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Title: WE-AB-BRA-08: Correction of Patient Motion in C-Arm Cone-Beam CT Using 3D-2D Registration

Abstract

Purpose: Intraoperative C-arm cone-beam CT (CBCT) is subject to artifacts arising from patient motion during the fairly long (∼5–20 s) scan times. We present a fiducial free method to mitigate motion artifacts using 3D-2D image registration that simultaneously corrects residual errors in geometric calibration. Methods: A 3D-2D registration process was used to register each projection to DRRs computed from the 3D image by maximizing gradient orientation (GO) using the CMA-ES optimizer. The resulting rigid 6 DOF transforms were applied to the system projection matrices, and a 3D image was reconstructed via model-based image reconstruction (MBIR, which accommodates the resulting noncircular orbit). Experiments were conducted using a Zeego robotic C-arm (20 s, 200°, 496 projections) to image a head phantom undergoing various types of motion: 1) 5° lateral motion; 2) 15° lateral motion; and 3) 5° lateral motion with 10 mm periodic inferior-superior motion. Images were reconstructed using a penalized likelihood (PL) objective function, and structural similarity (SSIM) was measured for axial slices of the reconstructed images. A motion-free image was acquired using the same protocol for comparison. Results: There was significant improvement (p < 0.001) in the SSIM of the motion-corrected (MC) images compared to uncorrected images. The SSIM inmore » MC-PL images was >0.99, indicating near identity to the motion-free reference. The point spread function (PSF) measured from a wire in the phantom was restored to that of the reference in each case. Conclusion: The 3D-2D registration method provides a robust framework for mitigation of motion artifacts and is expected to hold for applications in the head, pelvis, and extremities with reasonably constrained operative setup. Further improvement can be achieved by incorporating multiple rigid components and non-rigid deformation within the framework. The method is highly parallelizable and could in principle be run with every acquisition. Research supported by National Institutes of Health Grant No. R01-EB-017226 and academic-industry partnership with Siemens Healthcare (AX Division, Forcheim, Germany).« less

Authors:
; ; ;  [1];  [2]
  1. Johns Hopkins University, Baltimore, MD (United States)
  2. Siemens Medical Solutions USA, Inc., Hoffman Estates, IL (United States)
Publication Date:
OSTI Identifier:
22654098
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; COMPUTERIZED TOMOGRAPHY; CORRECTIONS; FEDERAL REPUBLIC OF GERMANY; IMAGE PROCESSING; PATIENTS

