insights into imaging · 2025Article
- Identification of SMAD4-mutated pancreatic ductal adenocarcinoma using preoperative contrast-enhanced MRI and clinical characteristics.BMC medical imaging · 2024Article
- The association between non-HDL cholesterol and high-grade pancreatic neuroendocrine neoplasms.Endocrine · 2024Article
- Artificial Intelligence in Pancreatic Image Analysis: A Review.Sensors (Basel, Switzerland) · 2024Review
- Prediction of the lymphatic, microvascular, and perineural invasion of pancreatic neuroendocrine tumors using preoperative magnetic resonance imaging.World journal of gastrointestinal surgery · 2023Article
- Preoperative prediction of lymph node metastasis in nonfunctioning pancreatic neuroendocrine tumors from clinical and MRI features: a multicenter study.Insights into imaging · 2022Article
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4 authors at 2 institutions in 1 country.
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Abstract
objectivesTo investigate useful MRI features in pancreatic neuroendocrine tumor (PNET) patients for predicting recurrence and its timing after surgery.
methodsA total of 99 patients with PNET who underwent MRI and surgery from 2000 to 2018 were enrolled. Two radiologists independently assessed MRI findings, including size, location, margin, T1 and T2 signal intensity, enhancement patterns, common bile duct (CBD) or main pancreatic duct (MPD) dilatation, vascular invasion, lymph node enlargement, DWI, and ADC value. Imaging findings associated with recurrence and disease-free survival (DFS) were assessed using logistic regression analysis and Cox proportional hazard regression analysis.
resultsThe median follow-up period was 40.4 months, and recurrence after surgery occurred in 12.1% (12/99). Among them, 6 patients experienced recurrence within 1 year, and 9 patients experienced recurrence within 2 years after surgery. In multivariate analysis, major venous invasion (OR 10.76 [1.14-101.85], p = 0.04) was associated with recurrence within 1 year, and portal phase iso- to hypoenhancement (OR 51.89 [1.73-1557.89], p = 0.02), CBD or MPD dilatation (OR 10.49 [1.35-81.64], p = 0.03) and larger size (OR 1.05 [1.00-1.10], p = 0.046) were associated with recurrence within 2 years. The mean DFS was 116.4 ± 18.5 months, and the 5-year DFS rate was 85.7%. In multivariate analysis, portal phase iso- to hypoenhancement (HR 21.36 [2.01-197.77], p = 0.01), ductal dilatation (HR 5.22 [1.46-18.68], p = 0.01), major arterial invasion (HR 42.90 [3.66-502.48], p = 0.003), and larger size (HR 1.04 [1.01-1.06], p = 0.01) showed a significant effect on poor DFS.
conclusionMRI features, including size, enhancement pattern, vascular invasion, and ductal dilatation, are useful in predicting recurrence and poor DFS after surgery in PNET. Key Points • MRI features are useful for predicting prognosis in patients with PNET after surgery. • PV or SMV invasion (OR 10.49 [1.35-81.64], p = 0.04) was significantly associated with 1-year recurrence. • Portal phase iso- to hypoenhancement (HR 21.36), CBD or MPD dilatation (HR 5.22), arterial invasion (HR 42.90), and larger size (HR 1.04) had significant effects on poor DFS (p < 0.05).
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