Presles Benoît, Fargier-Voiron Marie, Biston Marie-Claude, Lynch Rod, Munoz Alexandre, Liebgott Hervé, Pommier Pascal, Rit Simon, Sarrut David
Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1, Lyon F-69621, France and Léon Bérard Cancer Center, Université de Lyon, Lyon F-69373, France.
Université de Lyon, CREATIS, CNRS UMR5220, Inserm U1044, INSA-Lyon, Université Lyon 1, Lyon F-69621, France.
Med Phys. 2014 Dec;41(12):122903. doi: 10.1118/1.4901642.
The aim of the present work is to propose and evaluate registration algorithms of three-dimensional (3D) transabdominal (TA) ultrasound (US) images to setup postprostatectomy patients during radiation therapy.
Three registration methods have been developed and evaluated to register a reference 3D-TA-US image acquired during the planning CT session and a 3D-TA-US image acquired before each treatment session. The first method (method A) uses only gray value information, whereas the second one (method B) uses only gradient information. The third one (method C) combines both sets of information. All methods restrict the comparison to a region of interest computed from the dilated reference positioning volume drawn on the reference image and use mutual information as a similarity measure. The considered geometric transformations are translations and have been optimized by using the adaptive stochastic gradient descent algorithm. Validation has been carried out using manual registration by three operators of the same set of image pairs as the algorithms. Sixty-two treatment US images of seven patients irradiated after a prostatectomy have been registered to their corresponding reference US image. The reference registration has been defined as the average of the manual registration values. Registration error has been calculated by subtracting the reference registration from the algorithm result. For each session, the method has been considered a failure if the registration error was above both the interoperator variability of the session and a global threshold of 3.0 mm.
All proposed registration algorithms have no systematic bias. Method B leads to the best results with mean errors of -0.6, 0.7, and -0.2 mm in left-right (LR), superior-inferior (SI), and anterior-posterior (AP) directions, respectively. With this method, the standard deviations of the mean error are of 1.7, 2.4, and 2.6 mm in LR, SI, and AP directions, respectively. The latter are inferior to the interoperator registration variabilities which are of 2.5, 2.5, and 3.5 mm in LR, SI, and AP directions, respectively. Failures occur in 5%, 18%, and 10% of cases in LR, SI, and AP directions, respectively. 69% of the sessions have no failure.
Results of the best proposed registration algorithm of 3D-TA-US images for postprostatectomy treatment have no bias and are in the same variability range as manual registration. As the algorithm requires a short computation time, it could be used in clinical practice provided that a visual review is performed.
本研究的目的是提出并评估三维（3D）经腹（TA）超声（US）图像的配准算法，用于前列腺切除术后患者在放射治疗期间的摆位。
已开发并评估了三种配准方法，用于配准在计划CT扫描期间获取的参考3D-TA-US图像和每次治疗前获取的3D-TA-US图像。第一种方法（方法A）仅使用灰度值信息，而第二种方法（方法B）仅使用梯度信息。第三种方法（方法C）结合了这两组信息。所有方法都将比较限制在根据参考图像上绘制的扩张参考定位体积计算出的感兴趣区域内，并使用互信息作为相似性度量。所考虑的几何变换是平移，并使用自适应随机梯度下降算法进行了优化。使用与算法相同的一组图像对由三名操作员进行手动配准来进行验证。对七名前列腺切除术后接受放疗的患者的62张治疗US图像进行了与其相应参考US图像的配准。参考配准被定义为手动配准值的平均值。通过从算法结果中减去参考配准来计算配准误差。对于每个疗程，如果配准误差高于该疗程的操作员间变异性和3.0 mm的全局阈值，则认为该方法失败。
所有提出的配准算法均无系统偏差。方法B产生的结果最佳，在左右（LR）、上下（SI）和前后（AP）方向上的平均误差分别为-0.6、0.7和-0.2 mm。使用该方法，平均误差在LR、SI和AP方向上的标准差分别为1.7、2.4和2.6 mm。后者低于操作员间配准变异性，在LR、SI和AP方向上分别为2.5、2.5和3.5 mm。在LR、SI和AP方向上分别有5%、18%和10%的病例出现失败。69%的疗程没有失败。
为前列腺切除术后治疗提出的最佳3D-TA-US图像配准算法的结果无偏差，且与手动配准的变异性范围相同。由于该算法计算时间短，只要进行视觉检查，就可用于临床实践。
