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Assessment of radio frequency treatment of hepatic tumors

机译:射频治疗肝肿瘤的评估

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It is fundamentally important that all cancerous cells be adequately destroyed during Radio Frequency Ablation (RFA) procedures. To help achieve this goal, probe manufacturers advise physicians to increase the treatment region by one centimeter (1cm) in all directions around the diseased tissue. This enlarged treatment region provides a buffer to insure that cancer cells that migrated into surrounding tissue are adequately treated and necrose. Even though RFA is a minimally invasive, image-guided procedure, it is difficult for physicians to confidently follow the specified treatment protocol. In this paper we visually assess an RFA treatment by comparing a registered image set containing the untreated tumor, including the 1 cm safety boundary, to that of an image set containing the treated region acquired one month after surgery. For this study, we used Computerized Tomography images as both the tumor and treated regions are visible. To align the image sets of the abdomen, we investigate three different registration techniques; an affine transform that minimizes the correlation ratio, a point (or landmark) based 3D thin-plate spline approach, and a nonlinear B-spline elastic registration methodology. We found the affine registration technique simple and easy to use because it is fully automatic. Unfortunately, this method resulted in the largest visible discrepancy between the liver in the fused images. The thin-plate spline technique required the physician to identify corresponding landmarks in both image sets, but resulted in better visual accuracy in the fused images. Finally, the non-linear, B-spline, elastic registration technique used the registration results of the thin-plate spline method as a starting point and then required a significant amount of computation to determine its transformation, but also provided the most visually accurate fused image set.
机译:从根本上重要的是在射频消融(RFA)程序中充分破坏所有癌细胞。为了帮助实现这一目标,探针制造商建议医师将患病组织周围各个方向的治疗区域增加一厘米(1厘米)。这个扩大的治疗区域提供了一个缓冲区,以确保迁移到周围组织中的癌细胞得到充分的治疗,并且可以消融。即使RFA是一种微创,图像引导的程序,医生也很难自信地遵循指定的治疗方案。在本文中,我们通过比较包含未治疗肿瘤(包括1 cm安全边界)的已注册图像集与包含术后一个月获得的已治疗区域的图像集的视觉形象,评估了RFA治疗。对于本研究,我们使用计算机断层扫描图像,因为可见肿瘤和治疗区域。为了对齐腹部的图像集,我们研究了三种不同的配准技术:最小化相关比率的仿射变换,基于点(或界标)的3D薄板样条方法以及非线性B样条弹性配准方法。我们发现仿射配准技术简单易用,因为它是全自动的。不幸的是,这种方法导致了融合图像中肝脏之间最大的可见差异。薄板样条线技术要求医生在两个图像集中识别相应的界标,但是在融合图像中产生了更好的视觉准确性。最后,非线性B样条弹性配准技术以薄板样条法的配准结果为起点,然后需要大量的计算来确定其变换,而且还提供了视觉上最准确的融合图像集。

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