Engineering topics

Cai, W

Publications and source records attributed to Cai, W.

7 records

DOE OSTI2016

SU-C-209-02: 3D Fluoroscopic Image Generation From Patient-Specific 4DCBCT-Based Motion Models Derived From Clinical Patient Images

Purpose: We develop a method to generate time varying volumetric images (3D fluoroscopic images) using patient-specific motion models derived from four-dimensional cone-beam CT (4DCBCT). Methods: Motion models are derived by selecting one 4DCBCT phase as a reference image, and registering the remaining images to it. Principal component analysis (PCA) is performed on the resultant displacement vector fields (DVFs) to create a reduced set of PCA eigenvectors that capture the majority of respiratory motion. 3D fluoroscopic images are generated by optimizing the weights of the PCA eigenvectors iteratively through comparison of measured cone-beam projections and simulated projections generated from the motion model. This method was applied to images from five lung-cancer patients. The spatial accuracy of this method is evaluated by comparing landmark positions in the 3D fluoroscopic images to manually defined ground truth positions in the patient cone-beam projections. Results: 4DCBCT motion models were shown to accurately generate 3D fluoroscopic images when the patient cone-beam projections contained clearly visible structures moving with respiration (e.g., the diaphragm). When no moving anatomical structure was clearly visible in the projections, the 3D fluoroscopic images generated did not capture breathing deformations, and reverted to the reference image. For the subset of 3D fluoroscopic images generated from projections with visibly moving anatomy, the average tumor localization error and the 95th percentile were 1.6 mm and 3.1 mm respectively. Conclusion: This study showed that 4DCBCT-based 3D fluoroscopic images can accurately capture respiratory deformations in a patient dataset, so long as the cone-beam projections used contain visible structures that move with respiration. For clinical implementation of 3D fluoroscopic imaging for treatment verification, an imaging field of view (FOV) that contains visible structures moving with respiration should be selected. If no other appropriate structures are visible, the images should include the diaphragm. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc, Palo Alto, CA.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-T-410: Investigation of Treatment Planning Accuracy with the Presence of Magnetic Injection Port (breast Tissue Expander)

Purpose: Mastectomy patients with breast reconstruction usually have a magnetic injection port inside the breast during radiation treatments. The magnet has a very high CT number and produces severe streaking artifact across the entire breast in CT images. Our routine strategy is to replace the artifact volumes with uniform water, and it is necessary to validate that the planned dose, with such an artifact correction, is sufficiently accurate. Methods: A phantom was made with a gelatine-filled container sitting on a Matrixx detector, and the magnetic port was inserted into gelatine with specific depths and orientations. The phantom was scanned on a CT simulator and imported into Eclipse for treatment planning. The dose distribution at the Matrixx detector plane was calculated for raw CT images and artifact-corrected images. The treatment beams were then delivered to the phantom and the dose distributions were acquired by the Matrixx detector. Gamma index was calculated to compare the planned dose and the measurement. Results: Three field sizes (10×10, 15×15 and 20×20) and two depths (50mm and 20mm) were investigated. With the 2%/2mm or 3%/3mm criteria, several points (6–10) failed in the plan for raw CT images, and the number of failure was reduced close to zero for the corrected CT images. An assignment of 10,000 HU to the magnet further reduced the dose error directly under the magnet. Conclusion: It is validated that our routine strategy of artifact correction can effectively reduce the number of failures in the detector plane. It is also recommended to set the magnet with a CT number of 10,000HU, which could potentially improve the dose calculation at the points right behind the magnet.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-EF-207A-02: Imaging Pancreatic Î{sup 2}-Cell Function with 51/52Mn-PET

