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Title: SU-F-J-175: Evaluation of Metal Artifact Reduction Algorithms in Computed Tomography and Their Application to Radiation Therapy Treatment Planning

Abstract

Purpose: High-Z (metal) implants in CT scans cause significant streak-like artifacts in the reconstructed dataset. This results in both inaccurate CT Hounsfield units for the tissue as well as obscuration of the target and organs at risk (OARs) for radiation therapy planning. Herein we analyze two metal artifact reduction algorithms: GE’s Smart MAR and a Metal Deletion Technique (MDT) for geometric and Hounsfield Unit (HU) accuracy. Methods: A CT-to-electron density phantom, with multiple inserts of various densities and a custom Cerrobend insert (Zeff=76.8), is utilized in this continuing study. The phantom is scanned without metal (baseline) and again with the metal insert. Using one set of projection data, reconstructed CT volumes are created with filtered-back-projection (FBP) and the MAR and the MDT algorithms. Regions-of-Interest (ROIs) are evaluated for each insert for HU accuracy; the metal insert’s Full-Width-Half-Maximum (FWHM) is used to evaluate the geometric accuracy. Streak severity is quantified with an HU error metric over the phantom volume. Results: The original FBP reconstruction has a Root-Mean-Square-Error (RMSE) of 57.55 HU (STD=29.19, range=−145.8 to +79.2) compared to baseline. The MAR reconstruction has a RMSE of 20.98 HU (STD=13.92, range=−18.3 to +61.7). The MDT reconstruction has a RMSE of 10.05 HU (STD=10.5,more » range=−14.8 to +18.6). FWHM for baseline=162.05; FBP=161.84 (−0.13%); MAR=162.36 (+0.19%); MDT=162.99 (+0.58%). Streak severity metric for FBP=19.73 (22.659% bad pixels); MAR=8.743 (9.538% bad); MDT=4.899 (5.303% bad). Conclusion: Image quality, in terms of HU accuracy, in the presence of high-Z metal objects in CT scans is improved by metal artifact reduction reconstruction algorithms. The MDT algorithm had the highest HU value accuracy (RMSE=10.05 HU) and best streak severity metric, but scored the worst in terms of geometric accuracy. Qualitatively, the MAR and MDT algorithms increased detectability of inserts, although there is a loss of in-plane resolution near the metallic insert.« less

Authors:
; ;  [1]
  1. Baylor Scott & White Health, Temple, TX (United States)
Publication Date:
OSTI Identifier:
22634772
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; ALGORITHMS; COMPUTERIZED TOMOGRAPHY; DATASETS; ERRORS; HAZARDS; IMAGE PROCESSING; IMAGES; IMPLANTS; METRICS; ORGANS; PHANTOMS; PLANNING; RADIOTHERAPY

