Abdominal Computerized Tomography Research Cedars-Sinai Skip to content Close Select your preferred language English عربى 简体中文 繁體中文 فارسي עִברִית 日本語 한국어 Русский Español Tagalog English English عربى 简体中文 繁體中文 فارسي עִברִית 日本語 한국어 Русский Español Tagalog Translation is unavailable for Internet Explorer Cedars-Sinai Home 1-800-CEDARS-1 1-800-CEDARS-1 Close Find a Doctor Locations Programs & Services Health Library Patient & Visitors Community My CS-Link RESEARCH clear Go Close Navigation Links Academics Faculty Development Community Engagement Calendar Research Research Areas Research Labs Departments & Institutes Find Clinical Trials Research Cores Research Administration Basic Science Research Clinical & Translational Research Center (CTRC) Technology & Innovations News & Breakthroughs Education Graduate Medical Education Continuing Medical Education Graduate School of Biomedical Sciences Professional Training Programs Medical Students Campus Life Office of the Dean Simulation Center Medical Library Program in the History of Medicine About Us All Education Programs Departments & Institutes Faculty Directory Biomedical Imaging Research Institute Back to Biomedical Imaging Research Institute About Us Research Abdominal Computerized Tomography Research Breast Cancer Metabolism Research Cancer Molecular Imaging Research Lung Imaging Research MRI Hardware Engineering Program Neuroimaging Research Neurovascular Imaging Research Oncologic Radiation Therapy Imaging Research Quantitative Imaging Analysis Program Skeletal Regeneration and Stem Cell Therapy Imaging Research Translational Cardiac Imaging Research Team News Events Key Collaborations BIRI Membership Volunteer For a Research Study Abdominal Computerized Tomography Research Mission The mission of the Abdominal Computerized Tomography Research program led by Yifang (Jimmy) Zhou, PhD, is to determine consistent low-contrast detectability and corresponding dose in abdominal computerized tomography (CT) for variable patient sizes. Patient radiation dose during CT scans is a serious concern for the public and research communities, and a variety of dose-reduction methods have been proposed or implemented. However, diagnosis task specifics, a key aspect in dose reduction, have not been incorporated analytically. Our study proposes a quantitative model to incorporate the diagnosis task specifics and patient size in the optimal dose computation. Faculty Yifang (Jimmy) Zhou, PhD Focus Dose reduction for children is widely promoted in the Image Gently campaign by the Alliance for Radiation Safety in Pediatric Imaging. For adult imaging, a similar effort has been made in the Image Wisely campaign by the Joint Task Force on Adult Radiation Protection. From pediatric to bariatric patients, patient sizes differ across a substantial range. The proper implementation of dose reduction for such a wide range of patient sizes remains challenging. In principle, the degree of dose reduction should adhere to the preservation of image quality; hence, it is a process of dose optimization. However, different definitions of the image quality metric have been proposed from past studies, including constant pixel noise or constant contrast-to-noise ratio (CNR). The former has been implemented on many commercial scanners for automatic tube current modulation. Constant detector energy deposition was also studied. Nevertheless, neither of these metrics adequately addresses task-specific low-contrast detectability. In previous work, we utilized statistically defined low-contrast detectability (SD-LCD) as the task-specific image quality metric for an abdomen phantom of medium size. Based on those studies, using two different scanners, the relationship of the dose to SD-LCD and lesion size was found to be in the form of a power law. However, several important questions remained unanswered. First, a power law form identified using a medium-size phantom may or may not be valid for the phantoms of other sizes, because the influences of multiple bow-tie filters and scatter are unknown. More important, the explicit patient size dependency of the minimum detectable contrast remains unknown. This is true even if the general power law form is valid, so we continue to investigate whether the patient size dependency is in the power indices or in the proportionality factor. Furthermore, it remains unclear whether there exists a generic or scanner design — dependent relationship with which to gauge the dose modulation for different patient sizes. In this study, we used two approaches to address these questions. We first used a simplified theoretical model to