Prakash Varuna, Stainsby Jeffrey A, Satkunasingham Janakan, Craig Tim, Catton Charles, Chan Philip, Dawson Laura, Hensel Jennifer, Jaffray David, Milosevic Michael, Nichol Alan, Sussman Marshall S, Lockwood Gina, Ménard Cynthia
Department of Radiation Oncology, Princess Margaret Hospital, Toronto, ON, Canada.
Int J Radiat Oncol Biol Phys. 2008 Jul 15;71(4):1253-60. doi: 10.1016/j.ijrobp.2007.11.021. Epub 2008 Jan 22.
To validate a correlation coefficient template-matching algorithm applied to the supervised automated quantification of abdominal-pelvic organ motion captured on time-resolved magnetic resonance imaging.
Magnetic resonance images of 21 patients across four anatomic sites were analyzed. Representative anatomic points of interest were chosen as surrogates for organ motion. The point of interest displacements across each image frame relative to baseline were quantified manually and through the use of a template-matching software tool, termed "Motiontrack." Automated and manually acquired displacement measures, as well as the standard deviation of intrafraction motion, were compared for each image frame and for each patient.
Discrepancies between the automated and manual displacements of > or =2 mm were uncommon, ranging in frequency of 0-9.7% (liver and prostate, respectively). The standard deviations of intrafraction motion measured with each method correlated highly (r = 0.99). Considerable interpatient variability in organ motion was demonstrated by a wide range of standard deviations in the liver (1.4-7.5 mm), uterus (1.1-8.4 mm), and prostate gland (0.8-2.7 mm). The automated algorithm performed successfully in all patients but 1 and substantially improved efficiency compared with manual quantification techniques (5 min vs. 60-90 min).
Supervised automated quantification of organ motion captured on magnetic resonance imaging using a correlation coefficient template-matching algorithm was efficient, accurate, and may play an important role in off-line adaptive approaches to intrafraction motion management.
验证一种相关系数模板匹配算法，该算法应用于对时间分辨磁共振成像所捕获的腹盆腔器官运动进行监督式自动定量分析。
分析了21例患者四个解剖部位的磁共振图像。选择具有代表性的解剖感兴趣点作为器官运动的替代指标。相对于基线，手动并通过使用一种名为“Motiontrack”的模板匹配软件工具，对每个图像帧中感兴趣点的位移进行定量分析。比较了每个图像帧和每位患者自动获取与手动获取的位移测量值以及分次内运动的标准差。
自动与手动位移之间相差≥2 mm的情况并不常见，频率范围为0 - 9.7%（分别为肝脏和前列腺）。两种方法测量的分次内运动标准差高度相关（r = 0.99）。肝脏（1.4 - 7.5 mm）、子宫（1.1 - 8.4 mm）和前列腺（0.8 - 2.7 mm）的标准差范围表明患者间器官运动存在相当大的变异性。除1例患者外，自动算法在所有患者中均成功运行，与手动定量技术相比，效率大幅提高（5分钟对60 - 90分钟）。
使用相关系数模板匹配算法对磁共振成像所捕获的器官运动进行监督式自动定量分析是高效、准确的，并且可能在分次内运动管理的离线自适应方法中发挥重要作用。
