Differentiation of intrapancreatic accessory spleen from small hypervascular neuroendocrine tumor of the pancreas: textural analysis on contrast-enhanced computed tomography

Author:

Lin Xubo1,Xu Lei1,Wu Aiqin1ORCID,Guo Chuangen2,Chen Xiao3,Wang Zhongqiu3

Affiliation:

1. Department of Radiology, the Second Affiliated Hospital and Yuying Children's Hospital of Wenzhou Medical University, Wenzhou Medical University, Wenzhou, PR China

2. Department of Radiology, the First Affiliated Hospital, College of Medicine Zhejiang University, Hangzhou, PR China

3. Department of Radiology, the Affiliated Hospital of Nanjing University of Chinese Medicine, Nanjing, PR China

Abstract

Background Intrapancreatic accessory spleens (IPASs) are usually misdiagnosed as pancreatic neuroendocrine tumors (PNETs). Texture analysis is valuable in tumor detection, diagnosis, and staging. Purpose To identify the potential of texture features in differentiating IPASs from small hypervascular PNETs. Material and Methods Twenty-one patients with PNETs and 13 individuals with IPASs who underwent pretreatment dynamic contrast-enhanced computed tomography (CT) were retrospectively analyzed. The routine imaging features—such as location, size, margin, cystic or solid appearance, enhancement degree and pattern, and lymph node enlargement—were recorded. Texture features, such as entropy, skewness, kurtosis, and uniformity, on contrast-enhanced images were analyzed. Receiver operating characteristic (ROC) analysis was performed to differentiate IPASs from PNETs. Results No significant differences were observed in margin, enhancement degree (arterial and portal phase), lymph node enlargement, or size between PNETs and IPASs (all P > 0.05). However, IPASs usually showed heterogeneous enhancement at the arterial phase and the same degree of enhancement as the spleen at the portal phase, both of which were greater than those of PNETs (69% vs. 35%, P = 0.06; 100% vs. 29%, P = 0.04). Entropy and uniformity were significantly different between IPASs and PNETs at moderate (1.5) and high sigma values (2.5) (both P < 0.01). ROC analysis showed that uniformity at moderate and high sigma had the highest area under the curve (0.82 and 0.89) with better sensitivity (85.0–95.0%) and acceptable specificity (75.0–83.3%) for differentiating IPASs from PNETs. Conclusions Texture parameters have potential in differentiating IPASs from PNETs.

Funder

Zhejiang Medical Science and Technology Project

Primary Research & Development Plan of Jiangsu Province

Publisher

SAGE Publications

Subject

Radiology, Nuclear Medicine and imaging,General Medicine,Radiological and Ultrasound Technology

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