relate the minimum detectable contrast to the patient size, dose and lesion size. The result of this model also indicated a connection between the minimum detectable contrast and the bow-tie filter design. We extended the conclusion to a general equation that could be experimentally validated. The validation was then carried out using abdomen phantoms of various sizes, scanned with two different scanners. The answers can be used to obtain the doses for different patient sizes to achieve consistent low-contrast detectability, which therefore may benefit Image Gently and Image Wisely. Collaborative Research Alexander Scott, PhD Jessica Nute, PhD Joseph Giaconi, MD Presentations Abstracts Zhou Y. Dose optimization in CT. Invited to present at Associated Sciences Consortium, Radiology Society of North America, Chicago, Illinois. Nov 29, 2016. http://archive.rsna.org/2016/16001498.html. Zhou Y, Nute J, Scott II A, Lee C. Consistent low contrast detectability and optimal dose for different patient sizes in abdominal CT. American Association of Physicists in Medicine Annual Meeting, District of Columbia. Med Phys. 2016;43:3641. http://onlinelibrary.wiley.com/doi/10.1118/1.4956950/full. Zhou Y, Scott II A. Minimization of resolution loss for CT scans of the elbow at lateral position. American Association of Physicists in Medicine Annual Meeting, District of Columbia. Med Phys. 2016;43:3393. http://onlinelibrary.wiley.com/doi/10.1118/1.4955858/full. Nute J, Zhou Y, Scott II A, Lee C. Relationship between pixel noise and task-specific low contrast detectability for various patient sizes in abdomen CT. 2016 American Association of Physicists in Medicine Annual Meeting, District of Columbia. http://www.aapm.org/meetings/2016AM/PRAbs.asp?mid=115&aid=33129. Scott II A, Zhou Y, Allahverdian J, Nute J, Lee C. Estimating peak skin dose in the cath lab using Gafchromic film. 2016 American Association of Physicists in Medicine Spring Meeting, Salt Lake City, Utah. https://www.aapm.org/meetings/2016SCM/PRAbs.asp?mid=113&aid=31205. Zhou Y, Scott II A, Allahverdian J, Lee C. On the relationship of minimum required dose to low contrast detectability and blending fractions with adaptive statistical iterative reconstruction (ASIR) in abdominal CT. American Association of Physicists in Medicine, Annual Meeting, Anaheim, California. Med Phys. 2015;42:3544. http://onlinelibrary.wiley.com/doi/10.1118/1.4925255/full. Zhou Y, Scott II A, Allahverdian J, Lee C. Band-limited noise structure analysis on images with adaptive statistical iterative reconstruction (ASIR) in abdominal CT. American Association of Physicists in Medicine, Annual Meeting, Anaheim, California. Med Phys. 2015;42:3545. http://onlinelibrary.wiley.com/doi/10.1118/1.4925259/full. Scott II A, Zhou Y, Allahverdian J, Lee C. Evaluation of a radiation dose control program using exposure index. American Association of Physicists in Medicine, Annual Meeting, Anaheim, California. Med Phys. 2015;42:3718. http://onlinelibrary.wiley.com/doi/10.1118/1.4926188/full. Patents Systems and methods for determining radiation dose in computed tomography scans. US 20160166224 A1. PCT/US2014/049647. June 16, 2016. Publications Zhou Y, Nute J, Scott II A, Lee C. Consistent low contrast detectability for variable patient sizes and corresponding dose in abdominal CT [published online ahead of print December 31, 2016]. Med Phys. http://onlinelibrary.wiley.com/doi/10.1002/mp.12085/abstract Zhou Y, Scott II A, Allahverdian J, Frankel S. Evaluation of automatic exposure control options in digital mammography. J Xray Sci Technol. 2014;22(3):377-394. http://content.iospress.com/articles/journal-of-x-ray-science-and-technology/xst00433. Zhou Y, Scott II A, Allahverdian J, Lee C, Kightlinger B, Azizyan A, Miller J. On the relationship of minimum detectable contrast to dose and lesion size in abdominal CT. Phys Med Biol. 2015;60(19):7671-7694. http://iopscience.iop.org/article/10.1088/0031-9155/60/19/7671. Scott II A, Zhou Y, Allahverdian J, Nute J, Lee C. Evaluation of digital radiography practice using exposure index tracking. J Appl Clin Med Phys. 2016;17(6): 343-355. http://onlinelibrary.wiley.com/doi/10.1120/jacmp.v17i6.6082/full. Have Questions or Need Help If you have questions or would like to learn more about the Biomedical Imaging Research Institute at Cedars-Sinai, please call or send us a message. Biomedical Imaging Research Institute Pacific Theatres Building, Suite 400 116 N. Robertson Blvd. Los Angeles, CA 90048 310-423-7766 Fax:310-248-8682 Send A Message TWITTER FACEBOOK Please ensure Javascript is enabled for purposes of website accessibility