Xu Helen, Lasso Andras, Vikal Siddharth, Guion Peter, Krieger Axel, Kaushal Aradhana, Whitcomb Louis L, Fichtinger Gabor
Queen's University, Kingston, Canada.
Med Image Comput Comput Assist Interv. 2010;13(Pt 3):383-91. doi: 10.1007/978-3-642-15711-0_48.
Prostate cancer is a major health threat for men. For over five years, the U.S. National Cancer Institute has performed prostate biopsies with a magnetic resonance imaging (MRI)-guided robotic system.
A retrospective evaluation methodology and analysis of the clinical accuracy of this system is reported.
Using the pre and post-needle insertion image volumes, a registration algorithm that contains a two-step rigid registration followed by a deformable refinement was developed to capture prostate dislocation during the procedure. The method was validated by using three-dimensional contour overlays of the segmented prostates and the registrations were accurate up to 2 mm.
It was found that tissue deformation was less of a factor than organ displacement. Out of the 82 biopsies from 21 patients, the mean target displacement, needle placement error, and clinical biopsy error was 5.9 mm, 2.3 mm, and 4 mm, respectively.
The results suggest that motion compensation for organ displacement should be used to improve targeting accuracy.
前列腺癌是男性的主要健康威胁。五年多来，美国国家癌症研究所一直使用磁共振成像（MRI）引导的机器人系统进行前列腺活检。
报告该系统临床准确性的回顾性评估方法和分析。
利用穿刺前后的图像体积，开发了一种配准算法，该算法包括两步刚性配准，随后进行可变形细化，以捕捉手术过程中前列腺的脱位。通过使用分割前列腺的三维轮廓叠加来验证该方法，配准精度高达2毫米。
发现组织变形比器官位移的影响小。在21名患者的82次活检中，平均目标位移、针放置误差和临床活检误差分别为5.9毫米、2.3毫米和4毫米。
结果表明，应采用器官位移的运动补偿来提高靶向准确性。
