Abstract
Pancreatic neuroendocrine tumors (p-NETs) are a rare group of neoplasms that often present with liver metastases. Histological characteristics, metabolic behavior, and liver tumor burden (LTB) are important prognostic factors. In this study, the usefulness of texture analysis of liver metastases in evaluating the biological aggressiveness of p-NETs was assessed. Fifty-six patients with liver metastases from p-NET were retrospectively enrolled. Qualitative and quantitative CT features of LTB were evaluated. Histogram-derived parameters of liver metastases were calculated and correlated with the tumor grade (G) and 18F-fluorodeoxyglucose (18F-FDG) standardized uptake value (SUV). Arterial relative enhancement was inversely related with G (−0.37, p = 0.006). Different metastatic spread patterns of LTB were not associated with histological grade. Arterialentropy was significantly correlated to G (−0.368, p = 0.038) and to Ki67 percentage (−0.421, p = 0.018). The ROC curve for the Arterialentropy reported an area under the curve (AUC) of 0.736 (95% confidence interval 0.545–0.928, p = 0.035) in the identification of G1–2 tumors. Arterialuniformity values were correlated to G (0.346, p = 0.005) and Ki67 levels (0.383, p = 0.033). Arterialentropy values were directly correlated with the SUV (0.449, p = 0.047) which was inversely correlated with Arterialuniformity (−0.499, p = 0.025). Skewness and kurtosis reported no significant correlations. In conclusion, histogram-derived parameters may predict adverse histological features and metabolic behavior of p-NET liver metastases.
Highlights
Pancreatic neuroendocrine neoplasms represent a rare condition that includes a heterogeneous group of tumors
Well-differentiated pancreatic neuroendocrine tumors (p-NETs) are divided into three sub-categories depending on the Ki67 index, reporting a five-year survival up to 85%
The aim of this study was to evaluate the major qualitative and quantitative imaging features related to metastatic p-NET liver tumor burden, with a particular focus on histogram-derived parameters of the CT texture analysis, in the prediction of histological tumor grade and metabolic activity
Summary
Pancreatic neuroendocrine neoplasms represent a rare condition that includes a heterogeneous group of tumors. Well-differentiated pancreatic neuroendocrine tumors (p-NETs) are divided into three sub-categories depending on the Ki67 index, reporting a five-year survival up to 85%. The second group is represented by poorly differentiated tumors or pancreatic neuroendocrine carcinoma, for which five-year survival is 9% [3]. The Ki67 percentage is considered the most important prognostic index in gastro-entero-pancreatic neuroendocrine neoplasms [4,5] and is used to define tumor grading (G) and subsequent management. Metastases represent another important prognostic key factor, involving the liver in up to 70% of cases [6,7].
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