Fortunati Valerio, Verhaart René F, Angeloni Francesco, van der Lugt Aad, Niessen Wiro J, Veenland Jifke F, Paulides Margarethus M, van Walsum Theo
Biomedical Imaging Group Rotterdam, Department of Medical Informatics and Radiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands.
Hyperthermia Unit, Department of Radiation Oncology, Erasmus MC University Medical Center Cancer Institute, Rotterdam, The Netherlands.
Int J Radiat Oncol Biol Phys. 2014 Sep 1;90(1):85-93. doi: 10.1016/j.ijrobp.2014.05.027. Epub 2014 Jul 8.
To investigate the feasibility of using deformable registration in clinical practice to fuse MR and CT images of the head and neck for treatment planning.
A state-of-the-art deformable registration algorithm was optimized, evaluated, and compared with rigid registration. The evaluation was based on manually annotated anatomic landmarks and regions of interest in both modalities. We also developed a multiparametric registration approach, which simultaneously aligns T1- and T2-weighted MR sequences to CT. This was evaluated and compared with single-parametric approaches.
Our results show that deformable registration yielded a better accuracy than rigid registration, without introducing unrealistic deformations. For deformable registration, an average landmark alignment of approximatively 1.7 mm was obtained. For all the regions of interest excluding the cerebellum and the parotids, deformable registration provided a median modified Hausdorff distance of approximatively 1 mm. Similar accuracies were obtained for the single-parameter and multiparameter approaches.
This study demonstrates that deformable registration of head-and-neck CT and MR images is feasible, with overall a significanlty higher accuracy than for rigid registration.
研究在临床实践中使用可变形配准融合头颈部磁共振成像(MR)和计算机断层扫描(CT)图像以进行治疗计划的可行性。
对一种先进的可变形配准算法进行了优化、评估,并与刚性配准进行了比较。评估基于两种模态中手动标注的解剖标志点和感兴趣区域。我们还开发了一种多参数配准方法,该方法同时将T1加权和T2加权MR序列与CT对齐。对其进行了评估并与单参数方法进行了比较。
我们的结果表明,可变形配准比刚性配准具有更高的准确性,且不会引入不切实际的变形。对于可变形配准,平均标志点对齐误差约为1.7毫米。对于除小脑和腮腺外的所有感兴趣区域,可变形配准提供的中位修正豪斯多夫距离约为1毫米。单参数和多参数方法获得了相似的准确性。
本研究表明,头颈部CT和MR图像的可变形配准是可行的,总体上比刚性配准具有显著更高的准确性。