Citation Formats

Norris, H, Rangaraj, D, and Kim, S. SU-F-J-175: Evaluation of Metal Artifact Reduction Algorithms in Computed Tomography and Their Application to Radiation Therapy Treatment Planning. United States: N. p., 2016. Web. doi:10.1118/1.4956083.
Norris, H, Rangaraj, D, & Kim, S. SU-F-J-175: Evaluation of Metal Artifact Reduction Algorithms in Computed Tomography and Their Application to Radiation Therapy Treatment Planning. United States. doi:10.1118/1.4956083.
Norris, H, Rangaraj, D, and Kim, S. 2016. "SU-F-J-175: Evaluation of Metal Artifact Reduction Algorithms in Computed Tomography and Their Application to Radiation Therapy Treatment Planning". United States. doi:10.1118/1.4956083.
@article{osti_22634772,
title = {SU-F-J-175: Evaluation of Metal Artifact Reduction Algorithms in Computed Tomography and Their Application to Radiation Therapy Treatment Planning},
author = {Norris, H and Rangaraj, D and Kim, S},
abstractNote = {Purpose: High-Z (metal) implants in CT scans cause significant streak-like artifacts in the reconstructed dataset. This results in both inaccurate CT Hounsfield units for the tissue as well as obscuration of the target and organs at risk (OARs) for radiation therapy planning. Herein we analyze two metal artifact reduction algorithms: GE’s Smart MAR and a Metal Deletion Technique (MDT) for geometric and Hounsfield Unit (HU) accuracy. Methods: A CT-to-electron density phantom, with multiple inserts of various densities and a custom Cerrobend insert (Zeff=76.8), is utilized in this continuing study. The phantom is scanned without metal (baseline) and again with the metal insert. Using one set of projection data, reconstructed CT volumes are created with filtered-back-projection (FBP) and the MAR and the MDT algorithms. Regions-of-Interest (ROIs) are evaluated for each insert for HU accuracy; the metal insert’s Full-Width-Half-Maximum (FWHM) is used to evaluate the geometric accuracy. Streak severity is quantified with an HU error metric over the phantom volume. Results: The original FBP reconstruction has a Root-Mean-Square-Error (RMSE) of 57.55 HU (STD=29.19, range=−145.8 to +79.2) compared to baseline. The MAR reconstruction has a RMSE of 20.98 HU (STD=13.92, range=−18.3 to +61.7). The MDT reconstruction has a RMSE of 10.05 HU (STD=10.5, range=−14.8 to +18.6). FWHM for baseline=162.05; FBP=161.84 (−0.13%); MAR=162.36 (+0.19%); MDT=162.99 (+0.58%). Streak severity metric for FBP=19.73 (22.659% bad pixels); MAR=8.743 (9.538% bad); MDT=4.899 (5.303% bad). Conclusion: Image quality, in terms of HU accuracy, in the presence of high-Z metal objects in CT scans is improved by metal artifact reduction reconstruction algorithms. The MDT algorithm had the highest HU value accuracy (RMSE=10.05 HU) and best streak severity metric, but scored the worst in terms of geometric accuracy. Qualitatively, the MAR and MDT algorithms increased detectability of inserts, although there is a loss of in-plane resolution near the metallic insert.},
doi = {10.1118/1.4956083},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: In this article, an approach to metal artifact reduction is proposed that is practical for clinical use in radiation therapy. It is based on a new interpolation scheme of the projections associated with metal implants in helical computed tomography (CT) scanners. Methods and Materials: A three-step approach was developed consisting of an automatic algorithm for metal implant detection, a correction algorithm for helical projections, and a new, efficient algorithm for projection interpolation. The modified raw projection data are transferred back to the CT scanner device where CT slices are regenerated using the built-in reconstruction operator. The algorithm was testedmore » on a CT calibration phantom in which the density of inserted objects are known and on clinical prostate cases with two hip prostheses. The results are evaluated using the CT number and shape of the objects. Results: The validations on a CT calibration phantom with various inserts of known densities show that the algorithm improved the overall image quality by restoring the shape and the representative CT number of the objects in the image. For the clinical hip replacement cases, a large fraction of the bladder, rectum, and prostate that were not visible on the original CT slices were recovered using the algorithm. Precise contouring of the target volume was thus feasible. Without this enhancement, physicians would have drawn bigger margins to be sure to include the target and, at the same time, could have prescribed a lower dose to keep the same level of normal tissue toxicity. Conclusions: In both phantom experiment and patient studies, the algorithm resulted in significant artifact reduction with increases in the reliability of planning procedure for the case of metallic hip prostheses. This algorithm is now clinically used as a preprocessing before treatment planning for metal artifact reduction.« less
  • Purpose: Metal in patients creates streak artifacts in CT images. When used for radiation treatment planning, these artifacts make it difficult to identify internal structures and affects radiation dose calculations, which depend on HU numbers for inhomogeneity correction. This work quantitatively evaluates a new metal artifact reduction (MAR) CT image reconstruction algorithm (GE Healthcare CT-0521-04.13-EN-US DOC1381483) when metal is present. Methods: A Gammex Model 467 Tissue Characterization phantom was used. CT images were taken of this phantom on a GE Optima580RT CT scanner with and without steel and titanium plugs using both the standard and MAR reconstruction algorithms. HU valuesmore » were compared pixel by pixel to determine if the MAR algorithm altered the HUs of normal tissues when no metal is present, and to evaluate the effect of using the MAR algorithm when metal is present. Also, CT images of patients with internal metal objects using standard and MAR reconstruction algorithms were compared. Results: Comparing the standard and MAR reconstructed images of the phantom without metal, 95.0% of pixels were within ±35 HU and 98.0% of pixels were within ±85 HU. Also, the MAR reconstruction algorithm showed significant improvement in maintaining HUs of non-metallic regions in the images taken of the phantom with metal. HU Gamma analysis (2%, 2mm) of metal vs. non-metal phantom imaging using standard reconstruction resulted in an 84.8% pass rate compared to 96.6% for the MAR reconstructed images. CT images of patients with metal show significant artifact reduction when reconstructed with the MAR algorithm. Conclusion: CT imaging using the MAR reconstruction algorithm provides improved visualization of internal anatomy and more accurate HUs when metal is present compared to the standard reconstruction algorithm. MAR reconstructed CT images provide qualitative and quantitative improvements over current reconstruction algorithms, thus improving radiation treatment planning accuracy.« less
