Burgos Ninon, Guerreiro Filipa, McClelland Jamie, Presles Benoît, Modat Marc, Nill Simeon, Dearnaley David, deSouza Nandita, Oelfke Uwe, Knopf Antje-Christin, Ourselin Sébastien, Jorge Cardoso M
Translational Imaging Group, CMIC, University College London, London, United Kingdom.
Phys Med Biol. 2017 Jun 7;62(11):4237-4253. doi: 10.1088/1361-6560/aa66bf. Epub 2017 Mar 14.
To tackle the problem of magnetic resonance imaging (MRI)-only radiotherapy treatment planning (RTP), we propose a multi-atlas information propagation scheme that jointly segments organs and generates pseudo x-ray computed tomography (CT) data from structural MR images (T1-weighted and T2-weighted). As the performance of the method strongly depends on the quality of the atlas database composed of multiple sets of aligned MR, CT and segmented images, we also propose a robust way of registering atlas MR and CT images, which combines structure-guided registration, and CT and MR image synthesis. We first evaluated the proposed framework in terms of segmentation and CT synthesis accuracy on 15 subjects with prostate cancer. The segmentations obtained with the proposed method were compared using the Dice score coefficient (DSC) to the manual segmentations. Mean DSCs of 0.73, 0.90, 0.77 and 0.90 were obtained for the prostate, bladder, rectum and femur heads, respectively. The mean absolute error (MAE) and the mean error (ME) were computed between the reference CTs (non-rigidly aligned to the MRs) and the pseudo CTs generated with the proposed method. The MAE was on average [Formula: see text] HU and the ME [Formula: see text] HU. We then performed a dosimetric evaluation by re-calculating plans on the pseudo CTs and comparing them to the plans optimised on the reference CTs. We compared the cumulative dose volume histograms (DVH) obtained for the pseudo CTs to the DVH obtained for the reference CTs in the planning target volume (PTV) located in the prostate, and in the organs at risk at different DVH points. We obtained average differences of [Formula: see text] in the PTV for [Formula: see text], and between [Formula: see text] and 0.05% in the PTV, bladder, rectum and femur heads for D and [Formula: see text]. Overall, we demonstrate that the proposed framework is able to automatically generate accurate pseudo CT images and segmentations in the pelvic region, potentially bypassing the need for CT scan for accurate RTP.
为了解决仅基于磁共振成像（MRI）的放射治疗计划（RTP）问题，我们提出了一种多图谱信息传播方案，该方案可联合分割器官并从结构磁共振图像（T1加权和T2加权）生成伪X射线计算机断层扫描（CT）数据。由于该方法的性能在很大程度上取决于由多组对齐的MR、CT和分割图像组成的图谱数据库的质量，我们还提出了一种稳健的图谱MR和CT图像配准方法，该方法结合了结构引导配准以及CT和MR图像合成。我们首先在15名前列腺癌患者身上评估了所提出框架在分割和CT合成准确性方面的性能。使用Dice评分系数（DSC）将所提方法获得的分割结果与手动分割结果进行比较。前列腺、膀胱、直肠和股骨头的平均DSC分别为0.73、0.90、0.77和0.90。在参考CT（与MR进行非刚性对齐）和所提方法生成的伪CT之间计算平均绝对误差（MAE）和平均误差（ME）。MAE平均为[公式：见原文]HU，ME为[公式：见原文]HU。然后，我们通过在伪CT上重新计算计划并将其与在参考CT上优化的计划进行比较，进行了剂量学评估。我们将在位于前列腺的计划靶体积（PTV）以及不同剂量体积直方图（DVH）点处的危及器官中为伪CT获得的累积DVH与为参考CT获得的DVH进行了比较。对于[公式：见原文]，在PTV中我们获得的平均差异为[公式：见原文]，对于D和[公式：见原文]，在PTV、膀胱、直肠和股骨头中平均差异在[公式：见原文]和0.05%之间。总体而言，我们证明所提出的框架能够在盆腔区域自动生成准确的伪CT图像和分割结果，有可能无需CT扫描即可进行准确的放射治疗计划。
