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Title: SU-F-J-117: Impact of Motion Artifacts On Image Quality and Accuracy of Tumor Motion Reconstruction in 4D CT-On-Rails and MV-CBCT Scans: A Phantom Study

Abstract

Purpose: To compare and quantify respiratory motion artifacts in images from free breathing 4D-CT-on-Rails(CTOR) and those from MV-Cone-beam-CT(MVCB) and facilitate respiratory motion guided radiation therapy. Methods: 4D-CTOR: Siemens Somatom CT-on-Rails system with Anzai belt loaded with pressure sensor load cells. 4D scans were performed in helical mode, pitch 0.1, gantry rotation time 0.5s, 1.5mm slice thickness, 120kVp, 400 mAs. Normal and fast breathing (>12rpm) scanning protocols were investigated. Helical scan, AIP(average intensity projection) and MIP(maximum intensity projection) were generated from 4D-CTOR scans with amplitude sorting into 10 phases.MVCB: Siemens Artiste diamond view(1MV)MVCB was performed with 5MU thorax protocol with 60 second of full rotation.Phantom: Anzai AZ-733V respiratory phantom. The settings were set to normal and resp. modes with repetition rates at 15 rpm and 10 rpm. Surgical clips, acrylic, wooden, rubber and lung density, total six mock-ups were scanned and compared in this study.Signal-to-noise ratio(SNR), contrast-to-noise ratio(CNR) and reconstructed motion volume were compared to different respiratory setups for the mock-ups. Results: Reconstructed motion volume was compared to the real object volume for the six test mock-ups. It shows that free breathing helical in all instances underestimates the object excursions largest to −67.4% and least −6.3%. Under normal breathing settings, MIPmore » can predict very precise motion volume with minimum 0.4% and largest −13.9%. MVCB shows underestimate of the motion volume with −1.11% minimum and −18.0% maximum. With fast breathing, AIP provides bad representation of the object motion; however, the MIP can predict the motion volume with −2.0% to −11.4% underestimate. Conclusion: Respiratory motion guided radiation therapy requires good motion recording. This study shows that regular CTOR helical scans provides bad guidance, 4D CTOR AIP cannot represent the fast breathing pattern, MIP can represent the best motion volume, MVCBCT can only be used for normal breathing with acceptable uncertainties.« less

Authors:
;  [1]
  1. Fox Chase Cancer Center, Philadelphia, PA (United States)
Publication Date:
OSTI Identifier:
22634724
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; ACCURACY; CHEST; COMPUTERIZED TOMOGRAPHY; IMAGES; LUNGS; NEOPLASMS; NOISE; PHANTOMS; RADIOTHERAPY; RESPIRATION; SIGNAL-TO-NOISE RATIO; SURGERY; THICKNESS

