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基于粒子时空分布模型的乳腺癌患者腋窝淋巴结转移概率分析

Probability analysis of axillary lymph node metastasis in breast cancer patients using particle space-time distribution model.

作者信息

Chen Fang, Liu Jia, Zhang Xinran, Liao Hongen

机构信息

Department of Computer Science and Engineering, Nanjing University of Aeronautics and Astronautics, MIIT Key Laboratory of Pattern Analysis and Machine Intelligence, Nanjing 210016, People's Republic of China.

Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 10084, People's Republic of China.

出版信息

Healthc Technol Lett. 2019 Nov 26;6(6):266-270. doi: 10.1049/htl.2019.0072. eCollection 2019 Dec.

Abstract

The possibility of axillary lymph node metastasis differs in different breast cancer patients and is the strongest prognostic indicator in breast cancer. The existing studies mainly explored the relationship of axillary ultrasound imaging and axillary lymph node metastasis, without exploring whether ultrasound imaging of breast tumour can affect and perform axillary lymph node prediction. Therefore, this Letter proposes a novel particle space-time distribution model to find the correlation between contrast-enhanced ultrasonography of breast tumour and axillary lymphatic metastasis. Starting from the imaging principle of dynamic contrast-enhanced ultrasonography, the particle space-time distribution model not only comprises space-time features of contrast-enhanced ultrasonography with an encoder-decoder network, but also the flow field information of microbubble particles is integrated into the space-time features that better serves the metastasis prediction by enhancing the particle distribution information. Extensive experiments on real patients have demonstrated that dynamic contrast-enhanced ultrasonography of breast tumour can be used to predict the probability of lymphatic metastasis. This conclusion can be interpretable from the clinical and pathological perspectives.

摘要

不同乳腺癌患者发生腋窝淋巴结转移的可能性存在差异,且是乳腺癌最强的预后指标。现有研究主要探讨腋窝超声成像与腋窝淋巴结转移的关系,未探讨乳腺肿瘤的超声成像是否会影响及进行腋窝淋巴结预测。因此,本信函提出一种新型粒子时空分布模型,以寻找乳腺肿瘤超声造影与腋窝淋巴转移之间的相关性。从动态超声造影成像原理出发,粒子时空分布模型不仅通过编码器 - 解码器网络包含超声造影的时空特征,还将微泡粒子的流场信息整合到时空特征中,通过增强粒子分布信息更好地服务于转移预测。对真实患者的大量实验表明,乳腺肿瘤动态超声造影可用于预测淋巴转移概率。这一结论可从临床和病理角度进行解读。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6aac/6952258/cf09e7c26a7b/HTL.2019.0072.01.jpg

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