Engineering topics

Kwak, Jungwon

Publications and source records attributed to Kwak, Jungwon.

3 records

DOE OSTI2015

Verification of Accuracy of CyberKnife Tumor-tracking Radiation Therapy Using Patient-specific Lung Phantoms

Purpose: To investigate the accuracy of the CyberKnife Xsight Lung Tracking System (XLTS) compared with that of a fiducial-based target tracking system (FTTS) using patient-specific lung phantoms. Methods and Materials: Three-dimensional printing technology was used to make individualized lung phantoms that closely mimicked the lung anatomy of actual patients. Based on planning computed tomographic data from 6 lung cancer patients who underwent stereotactic ablative radiation therapy using the CyberKnife, the volume above a certain Hounsfield unit (HU) was assigned as the structure to be filled uniformly with polylactic acid material by a 3-dimensional printer (3D Edison, Lokit, Korea). We evaluated the discrepancies between the measured and modeled target positions, representing the total tracking error, using 3 log files that were generated during each treatment for both the FTTS and the XLTS. We also analyzed the γ index between the film dose measured under the FTTS and XLTS. Results: The overall mean values and standard deviations of total tracking errors for the FTTS were 0.36 ± 0.39 mm, 0.15 ± 0.64 mm, and 0.15 ± 0.62 mm for the craniocaudal (CC), left–right (LR), and anteroposterior (AP) components, respectively. Those for the XLTS were 0.38 ± 0.54 mm, 0.13 ± 0.18 mm, and 0.14 ± 0.37 mm for the CC, LR, and AP components, respectively. The average of γ passing rates was 100% for the criteria of 3%, 3 mm; 99.6% for the criteria of 2%, 2 mm; and 86.8% for the criteria of 1%, 1 mm. Conclusions: The XLTS has segmentation accuracy comparable with that of the FTTS and small total tracking errors.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2015

Sparse-view proton computed tomography using modulated proton beams

Purpose: Proton imaging that uses a modulated proton beam and an intensity detector allows a relatively fast image acquisition compared to the imaging approach based on a trajectory tracking detector. In addition, it requires a relatively simple implementation in a conventional proton therapy equipment. The model of geometric straight ray assumed in conventional computed tomography (CT) image reconstruction is however challenged by multiple-Coulomb scattering and energy straggling in the proton imaging. Radiation dose to the patient is another important issue that has to be taken care of for practical applications. In this work, the authors have investigated iterative image reconstructions after a deconvolution of the sparsely view-sampled data to address these issues in proton CT. Methods: Proton projection images were acquired using the modulated proton beams and the EBT2 film as an intensity detector. Four electron-density cylinders representing normal soft tissues and bone were used as imaged object and scanned at 40 views that are equally separated over 360°. Digitized film images were converted to water-equivalent thickness by use of an empirically derived conversion curve. For improving the image quality, a deconvolution-based image deblurring with an empirically acquired point spread function was employed. They have implemented iterative image reconstruction algorithms such as adaptive steepest descent-projection onto convex sets (ASD-POCS), superiorization method–projection onto convex sets (SM-POCS), superiorization method–expectation maximization (SM-EM), and expectation maximization-total variation minimization (EM-TV). Performance of the four image reconstruction algorithms was analyzed and compared quantitatively via contrast-to-noise ratio (CNR) and root-mean-square-error (RMSE). Results: Objects of higher electron density have been reconstructed more accurately than those of lower density objects. The bone, for example, has been reconstructed within 1% error. EM-based algorithms produced an increased image noise and RMSE as the iteration reaches about 20, while the POCS-based algorithms showed a monotonic convergence with iterations. The ASD-POCS algorithm outperformed the others in terms of CNR, RMSE, and the accuracy of the reconstructed relative stopping power in the region of lung and soft tissues. Conclusions: The four iterative algorithms, i.e., ASD-POCS, SM-POCS, SM-EM, and EM-TV, have been developed and applied for proton CT image reconstruction. Although it still seems that the images need to be improved for practical applications to the treatment planning, proton CT imaging by use of the modulated beams in sparse-view sampling has demonstrated its feasibility.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2011

Proton Range Uncertainty Due to Bone Cement Injected Into the Vertebra in Radiation Therapy Planning

We wanted to evaluate the influence of bone cement on the proton range and to derive a conversion factor predicting the range shift by correcting distorted computed tomography (CT) data as a reference to determine whether the correction is needed. Two CT datasets were obtained with and without a bone cement disk placed in a water phantom. Treatment planning was performed on a set of uncorrected CT images with the bone cement disk, and the verification plan was applied to the same set of CT images with an effective CT number for the bone cement disk. The effective CT number was determined by measuring the actual proton range with the bone cement disk. The effects of CT number, thicknesses, and position of bone cement on the proton range were evaluated in the treatment planning system (TPS) to draw a conversion factor predicting the range shift by correcting the CT number of bone cement. The effective CT number of bone cement was 260 Hounsfield units (HU). The calculated proton range for native CT data was significantly shorter than the measured proton range. However, the calculated range for the corrected CT data with the effective CT number coincided exactly with the measured range. The conversion factor was 209.6 [HU . cm/mm] for bone cement and predicted the range shift by approximately correcting the CT number. We found that the heterogeneity of bone cement could cause incorrect proton ranges in treatment plans using CT images. With an effective CT number of bone cement derived from the proton range and relative stopping power, a more actual proton range could be calculated in the TPS. The conversion factor could predict the necessity for CT data correction with sufficient accuracy.

61 RADIATION PROTECTION AND DOSIMETRY↗