Isabella Martini1, Michela Polici2, Marta Zerunian3, Francesco Panzuto4, Maria Rinzivillo5, Federica Landolfi6, Ludovica Magi7, Damiano Caruso8, Marwen Eid9, Bruno Annibale10, Andrea Laghi11, Elsa Iannicelli12. 1. Radiology Unit, Sant'Andrea Hospital, Faculty of Medicine and Psychology, Sapienza University of Rome, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: isabella.martini88@gmail.com. 2. Radiology Unit, Sant'Andrea Hospital, Faculty of Medicine and Psychology, Sapienza University of Rome, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: policimichela28@gmail.com. 3. Radiology Unit, Sant'Andrea Hospital, Faculty of Medicine and Psychology, Sapienza University of Rome, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: marta.zerunian@gmail.com. 4. Digestive Disease Unit, Sant'Andrea Hospital, ENETS Center of Excellence, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: fpanzuto@ospedalesantandrea.it. 5. Digestive Disease Unit, Sant'Andrea Hospital, ENETS Center of Excellence, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: mariarinzivillo@gmail.com. 6. Radiology Unit, Sant'Andrea Hospital, Faculty of Medicine and Psychology, Sapienza University of Rome, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: federica.l2005@libero.it. 7. Digestive Disease Unit, Sant'Andrea Hospital, ENETS Center of Excellence, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: ludovicamagi@hotmail.it. 8. Radiology Unit, Sant'Andrea Hospital, Faculty of Medicine and Psychology, Sapienza University of Rome, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: dcaruso85@gmail.com. 9. Internal Medicine, Nortwell Health-Staten Island University Hospital, 475 Seaview Avenue 10305, NewYork, USA. Electronic address: eid.marwen@gmail.com. 10. Digestive Disease Unit, Sant'Andrea Hospital, ENETS Center of Excellence, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: bruno.annibale@uniroma1.it. 11. Radiology Unit, Sant'Andrea Hospital, Faculty of Medicine and Psychology, Sapienza University of Rome, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: andrea.laghi@uniroma1.it. 12. Radiology Unit, Sant'Andrea Hospital, Faculty of Medicine and Psychology, Sapienza University of Rome, 1035 Grottarossa Street, 00189, Rome, Italy. Electronic address: elsa.iannicelli@uniroma1.it.
Abstract
PURPOSE: To compare CT and Texture features of liver metastases in Pancreatic Neuroendocrine Tumors (PNETs) and in Non-Pancreatic Neuroendocrine Tumors (NPNETs) according to tumor grading, overall survival (OS), time to progression (TTP) and Ki67 index. METHODS: 23 patients with PNETs and 25 patients with NPNETs affected by liver metastases were compared. The lesions were G1 and G2 according to WHO classification of tumors. Texture parameters (Mean, Standard Deviation, Entropy, Kurtosis, Skewness, Mean of Positive Pixel) at different spatial scale image filtration (SSF) were evaluated in both arterial and portal phase using a dedicated software for volumetric analysis. All CT images were acquired before the beginning of any medical treatment. RESULTS: The following significant results (P < 0.05) were found: in the arterial phase for value of Skewness between PNETs G2 and NPNETs G2; in the portal phase between PNETs versus NPNETs, PNETs G1 versus NPNETs G1, PNETs G2 versus NPNETs G2; value of Mean in portal phase in PNETs vs NPNETs. Regarding PNETs, a P < 0.05 was found in: inverse correlation between Entropy and TTP; direct correlation between Mean and OS; correlating Kurtosis and high risk of death; correlating Skewness and low risk of death. Regarding NPNETs, P < 0.05 was found in: inverse correlation between Entropy and OS; correlating Entropy and high risk of dying. CONCLUSIONS: This study shows that CT texture features are significantly different in PNETs from NPNETs. Additionally, textural features such as Entropy, Kurtosis and Skewness, were found to have significant correlation with higher mortality risk.
PURPOSE: To compare CT and Texture features of liver metastases in Pancreatic Neuroendocrine Tumors (PNETs) and in Non-Pancreatic Neuroendocrine Tumors (NPNETs) according to tumor grading, overall survival (OS), time to progression (TTP) and Ki67 index. METHODS: 23 patients with PNETs and 25 patients with NPNETs affected by liver metastases were compared. The lesions were G1 and G2 according to WHO classification of tumors. Texture parameters (Mean, Standard Deviation, Entropy, Kurtosis, Skewness, Mean of Positive Pixel) at different spatial scale image filtration (SSF) were evaluated in both arterial and portal phase using a dedicated software for volumetric analysis. All CT images were acquired before the beginning of any medical treatment. RESULTS: The following significant results (P < 0.05) were found: in the arterial phase for value of Skewness between PNETs G2 and NPNETs G2; in the portal phase between PNETs versus NPNETs, PNETs G1 versus NPNETs G1, PNETs G2 versus NPNETs G2; value of Mean in portal phase in PNETs vs NPNETs. Regarding PNETs, a P < 0.05 was found in: inverse correlation between Entropy and TTP; direct correlation between Mean and OS; correlating Kurtosis and high risk of death; correlating Skewness and low risk of death. Regarding NPNETs, P < 0.05 was found in: inverse correlation between Entropy and OS; correlating Entropy and high risk of dying. CONCLUSIONS: This study shows that CT texture features are significantly different in PNETs from NPNETs. Additionally, textural features such as Entropy, Kurtosis and Skewness, were found to have significant correlation with higher mortality risk.
Authors: Femke C R Staal; Else A Aalbersberg; Daphne van der Velden; Erica A Wilthagen; Margot E T Tesselaar; Regina G H Beets-Tan; Monique Maas Journal: Eur Radiol Date: 2022-07-26 Impact factor: 7.034