Cargando…

Liver Tumor Burden in Pancreatic Neuroendocrine Tumors: CT Features and Texture Analysis in the Prediction of Tumor Grade and (18)F-FDG Uptake

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Beleù, Alessandro, Rizzo, Giulio, De Robertis, Riccardo, Drudi, Alessandro, Aluffi, Gregorio, Longo, Chiara, Sarno, Alessandro, Cingarlini, Sara, Capelli, Paola, Landoni, Luca, Scarpa, Aldo, Bassi, Claudio, D’Onofrio, Mirko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7352332/
https://www.ncbi.nlm.nih.gov/pubmed/32517291
http://dx.doi.org/10.3390/cancers12061486
Descripción
Sumario: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 (18)F-fluorodeoxyglucose ((18)F-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. Arterial(entropy) was significantly correlated to G (−0.368, p = 0.038) and to Ki67 percentage (−0.421, p = 0.018). The ROC curve for the Arterial(entropy) 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. Arterial(uniformity) values were correlated to G (0.346, p = 0.005) and Ki67 levels (0.383, p = 0.033). Arterial(entropy) values were directly correlated with the SUV (0.449, p = 0.047) which was inversely correlated with Arterial(uniformity) (−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.