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Title: SU-F-J-41: Experimental Validation of a Cascaded Linear System Model for MVCBCT with a Multi-Layer EPID

Abstract

Purpose: The purpose of this study was to validate the use of a cascaded linear system model for MV cone-beam CT (CBCT) using a multi-layer (MLI) electronic portal imaging device (EPID) and provide experimental insight into image formation. A validated 3D model provides insight into salient factors affecting reconstructed image quality, allowing potential for optimizing detector design for CBCT applications. Methods: A cascaded linear system model was developed to investigate the potential improvement in reconstructed image quality for MV CBCT using an MLI EPID. Inputs to the three-dimensional (3D) model include projection space MTF and NPS. Experimental validation was performed on a prototype MLI detector installed on the portal imaging arm of a Varian TrueBeam radiotherapy system. CBCT scans of up to 898 projections over 360 degrees were acquired at exposures of 16 and 64 MU. Image volumes were reconstructed using a Feldkamp-type (FDK) filtered backprojection (FBP) algorithm. Flat field images and scans of a Catphan model 604 phantom were acquired. The effect of 2×2 and 4×4 detector binning was also examined. Results: Using projection flat fields as an input, examination of the modeled and measured NPS in the axial plane exhibits good agreement. Binning projection images was shown tomore » improve axial slice SDNR by a factor of approximately 1.4. This improvement is largely driven by a decrease in image noise of roughly 20%. However, this effect is accompanied by a subsequent loss in image resolution. Conclusion: The measured axial NPS shows good agreement with the theoretical calculation using a linear system model. Binning of projection images improves SNR of large objects on the Catphan phantom by decreasing noise. Specific imaging tasks will dictate the implementation image binning to two-dimensional projection images. The project was partially supported by a grant from Varian Medical Systems, Inc. and grant No. R01CA188446-01 from the National Cancer Institute.« less

Authors:
; ; ;  [1]; ;  [2]; ; ;  [3]
  1. Department of Radiation Oncology, Brigham and Women’s Hospital, Dana Farber Cancer Institute and Harvard Medical School, Boston, MA. (United States)
  2. Varian Medical Systems, Dattwil, Aargau (Switzerland)
  3. Varian Medical Systems, Palo Alto, CA (United States)
Publication Date:
OSTI Identifier:
22632173
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; ALGORITHMS; BIOMEDICAL RADIOGRAPHY; COMPUTERIZED TOMOGRAPHY; IMAGES; NEOPLASMS; OPTIMIZATION; PHANTOMS; RADIOTHERAPY; VALIDATION

Citation Formats

Hu, Y, Rottmann, J, Myronakis, M, Berbeco, R, Fueglistaller, R, Morf, D, Wang, A, Shedlock, D, and Star-Lack, J. SU-F-J-41: Experimental Validation of a Cascaded Linear System Model for MVCBCT with a Multi-Layer EPID. United States: N. p., 2016. Web. doi:10.1118/1.4955949.
Hu, Y, Rottmann, J, Myronakis, M, Berbeco, R, Fueglistaller, R, Morf, D, Wang, A, Shedlock, D, & Star-Lack, J. SU-F-J-41: Experimental Validation of a Cascaded Linear System Model for MVCBCT with a Multi-Layer EPID. United States. doi:10.1118/1.4955949.
Hu, Y, Rottmann, J, Myronakis, M, Berbeco, R, Fueglistaller, R, Morf, D, Wang, A, Shedlock, D, and Star-Lack, J. 2016. "SU-F-J-41: Experimental Validation of a Cascaded Linear System Model for MVCBCT with a Multi-Layer EPID". United States. doi:10.1118/1.4955949.
@article{osti_22632173,
title = {SU-F-J-41: Experimental Validation of a Cascaded Linear System Model for MVCBCT with a Multi-Layer EPID},
author = {Hu, Y and Rottmann, J and Myronakis, M and Berbeco, R and Fueglistaller, R and Morf, D and Wang, A and Shedlock, D and Star-Lack, J},
abstractNote = {Purpose: The purpose of this study was to validate the use of a cascaded linear system model for MV cone-beam CT (CBCT) using a multi-layer (MLI) electronic portal imaging device (EPID) and provide experimental insight into image formation. A validated 3D model provides insight into salient factors affecting reconstructed image quality, allowing potential for optimizing detector design for CBCT applications. Methods: A cascaded linear system model was developed to investigate the potential improvement in reconstructed image quality for MV CBCT using an MLI EPID. Inputs to the three-dimensional (3D) model include projection space MTF and NPS. Experimental validation was performed on a prototype MLI detector installed on the portal imaging arm of a Varian TrueBeam radiotherapy system. CBCT scans of up to 898 projections over 360 degrees were acquired at exposures of 16 and 64 MU. Image volumes were reconstructed using a Feldkamp-type (FDK) filtered backprojection (FBP) algorithm. Flat field images and scans of a Catphan model 604 phantom were acquired. The effect of 2×2 and 4×4 detector binning was also examined. Results: Using projection flat fields as an input, examination of the modeled and measured NPS in the axial plane exhibits good agreement. Binning projection images was shown to improve axial slice SDNR by a factor of approximately 1.4. This improvement is largely driven by a decrease in image noise of roughly 20%. However, this effect is accompanied by a subsequent loss in image resolution. Conclusion: The measured axial NPS shows good agreement with the theoretical calculation using a linear system model. Binning of projection images improves SNR of large objects on the Catphan phantom by decreasing noise. Specific imaging tasks will dictate the implementation image binning to two-dimensional projection images. The project was partially supported by a grant from Varian Medical Systems, Inc. and grant No. R01CA188446-01 from the National Cancer Institute.},
doi = {10.1118/1.4955949},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
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