Evaluation of low-contrast detectability of iterative reconstruction across multiple institutions, ct scanner manufacturers, and radiation exposure levels<sup>1</sup>

Ganesh Saiprasad, James Filliben, Adele Peskin, Eliot Siegel, Joseph Chen, Christopher Trimble, Zhitong Yang, Olav Christianson, Ehsan Samei, Elizabeth A Krupinski, Alden Dima

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

Purpose: To compare image resolution from iterative reconstruction with resolution from filtered back projection for lowcontrast objects on phantom computed tomographic (CT) images across vendors and exposure levels. Materials and Methods: Randomized repeat scans of an American College of Radiology CT accreditation phantom (module 2, low contrast) were performed for multiple radiation exposures, vendors, and vendor iterative reconstruction algorithms. Eleven volunteers were presented with 900 images by using 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% iterative 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 significant difference in mean correct classification rate between vendor B and the other two vendors. Across all exposure levels, images obtained by using vendor B's scanner outperformed the other vendors, with a mean correct 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.

Original languageEnglish (US)
Pages (from-to)124-133
Number of pages10
JournalRadiology
Volume277
Issue number1
DOIs
StatePublished - Oct 1 2015

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Radiation Exposure
Accreditation
Radiology
Volunteers
Analysis of Variance
Radiation

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

Cite this

Evaluation of low-contrast detectability of iterative reconstruction across multiple institutions, ct scanner manufacturers, and radiation exposure levels<sup>1</sup> / Saiprasad, Ganesh; Filliben, James; Peskin, Adele; Siegel, Eliot; Chen, Joseph; Trimble, Christopher; Yang, Zhitong; Christianson, Olav; Samei, Ehsan; Krupinski, Elizabeth A; Dima, Alden.

In: Radiology, Vol. 277, No. 1, 01.10.2015, p. 124-133.

Research output: Contribution to journalArticle

Saiprasad, G, Filliben, J, Peskin, A, Siegel, E, Chen, J, Trimble, C, Yang, Z, Christianson, O, Samei, E, Krupinski, EA & Dima, A 2015, 'Evaluation of low-contrast detectability of iterative reconstruction across multiple institutions, ct scanner manufacturers, and radiation exposure levels<sup>1</sup>', Radiology, vol. 277, no. 1, pp. 124-133. https://doi.org/10.1148/radiol.2015141260
Saiprasad, Ganesh ; Filliben, James ; Peskin, Adele ; Siegel, Eliot ; Chen, Joseph ; Trimble, Christopher ; Yang, Zhitong ; Christianson, Olav ; Samei, Ehsan ; Krupinski, Elizabeth A ; Dima, Alden. / Evaluation of low-contrast detectability of iterative reconstruction across multiple institutions, ct scanner manufacturers, and radiation exposure levels<sup>1</sup>. In: Radiology. 2015 ; Vol. 277, No. 1. pp. 124-133.
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abstract = "Purpose: To compare image resolution from iterative reconstruction with resolution from filtered back projection for lowcontrast objects on phantom computed tomographic (CT) images across vendors and exposure levels. Materials and Methods: Randomized repeat scans of an American College of Radiology CT accreditation phantom (module 2, low contrast) were performed for multiple radiation exposures, vendors, and vendor iterative reconstruction algorithms. Eleven volunteers were presented with 900 images by using 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{\%} iterative 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 significant difference in mean correct classification rate between vendor B and the other two vendors. Across all exposure levels, images obtained by using vendor B's scanner outperformed the other vendors, with a mean correct 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.",
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AU - Chen, Joseph

AU - Trimble, Christopher

AU - Yang, Zhitong

AU - Christianson, Olav

AU - Samei, Ehsan

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N2 - Purpose: To compare image resolution from iterative reconstruction with resolution from filtered back projection for lowcontrast objects on phantom computed tomographic (CT) images across vendors and exposure levels. Materials and Methods: Randomized repeat scans of an American College of Radiology CT accreditation phantom (module 2, low contrast) were performed for multiple radiation exposures, vendors, and vendor iterative reconstruction algorithms. Eleven volunteers were presented with 900 images by using 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% iterative 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 significant difference in mean correct classification rate between vendor B and the other two vendors. Across all exposure levels, images obtained by using vendor B's scanner outperformed the other vendors, with a mean correct 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.

AB - Purpose: To compare image resolution from iterative reconstruction with resolution from filtered back projection for lowcontrast objects on phantom computed tomographic (CT) images across vendors and exposure levels. Materials and Methods: Randomized repeat scans of an American College of Radiology CT accreditation phantom (module 2, low contrast) were performed for multiple radiation exposures, vendors, and vendor iterative reconstruction algorithms. Eleven volunteers were presented with 900 images by using 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% iterative 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 significant difference in mean correct classification rate between vendor B and the other two vendors. Across all exposure levels, images obtained by using vendor B's scanner outperformed the other vendors, with a mean correct 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.

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