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局灶性肝病变:通过超分辨率超声成像进行多参数微血管特征分析

Focal liver lesions: multiparametric microvasculature characterization via super-resolution ultrasound imaging.

作者信息

Zeng Qian-Qian, An Shi-Zhe, Chen Chao-Nan, Wang Zhen, Liu Jia-Cheng, Wan Ming-Xi, Zong Yu-Jin, Jian Xiao-Hua, Yu Jie, Liang Ping

机构信息

Department of Interventional Ultrasound, Senior Department of Oncology, The Fifth Medical Center of PLA General Hospital, Fengtai District, Beijing, 100853, China.

Chinese People's Liberation Army (PLA) Medical School, Haidian District, Beijing, 100853, China.

出版信息

Eur Radiol Exp. 2024 Dec 5;8(1):138. doi: 10.1186/s41747-024-00540-3.

DOI:10.1186/s41747-024-00540-3
PMID:39636384
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11621259/
Abstract

BACKGROUND

Noninvasive and functional imaging of the focal liver lesion (FLL) vasculature at microscopic scales is clinically challenging. We investigated the feasibility of using super-resolution ultrasound (SR-US) imaging for visualizing and quantifying the microvasculature of intraparenchymal FLLs.

METHODS

Patients with FLLs between June 2022 and February 2023 were prospectively screened. Following bolus injection of microbubbles at clinical concentration, SR-US was performed using a high frame rate (350-500 Hz) modified ultrasound scanner and a convex array transducer with a central frequency of 3.1 MHz.

RESULTS

In total, 47 pathologically proven FLLs at a depth of 5.7 ± 1.7 cm (mean ± standard deviation) were included: 30 hepatocellular carcinomas (HCC), 11 liver metastases (LM), and 6 focal nodular hyperplasias (FNH). The smallest detectable vessel size of the hepatic microvasculature was 128.4 ± 18.6 μm (mean ± standard deviation) at a depth of 8 cm. Significant differences were observed among the three types of lesions in terms of pattern categories, vessel density, minimum flow velocity, and perfusion index. We observed higher vessel density for FNH versus liver parenchyma (p < 0.001) as well as fractal dimension and local flow direction entropy value for FNH versus HCC (p = 0.002 and p < 0.001, respectively) and for FNH versus LM (p = 0.006 and p = 0.002, respectively).

CONCLUSION

Multiparametric SR-US showed that these three pathological types of FLLs have specific microvascular phenotypes. Vessel density, fractal dimension and local flow direction entropy served as valuable parameters in distinguishing between benign and malignant FLLs.

TRIAL REGISTRATION

ClinicalTrials.gov (NCT06018142).

RELEVANCE STATEMENT

Multiparametric SR-US imaging offers precise morphological and functional assessment of the microvasculature of intraparenchymal focal liver lesions, providing insights into tumor heterogeneity and angiogenesis.

KEY POINTS

Super-resolution (SR)-US imaging allowed morphological and functional evaluation of intraparenchymal hepatic lesion microvasculature. Hepatocellular carcinoma, liver metastasis, and focal nodular hyperplasia exhibit distinct microvascular architectures and hemodynamic profiles. Multiparametric microvasculature characterization via SR-US imaging facilitates the differentiation between benign and malignant microvascular phenotypes.

摘要

背景

在微观尺度上对肝脏局灶性病变(FLL)的血管系统进行无创性和功能性成像在临床上具有挑战性。我们研究了使用超分辨率超声(SR-US)成像来可视化和量化肝实质内FLL微血管系统的可行性。

方法

对2022年6月至2023年2月期间患有FLL的患者进行前瞻性筛查。在以临床浓度推注微泡后,使用高帧率(350 - 500Hz)的改良超声扫描仪和中心频率为3.1MHz的凸阵换能器进行SR-US检查。

结果

总共纳入了47个经病理证实的FLL,深度为5.7±1.7cm(平均值±标准差),其中包括30例肝细胞癌(HCC)、11例肝转移瘤(LM)和6例局灶性结节性增生(FNH)。在8cm深度处,肝脏微血管系统的最小可检测血管大小为128.4±18.6μm(平均值±标准差)。在模式类别、血管密度、最小流速和灌注指数方面,三种类型的病变之间观察到显著差异。我们观察到FNH与肝实质相比血管密度更高(p < 0.001),FNH与HCC相比分形维数和局部血流方向熵值更高(分别为p = 0.002和p < 0.001),FNH与LM相比分形维数和局部血流方向熵值更高(分别为p = 0.006和p = 0.002)。

结论

多参数SR-US显示这三种病理类型的FLL具有特定的微血管表型。血管密度、分形维数和局部血流方向熵是区分良性和恶性FLL的有价值参数。

试验注册

ClinicalTrials.gov(NCT06018142)。

相关性声明

多参数SR-US成像可对肝实质内局灶性肝脏病变的微血管系统进行精确的形态学和功能评估,为肿瘤异质性和血管生成提供见解。

关键点

超分辨率(SR)-US成像可对肝实质内肝脏病变微血管系统进行形态学和功能评估。肝细胞癌、肝转移瘤和局灶性结节性增生表现出不同的微血管结构和血流动力学特征。通过SR-US成像进行多参数微血管特征分析有助于区分良性和恶性微血管表型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fe/11621259/bf571bee0aa3/41747_2024_540_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fe/11621259/c494e756a110/41747_2024_540_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fe/11621259/bf571bee0aa3/41747_2024_540_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fe/11621259/c494e756a110/41747_2024_540_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fe/11621259/4bda0b257185/41747_2024_540_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fe/11621259/ac6055e13165/41747_2024_540_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fe/11621259/95297671e4bd/41747_2024_540_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fe/11621259/c3af67f505a9/41747_2024_540_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d9fe/11621259/bf571bee0aa3/41747_2024_540_Fig6_HTML.jpg

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