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Modeling and Predicting Tissue Movement and Deformation for High Intensity Focused Ultrasound Therapy
PURPOSE: In ultrasound-guided High Intensity Focused Ultrasound (HIFU) therapy, the target tissue (such as a tumor) often moves and/or deforms in response to an external force. This problem creates difficulties in treating patients and can lead to the destruction of normal tissue. In order to solve...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4439056/ https://www.ncbi.nlm.nih.gov/pubmed/25993644 http://dx.doi.org/10.1371/journal.pone.0127873 |
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author | Liao, Xiangyun Yuan, Zhiyong Lai, Qianfeng Guo, Jiaxiang Zheng, Qi Yu, Sijiao Tong, Qianqian Si, Weixin Sun, Mingui |
author_facet | Liao, Xiangyun Yuan, Zhiyong Lai, Qianfeng Guo, Jiaxiang Zheng, Qi Yu, Sijiao Tong, Qianqian Si, Weixin Sun, Mingui |
author_sort | Liao, Xiangyun |
collection | PubMed |
description | PURPOSE: In ultrasound-guided High Intensity Focused Ultrasound (HIFU) therapy, the target tissue (such as a tumor) often moves and/or deforms in response to an external force. This problem creates difficulties in treating patients and can lead to the destruction of normal tissue. In order to solve this problem, we present a novel method to model and predict the movement and deformation of the target tissue during ultrasound-guided HIFU therapy. METHODS: Our method computationally predicts the position of the target tissue under external force. This prediction allows appropriate adjustments in the focal region during the application of HIFU so that the treatment head is kept aligned with the diseased tissue through the course of therapy. To accomplish this goal, we utilize the cow tissue as the experimental target tissue to collect spatial sequences of ultrasound images using the HIFU equipment. A Geodesic Localized Chan-Vese (GLCV) model is developed to segment the target tissue images. A 3D target tissue model is built based on the segmented results. A versatile particle framework is constructed based on Smoothed Particle Hydrodynamics (SPH) to model the movement and deformation of the target tissue. Further, an iterative parameter estimation algorithm is utilized to determine the essential parameters of the versatile particle framework. Finally, the versatile particle framework with the determined parameters is used to estimate the movement and deformation of the target tissue. RESULTS: To validate our method, we compare the predicted contours with the ground truth contours. We found that the lowest, highest and average Dice Similarity Coefficient (DSC) values between predicted and ground truth contours were, respectively, 0.9615, 0.9770 and 0.9697. CONCLUSION: Our experimental result indicates that the proposed method can effectively predict the dynamic contours of the moving and deforming tissue during ultrasound-guided HIFU therapy. |
format | Online Article Text |
id | pubmed-4439056 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-44390562015-05-29 Modeling and Predicting Tissue Movement and Deformation for High Intensity Focused Ultrasound Therapy Liao, Xiangyun Yuan, Zhiyong Lai, Qianfeng Guo, Jiaxiang Zheng, Qi Yu, Sijiao Tong, Qianqian Si, Weixin Sun, Mingui PLoS One Research Article PURPOSE: In ultrasound-guided High Intensity Focused Ultrasound (HIFU) therapy, the target tissue (such as a tumor) often moves and/or deforms in response to an external force. This problem creates difficulties in treating patients and can lead to the destruction of normal tissue. In order to solve this problem, we present a novel method to model and predict the movement and deformation of the target tissue during ultrasound-guided HIFU therapy. METHODS: Our method computationally predicts the position of the target tissue under external force. This prediction allows appropriate adjustments in the focal region during the application of HIFU so that the treatment head is kept aligned with the diseased tissue through the course of therapy. To accomplish this goal, we utilize the cow tissue as the experimental target tissue to collect spatial sequences of ultrasound images using the HIFU equipment. A Geodesic Localized Chan-Vese (GLCV) model is developed to segment the target tissue images. A 3D target tissue model is built based on the segmented results. A versatile particle framework is constructed based on Smoothed Particle Hydrodynamics (SPH) to model the movement and deformation of the target tissue. Further, an iterative parameter estimation algorithm is utilized to determine the essential parameters of the versatile particle framework. Finally, the versatile particle framework with the determined parameters is used to estimate the movement and deformation of the target tissue. RESULTS: To validate our method, we compare the predicted contours with the ground truth contours. We found that the lowest, highest and average Dice Similarity Coefficient (DSC) values between predicted and ground truth contours were, respectively, 0.9615, 0.9770 and 0.9697. CONCLUSION: Our experimental result indicates that the proposed method can effectively predict the dynamic contours of the moving and deforming tissue during ultrasound-guided HIFU therapy. Public Library of Science 2015-05-20 /pmc/articles/PMC4439056/ /pubmed/25993644 http://dx.doi.org/10.1371/journal.pone.0127873 Text en © 2015 Liao et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Liao, Xiangyun Yuan, Zhiyong Lai, Qianfeng Guo, Jiaxiang Zheng, Qi Yu, Sijiao Tong, Qianqian Si, Weixin Sun, Mingui Modeling and Predicting Tissue Movement and Deformation for High Intensity Focused Ultrasound Therapy |
title | Modeling and Predicting Tissue Movement and Deformation for High Intensity Focused Ultrasound Therapy |
title_full | Modeling and Predicting Tissue Movement and Deformation for High Intensity Focused Ultrasound Therapy |
title_fullStr | Modeling and Predicting Tissue Movement and Deformation for High Intensity Focused Ultrasound Therapy |
title_full_unstemmed | Modeling and Predicting Tissue Movement and Deformation for High Intensity Focused Ultrasound Therapy |
title_short | Modeling and Predicting Tissue Movement and Deformation for High Intensity Focused Ultrasound Therapy |
title_sort | modeling and predicting tissue movement and deformation for high intensity focused ultrasound therapy |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4439056/ https://www.ncbi.nlm.nih.gov/pubmed/25993644 http://dx.doi.org/10.1371/journal.pone.0127873 |
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