Prediction of non-functioning pancreatic neuroendocrine tumor grades with fractal analysis of preoperative contrast-enhanced computed tomography images. Issue 141 (August 2021)

• Record Type: Journal Article
• Authors: Nakano, Akira; Hayano, Koichi; Tochigi, Toru; Mashiko, Taro; Masuoka, Yoshihito; Yamamoto, Seiichiro; Ozawa, Soji; Nakagohri, Toshio
• Is Part Of: European journal of radiology. Issue 141(2021)
• Publication Date: 2021-08
• Subjects: CT Computed tomography -- PNETs Pancreatic neuroendocrine tumors -- NF-PNETs Non-functioning pancreatic neuroendocrine tumors -- ITS Intratumoral heterogeneity -- EUS-FNA Endoscopic ultrasound-guided fine needle aspiration -- FD Fractal dimension -- FDmax Maximum value of fractal dimension -- LN Lymph node -- HPF High power field -- ROI Region of interest -- AUC Area under the curve -- ROC Receiver operating characteristic -- OS Overall survival -- DFS Disease-free survival -- NEC Neuroendocrine carcinoma -- DPM1 Positive dissected peripancreatic tissue margin -- MST Median survival time; Pancreatic neuroendocrine tumor -- Intratumoral heterogeneity -- Contrast-enhanced -computed tomography -- Fractal analysis -- Non-functioning tumor -- Ki-67 labeling index; Medical radiology -- Periodicals; Radiology -- Periodicals; Radiologie médicale -- Périodiques; Medical radiology; Periodicals; 616.075705
• DOI: 10.1016/j.ejrad.2021.109803
• Languages: English
• ISSNs: 0720-048X

Abstract

Highlights: Intra-tumoral heterogeneity of PNETs could be quantified with fractal analysis. Fractal analysis of preoperative CE-CT could predict grades of PNETs. Fractal analysis of CE-CT could help in choosing treatment options for patients. Abstract: Purpose: To assess intra-tumoral heterogeneity (ITH) via fractal analysis of preoperative contrast-enhanced computed tomography (CT) images to predict pathological grades in non-functioning pancreatic neuroendocrine tumors (NF-PNETs) and verify its impact on patient survival. Methods: This retrospective study enrolled 40 patients with NF-PNET resected in our institution during a period from July 2005 to December 2018, except functioning tumors, unidentified tumors in CT, patients without preoperative contrast-enhanced CT. CT images were analyzed using plugin software for calculating fractal dimension (FD), and the maximum value was denoted as "FDmax, " and compared with pathological grades and patient survival between G1 and G2/3 group separating according to two different Ki-67 index thresholds (3% and 5%). All CT images were acquired in three-phases and arterial phase images were examined. Results: Ki-67 index and FDmax showed a direct correlation with significance (p < 0.01). The mean FDmax of the G2/3 tumor group was significantly higher than that of the G1 tumor group (p < 0.01 in both 3% and 5% thresholds). In the ROC analysis, FDmax showed 0.773 of AUC, and cut-off value of 1.036 reported 62.5 % sensitivity, 90.0 % specificity, 86.2 % PPV, and 70.6 % NPV to distinguish G2/3 patients. The high-FD (≥1.036) group showed a significantly shorter disease-free survival (DFS) than the low-FD group (p = 0.0128). In multivariate analysis of prognostic factors, high FD was the only significant factor for DFS (HR, 5.793; 95 % CI: 1.213−27.664; p = 0.028). Conclusions: The tumor's FDmax using CE-CT analysis might be a potential biomarker for preoperative prediction of G2/3 tumors, and predicting recurrence.