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

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...

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Detalles Bibliográficos
Autores principales: Chen, Fang, Liu, Jia, Zhang, Xinran, Liao, Hongen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Institution of Engineering and Technology 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6952258/
https://www.ncbi.nlm.nih.gov/pubmed/32038869
http://dx.doi.org/10.1049/htl.2019.0072
Descripción
Sumario: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.