Purpose: To image β-cells noninvasively using radio-manganese PET and to develop efficient small cyclotron production of {sup 51}Mn (t1/2=46m, β{sup +}=97%) and {sup 52}Mn (t1/2=5.6d, β{sup +}=29%). Methods: {sup 51}Mn and {sup 52}Mn were produced by 16 MeV proton irradiation (GE PETtrace) of electrodeposited {sup 54}Fe on silver and Cr metal pressed into a silver disc, respectively. {sup 51}Mn was radiochemically isolated from target material by anion exchange chromatography and {sup 52}Mn was isolated by ethanolic anion exchange trap-and-release. A final injectable product of {sup 51}Mn{sup 2+} or {sup 52}Mn{sup 2+} was obtained in 0.01M pH 6.0 NaOAc. To assess pancreatic uptake, fasted ICR mice were administered and intravenous bolus or infusion of {sup 52}Mn{sup 2+}. Additionally, to demonstrate the correlation between β-cell function and {sup 52}Mn{sup 2+} pancreatic uptake, prior to tracer administration groups of ICR mice were administered glibenclamide (5mg/kg) and diazoxide (20 mg/kg) as an insulin release stimulator and blocker, respectively. To validate PET ROI quantification, ex vivo biodistribtution studies were conducted on each subject after the final imaging time-point. Results: Dynamic PET data using a left atrium ROI revealed that {sup 52}Mn{sup 2+} cleared from the blood with a 10 second half-life. Significant uptake was seen in the pancreas (approximately 20% ID/g, SUVmean= 5.5), liver, kidneys, intestine, heart, and thyroid. Pancreatic uptake was found to be highly sensitive to volatile anesthesia administration (p=0.0002), insulin release stimulation by glibenclamide (p=0.017), and by insulin release inhibition by diazoxide (p=0.046). Excellent agreement was found between in vivo PET ROI quantification and ex vivo biodistribution measurements. Conclusion: This work demonstrates the feasibility of using radiomanganese-PET for measuring functional β-cell mass in vivo. The decay characteristics and dosimetric properties of {sup 51}Mn are well suited for clinical PET, which will allow for rapid translation and application.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-P-59: A Graphical Interface for XCAT Phantom Configuration, Generation and Processing

Purpose: To design a comprehensive open-source, publicly available, graphical user interface (GUI) to facilitate the configuration, generation, processing and use of the 4D Extended Cardiac-Torso (XCAT) phantom. Methods: The XCAT phantom includes over 9000 anatomical objects as well as respiratory, cardiac and tumor motion. It is widely used for research studies in medical imaging and radiotherapy. The phantom generation process involves the configuration of a text script to parameterize the geometry, motion, and composition of the whole body and objects within it, and to generate simulated PET or CT images. To avoid the need for manual editing or script writing, our MATLAB-based GUI uses slider controls, drop-down lists, buttons and graphical text input to parameterize and process the phantom. Results: Our GUI can be used to: a) generate parameter files; b) generate the voxelized phantom; c) combine the phantom with a lesion; d) display the phantom; e) produce average and maximum intensity images from the phantom output files; f) incorporate irregular patient breathing patterns; and f) generate DICOM files containing phantom images. The GUI provides local help information using tool-tip strings on the currently selected phantom, minimizing the need for external documentation. The DICOM generation feature is intended to simplify the process of importing the phantom images into radiotherapy treatment planning systems or other clinical software. Conclusion: The GUI simplifies and automates the use of the XCAT phantom for imaging-based research projects in medical imaging or radiotherapy. This has the potential to accelerate research conducted with the XCAT phantom, or to ease the learning curve for new users. This tool does not include the XCAT phantom software itself. We would like to acknowledge funding from MRA, Varian Medical Systems Inc.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-151: Day-To-Day Variations in Fraction-Specific Motion Modeling Using Patient 4DCBCT Images

Purpose: The goal of this study is to quantify the interfraction reproducibility of patient-specific motion models derived from 4DCBCT acquired on the day of treatment of lung cancer stereotactic body radiotherapy (SBRT) patients. Methods: Motion models are derived from patient 4DCBCT images acquired daily over 3–5 fractions of treatment by 1) applying deformable image registration between each 4DCBCT image and a reference phase from that day, resulting in a set of displacement vector fields (DVFs), and 2) performing principal component analysis (PCA) on the DVFs to derive a motion model. The motion model from the first day of treatment is compared to motion models from each successive day of treatment to quantify variability in motion models generated from different days. Four SBRT patient datasets have been acquired thus far in this IRB approved study. Results: Fraction-specific motion models for each fraction and patient were derived and PCA eigenvectors and their associated eigenvalues are compared for each fraction. For the first patient dataset, the average root mean square error between the first two eigenvectors associated with the highest two eigenvalues, in four fractions was 0.1, while it was 0.25 between the last three PCA eigenvectors associated with the lowest three eigenvalues. It was found that the eigenvectors and eigenvalues of PCA motion models for each treatment fraction have variations and the first few eigenvectors are shown to be more stable across treatment fractions than others. Conclusion: Analysis of this dataset showed that the first two eigenvectors of the PCA patient-specific motion models derived from 4DCBCT were stable over the course of several treatment fractions. The third, fourth, and fifth eigenvectors had larger variations.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-186: Using 4DCT-Based Motion Modeling to Predict Motion and Duty Cycle On Successive Days of Gated Radiotherapy

