评价肝细胞癌局部治疗的非刚性登记

Chunhua Dong, T. Seki, Ryosuke Inoguchi, Chen-Lun Lin, X. Han, Yenwei Chen
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引用次数: 2

摘要

对肝细胞癌(HCC)进行局部治疗(LT)的治疗边缘评估,是大多数医院预测HCC复发的常用方法。然而,在有限的条件下,LT有时不能清楚地切除肿瘤。HCC的治疗效果通常是通过比较术前和术后CT或MRI的二维融合图像来评估的。然而,利用二维切片有时很难判断肝移植后手术切缘是否存在肿瘤。需要开发一种合适的图像配准算法来自动对齐两个体积,以便将术后体积的治疗边缘转换为术前体积的肿瘤,以评估HCC治疗后的治疗效果。考虑到这些,本文提出了一种医学图像的自动三维融合成像方法,采用非刚性配准方法,将消融边缘(即肝细胞癌术后治疗边缘)对准肝细胞癌的位置。在我们的配准算法中,采用结合局部b样条的刚性全局变换来估计肝移植前后的显著非刚性运动。我们提出的方法可以确保评估HCC治疗边缘的可行性、准确性和有效性。此外,该方法可适用于多模态医学图像的配准。通过比较医学图像融合评价的不同准则,验证了该方法的有效性。结果清楚地表明,我们的方法在评估处理后的边缘时非常有用,而且它保留了体积的运动和局部变形。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Nonrigid registration for evaluating locoregional therapy of hepatocellular carcinoma
The assessment of the treated margin with locoregional therapy (LT), for hepatocellular carcinoma (HCC), is the common method for predicting HCC recurrence in most hospital. However, tumors sometimes cannot be removed clearly with LT in limited conditions. The therapeutic efficiency of HCC is often evaluated by comparing 2D fusion images of computed tomography (CT) or magnetic resonance imaging (MRI) between the preoperation and the postoperation. However, judgment about whether the tumors exist in the treated margin after LT by using 2D slices sometimes is difficult. It is desirable to develop a suitable image registration algorithm to automatically align the two volumes in order to transform the treated margin of the postoperative volume to the tumor of the preoperative volume to assess the therapeutic efficiency after treatment of HCC. With taking these into consideration, this paper proposed an automatic 3D fusion imaging approach for medical image by using the nonrigid registration method that aligning an ablative margin - that is the treated margin after LT, onto the locations of HCC. In our registration algorithm, a rigid global transformation combined with localized B-spline is used to estimate the significant nonrigid motions of the liver between before and after LT. Our proposed approach can ensure the feasibility, the accuracy and the efficacy to assess the treated margin for HCC. Furthermore, this method can be adapted to register multi-modality medical images. We demonstrate the effectiveness of our proposed method by comparing the difference criterions of fusion evaluation on medical images. The results clearly indicate that our method extremely useful in the evaluation of the treated margin, in addition, it remain the motion and local deformation of the volume.
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