利用术前磁共振成像预测胰腺神经内分泌肿瘤的淋巴管、微血管及神经周围侵犯情况。

Prediction of the lymphatic, microvascular, and perineural invasion of pancreatic neuroendocrine tumors using preoperative magnetic resonance imaging.

作者信息

Liu Yu-Liang, Zhu Hai-Bin, Chen Mai-Lin, Sun Wei, Li Xiao-Ting, Sun Ying-Shi

机构信息

Department of Radiology, Peking University Cancer Hospital and Institute, Beijing 100142, China.

Department of Pathology, Peking University Cancer Hospital and Institute, Beijing 100142, China.

出版信息

World J Gastrointest Surg. 2023 Dec 27;15(12):2809-2819. doi: 10.4240/wjgs.v15.i12.2809.

DOI:10.4240/wjgs.v15.i12.2809

PMID:38222000

原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10784819/

Abstract

BACKGROUND

Significant correlation between lymphatic, microvascular, and perineural invasion (LMPI) and the prognosis of pancreatic neuroendocrine tumors (PENTs) was confirmed by previous studies. There was no previous study reported the relationship between magnetic resonance imaging (MRI) parameters and LMPI.

AIM

To determine the feasibility of using preoperative MRI of the pancreas to predict LMPI in patients with non-functioning PENTs (NFPNETs).

METHODS

A total of 61 patients with NFPNETs who underwent MRI scans and lymphadenectomy from May 2011 to June 2018 were included in this retrospective study. The patients were divided into group 1 ( = 34, LMPI negative) and group 2 ( = 27, LMPI positive). The clinical characteristics and qualitative MRI features were collected. In order to predict LMPI status in NF-PNETs, a multivariate logistic regression model was constructed. Diagnostic performance was evaluated by calculating the receiver operator characteristic (ROC) curve with area under ROC, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy.

RESULTS

There were significant differences in the lymph node metastasis stage, tumor grade, neuron-specific enolase levels, tumor margin, main pancreatic ductal dilatation, common bile duct dilatation, enhancement pattern, vascular and adjacent tissue involvement, synchronous liver metastases, the long axis of the largest lymph node, the short axis of the largest lymph node, number of the lymph nodes with short axis > 5 or 10 mm, and tumor volume between two groups ( < 0.05). Multivariate analysis showed that tumor margin (odds ratio = 11.523, < 0.001) was a predictive factor for LMPI of NF-PNETs. The area under the receiver value for the predictive performance of combined predictive factors was 0.855. The sensitivity, specificity, PPV, NPV and accuracy of the model were 48.1% (14/27), 97.1% (33/34), 97.1% (13/14), 70.2% (33/47) and 0.754, respectively.

CONCLUSION

Using preoperative MRI, ill-defined tumor margins can effectively predict LMPI in patients with NF-PNETs.

摘要

背景

先前的研究证实了淋巴管、微血管及神经周围侵犯（LMPI）与胰腺神经内分泌肿瘤（PENTs）预后之间存在显著相关性。此前尚无研究报道磁共振成像（MRI）参数与LMPI之间的关系。

目的

确定利用胰腺术前MRI预测无功能性PENTs（NFPNETs）患者LMPI的可行性。

方法

本回顾性研究纳入了2011年5月至2018年6月期间接受MRI扫描及淋巴结切除术的61例NFPNETs患者。患者被分为1组（n = 34，LMPI阴性）和2组（n = 27，LMPI阳性）。收集临床特征及MRI定性特征。为预测NF-PNETs中的LMPI状态，构建了多因素逻辑回归模型。通过计算受试者操作特征（ROC）曲线及其曲线下面积、灵敏度、特异度、阳性预测值（PPV）、阴性预测值（NPV）及准确性来评估诊断性能。

结果

两组在淋巴结转移分期、肿瘤分级、神经元特异性烯醇化酶水平、肿瘤边界、主胰管扩张、胆总管扩张、强化方式、血管及邻近组织受累情况、同步肝转移、最大淋巴结长径、最大淋巴结短径、短径>5或10 mm的淋巴结数量及肿瘤体积方面存在显著差异（P<0.05）。多因素分析显示，肿瘤边界（比值比=11.523，P<0.001）是NF-PNETs中LMPI的预测因素。联合预测因素预测性能的受试者值下面积为0.855。该模型的灵敏度、特异度、PPV、NPV及准确性分别为48.1%（14/27）、97.1%（33/34）、97.1%（13/14）、70.2%（33/47）及0.754。