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Pancreatic neuroendocrine neoplasms at magnetic resonance imaging: comparison between grade 3 and grade 1/2 tumors.
BACKGROUND: The grading of pancreatic neuroendocrine neoplasms (PanNENs) is associated with the choice of treatment strategy. The aim of this study is to identify the magnetic resonance imaging (MRI) features in differentiating pancreatic neuroendocrine tumors (PanNETs) grade 1/2 (G1/G2) and pancreatic neuroendocrine carcinoma grade 3 (PanNEC G3).
PATIENTS AND METHODS: A total of 59 patients with histologically proven PanNENs and who underwent pretreatment MRI were retrospectively analyzed. Tumor location, size, boundary, cystic or solid appearance, enhancement degree, pancreatic duct dilatation, metastases and MRI signal were evaluated. Apparent diffusion coefficients (ADCs) were measured on ADC maps. Receiver operating characteristic curve was used to determine the cut off values and the sensitivity and specificity of prediction. Spearman correlation and logistic regression analysis were adopted to identify the association between MRI features and pathological parameters.
RESULTS: A total of 47 lesions were PanNETs G1/G2 and 12 lesions were PanNEC G3. G1/G2 tumors were more common with well-circumscribed border compared with PanNEC G3. Ill- defined boundary, big size, necrosis, low-moderate enhancement, pancreatic duct dilatation, metastases and high diffusion-weighted imaging (DWI) intensity were more common in PanNEC G3 than in PanNETs G1/G2. The ADC values of PanNEC G3 were also significantly lower compared with the PanNETs G1/G2 and normal pancreatic parenchyma. The cut off value of ADC was 0.95×10(-3) mm(2)/s for differentiating PanNEC G3 from PanNETs G1/G2 with 72.3% sensitivity and 91.6% specificity, respectively. Ki-67 index and mitosis count positively correlated with tumor size, pancreatic duct dilatation and metastases (P<0.05) and negatively correlated with ADC values (P<0.01), respectively. Regression analysis further showed that metastases and ADC value were associated with PanNENs grade.
CONCLUSION: Metastases and ADC value may have potential for differentiating PanNEC G3 from PanNETs G1/G2.
PATIENTS AND METHODS: A total of 59 patients with histologically proven PanNENs and who underwent pretreatment MRI were retrospectively analyzed. Tumor location, size, boundary, cystic or solid appearance, enhancement degree, pancreatic duct dilatation, metastases and MRI signal were evaluated. Apparent diffusion coefficients (ADCs) were measured on ADC maps. Receiver operating characteristic curve was used to determine the cut off values and the sensitivity and specificity of prediction. Spearman correlation and logistic regression analysis were adopted to identify the association between MRI features and pathological parameters.
RESULTS: A total of 47 lesions were PanNETs G1/G2 and 12 lesions were PanNEC G3. G1/G2 tumors were more common with well-circumscribed border compared with PanNEC G3. Ill- defined boundary, big size, necrosis, low-moderate enhancement, pancreatic duct dilatation, metastases and high diffusion-weighted imaging (DWI) intensity were more common in PanNEC G3 than in PanNETs G1/G2. The ADC values of PanNEC G3 were also significantly lower compared with the PanNETs G1/G2 and normal pancreatic parenchyma. The cut off value of ADC was 0.95×10(-3) mm(2)/s for differentiating PanNEC G3 from PanNETs G1/G2 with 72.3% sensitivity and 91.6% specificity, respectively. Ki-67 index and mitosis count positively correlated with tumor size, pancreatic duct dilatation and metastases (P<0.05) and negatively correlated with ADC values (P<0.01), respectively. Regression analysis further showed that metastases and ADC value were associated with PanNENs grade.
CONCLUSION: Metastases and ADC value may have potential for differentiating PanNEC G3 from PanNETs G1/G2.
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