ORIGINAL RESEARCH n MEDICAL PHYSICS 124 radiology.rsna.org n Radiology: Volume 277: Number 1—October 2015 1 From the Software and Systems Division, National Institute of Standards and Technology, 325 Broadway St, Boulder, CO 80305 (G.S., J.F., A.P., A.D.); Department of Diagnostic Radiology, University of Maryland Medical Cen- ter, Baltimore, Md (E. Siegel, J.C., C.T., Z.Y.); Departments of Medical Physics (O.C.) and Radiology (E. Samei), Duke University School of Medicine, Durham, NC; and Depart- ment of Radiology–Research, University of Arizona School of Medicine, Tucson, Ariz (E.K.). Received June 5, 2014; revision requested July 16; revision received November 24; accepted December 15; final version accepted February 19, 2015. Address correspondence to A.P. (e-mail: adele. peskin@nist.gov). q RSNA, 2015 Purpose: To compare image resolution from iterative reconstruc- tion with resolution from filtered back projection for low- contrast objects on phantom computed tomographic (CT) images across vendors and exposure levels. Materials and Methods: Randomized repeat scans of an American College of Ra- diology CT accreditation phantom (module 2, low con- trast) were performed for multiple radiation exposures, vendors, and vendor iterative reconstruction algorithms. Eleven volunteers were presented with 900 images by us- ing a custom-designed graphical user interface to perform a task created specifically for this reader study. Results were analyzed by using statistical graphics and analysis of variance. Results: Across three vendors (blinded as A, B, and C) and across three exposure levels, the mean correct classification rate was higher for iterative reconstruction than filtered back projection (P , .01): 87.4% iterative reconstruction and 81.3% filtered back projection at 20 mGy, 70.3% itera- tive reconstruction and 63.9% filtered back projection at 12 mGy, and 61.0% iterative reconstruction and 56.4% filtered back projection at 7.2 mGy. There was a signif- icant difference in mean correct classification rate be- tween vendor B and the other two vendors. Across all exposure levels, images obtained by using vendor B’s scan- ner outperformed the other vendors, with a mean cor- rect classification rate of 74.4%, while the mean correct classification rate for vendors A and C was 68.1% and 68.3%, respectively. Across all readers, the mean correct classification rate for iterative reconstruction (73.0%) was higher compared with the mean correct classification rate for filtered back projection (67.0%). Conclusion: The potential exists to reduce radiation dose without compromising low-contrast detectability by using iterative reconstruction instead of filtered back projection. There is substantial variability across vendor reconstruction algorithms. q RSNA, 2015 Ganesh Saiprasad, PhD James Filliben, PhD Adele Peskin, PhD Eliot Siegel, MD Joseph Chen, MD Christopher Trimble, MD Zhitong Yang, PhD Olav Christianson, MS Ehsan Samei, PhD Elizabeth Krupinski, PhD Alden Dima, MS Evaluation of Low-Contrast Detectability of Iterative Reconstruction across Multiple Institutions, CT Scanner Manufacturers, and Radiation Exposure Levels 1 Note: This copy is for your personal non-commercial use only. To order presentation-ready copies for distribution to your colleagues or clients, contact us at www.rsna.org/rsnarights.