IEEE Trans Med Imaging. 2017 Oct;36(10):2010-2020. doi: 10.1109/TMI.2017.2703150. Epub 2017 May 10.
In magnetic resonance (MR)-targeted, 3-D transrectal ultrasound (TRUS)-guided biopsy, prostate motion during the procedure increases the needle targeting error and limits the ability to accurately sample MR-suspicious tumor volumes. The robustness of the 2-D-3-D registration methods for prostate motion compensation is impacted by local optima in the search space. In this paper, we analyzed the prostate motion characteristics and investigated methods to incorporate such knowledge into the registration optimization framework to improve robustness against local optima. Rigid motion of the prostate was analyzed adopting a mixture-of-Gaussian (MoG) model using 3-D TRUS images acquired at bilateral sextant probe positions with a mechanically assisted biopsy system. The learned motion characteristics were incorporated into Powell's direction set method by devising multiple initial search positions and initial search directions. Experiments were performed on data sets acquired during clinical biopsy procedures, and registration error was evaluated using target registration error (TRE) and converged image similarity metric values after optimization. After incorporating the learned initialization positions and directions in Powell's method, 2-D-3-D registration to compensate for motion during prostate biopsy was performed with rms ± std TRE of 2.33 ± 1.09 mm with ~3 s mean execution time per registration. This was an improvement over 3.12 ± 1.70 mm observed in Powell's standard approach. For the data acquired under clinical protocols, the converged image similarity metric value improved in ≥8% of the registrations whereas it degraded only ≤1% of the registrations. The reported improvements in optimization indicate useful advancements in robustness to ensure smooth clinical integration of a registration solution for motion compensation that facilitates accurate sampling of the smallest clinically significant tumors.
在磁共振（MR）靶向、三维经直肠超声（TRUS）引导活检中，前列腺在手术过程中的运动增加了针的靶向误差，并限制了准确采样 MR 可疑肿瘤体积的能力。2D-3D 配准方法对前列腺运动补偿的稳健性受到搜索空间中局部最优值的影响。在本文中，我们分析了前列腺运动特征，并研究了将这些知识纳入配准优化框架中的方法，以提高对局部最优值的稳健性。采用混合高斯（MoG）模型分析前列腺的刚性运动，使用机械辅助活检系统在双侧六分仪探头位置采集 3D TRUS 图像。通过设计多个初始搜索位置和初始搜索方向，将学习到的运动特征纳入 Powell 方向集方法中。在临床活检过程中采集的数据集中进行了实验，并使用目标配准误差（TRE）和优化后的收敛图像相似性度量值评估了配准误差。在 Powell 方法中加入学习到的初始化位置和方向后，2D-3D 配准用于补偿前列腺活检过程中的运动，rms ± std TRE 为 2.33 ± 1.09mm，平均每个配准执行时间约为 3s。这比 Powell 标准方法观察到的 3.12 ± 1.70mm 有所改善。对于在临床方案下采集的数据，收敛图像相似性度量值在≥8%的配准中得到了改善，而只有≤1%的配准中恶化。优化报告的改进表明，在确保注册解决方案平稳临床集成以促进对最小临床显著肿瘤进行准确采样的运动补偿方面，稳健性得到了有用的提高。
