Abstract: Articulated Head and Neck Patient Model for Adaptive Radiotherapy
Abstract: Articulated Head and Neck Patient Model for Adaptive Radiotherapy
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摘要：用于适应性放射治疗的铰接头颈患者模型
DOI：
10.1007/978-3-662-54345-0_58
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Giske K
中科院分区：
文献类型：
--
作者：
Teske H;Bartelheimer K;Meis J;Stoiber EM;Bendl R;Giske K
最先进的放射疗法能够精确塑造剂量分布，以保持肿瘤控制，同时保留有风险的器官。在线自适应放疗通过考虑整个治疗过程中解剖结构的分次间变化来改善这一点。特别是头颈部癌症患者的姿势变化会导致解剖结构发生较大变形，可能导致与计划剂量分布的相当大的偏差。调整治疗计划以补偿这种变化需要准确评估解剖变形。通常使用的模型不区分骨组织和软组织，从而导致骨骼的不切实际的变形。我们提出了一个铰接的病人模型的头部和颈部区域，它固有地保留了刚度的骨骼，同时允许模拟任意姿势的病人。在规划CT中，根据骨骼的分割来组装铰接的骨架模型。对于示例性头颈癌患者，40个单独的骨骼通过45个关节连接。所有的关节都被建模为球窝关节，赋予围绕三个身体轴的旋转移动性。通过使用逆运动学方法[1]来实现骨骼模型内的运动传播。在消费者PC上，不同的姿势以每秒约25个的速度交互生成。为了研究其优点和局限性，该模型被用于对患者的任意姿势的图像进行采样。除了骨骼模型之外，还耦合了基于链甲的模型以考虑软组织变形。生成逼真的复杂姿态，实现了仅使用多达8个用户定义的支持向量。骨骼的分割是手动生成的。由此产生的采样图像表明，我们的模型能够准确地评估患者的不同分次间姿势。结合其时间有效的计算，它可以进一步用于图像配准环境中。
State of the art radiotherapy enables for precise shaping of dose distributions to maintain tumor control while sparing organs at risk. Online adaptive radiotherapy improves that by taking into account inter-fractional changes of the anatomy throughout the treatment course. Especially variations in the posture of head and neck cancer patients cause large deformations in the anatomy, potentially leading to considerable deviations from the planned dose distributions. Adapting the treatment plan to compensate for such changes requires an accurate assessment of anatomical deformations. Commonly used models do not distinguish between bony tissue and soft tissue and thus result in unrealistic deformations of the bones. We propose an articulated patient model for the head and neck region, which inherently preserves the rigidity of the bones while allowing for modelling arbitrary postures of the patient. An articulated skeleton model is assembled from the segmentations of the bones in the planning CT. For an exemplary head and neck cancer patient, 40 individual bones were connected by 45 joints. All the joints were modelled as ball and socket joints, granting rotational mobility around the three body axes. Propagation of motion within the skeletal model is achieved by using an inverse kinematics approach [1]. On a consumer PC, different postures are generated interactively at a rate of ~25 per second. To investigate the advantages and limitations, this model was used to sample images of arbitrary postures of the patient. In addition to the skeletal model, a chainmail-based model was coupled to account for soft tissue deformation. Generation of realistic complex postures was achieved by using only up to 8 user-defined supporting vectors. The segmentations of the bones were generated manually. The resulting sampled images suggest that our model is able to accurately assess different inter-fractional postures of the patient. In combination with its time-efficient computation, it can further be used in the image registration context.
DOI：
10.1016/j.piutam.2011.04.023
发表时间：
2011
期刊：
Procedia IUTAM
影响因子：
--
作者：
Sherman, Michael A;Seth, Ajay;Delp, Scott L
通讯作者：
Delp, Scott L