  • Purpose: To evaluate three commercial metal artifact reduction methods (MAR) in the context of radiation therapy treatment planning. Methods: Three MAR strategies were evaluated: Philips O-MAR, monochromatic imaging using Gemstone Spectral Imaging (GSI) dual energy CT, and monochromatic imaging with metal artifact reduction software (GSIMARs). The Gammex RMI 467 tissue characterization phantom with several metal rods and two anthropomorphic phantoms (pelvic phantom with hip prosthesis and head phantom with dental fillings), were scanned with and without (baseline) metals. Each MAR method was evaluated based on CT number accuracy, metal size accuracy, and reduction in the severity of streak artifacts. CTmore » number difference maps between the baseline and metal scan images were calculated, and the severity of streak artifacts was quantified using the percentage of pixels with >40 HU error (“bad pixels”). Results: Philips O-MAR generally reduced HU errors in the RMI phantom. However, increased errors and induced artifacts were observed for lung materials. GSI monochromatic 70keV images generally showed similar HU errors as 120kVp imaging, while 140keV images reduced errors. GSI-MARs systematically reduced errors compared to GSI monochromatic imaging. All imaging techniques preserved the diameter of a stainless steel rod to within ±1.6mm (2 pixels). For the hip prosthesis, O-MAR reduced the average % bad pixels from 47% to 32%. For GSI 140keV imaging, the percent of bad pixels was reduced from 37% to 29% compared to 120kVp imaging, while GSI-MARs further reduced it to 12%. For the head phantom, none of the MAR methods were particularly successful. Conclusion: The three MAR methods all improve CT images for treatment planning to some degree, but none of them are globally effective for all conditions. The MAR methods were successful for large metal implants in a homogeneous environment (hip prosthesis) but were not successful for the more complicated case of dental artifacts.« less
  • Purpose: To evaluate the metal artifacts in diagnostic kilovoltage computed tomography (kVCT) images of patients that are corrected by use of a normalized metal artifact reduction (NMAR) method with megavoltage CT (MVCT) prior images: MVCT-NMAR. Methods and Materials: MVCT-NMAR was applied to images from 5 patients: 3 with dual hip prostheses, 1 with a single hip prosthesis, and 1 with dental fillings. The corrected images were evaluated for visualization of tissue structures and their interfaces and for radiation therapy dose calculations. They were compared against the corresponding images corrected by the commercial orthopedic metal artifact reduction algorithm in a Phillipsmore » CT scanner. Results: The use of MVCT images for correcting kVCT images in the MVCT-NMAR technique greatly reduces metal artifacts, avoids secondary artifacts, and makes patient images more useful for correct dose calculation in radiation therapy. These improvements are significant, provided the MVCT and kVCT images are correctly registered. The remaining and the secondary artifacts (soft tissue blurring, eroded bones, false bones or air pockets, CT number cupping within the metal) present in orthopedic metal artifact reduction corrected images are removed in the MVCT-NMAR corrected images. A large dose reduction was possible outside the planning target volume (eg, 59.2 Gy to 52.5 Gy in pubic bone) when these MVCT-NMAR corrected images were used in TomoTherapy treatment plans without directional blocks for a prostate cancer patient. Conclusions: The use of MVCT-NMAR corrected images in radiation therapy treatment planning could improve the treatment plan quality for patients with metallic implants.« less
  • Purpose: To evaluate the feasibility of using a metal artifact reduction technique in depleting metal artifact and its application in improving dose calculation in External Radiation Therapy Planning. Methods: CIRS electron density phantom was scanned with and without steel drill bits placed in some plug holes. Meta artifact reduction software with Metal Deletion Technique (MDT) was used to remove metal artifacts for scanned image with metal. Hounsfield units of electron density plugs from artifact free reference image and MDT processed images were compared. To test the dose calculation improvement after the MDT processed images, clinically approved head and neck planmore » with manual dental artifact correction was tested. Patient images were exported and processed with MDT and plan was recalculated with new MDT image without manual correction. Dose profiles near the metal artifacts were compared. Results: The MDT used in this study effectively reduced the metal artifact caused by beam hardening and scatter. The windmill around the metal drill was greatly improved with smooth rounded view. Difference of the mean HU in each density plug between reference and MDT images were less than 10 HU in most of the plugs. Dose difference between original plan and MDT images were minimal. Conclusion: Most metal artifact reduction methods were developed for diagnostic improvement purpose. Hence Hounsfield unit accuracy was not rigorously tested before. In our test, MDT effectively eliminated metal artifacts with good HU reproduciblity. However, it can introduce new mild artifacts so the MDT images should be checked with original images.« less