Citation Formats

Lin, T, and Ma, C. SU-F-J-117: Impact of Motion Artifacts On Image Quality and Accuracy of Tumor Motion Reconstruction in 4D CT-On-Rails and MV-CBCT Scans: A Phantom Study. United States: N. p., 2016. Web. doi:10.1118/1.4956025.
Lin, T, & Ma, C. SU-F-J-117: Impact of Motion Artifacts On Image Quality and Accuracy of Tumor Motion Reconstruction in 4D CT-On-Rails and MV-CBCT Scans: A Phantom Study. United States. doi:10.1118/1.4956025.
Lin, T, and Ma, C. 2016. "SU-F-J-117: Impact of Motion Artifacts On Image Quality and Accuracy of Tumor Motion Reconstruction in 4D CT-On-Rails and MV-CBCT Scans: A Phantom Study". United States. doi:10.1118/1.4956025.
@article{osti_22634724,
title = {SU-F-J-117: Impact of Motion Artifacts On Image Quality and Accuracy of Tumor Motion Reconstruction in 4D CT-On-Rails and MV-CBCT Scans: A Phantom Study},
author = {Lin, T and Ma, C},
abstractNote = {Purpose: To compare and quantify respiratory motion artifacts in images from free breathing 4D-CT-on-Rails(CTOR) and those from MV-Cone-beam-CT(MVCB) and facilitate respiratory motion guided radiation therapy. Methods: 4D-CTOR: Siemens Somatom CT-on-Rails system with Anzai belt loaded with pressure sensor load cells. 4D scans were performed in helical mode, pitch 0.1, gantry rotation time 0.5s, 1.5mm slice thickness, 120kVp, 400 mAs. Normal and fast breathing (>12rpm) scanning protocols were investigated. Helical scan, AIP(average intensity projection) and MIP(maximum intensity projection) were generated from 4D-CTOR scans with amplitude sorting into 10 phases.MVCB: Siemens Artiste diamond view(1MV)MVCB was performed with 5MU thorax protocol with 60 second of full rotation.Phantom: Anzai AZ-733V respiratory phantom. The settings were set to normal and resp. modes with repetition rates at 15 rpm and 10 rpm. Surgical clips, acrylic, wooden, rubber and lung density, total six mock-ups were scanned and compared in this study.Signal-to-noise ratio(SNR), contrast-to-noise ratio(CNR) and reconstructed motion volume were compared to different respiratory setups for the mock-ups. Results: Reconstructed motion volume was compared to the real object volume for the six test mock-ups. It shows that free breathing helical in all instances underestimates the object excursions largest to −67.4% and least −6.3%. Under normal breathing settings, MIP can predict very precise motion volume with minimum 0.4% and largest −13.9%. MVCB shows underestimate of the motion volume with −1.11% minimum and −18.0% maximum. With fast breathing, AIP provides bad representation of the object motion; however, the MIP can predict the motion volume with −2.0% to −11.4% underestimate. Conclusion: Respiratory motion guided radiation therapy requires good motion recording. This study shows that regular CTOR helical scans provides bad guidance, 4D CTOR AIP cannot represent the fast breathing pattern, MIP can represent the best motion volume, MVCBCT can only be used for normal breathing with acceptable uncertainties.},
doi = {10.1118/1.4956025},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: To investigate the effects of scanning parameters and respiratory patterns on the image quality for 4-dimensional cone-beam computed tomography(4D-CBCT) imaging, and assess the accuracy of computed tumor trajectory for lung imaging using registration of phased 4D-CBCT imaging with treatment planning-CT. Methods: We simulated a periodic and non-sinusoidal respirations with various breathing periods and amplitudes using a respiratory phantom(Quasar, Modus Medical Devices Inc) to acquire respiration-correlated 4D-CBCT images. 4D-CBCT scans(Elekta Oncology Systems Ltd) were performed with different scanning parameters for collimation size(e.g., small and medium field-of-views) and scanning speed(e.g., slow 50°·min{sup −1}, fast 100°·min{sup −1}). Using a standard CBCT-QA phantom(Catphan500,more » The Phantom Laboratory), the image qualities of all phases in 4D-CBCT were evaluated with contrast-to-noise ratio(CNR) for lung tissue and uniformity in each module. Using a respiratory phantom, the target imaging in 4D-CBCT was compared to 3D-CBCT target image. The target trajectory from 10-respiratory phases in 4D-CBCT was extracted using an automatic image registration and subsequently assessed the accuracy by comparing with actual motion of the target. Results: Image analysis indicated that a short respiration with a small amplitude resulted in superior CNR and uniformity. Smaller variation of CNR and uniformity was present amongst different respiratory phases. The small field-of-view with a partial scan using slow scan can improve CNR, but degraded uniformity. Large amplitude of respiration can degrade image quality. RMS of voxel densities in tumor area of 4D-CBCT images between sinusoidal and non-sinusoidal motion exhibited no significant difference. The maximum displacement errors of motion trajectories were less than 1.0 mm and 13.5 mm, for sinusoidal and non-sinusoidal breathings, respectively. The accuracy of motion reconstruction showed good overall agreement with the 4D-CBCT image quality results only using sinusoidal breathings. Conclusion: This information can be used to determine the appropriate acquisition parameters of 4D-CBCT imaging for registration accuracy and target trajectory measurements in a clinical setting.« less
  • Purpose: SymmetryTM 4D IGRT system of Elekta has been installed at our institution, which offers the 4D CBCT registration option. This study is to evaluate the accuracy of 4D CBCT system by using the CIRS 4D motion phantom and to perform a feasibility study on the implementation of 4D-CBCT as image guidance for SBRT treatment. Methods: The 3D and 4D CT image data sets are acquired using the CIRS motion phantom on a Philips large bore CT simulator. The motion was set as 0.5 cm superior and inferior directions with 6 seconds recycle time. The 4D CT data were sortedmore » as 10 phases. One identifiable part of the 4D CT QA insert from CIRS phantom was used as the target. The ITV MIP was drawn based on maximum intensity projection (MIP) and transferred as a planning structure into 4D CBCT system. Then the 3D CBCT and 4D CBCT images were taken and registered with the free breath (3D), MIP (4D) and average intensity projection (AIP)(4D) reference data sets. The couch shifts (X, Y, Z) are recorded and compared. Results: Table 1 listed the twelve couch shifts based on the registration of MIP, AIP and free breath CT data sets with 3D CBCT and 4D CBCT for both whole body and local registration. X, Y and Z represent couch shifts in the direction of the right-left, superior-inferior and anterior-posterior. The biggest differences of 0.73 cm and 0.57 cm are noted in the free breath CT data with 4D CBCT and 3D CBCT data registration. Fig. 1 and Fig. 2 are the shift analysis in diagram. Fig. 3 shows the registration. Conclusion: Significant differences exist in the shifts corresponding with the direction of target motion. Further investigations are ongoing.« less
