Department of Medical Physics in Radiation Oncology, German Cancer Research Center, Heidelberg, Germany.
Med Phys. 2012 Apr;39(4):2186-92. doi: 10.1118/1.3697524.
In fractionated radiation therapy, image guidance with daily tomographic imaging becomes more and more clinical routine. In principle, this allows for daily computation of the delivered dose and for accumulation of these daily dose distributions to determine the actually delivered total dose to the patient. However, uncertainties in the mapping of the images can translate into errors of the accumulated total dose, depending on the dose gradient. In this work, an approach to estimate the uncertainty of mapping between medical images is proposed that identifies areas bearing a significant risk of inaccurate dose accumulation.
This method accounts for the geometric uncertainty of image registration and the heterogeneity of the dose distribution, which is to be mapped. Its performance is demonstrated in context of dose mapping based on b-spline registration. It is based on evaluation of the sensitivity of dose mapping to variations of the b-spline coefficients combined with evaluation of the sensitivity of the registration metric with respect to the variations of the coefficients. It was evaluated based on patient data that was deformed based on a breathing model, where the ground truth of the deformation, and hence the actual true dose mapping error, is known.
The proposed approach has the potential to distinguish areas of the image where dose mapping is likely to be accurate from other areas of the same image, where a larger uncertainty must be expected.
An approach to identify areas where dose mapping is likely to be inaccurate was developed and implemented. This method was tested for dose mapping, but it may be applied in context of other mapping tasks as well.
在分次放射治疗中，每日层析成像的图像引导越来越成为临床常规。原则上，这允许每天计算所给予的剂量，并将这些每日剂量分布累积起来，以确定患者实际接受的总剂量。然而，图像映射中的不确定性可能会转化为累积总剂量的误差，这取决于剂量梯度。在这项工作中，提出了一种估计医学图像之间映射不确定性的方法，该方法可识别存在剂量累积不准确风险的显著区域。
该方法考虑了图像配准的几何不确定性和待映射的剂量分布的非均质性。它的性能在基于 B 样条配准的剂量映射的背景下得到了验证。它基于评估剂量映射对 B 样条系数变化的敏感性，结合评估配准度量对系数变化的敏感性。它是基于基于呼吸模型变形的患者数据进行评估的，其中变形的真实值，因此实际的真实剂量映射误差是已知的。
所提出的方法有可能区分图像中剂量映射可能准确的区域和同一图像中其他区域，这些区域需要更大的不确定性。
已经开发并实现了一种识别剂量映射可能不准确的区域的方法。该方法已针对剂量映射进行了测试，但也可应用于其他映射任务。
