Link to the University of Pittsburgh Homepage
Link to the University Library System Homepage Link to the Contact Us Form
D-Scholarship @ Pitt Banner and Links to Homepage

Modeling and predicting tissue movement and deformation for high intensity focused ultrasound therapy

Liao, X and Yuan, Z and Lai, Q and Guo, J and Zheng, Q and Yu, S and Tong, Q and Si, W and Sun, M (2015) Modeling and predicting tissue movement and deformation for high intensity focused ultrasound therapy. PLoS ONE, 10 (5).

[img]
Preview
 PDF
Published Version
Available under License : See the attached license file.
Download (5MB)
[img] Plain Text (licence)
Available under License : See the attached license file.
Download (1kB)

Abstract

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.

Share

Citation/Export:
Social Networking:
Share |

Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Liao, X
Yuan, Z
Lai, Q
Guo, J
Zheng, Q
Yu, S
Tong, Q
Si, W
Sun, Mdrsun@pitt.eduDRSUN
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorTalkachova, AlenaUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date: 20 May 2015
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: PLoS ONE
Volume: 10
Number: 5
DOI or Unique Handle: 10.1371/journal.pone.0127873
Institution: University of Pittsburgh
Schools and Programs: School of Medicine > Medicine
Refereed: Yes
Date Deposited: 23 Aug 2016 14:10
Last Modified: 30 Mar 2021 14:55
URI: http://d-scholarship.pitt.edu/id/eprint/28476

Metrics

Monthly Views for the past 3 years

Plum Analytics

Altmetric.com

Actions (login required)

View Item View Item