Purpose: To determine if 4DCT-based motion modeling and external surrogate motion measured during treatment simulation can enhance prediction of residual tumor motion and duty cycle during treatment delivery. Methods: This experiment was conducted using simultaneously recorded tumor and external surrogate motion acquired over multiple fractions of lung cancer radiotherapy. These breathing traces were combined with the XCAT phantom to simulate CT images. Data from the first day was used to estimate the residual tumor motion and duty cycle both directly from the 4DCT (the current clinical standard), and from external-surrogate based motion modeling. The accuracy of these estimated residual tumor motions and duty cycles are evaluated by comparing to the measured internal/external motions from other treatment days. Results: All calculations were done for 25% and 50% duty cycles. The results indicated that duty cycle derived from 4DCT information alone is not enough to accurately predict duty cycles during treatment. Residual tumor motion was determined from the recorded data and compared with the estimated residual tumor motion from 4DCT. Relative differences in residual tumor motion varied from −30% to 55%, suggesting that more information is required to properly predict residual tumor motion. Compared to estimations made from 4DCT, in three out of four patients examined, the 30 seconds of motion modeling data was able to predict the duty cycle with better accuracy than 4DCT. No improvement was observed in prediction of residual tumor motion for this dataset. Conclusion: Motion modeling during simulation has the potential to enhance 4DCT and provide more information about target motion, duty cycles, and delivered dose. Based on these four patients, 30 seconds of motion modeling data produced improve duty cycle estimations but showed no measurable improvement in residual tumor motion prediction. More patient data is needed to verify this Result. I would like to acknowledge funding from MRA, VARIAN Medical Systems, Inc.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-G-207-06: 3D Fluoroscopic Image Generation From Patient-Specific 4DCBCT-Based Motion Models Derived From Physical Phantom and Clinical Patient Images

Purpose: Respiratory-correlated cone-beam CT (4DCBCT) images acquired immediately prior to treatment have the potential to represent patient motion patterns and anatomy during treatment, including both intra- and inter-fractional changes. We develop a method to generate patient-specific motion models based on 4DCBCT images acquired with existing clinical equipment and used to generate time varying volumetric images (3D fluoroscopic images) representing motion during treatment delivery. Methods: Motion models are derived by deformably registering each 4DCBCT phase to a reference phase, and performing principal component analysis (PCA) on the resulting displacement vector fields. 3D fluoroscopic images are estimated by optimizing the resulting PCA coefficients iteratively through comparison of the cone-beam projections simulating kV treatment imaging and digitally reconstructed radiographs generated from the motion model. Patient and physical phantom datasets are used to evaluate the method in terms of tumor localization error compared to manually defined ground truth positions. Results: 4DCBCT-based motion models were derived and used to generate 3D fluoroscopic images at treatment time. For the patient datasets, the average tumor localization error and the 95th percentile were 1.57 and 3.13 respectively in subsets of four patient datasets. For the physical phantom datasets, the average tumor localization error and the 95th percentile were 1.14 and 2.78 respectively in two datasets. 4DCBCT motion models are shown to perform well in the context of generating 3D fluoroscopic images due to their ability to reproduce anatomical changes at treatment time. Conclusion: This study showed the feasibility of deriving 4DCBCT-based motion models and using them to generate 3D fluoroscopic images at treatment time in real clinical settings. 4DCBCT-based motion models were found to account for the 3D non-rigid motion of the patient anatomy during treatment and have the potential to localize tumor and other patient anatomical structures at treatment time even when inter-fractional changes occur. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc., Palo Alto, CA. The project was also supported, in part, by Award Number R21CA156068 from the National Cancer Institute.

60 APPLIED LIFE SCIENCES↗