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基于动态对比增强超声定量分析预测胰腺神经内分泌肿瘤的病理分级

Prediction of Pathological Grades of Pancreatic Neuroendocrine Tumors Based on Dynamic Contrast-Enhanced Ultrasound Quantitative Analysis.

作者信息

Yang Dao-Hui, Cheng Juan, Tian Xiao-Fan, Zhang Qi, Yu Ling-Yun, Qiu Yi-Jie, Lu Xiu-Yun, Lou Wen-Hui, Dong Yi, Wang Wen-Ping

机构信息

Department of Ultrasound, Zhongshan Hospital, Fudan University (Xiamen Branch), Xiamen 361006, China.

Department of Ultrasound, Xinhua Hospital Affiliated to Shanghai Jiaotong University School of Medicine, Shanghai 200092, China.

出版信息

Diagnostics (Basel). 2023 Jan 9;13(2):238. doi: 10.3390/diagnostics13020238.

DOI:10.3390/diagnostics13020238
PMID:36673048
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9858178/
Abstract

Objective: To investigate whether the dynamic contrast-enhanced ultrasound (DCE-US) analysis and quantitative parameters could be helpful for predicting histopathologic grades of pancreatic neuroendocrine tumors (pNETs). Methods: This retrospective study conducted a comprehensive review of the CEUS database between March 2017 and November 2021 in Zhongshan Hospital, Fudan University. Ultrasound examinations were performed by an ACUSON Sequioa unit equipped with a 3.5 MHz 6C−1 convex array transducer, and an ACUSON OXANA2 unit equipped with a 3.5 MHz 5C−1 convex array transducer. SonoVue® (Bracco Inc., Milan, Italy) was used for all CEUS examinations. Time intensity curves (TICs) and quantitative parameters of DCE-US were created by Vuebox® software (Bracco, Italy). Inclusion criteria were: patients with histopathologically proved pNETs, patients who underwent pancreatic B-mode ultrasounds (BMUS) and CEUS scans one week before surgery or biopsy and had DCE-US imaging documented for more than 2 min, patients with solid or predominantly solid lesions and patients with definite diagnosis of histopathological grades of pNETs. Based on their prognosis, patients were categorized into two groups: pNETs G1/G2 group and pNETs G3/pNECs group. Results: A total of 42 patients who underwent surgery (n = 38) or biopsy (n = 4) and had histopathologically confirmed pNETs were included. According to the WHO 2019 criteria, all pNETs were classified into grade 1 (G1, n = 10), grade 2 (G2, n = 21), or grade 3 (G3)/pancreatic neuroendocrine carcinomas (pNECs) (n = 11), based on the Ki−67 proliferation index and the mitotic activity. The majority of the TICs (27/31) of pNETs G1/G2 were above or equal to those of pancreatic parenchyma in the arterial phase, but most (7/11) pNETs G3/pNECs had TICs below those of pancreatic parenchyma from arterial phase to late phase (p < 0.05). Among all the CEUS quantitative parameters of DCE-US, values of relative rise time (rPE), relative mean transit time (rmTT) and relative area under the curve (rAUC) were significantly higher in pNETs G1/G2 group than those in pNETs G3/pNECs group (p < 0.05). Taking an rPE below 1.09 as the optimal cut-off value, the sensitivity, specificity and accuracy for prediction of pNETs G3/pNECs from G1/G2 were 90.91% [58.70% to 99.80%], 67.64% [48.61% to 83.32%] and 85.78% [74.14% to 97.42%], respectively. Taking rAUC below 0.855 as the optimal cut-off value, the sensitivity, specificity and accuracy for prediction of pNETs G3/pNECs from G1/G2 were 90.91% [66.26% to 99.53%], 83.87% [67.37% to 92.91%] and 94.72% [88.30% to 100.00%], respectively. Conclusions: Dynamic contrast-enhanced ultrasound analysis might be helpful for predicting the pathological grades of pNETs. Among all quantitative parameters, rPE, rmTT and rAUC are potentially useful parameters for predicting G3/pNECs with aggressive behavior.

摘要

目的

探讨动态对比增强超声(DCE-US)分析及定量参数是否有助于预测胰腺神经内分泌肿瘤(pNETs)的组织病理学分级。方法:本回顾性研究对2017年3月至2021年11月复旦大学附属中山医院的CEUS数据库进行了全面回顾。超声检查采用配备3.5 MHz 6C−1凸阵探头的ACUSON Sequioa超声仪和配备3.5 MHz 5C−1凸阵探头的ACUSON OXANA2超声仪。所有CEUS检查均使用声诺维®(意大利米兰百胜公司)。DCE-US的时间强度曲线(TICs)和定量参数由Vuebox®软件(意大利百胜)生成。纳入标准为:组织病理学证实为pNETs的患者;术前或活检前一周接受过胰腺B超(BMUS)和CEUS扫描且DCE-US成像记录超过2分钟的患者;实性或主要为实性病变的患者;pNETs组织病理学分级明确诊断的患者。根据预后情况,将患者分为两组:pNETs G1/G2组和pNETs G3/pNECs组。结果:共纳入42例接受手术(n = 38)或活检(n = 4)且组织病理学确诊为pNETs的患者。根据世界卫生组织2019年标准,基于Ki−67增殖指数和有丝分裂活性,所有pNETs分为1级(G1,n = 10)、2级(G2,n = 21)或3级(G3)/胰腺神经内分泌癌(pNECs)(n = 11)。pNETs G1/G2的大多数TICs(27/31)在动脉期高于或等于胰腺实质,但大多数(7/11)pNETs G3/pNECs从动脉期到晚期的TICs低于胰腺实质(p < 0.05)。在DCE-US的所有CEUS定量参数中,pNETs G1/G2组的相对上升时间(rPE)、相对平均通过时间(rmTT)和相对曲线下面积(rAUC)值显著高于pNETs G3/pNECs组(p < 0.05)。以rPE低于1.09作为最佳截断值,从G1/G2预测pNETs G3/pNECs的敏感性、特异性和准确性分别为90.91%[58.70%至99.80%]、67.64%[48.61%至83.32%]和85.78%[74.14%至97.42%]。以rAUC低于0.855作为最佳截断值,从G1/G2预测pNETs G3/pNECs的敏感性、特异性和准确性分别为90.91%[66.26%至99.53%]、83.87%[67.37%至92.91%]和94.72%[88.30%至100.00%]。结论:动态对比增强超声分析可能有助于预测pNETs的病理分级。在所有定量参数中

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6107/9858178/491c473895d5/diagnostics-13-00238-g004.jpg
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