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Patient-specific Deformation Modelling via Elastography: Application to Image-guided Prostate Interventions
Image-guided prostate interventions often require the registration of preoperative magnetic resonance (MR) images to real-time transrectal ultrasound (TRUS) images to provide high-quality guidance. One of the main challenges for registering MR images to TRUS images is how to estimate the TRUS-probe-...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4895338/ https://www.ncbi.nlm.nih.gov/pubmed/27272239 http://dx.doi.org/10.1038/srep27386 |
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author | Wang, Yi Ni, Dong Qin, Jing Xu, Ming Xie, Xiaoyan Heng, Pheng-Ann |
author_facet | Wang, Yi Ni, Dong Qin, Jing Xu, Ming Xie, Xiaoyan Heng, Pheng-Ann |
author_sort | Wang, Yi |
collection | PubMed |
description | Image-guided prostate interventions often require the registration of preoperative magnetic resonance (MR) images to real-time transrectal ultrasound (TRUS) images to provide high-quality guidance. One of the main challenges for registering MR images to TRUS images is how to estimate the TRUS-probe-induced prostate deformation that occurs during TRUS imaging. The combined statistical and biomechanical modeling approach shows promise for the adequate estimation of prostate deformation. However, the right setting of the biomechanical parameters is very crucial for realistic deformation modeling. We propose a patient-specific deformation model equipped with personalized biomechanical parameters obtained from shear wave elastography to reliably predict the prostate deformation during image-guided interventions. Using data acquired from a prostate phantom and twelve patients with suspected prostate cancer, we compared the prostate deformation model with and without patient-specific biomechanical parameters in terms of deformation estimation accuracy. The results show that the patient-specific deformation model possesses favorable model ability, and outperforms the model without patient-specific biomechanical parameters. The employment of the patient-specific biomechanical parameters obtained from elastography for deformation modeling shows promise for providing more precise deformation estimation in applications that use computer-assisted image-guided intervention systems. |
format | Online Article Text |
id | pubmed-4895338 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48953382016-06-10 Patient-specific Deformation Modelling via Elastography: Application to Image-guided Prostate Interventions Wang, Yi Ni, Dong Qin, Jing Xu, Ming Xie, Xiaoyan Heng, Pheng-Ann Sci Rep Article Image-guided prostate interventions often require the registration of preoperative magnetic resonance (MR) images to real-time transrectal ultrasound (TRUS) images to provide high-quality guidance. One of the main challenges for registering MR images to TRUS images is how to estimate the TRUS-probe-induced prostate deformation that occurs during TRUS imaging. The combined statistical and biomechanical modeling approach shows promise for the adequate estimation of prostate deformation. However, the right setting of the biomechanical parameters is very crucial for realistic deformation modeling. We propose a patient-specific deformation model equipped with personalized biomechanical parameters obtained from shear wave elastography to reliably predict the prostate deformation during image-guided interventions. Using data acquired from a prostate phantom and twelve patients with suspected prostate cancer, we compared the prostate deformation model with and without patient-specific biomechanical parameters in terms of deformation estimation accuracy. The results show that the patient-specific deformation model possesses favorable model ability, and outperforms the model without patient-specific biomechanical parameters. The employment of the patient-specific biomechanical parameters obtained from elastography for deformation modeling shows promise for providing more precise deformation estimation in applications that use computer-assisted image-guided intervention systems. Nature Publishing Group 2016-06-07 /pmc/articles/PMC4895338/ /pubmed/27272239 http://dx.doi.org/10.1038/srep27386 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Wang, Yi Ni, Dong Qin, Jing Xu, Ming Xie, Xiaoyan Heng, Pheng-Ann Patient-specific Deformation Modelling via Elastography: Application to Image-guided Prostate Interventions |
title | Patient-specific Deformation Modelling via Elastography: Application to Image-guided Prostate Interventions |
title_full | Patient-specific Deformation Modelling via Elastography: Application to Image-guided Prostate Interventions |
title_fullStr | Patient-specific Deformation Modelling via Elastography: Application to Image-guided Prostate Interventions |
title_full_unstemmed | Patient-specific Deformation Modelling via Elastography: Application to Image-guided Prostate Interventions |
title_short | Patient-specific Deformation Modelling via Elastography: Application to Image-guided Prostate Interventions |
title_sort | patient-specific deformation modelling via elastography: application to image-guided prostate interventions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4895338/ https://www.ncbi.nlm.nih.gov/pubmed/27272239 http://dx.doi.org/10.1038/srep27386 |
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