Modeling and predicting tissue movement and deformation for high intensity focused ultrasound therapy.
Modeling and predicting tissue movement and deformation for high intensity focused ultrasound therapy.
复制标题
建模和预测高强度聚焦超声治疗的组织运动和变形。
DOI：
10.1371/journal.pone.0127873
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Sun M
中科院分区：
文献类型：
--
作者：
Liao X;Yuan Z;Lai Q;Guo J;Zheng Q;Yu S;Tong Q;Si W;Sun M
在超声引导的高强度聚焦超声（HIFU）治疗中，目标组织（例如肿瘤）经常响应外力而移动和/或变形。这个问题给治疗患者带来了困难，并可能导致正常组织的破坏。为了解决这个问题，我们提出了一种新方法来建模和预测超声引导 HIFU 治疗期间目标组织的运动和变形。我们的方法通过计算预测目标组织在外力作用下的位置。这种预测允许在应用 HIFU 期间对焦点区域进行适当的调整，以便在治疗过程中治疗头与病变组织保持对齐。为了实现这一目标，我们利用牛组织作为实验目标组织，使用 HIFU 设备收集超声图像的空间序列。开发了测地线局部化 Chan-Vese (GLCV) 模型来分割目标组织图像。根据分割结果构建 3D 目标组织模型。基于平滑粒子流体动力学（SPH）构建了通用粒子框架来模拟目标组织的运动和变形。此外，利用迭代参数估计算法来确定通用粒子框架的基本参数。最后，使用具有确定参数的通用粒子框架来估计目标组织的运动和变形。为了验证我们的方法，我们将预测轮廓与地面真实轮廓进行比较。我们发现预测轮廓和地面真实轮廓之间的最低、最高和平均 Dice 相似系数 (DSC) 值分别为 0.9615、0.9770 和 0.9697。我们的实验结果表明，该方法可以有效预测超声引导 HIFU 治疗过程中移动和变形组织的动态轮廓。
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. 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. 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. 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.
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HIFU 治疗中子宫肌瘤超声图像的多尺度和形状约束局部区域主动轮廓分割。
影响因子：
3.7
作者：
Liao X;Yuan Z;Zheng Q;Yin Q;Zhang D;Zhao J
通讯作者：
Zhao J
影响因子：
10.6
作者：
Chan, TF;Vese, LA
通讯作者：
Vese, LA
DOI：
10.1109/tvcg.2013.105
发表时间：
2014-03-01
影响因子：
5.2
作者：
Ihmsen, Markus;Cornelis, Jens;Teschner, Matthias
通讯作者：
Teschner, Matthias
影响因子：
8.8
作者：
通讯作者：
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影响因子：
6.2
作者：
Akinci, Nadir;Ihmsen, Markus;Teschner, Matthias
通讯作者：
Teschner, Matthias