Estimation of 6-Degree-of-Freedom (6-DOF) Rigid-Body Patient Motion From Projection Data by the Principal-Axes Method in Iterative Reconstruction

Development of a 6DOF robotic motion phantom for radiation therapy

PURPOSE

The use of medical technology capable of tracking patient motion or positioning patients along 6 degree-of-freedom (6DOF) has steadily increased in the field of radiation therapy. However, due to the complex nature of tracking and performing 6DOF motion, it is critical that such technology is properly verified to be operating within specifications in order to ensure patient safety. In this study, a robotic motion phantom is presented that can be programmed to perform highly accurate motion along any X (left-right), Y (superior-inferior), Z (anterior-posterior), pitch (around X), roll (around Y), and yaw (around Z) axes. In addition, highly synchronized motion along all axes can be performed in order to simulate the dynamic motion of a tumor in 6D. The accuracy and reproducibility of this 6D motion were characterized.

METHODS

An in-house designed and built 6D robotic motion phantom was constructed following the Stewart-Gough parallel kinematics platform archetype. The device was controlled using an inverse kinematics formulation, and precise movements in all 6 degrees-of-freedom (X, Y, Z, pitch, roll, and yaw) were performed, both simultaneously and separately for each degree-of-freedom. Additionally, previously recorded 6D cranial and prostate motions were effectively executed. The robotic phantom movements were verified using a 15 fps 6D infrared marker tracking system and the measured trajectories were compared quantitatively to the intended input trajectories. The workspace, maximum 6D velocity, backlash, and weight load capabilities of the system were also established.

RESULTS

Evaluation of the 6D platform demonstrated translational root mean square error (RMSE) values of 0.14, 0.22, and 0.08 mm over 20 mm in X and Y and 10 mm in Z, respectively, and rotational RMSE values of 0.16°, 0.06°, and 0.08° over 10° of pitch, roll, and yaw, respectively. The robotic stage also effectively performed controlled 6D motions, as well as reproduced cranial trajectories over 15 min, with a maximal RMSE of 0.04 mm translationally and 0.04° rotationally, and a prostate trajectory over 2 min, with a maximal RMSE of 0.06 mm translationally and 0.04° rotationally.

CONCLUSIONS

This 6D robotic phantom has proven to be accurate under clinical standards and capable of reproducing tumor motion in 6D. Such functionality makes the robotic phantom usable for either quality assurance or research purposes.

An evaluation of data-driven motion estimation in comparison to the usage of external-surrogates in cardiac SPECT imaging

Motion estimation methods in single photon emission computed tomography (SPECT) can be classified into methods which depend on just the emission data (data-driven), or those that use some other source of information such as an external surrogate. The surrogate-based methods estimate the motion exhibited externally which may not correlate exactly with the movement of organs inside the body. The accuracy of data-driven strategies on the other hand is affected by the type and timing of motion occurrence during acquisition, the source distribution, and various degrading factors such as attenuation, scatter, and system spatial resolution. The goal of this paper is to investigate the performance of two data-driven motion estimation schemes based on the rigid-body registration of projections of motion-transformed source distributions to the acquired projection data for cardiac SPECT studies. Comparison is also made of six intensity based registration metrics to an external surrogate-based method. In the data-driven schemes, a partially reconstructed heart is used as the initial source distribution. The partially-reconstructed heart has inaccuracies due to limited angle artifacts resulting from using only a part of the SPECT projections acquired while the patient maintained the same pose. The performance of different cost functions in quantifying consistency with the SPECT projection data in the data-driven schemes was compared for clinically realistic patient motion occurring as discrete pose changes, one or two times during acquisition. The six intensity-based metrics studied were mean-squared difference, mutual information, normalized mutual information (NMI), pattern intensity (PI), normalized cross-correlation and entropy of the difference. Quantitative and qualitative analysis of the performance is reported using Monte-Carlo simulations of a realistic heart phantom including degradation factors such as attenuation, scatter and system spatial resolution. Further the visual appearance of motion-corrected images using data-driven motion estimates was compared to that obtained using the external motion-tracking system in patient studies. Pattern intensity and normalized mutual information cost functions were observed to have the best performance in terms of lowest average position error and stability with degradation of image quality of the partial reconstruction in simulations. In all patients, the visual quality of PI-based estimation was either significantly better or comparable to NMI-based estimation. Best visual quality was obtained with PI-based estimation in one of the five patient studies, and with external-surrogate based correction in three out of five patients. In the remaining patient study there was little motion and all methods yielded similar visual image quality.