Evaluation of image guided motion management methods in lung cancer radiotherapy

Adaptive hypofractionted and stereotactic body radiotherapy for lung tumors with real-time MRI guidance

The treatment of central and ultracentral lung tumors with radiotherapy remains an ongoing clinical challenge. The risk of Grade 5 toxicity with ablative radiotherapy doses to these high-risk regions is significant as shown in recent prospective studies. Magnetic resonance (MR) image-guided adaptive radiotherapy (MRgART) is a new technology and may allow the delivery of ablative radiotherapy to these high-risk regions safely. MRgART is able to achieve this by utilizing small treatment margins, real-time gating/tracking and on-table plan adaptation to maintain dose to the tumor but limit dose to critical structures. The process of MRgART is complex and has nuances and challenges for the treatment of lung tumors. We outline the critical steps needed for appropriate delivery of MRgART for lung tumors safely and effectively.

Mooney-Rivlin biomechanical modeling of lung with Inhomogeneous material

In this study, the Mooney-Rivlin material with hyperelastic strain energy was proposed for biomechanical modeling of the lung. We modeled the lung as an inhomogeneous Mooney-Rivlin material with uncoupled deviatoric and volumetric behavior. The proposed method was evaluated on the lungs of eight lung cancer patients. For each patient, the lung was segmented from the 4D-CT images and tetrahedral volume mesh of the lung in phase 50% was created by using the adaptive mesh generation toolkit. The demons deformable registration algorithm was used to extract the displacement vector fields (DVFs). The Jacobian of the deformation gradient was calculated from DVFs, and the lung strain energy function was optimized to improve the tumor center of mass (TCM) motion simulation accuracy between respiratory phase 50% and 0%. The average TCM motion simulation error for the proposed strategy is 1.95 mm for eight patients. We observed 13% improvement in the TCM position prediction compared with the homogeneous Mooney-Rivlin modeling.

Evaluation of gantry speed on image quality and imaging dose for 4D cone-beam CT acquisition

Background

This study investigates the effect of gantry speed on 4DCBCT image quality and dose for the Varian On-Board Imager®.

Methods

A thoracic 4DCBCT protocol was designed using a 125 kVp spectrum. Image quality parameters were evaluated for 4DCBCT acquisition using Catphan® phantom with real-time position management™ system for gantry speeds varying between 1.0 to 6.0°/s. Superior-inferior motion of the phantom was executed using a sinusoidal waveform with five second period. Scans were retrospectively sorted into 4 phases (CBCT-4 ph) and 10 phases (CBCT-10 ph); average 4DCBCT (CBCT-ave), using all image data from the 4DCBCT acquisitions was also evaluated. The 4DCBCT images were evaluated using the following image quality metrics: spatial resolution, contrast-to-noise ratio (CNR), and uniformity index (UI). Additionally, Hounsfield unit (HU) sensitivity compared to a baseline CBCT and percent differences and RMS errors (RMSE) of excursion were also determined. Imaging dose was evaluated using an IBA CC13 ion chamber placed within CIRS Thorax phantom using the same sinusoidal motion and image acquisition settings as mentioned above.

Results

Spatial resolution decreased linearly from 5.93 to 3.82 lp/cm as gantry speed increased from 1.0 to 6.0°/s. CNR decreased linearly from 4.80 to 1.82 with gantry speed increasing from 1.0 to 6.0°/s, respectively. No noteworthy variations in UI, HU sensitivity, or excursion metrics were observed with changes in gantry speed. Ion chamber dose rates measured ranged from 2.30 (lung) to 5.18 (bone) E-3 cGy/mAs.

Conclusions

A quantitative analysis of the Varian OBI’s 4DCBCT capabilities was explored. Changing gantry speed changes the number of projections used for reconstruction, affecting both image quality and imaging dose if x-ray tube current is held constant. From the results of this study, a gantry speed between 2 and 3°/s was optimal when considering image quality, dose, and reconstruction time. The future of 4DCBCT clinical utility relies on further investigation of image acquisition and reconstruction optimization.

