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Incorporating seed orientation in brachytherapy implant reconstruction

机译:在近距离植入种植体重建中纳入种子方向

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Intra-operative quality assurance and dosimetry optimization in prostate brachytherapy critically depends on the ability of discerning the locations of implanted seeds. Various methods exist for seed matching and reconstruction from multiple segmented C-arm images. Unfortunately, using three or more images makes the problem NP-hard, i.e. no polynomial-time algorithm can provably compute the complete matching. Typically, a statistical analysis of performance is considered sufficient. Hence it is of utmost importance to exploit all the available information in order to minimize the matching and reconstruction errors. Current algorithms use only the information about seed centers, disregarding the information about the orientations and length of seeds. While the latter has little dosimetric impact, it can positively contribute to improving seed matching rate and 3D implant reconstruction accuracy. It can also become critical information when hidden and spuriously segmented seeds need to be matched, where reliable and generic methods are not yet available. Expecting orientation information to be useful in reconstructing large and dense implants, we have developed a method which incorporates seed orientation information into our previously proposed reconstruction algorithm (MARSHAL). Simulation study shows that under normal segmentation errors, when considering seed orientations, implants of 80 to 140 seeds with the density of 2.0- 3.0 seeds/cc give an average matching rate > 97% using three-image matching. It is higher than the matching rate of about 96% when considering only seed positions. This means that the information of seed orientations appears to be a valuable additive to fluoroscopy-based brachytherapy implant reconstruction.
机译:前列腺近距离放射治疗中的术中质量保证和剂量学优化关键取决于辨别植入种子位置的能力。存在用于从多个分割的C形臂图像进行种子匹配和重建的各种方法。不幸的是,使用三个或更多图像使问题变得难以解决,即没有多项式时间算法可证明地计算出完全匹配。通常,对性能进行统计分析就足够了。因此,利用所有可用信息以最小化匹配和重建误差至关重要。当前的算法仅使用有关种子中心的信息,而忽略有关种子的方向和长度的信息。尽管后者几乎没有剂量学上的影响,但可以为提高种子匹配率和3D植入物重建精度做出积极贡献。当隐藏的和散乱的种子需要匹配时,当可靠和通用的方法尚不可用时,它也可能成为关键信息。期望方向信息对重建大型且密集的植入物有用,因此我们开发了一种将种子方向信息合并到我们先前提出的重建算法(MARSHAL)中的方法。仿真研究表明,在正常分割误差下,考虑种子方向时,使用三图像匹配,植入密度为2.0-3.0种子/ cc的80到140个种子时,平均匹配率> 97%。仅考虑种子位置时,该匹配率高于约96%的匹配率。这意味着种子方向的信息似乎是基于荧光检查的近距离放射治疗植入物重建的有价值的补充。

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