  • Purpose: Prospective respiratory-gated 4D CT has been shown to reduce tumor image artifacts by up to 50% compared to conventional 4D CT. However, to date no studies have quantified the impact of gated 4D CT on normal lung tissue imaging, which is important in performing dose calculations based on accurate estimates of lung volume and structure. To determine the impact of gated 4D CT on thoracic image quality, the authors developed a novel simulation framework incorporating a realistic deformable digital phantom driven by patient tumor motion patterns. Based on this framework, the authors test the hypothesis that respiratory-gated 4D CTmore » can significantly reduce lung imaging artifacts. Methods: Our simulation framework synchronizes the 4D extended cardiac torso (XCAT) phantom with tumor motion data in a quasi real-time fashion, allowing simulation of three 4D CT acquisition modes featuring different levels of respiratory feedback: (i) “conventional” 4D CT that uses a constant imaging and couch-shift frequency, (ii) “beam paused” 4D CT that interrupts imaging to avoid oversampling at a given couch position and respiratory phase, and (iii) “respiratory-gated” 4D CT that triggers acquisition only when the respiratory motion fulfills phase-specific displacement gating windows based on prescan breathing data. Our framework generates a set of ground truth comparators, representing the average XCAT anatomy during beam-on for each of ten respiratory phase bins. Based on this framework, the authors simulated conventional, beam-paused, and respiratory-gated 4D CT images using tumor motion patterns from seven lung cancer patients across 13 treatment fractions, with a simulated 5.5 cm{sup 3} spherical lesion. Normal lung tissue image quality was quantified by comparing simulated and ground truth images in terms of overall mean square error (MSE) intensity difference, threshold-based lung volume error, and fractional false positive/false negative rates. Results: Averaged across all simulations and phase bins, respiratory-gating reduced overall thoracic MSE by 46% compared to conventional 4D CT (p ∼ 10{sup −19}). Gating leads to small but significant (p < 0.02) reductions in lung volume errors (1.8%–1.4%), false positives (4.0%–2.6%), and false negatives (2.7%–1.3%). These percentage reductions correspond to gating reducing image artifacts by 24–90 cm{sup 3} of lung tissue. Similar to earlier studies, gating reduced patient image dose by up to 22%, but with scan time increased by up to 135%. Beam paused 4D CT did not significantly impact normal lung tissue image quality, but did yield similar dose reductions as for respiratory-gating, without the added cost in scanning time. Conclusions: For a typical 6 L lung, respiratory-gated 4D CT can reduce image artifacts affecting up to 90 cm{sup 3} of normal lung tissue compared to conventional acquisition. This image improvement could have important implications for dose calculations based on 4D CT. Where image quality is less critical, beam paused 4D CT is a simple strategy to reduce imaging dose without sacrificing acquisition time.« less
  • Purpose: To investigate the accuracy and robustness, against image noise and artifacts (typical of CBCT images), of a commercial algorithm for deformable image registration (DIR), to propagate regions of interest (ROIs) in computational phantoms based on real prostate patient images. Methods: The Anaconda DIR algorithm, implemented in RayStation was tested. Two specific Deformation Vector Fields (DVFs) were applied to the reference data set (CTref) using the ImSimQA software, obtaining two deformed CTs. For each dataset twenty-four different level of noise and/or capping artifacts were applied to simulate CBCT images. DIR was performed between CTref and each deformed CTs and CBCTs.more » In order to investigate the relationship between image quality parameters and the DIR results (expressed by a logit transform of the Dice Index) a bilinear regression was defined. Results: More than 550 DIR-mapped ROIs were analyzed. The Statistical analysis states that deformation strenght and artifacts were significant prognostic factors of DIR performances, while noise appeared to have a minor role in DIR process as implemented in RayStation as expected by the image similarity metric built in the registration algorithm. Capping artifacts reveals a determinant role for the accuracy of DIR results. Two optimal values for capping artifacts were found to obtain acceptable DIR results (DICE> 075/ 0.85). Various clinical CBCT acquisition protocol were reported to evaluate the significance of the study. Conclusion: This work illustrates the impact of image quality on DIR performance. Clinical issues like Adaptive Radiation Therapy (ART) and Dose Accumulation need accurate and robust DIR software. The RayStation DIR algorithm resulted robust against noise, but sensitive to image artifacts. This result highlights the need of robustness quality assurance against image noise and artifacts in the commissioning of a DIR commercial system and underlines the importance to adopt optimized protocols for CBCT image acquisitions in ART clinical implementation.« less
  • The quality of lossy compressed images is often characterized by signal-to-noise ratios, informal tests of subjective quality, or receiver operating characteristic (ROC) curves that include subjective appraisals of the value of an image for a particular application. The authors believe that for medical applications, lossy compressed images should be judged by a more natural and fundamental aspect of relative image quality: their use in making accurate diagnoses. They apply a lossy compression algorithm to medical images, and quantify the quality of the images by the diagnostic performance of radiologists, as well as by traditional signal-to-noise ratios and subjective ratings. Themore » study is unlike previous studies of the effects of lossy compression in that they consider non-binary detection tasks, simulate actual diagnostic practice instead of using paired tests or confidence rankings, use statistical methods that are more appropriate for non-binary clinical data than are the popular ROC curves, and use low-complexity predictive tree-structured vector quantization for compression rather than DCT-based transform codes combined with entropy coding. Their diagnostic tasks are the identification of nodules (tumors) in the lungs and lymphadenopathy in the mediastinum from computerized tomography (CT) chest scans. For the image modality, compression algorithm, and diagnostic tasks they consider, the original 12 bit per pixel (bpp) CT image can be compressed to between 1 bpp and 2 bpp with no significant changes in diagnostic accuracy.« less