Handling images of patient postures in arms up and arms down position using a biomechanical skeleton model

Abstract

Deformable image registration is gradually becoming the tool of choice for motion extraction during adaptive radiotherapy. Achieving a motion vector field that accurately represents the anatomical changes requires a tissue specific transformation model. Therefore, widely used spline based models most likely fail in appropriately reproducing large anatomical changes such as the arms of the patient being positioned up and down. We present the application of a tissue specific biomechanical model with the goal to mimic patient motion even in presence of large motion. Based on the planning CT, delineated bones are used to represent the rigid anatomy of the patient. We implement ball-and-socket joints between corresponding bones in order to achieve mobility of the skeleton. An inverse kinematics approach enables the propagation of motion between individual bones across their joints, leading to an articulated skeleton that can be controlled by feature points on one or more bones. The transformation of each bone initializes a chainmail based soft tissue model to also propagate the motion into the surrounding heterogeneous soft tissue. Representation of different postures like arms up and down can be achieved within less than 1 s for the skeleton and ~10 s for the soft tissue.Especially for large anatomical changes, the kinematics approach benefits from the direct articulation at specific joints, considerably lowering the degrees of freedom for motion description. Being the input for the chainmail based soft tissue model, the transformed bones guarantee for its meaningful initialization. The proposed biomechanical skeleton model is promising to facilitate the registration of patients' anatomy, being positioned with arms up and arms down. The results encourage further refinement of the joints and the soft tissue model.

Biofidelic image registration for head and neck region utilizing an in-silico articulated skeleton as a transformation model

“…All joints are modeled as 3 degree-of-freedom ball-and-socket joints without mobility restrictions. Their position is either calculated as the nearest distance between a pair of connecting bones (Teske et al 2017a), or determined according to joint-specific rules (Teske et al 2017b). The newly positioned joints are shown in figure 1.…”

“…To generate the deformation vector field necessary for image transformation, the optimized skeletal posture is forwarded to a chainmail-based soft tissue deformation model published by Teske et al (2017b). Each bone voxel is initialized with the transformation parameters obtained from the registration process.…”