Citation Formats

Ouadah, S, Jacobson, M, Stayman, JW, Siewerdsen, JH, and Ehtiati, T. WE-AB-BRA-08: Correction of Patient Motion in C-Arm Cone-Beam CT Using 3D-2D Registration. United States: N. p., 2016. Web. doi:10.1118/1.4957737.
Ouadah, S, Jacobson, M, Stayman, JW, Siewerdsen, JH, & Ehtiati, T. WE-AB-BRA-08: Correction of Patient Motion in C-Arm Cone-Beam CT Using 3D-2D Registration. United States. doi:10.1118/1.4957737.
Ouadah, S, Jacobson, M, Stayman, JW, Siewerdsen, JH, and Ehtiati, T. 2016. "WE-AB-BRA-08: Correction of Patient Motion in C-Arm Cone-Beam CT Using 3D-2D Registration". United States. doi:10.1118/1.4957737.
@article{osti_22654098,
title = {WE-AB-BRA-08: Correction of Patient Motion in C-Arm Cone-Beam CT Using 3D-2D Registration},
author = {Ouadah, S and Jacobson, M and Stayman, JW and Siewerdsen, JH and Ehtiati, T},
abstractNote = {Purpose: Intraoperative C-arm cone-beam CT (CBCT) is subject to artifacts arising from patient motion during the fairly long (∼5–20 s) scan times. We present a fiducial free method to mitigate motion artifacts using 3D-2D image registration that simultaneously corrects residual errors in geometric calibration. Methods: A 3D-2D registration process was used to register each projection to DRRs computed from the 3D image by maximizing gradient orientation (GO) using the CMA-ES optimizer. The resulting rigid 6 DOF transforms were applied to the system projection matrices, and a 3D image was reconstructed via model-based image reconstruction (MBIR, which accommodates the resulting noncircular orbit). Experiments were conducted using a Zeego robotic C-arm (20 s, 200°, 496 projections) to image a head phantom undergoing various types of motion: 1) 5° lateral motion; 2) 15° lateral motion; and 3) 5° lateral motion with 10 mm periodic inferior-superior motion. Images were reconstructed using a penalized likelihood (PL) objective function, and structural similarity (SSIM) was measured for axial slices of the reconstructed images. A motion-free image was acquired using the same protocol for comparison. Results: There was significant improvement (p < 0.001) in the SSIM of the motion-corrected (MC) images compared to uncorrected images. The SSIM in MC-PL images was >0.99, indicating near identity to the motion-free reference. The point spread function (PSF) measured from a wire in the phantom was restored to that of the reference in each case. Conclusion: The 3D-2D registration method provides a robust framework for mitigation of motion artifacts and is expected to hold for applications in the head, pelvis, and extremities with reasonably constrained operative setup. Further improvement can be achieved by incorporating multiple rigid components and non-rigid deformation within the framework. The method is highly parallelizable and could in principle be run with every acquisition. Research supported by National Institutes of Health Grant No. R01-EB-017226 and academic-industry partnership with Siemens Healthcare (AX Division, Forcheim, Germany).},
doi = {10.1118/1.4957737},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: To balance dose reduction and image registration accuracy in breast setup imaging. In particular, the authors demonstrate the relationship between scan angle and dose delivery for cone beam tomosynthesis (CBTS) when employed for setup verification of breast cancer patients with surgical clips. Methods: The dose measurements were performed in a female torso phantom for varying scan angles of CBTS. Setup accuracy was measured using three registration methods: Clip centroid localization accuracy and the accuracy of two semiautomatic registration algorithms. The dose to the organs outside of the ipsilateral breast and registration accuracy information were compared to determine the optimalmore » scan angle for CBTS for breast patient setup verification. Isocenter positions at the center of the patient and at the breast-chest wall interface were considered. Results: Image registration accuracy was within 1 mm for the CBTS scan angles {theta} above 20 deg. for some scenarios and as large as 80 deg. for the worst case, depending on the imaged breast and registration algorithm. Registration accuracy was highest based on clip centroid localization. For left and right breast imaging with the isocenter at the chest wall, the dose to the contralateral side of the patient was very low (<0.5 cGy) for all scan angles considered. For central isocenter location, the optimal scan angles were 30 deg. - 50 deg. for the left breast imaging and 40 deg. - 50 deg. for the right breast imaging, with the difference due to the geometric asymmetry of the current clinical imaging system. Conclusions: The optimal scan angles for CBTS imaging were found to be between 10 deg. and 50 deg., depending on the isocenter location and ipsilateral breast. Use of the isocenter at the breast-chest wall locations always resulted in greater accuracy of image registration (<1 mm) at smaller angles (10 deg. - 20 deg.) and at lower doses (<0.1 cGy) to the contralateral organs. For chest wall isocenters, doses delivered to organs outside of the target breast were much smaller than the scattered and leakage doses of the treatment beams. The complete volumetric information of all clips in the region of interest, combined with the small dose to the contralateral organs and the small scan angle, could result in an advantage for small angle CBTS with off center isocenters over simple orthogonal pairs.« less
  • Purpose: To quantify the difference in isocenter shifts when co-registering MR and MR-based pseudo CTs (pCT) with on-board megavoltage conebeam CT (CBCT) images. Methods: Fast Spoiled Gradient Echo MRs were used to generate pCTs (research version of Advantage Sim MD™, GE Healthcare) for ten patients who had prior brain radiotherapy. The planning CT (rCT) for each was co-registered with the MR, and the plan isocenter and two other reference points were transferred to the MR and pCT. CBCT images (with the machine isocenter) from a single treatment day were coregistered with the 3 test images (MR, pCT and rCT), bymore » two observers and by an automated registration algorithm. The reference points were used to calculate patient shifts and rotations from the registrations. The shifts calculated from the test image registrations were compared to each other and to the shifts performed by the therapists who treated the patients on that day. Results: The average difference in absolute value between the isocenter shifts from the MR-, pCT- and rCT-CBCT registrations, and the therapist shifts, were 2.02, 3.01 and 0.89 mm (craniocaudal), 1.14, 1.34 and 0.46 mm (lateral), and 1.37, 3.43 and 1.43 mm (vertical), respectively. The MR- and pCT-CBCT registrations differed by 1.99, and 2.53 mm (craniocaudal), 1.36, and 1.37 mm (lateral), and 0.74 and 2.34 mm (vertical), respectively, from the average rCT-CBCT shifts. On average, differences of 2.39 (craniocaudal), 1.28 (lateral) and 2.84 mm (vertical) were seen between the MR and pCT shifts. Rotations relative to the CBCT coordinate system were on average <2° for the MR and rCT, and <6° for the pCT. Conclusion: In this study, FSPGR MR-CBCT registrations were more precise compared to the pCT-CBCT registrations. For improved accuracy, MR sequences that are optimal for bony anatomy visualization are necessary. GE healthcare has provided a research version of Advantage Sim MD to UCSF. No financial support was provided.« less