[Impact of the Infrared Monitor Signal Pattern on Accuracy of Target Imaging in 4-dimensional Cone-beam Computed Tomography]

To realize the high precision radiotherapy, localized radiation field of the moving target is very important, and visualization of a temporal location of the target can help to improve the accuracy of the target localization. However, conditions of the breathing and the patient's own motion differ from the situation of the treatment planning. Therefore, positions of the tumor are affected by these changes. In this study, we implemented a method to reconstruct target motions obtained with the 4D CBCT using the sorted projection data according to the phase and displacement of the extracorporeal infrared monitor signal, and evaluated the proposed method with a moving phantom. In this method, motion cycles and positions of the marker were sorted to reconstruct the image, and evaluated the image quality affected by changes in the cycle, phase, and positions of the marker. As a result, we realized the visualization of the moving target using the sorted projection data according to the infrared monitor signal. This method was based on the projection binning, in which the signal of the infrared monitor was surrogate of the tumor motion. Thus, further major efforts are needed to ensure the accuracy of the infrared monitor signal.

Sensitivity of tumor motion simulation accuracy to lung biomechanical modeling approaches and parameters

Finite element analysis (FEA)-based biomechanical modeling can be used to predict lung respiratory motion. In this technique, elastic models and biomechanical parameters are two important factors that determine modeling accuracy. We systematically evaluated the effects of lung and lung tumor biomechanical modeling approaches and related parameters to improve the accuracy of motion simulation of lung tumor center of mass (TCM) displacements. Experiments were conducted with four-dimensional computed tomography (4D-CT). A Quasi-Newton FEA was performed to simulate lung and related tumor displacements between end-expiration (phase 50%) and other respiration phases (0%, 10%, 20%, 30%, and 40%). Both linear isotropic and non-linear hyperelastic materials, including the neo-Hookean compressible and uncoupled Mooney-Rivlin models, were used to create a finite element model (FEM) of lung and tumors. Lung surface displacement vector fields (SDVFs) were obtained by registering the 50% phase CT to other respiration phases, using the non-rigid demons registration algorithm. The obtained SDVFs were used as lung surface displacement boundary conditions in FEM. The sensitivity of TCM displacement to lung and tumor biomechanical parameters was assessed in eight patients for all three models. Patient-specific optimal parameters were estimated by minimizing the TCM motion simulation errors between phase 50% and phase 0%. The uncoupled Mooney-Rivlin material model showed the highest TCM motion simulation accuracy. The average TCM motion simulation absolute errors for the Mooney-Rivlin material model along left-right, anterior-posterior, and superior-inferior directions were 0.80 mm, 0.86 mm, and 1.51 mm, respectively. The proposed strategy provides a reliable method to estimate patient-specific biomechanical parameters in FEM for lung tumor motion simulation.

Optimization of acquisition parameters and accuracy of target motion trajectory for four-dimensional cone-beam computed tomography with a dynamic thorax phantom

Our purpose in this study was to evaluate the performance of four-dimensional computed tomography (4D-CBCT) and to optimize the acquisition parameters. We evaluated the relationship between the acquisition parameters of 4D-CBCT and the accuracy of the target motion trajectory using a dynamic thorax phantom. The target motion was created three dimensionally using target sizes of 2 and 3 cm, respiratory cycles of 4 and 8 s, and amplitudes of 1 and 2 cm. The 4D-CBCT data were acquired under two detector configurations: "small mode" and "medium mode". The projection data acquired with scan times ranging from 1 to 4 min were sorted into 2, 5, 10, and 15 phase bins. The accuracy of the measured target motion trajectories was evaluated by means of the root mean square error (RMSE) from the setup values. For the respiratory cycle of 4 s, the measured trajectories were within 2 mm of the setup values for all acquisition times and target sizes. Similarly, the errors for the respiratory cycle of 8 s were <4 mm. When we used 10 or more phase bins, the measured trajectory errors were within 2 mm of the setup values. The trajectory errors for the two detector configurations showed similar trends. The acquisition times for achieving an RMSE of 1 mm for target sizes of 2 and 3 cm were 2 and 1 min, respectively, for respiratory cycles of 4 s. The results obtained in this study enable optimization of the acquisition parameters for target size, respiratory cycle, and desired measurement accuracy.