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Title: Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning

Abstract

Purpose: Traditionally, 2D radiographic preparatory scan images (scout scans) are used to plan diagnostic CT scans. However, a 3D CT volume with a full 3D organ segmentation map could provide superior information for customized scan planning and other purposes. A practical challenge is to design the volumetric scout acquisition and processing steps to provide good image quality (at least good enough to enable 3D organ segmentation) while delivering a radiation dose similar to that of the conventional 2D scout. Methods: The authors explored various acquisition methods, scan parameters, postprocessing methods, and reconstruction methods through simulation and cadaver data studies to achieve an ultralow dose 3D scout while simultaneously reducing the noise and maintaining the edge strength around the target organ. Results: In a simulation study, the 3D scout with the proposed acquisition, preprocessing, and reconstruction strategy provided a similar level of organ segmentation capability as a traditional 240 mAs diagnostic scan, based on noise and normalized edge strength metrics. At the same time, the proposed approach delivers only 1.25% of the dose of a traditional scan. In a cadaver study, the authors’ pictorial-structures based organ localization algorithm successfully located the major abdominal-thoracic organs from the ultralow dose 3D scout obtainedmore » with the proposed strategy. Conclusions: The authors demonstrated that images with a similar degree of segmentation capability (interpretability) as conventional dose CT scans can be achieved with an ultralow dose 3D scout acquisition and suitable postprocessing. Furthermore, the authors applied these techniques to real cadaver CT scans with a CTDI dose level of less than 0.1 mGy and successfully generated a 3D organ localization map.« less

Authors:
;  [1]; ;  [2];  [3];  [4];  [5]
  1. Image Reconstruction Laboratory, GE Global Research, Niskayuna, New York 12309 (United States)
  2. X-ray and CT Laboratory, GE Global Research, Shanghai 201203 (China)
  3. Biomedical Image Processing Laboratory, GE Global Research, Niskayuna, New York 12309 (United States)
  4. CT, X-ray and Functional Imaging, GE Global Research, Niskayuna, New York 12309 (United States)
  5. Thoracic and Cardiac Imaging, Massachusetts General Hospital, Boston, Massachusetts 02114 (United States)
Publication Date:
OSTI Identifier:
22413572
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 42; Journal Issue: 5; Other Information: (c) 2015 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; ALGORITHMS; CAT SCANNING; IMAGE PROCESSING; NOISE; PLANNING; RADIATION DOSES

Citation Formats

Yin, Zhye, De Man, Bruno, Yao, Yangyang, Wu, Mingye, Montillo, Albert, Edic, Peter M., and Kalra, Mannudeep. Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning. United States: N. p., 2015. Web. doi:10.1118/1.4921065.
Yin, Zhye, De Man, Bruno, Yao, Yangyang, Wu, Mingye, Montillo, Albert, Edic, Peter M., & Kalra, Mannudeep. Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning. United States. https://doi.org/10.1118/1.4921065
Yin, Zhye, De Man, Bruno, Yao, Yangyang, Wu, Mingye, Montillo, Albert, Edic, Peter M., and Kalra, Mannudeep. 2015. "Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning". United States. https://doi.org/10.1118/1.4921065.
@article{osti_22413572,
title = {Acquisition, preprocessing, and reconstruction of ultralow dose volumetric CT scout for organ-based CT scan planning},
author = {Yin, Zhye and De Man, Bruno and Yao, Yangyang and Wu, Mingye and Montillo, Albert and Edic, Peter M. and Kalra, Mannudeep},
abstractNote = {Purpose: Traditionally, 2D radiographic preparatory scan images (scout scans) are used to plan diagnostic CT scans. However, a 3D CT volume with a full 3D organ segmentation map could provide superior information for customized scan planning and other purposes. A practical challenge is to design the volumetric scout acquisition and processing steps to provide good image quality (at least good enough to enable 3D organ segmentation) while delivering a radiation dose similar to that of the conventional 2D scout. Methods: The authors explored various acquisition methods, scan parameters, postprocessing methods, and reconstruction methods through simulation and cadaver data studies to achieve an ultralow dose 3D scout while simultaneously reducing the noise and maintaining the edge strength around the target organ. Results: In a simulation study, the 3D scout with the proposed acquisition, preprocessing, and reconstruction strategy provided a similar level of organ segmentation capability as a traditional 240 mAs diagnostic scan, based on noise and normalized edge strength metrics. At the same time, the proposed approach delivers only 1.25% of the dose of a traditional scan. In a cadaver study, the authors’ pictorial-structures based organ localization algorithm successfully located the major abdominal-thoracic organs from the ultralow dose 3D scout obtained with the proposed strategy. Conclusions: The authors demonstrated that images with a similar degree of segmentation capability (interpretability) as conventional dose CT scans can be achieved with an ultralow dose 3D scout acquisition and suitable postprocessing. Furthermore, the authors applied these techniques to real cadaver CT scans with a CTDI dose level of less than 0.1 mGy and successfully generated a 3D organ localization map.},
doi = {10.1118/1.4921065},
url = {https://www.osti.gov/biblio/22413572}, journal = {Medical Physics},
issn = {0094-2405},
number = 5,
volume = 42,
place = {United States},
year = {Fri May 15 00:00:00 EDT 2015},
month = {Fri May 15 00:00:00 EDT 2015}
}