  • Purpose: To estimate the dose distributions delivered to the patient in each treatment fraction using deformable image registration (DIR) and assess the radiobiological impact of the inter-fraction variations due to patient deformation and setup. Methods: The work is based on the cone beam CT (CBCT) images and treatment plans of two lung cancer patients. Both patients were treated with intensity modulated radiation therapy (IMRT) to 66Gy in 2Gy/fraction. The treatment plans were exported from the treatment planning system (TPS) to the Velocity AI where DIR was performed and the same deformation matrix was used for the deformation of the plannedmore » dose distribution and organ contours to each CBCT dataset. A radiobiological analysis was performed based on the radiobiological parameters of the involved organs at risk (OARs) and planning target volume (PTV). Using the complication free tumor control probability (P+) index, differences in P+ were observed between each CBCT as well as between CBCT and planning dose distributions. Results: The optimal CBCT P? values ranged from 91.6 % to 94.8 % for patient #1 and from 88.8 % to 90.6 % for patient #2. At the dose level of the clinical prescription, the CBCT P+ values ranged from 80.3% to 80.7% for patient #1 and from 80.7% to 81.0% for the patient #2. The planning CT P+ values were 81.0% and 80.7% for the two patients, respectively. These differences emphasize the significance of using the radiobiological analysis when assessing changes in the dose distribution due to the tumor motion and lung deformations. Conclusion: Daily setup variations yield to differences in the actual dose delivered versus the planned one. The observed differences were rather small when only looking at the dosimetric comparison of the dose distributions, however the radiobiology analysis was able to detect clinically relevant differences among the studied dose distributions.« less
  • Purpose: In image-guided radiotherapy, an artifact typically seen in axial slices of x-ray cone-beam computed tomography (CBCT) reconstructions is a dark region or ''black hole'' situated below the scan isocenter. The authors trace the cause of the artifact to scattered radiation produced by radiotherapy patient tabletops and show it is linked to the use of the offset-detector acquisition mode to enlarge the imaging field-of-view. The authors present a hybrid scatter kernel superposition (SKS) algorithm to correct for scatter from both the object-of-interest and the tabletop. Methods: Monte Carlo simulations and phantom experiments were first performed to identify the source ofmore » the black hole artifact. For correction, a SKS algorithm was developed that uses separate kernels to estimate scatter from the patient tabletop and the object-of-interest. Each projection is divided into two regions, one defined by the shadow cast by the tabletop on the imager and one defined by the unshadowed region. The region not shadowed by the tabletop is processed using the recently developed fast adaptive scatter kernel superposition (fASKS) method which employs asymmetric kernels that best model scatter transport through bodylike objects. The shadowed region is convolved with a combination of slab-derived symmetric SKS kernels and asymmetric fASKS kernels. The composition of the hybrid kernels is projection-angle-dependent. To test the algorithm, pelvis phantom and in vivo data were acquired using a CBCT test stand, a Varian Acuity simulator, and a Varian On-Board Imager, all of which have similar geometries and components. Artifact intensities and Hounsfield unit (HU) accuracies in the reconstructions were assessed before and after the correction. Results: The hybrid kernel algorithm provided effective correction and produced substantially better scatter estimates than the symmetric SKS or asymmetric fASKS methods alone. HU nonuniformities in the reconstructed pelvis phantom were reduced from 220 to 50 HU (i.e., 22%-5%). In the in vivo scans, the black hole artifact was reduced by up to 147 HU, a 73% improvement, and anatomical details in the prostate and rectum areas were made considerably more visible. Conclusions: Radiotherapy tabletops, which are generally flatter and larger than those used for diagnostic CT, can produce significant scatter-related artifacts. The proposed hybrid SKS algorithm accurately estimates scatter from both the object-of-interest and the patient tabletop, and resulting image uniformities and HU accuracies are greatly improved.« less
  • Purpose: To study the variability of patient-specific motion models derived from 4-dimensional CT (4DCT) images using different deformable image registration (DIR) algorithms for lung cancer stereotactic body radiotherapy (SBRT) patients. Methods: Motion models are derived by 1) applying DIR between each 4DCT image and a reference image, resulting in a set of displacement vector fields (DVFs), and 2) performing principal component analysis (PCA) on the DVFs, resulting in a motion model (a set of eigenvectors capturing the variations in the DVFs). Three DIR algorithms were used: 1) Demons, 2) Horn-Schunck, and 3) iterative optical flow. The motion models derived weremore » compared using patient 4DCT scans. Results: Motion models were derived and the variations were evaluated according to three criteria: 1) the average root mean square (RMS) difference which measures the absolute difference between the components of the eigenvectors, 2) the dot product between the eigenvectors which measures the angular difference between the eigenvectors in space, and 3) the Euclidean Model Norm (EMN), which is calculated by summing the dot products of an eigenvector with the first three eigenvectors from the reference motion model in quadrature. EMN measures how well an eigenvector can be reconstructed using another motion model derived using a different DIR algorithm. Results showed that comparing to a reference motion model (derived using the Demons algorithm), the eigenvectors of the motion model derived using the iterative optical flow algorithm has smaller RMS, larger dot product, and larger EMN values than those of the motion model derived using Horn-Schunck algorithm. Conclusion: The study showed that motion models vary depending on which DIR algorithms were used to derive them. The choice of a DIR algorithm may affect the accuracy of the resulting model, and it is important to assess the suitability of the algorithm chosen for a particular application. This project was supported, in part, through a Master Research Agreement with Varian Medical Systems, Inc, Palo Alto, CA.« less