Yang Xiaofeng, Rossi Peter, Jani Ashesh B, Mao Hui, Ogunleye Tomi, Curran Walter J, Liu Tian
Department of Radiation Oncology and Winship Cancer Institute, Emory University, Atlanta, GA 30322.
Department of Radiology and Imaging Sciences and Winship Cancer Institute, Emory University, Atlanta, GA 30322.
Proc SPIE Int Soc Opt Eng. 2015 Feb;9413. doi: 10.1117/12.2077828. Epub 2015 Mar 20.
In this paper, we propose a 3D neurovascular bundles (NVB) segmentation method for ultrasound (US) image by integrating MR and transrectal ultrasound (TRUS) images through MR-TRUS deformable registration. First, 3D NVB was contoured by a physician in MR images, and the 3D MR-defined NVB was then transformed into US images using a MR-TRUS registration method, which models the prostate tissue as an elastic material, and jointly estimates the boundary deformation and the volumetric deformations under the elastic constraint. This technique was validated with a clinical study of 6 patients undergoing radiation therapy (RT) treatment for prostate cancer. The accuracy of our approach was assessed through the locations of landmarks, as well as previous ultrasound Doppler images of patients. MR-TRUS registration was successfully performed for all patients. The mean displacement of the landmarks between the post-registration MR and TRUS images was less than 2 mm, and the average NVB volume Dice Overlap Coefficient was over 89%. This NVB segmentation technique could be a useful tool as we try to spare the NVB in prostate RT, monitor NVB response to RT, and potentially improve post-RT potency outcomes.
在本文中,我们提出了一种通过磁共振成像(MR)和经直肠超声(TRUS)图像的MR-TRUS可变形配准来对超声(US)图像进行三维神经血管束(NVB)分割的方法。首先,由一名医生在MR图像中勾勒出三维NVB,然后使用MR-TRUS配准方法将三维MR定义的NVB转换到US图像中,该方法将前列腺组织建模为弹性材料,并在弹性约束下联合估计边界变形和体积变形。这项技术在一项对6名接受前列腺癌放射治疗(RT)的患者的临床研究中得到了验证。我们的方法的准确性通过地标位置以及患者先前的超声多普勒图像进行评估。所有患者均成功完成了MR-TRUS配准。配准后MR和TRUS图像之间地标点的平均位移小于2毫米,并且平均NVB体积的骰子重叠系数超过89%。当我们试图在前列腺RT中保留NVB、监测NVB对RT的反应并潜在地改善RT后的性功能结果时,这种NVB分割技术可能是一种有用的工具。