Construction of a nomogram combining CEUS and MRI imaging for preoperative diagnosis of microvascular invasion in hepatocellular carcinoma

IF 1.8 Q3 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Feiqian Wang , Kazushi Numata , Akihiro Funaoka , Takafumi Kumamoto , Kazuhisa Takeda , Makoto Chuma , Akito Nozaki , Litao Ruan , Shin Maeda
{"title":"Construction of a nomogram combining CEUS and MRI imaging for preoperative diagnosis of microvascular invasion in hepatocellular carcinoma","authors":"Feiqian Wang ,&nbsp;Kazushi Numata ,&nbsp;Akihiro Funaoka ,&nbsp;Takafumi Kumamoto ,&nbsp;Kazuhisa Takeda ,&nbsp;Makoto Chuma ,&nbsp;Akito Nozaki ,&nbsp;Litao Ruan ,&nbsp;Shin Maeda","doi":"10.1016/j.ejro.2024.100587","DOIUrl":null,"url":null,"abstract":"<div><h3>Purpose</h3><p>To use Sonazoid contrast-enhanced ultrasound (S-CEUS) and Gadolinium-Ethoxybenzyl-Diethylenetriamine Penta-Acetic Acid magnetic-resonance imaging (EOB-MRI), exploring a non-invasive preoperative diagnostic strategy for microvascular invasion (MVI) of hepatocellular carcinoma (HCC).</p></div><div><h3>Methods</h3><p>111 newly developed HCC cases were retrospectively collected. Both S-CEUS and EOB-MRI examinations were performed within one month of hepatectomy. The following indicators were investigated: size; vascularity in three phases of S-CEUS; margin, signal intensity, and peritumoral wedge shape in EOB-MRI; tumoral homogeneity, presence and integrity of the tumoral capsule in S-CEUS or EOB-MRI; presence of branching enhancement in S-CEUS; baseline clinical and serological data. The least absolute shrinkage and selection operator regression and multivariate logistic regression analysis were applied to optimize feature selection for the model. A nomogram for MVI was developed and verified by bootstrap resampling.</p></div><div><h3>Results</h3><p>Of the 16 variables we included, wedge and margin in HBP of EOB-MRI, capsule integrity in AP or HBP/PVP images of EOB-MRI/S-CEUS, and branching enhancement in AP of S-CEUS were identified as independent risk factors for MVI and incorporated into construction of the nomogram. The nomogram achieved an excellent diagnostic efficiency with an area under the curve of 0.8434 for full data training set and 0.7925 for bootstrapping validation set for 500 repetitions. In evaluating the nomogram, Hosmer–Lemeshow test for training set exhibited a good model fit with <em>P</em> &gt; 0.05. Decision curve analysis of nomogram model yielded excellent clinical net benefit with a wide range (5–80 % and 85–94 %) of risk threshold.</p></div><div><h3>Conclusions</h3><p>The MVI Nomogram established in this study may provide a strategy for optimizing the preoperative diagnosis of MVI, which in turn may improve the treatment and prognosis of MVI-related HCC.</p></div>","PeriodicalId":38076,"journal":{"name":"European Journal of Radiology Open","volume":"13 ","pages":"Article 100587"},"PeriodicalIF":1.8000,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S235204772400042X/pdfft?md5=ce4e261f345e48950b915bc3a9621dcf&pid=1-s2.0-S235204772400042X-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"European Journal of Radiology Open","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S235204772400042X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0

Abstract

Purpose

To use Sonazoid contrast-enhanced ultrasound (S-CEUS) and Gadolinium-Ethoxybenzyl-Diethylenetriamine Penta-Acetic Acid magnetic-resonance imaging (EOB-MRI), exploring a non-invasive preoperative diagnostic strategy for microvascular invasion (MVI) of hepatocellular carcinoma (HCC).

Methods

111 newly developed HCC cases were retrospectively collected. Both S-CEUS and EOB-MRI examinations were performed within one month of hepatectomy. The following indicators were investigated: size; vascularity in three phases of S-CEUS; margin, signal intensity, and peritumoral wedge shape in EOB-MRI; tumoral homogeneity, presence and integrity of the tumoral capsule in S-CEUS or EOB-MRI; presence of branching enhancement in S-CEUS; baseline clinical and serological data. The least absolute shrinkage and selection operator regression and multivariate logistic regression analysis were applied to optimize feature selection for the model. A nomogram for MVI was developed and verified by bootstrap resampling.

Results

Of the 16 variables we included, wedge and margin in HBP of EOB-MRI, capsule integrity in AP or HBP/PVP images of EOB-MRI/S-CEUS, and branching enhancement in AP of S-CEUS were identified as independent risk factors for MVI and incorporated into construction of the nomogram. The nomogram achieved an excellent diagnostic efficiency with an area under the curve of 0.8434 for full data training set and 0.7925 for bootstrapping validation set for 500 repetitions. In evaluating the nomogram, Hosmer–Lemeshow test for training set exhibited a good model fit with P > 0.05. Decision curve analysis of nomogram model yielded excellent clinical net benefit with a wide range (5–80 % and 85–94 %) of risk threshold.

Conclusions

The MVI Nomogram established in this study may provide a strategy for optimizing the preoperative diagnosis of MVI, which in turn may improve the treatment and prognosis of MVI-related HCC.

结合 CEUS 和 MRI 成像构建用于肝细胞癌微血管侵犯术前诊断的提名图
目的利用类 Sonazoid 对比增强超声波(S-CEUS)和钆-乙氧苄基-二乙烯三胺五乙酸磁共振成像(EOB-MRI),探索肝细胞癌(HCC)微血管侵犯(MVI)的无创术前诊断策略。S-CEUS 和 EOB-MRI 检查均在肝切除术后一个月内进行。研究指标包括:肿瘤大小;S-CEUS三期血管情况;EOB-MRI的边缘、信号强度和瘤周楔形;S-CEUS或EOB-MRI的肿瘤均匀性、肿瘤囊的存在和完整性;S-CEUS的分支强化情况;基线临床和血清学数据。应用最小绝对收缩和选择算子回归以及多变量逻辑回归分析来优化模型的特征选择。结果 在我们纳入的 16 个变量中,EOB-MRI HBP 中的楔形和边缘、EOB-MRI/S-CEUS AP 或 HBP/PVP 图像中的囊完整性、S-CEUS AP 中的分支增强被确定为 MVI 的独立风险因素,并被纳入提名图的构建中。该提名图的诊断效率极高,全数据训练集的曲线下面积为 0.8434,重复 500 次的引导验证集的曲线下面积为 0.7925。在评估提名图时,训练集的 Hosmer-Lemeshow 检验显示模型拟合良好,P > 0.05。结论 本研究建立的 MVI Nomogram 可为 MVI 的术前诊断提供优化策略,从而改善 MVI 相关 HCC 的治疗和预后。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
European Journal of Radiology Open
European Journal of Radiology Open Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
4.10
自引率
5.00%
发文量
55
审稿时长
51 days
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信