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An Algorithm for Intelligent Sorting of CT-Related Dose Parameters

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Abstract

Imaging centers nationwide are seeking innovative means to record and monitor computed tomography (CT)-related radiation dose in light of multiple instances of patient overexposure to medical radiation. As a solution, we have developed RADIANCE, an automated pipeline for extraction, archival, and reporting of CT-related dose parameters. Estimation of whole-body effective dose from CT dose length product (DLP)—an indirect estimate of radiation dose—requires anatomy-specific conversion factors that cannot be applied to total DLP, but instead necessitate individual anatomy-based DLPs. A challenge exists because the total DLP reported on a dose sheet often includes multiple separate examinations (e.g., chest CT followed by abdominopelvic CT). Furthermore, the individual reported series DLPs may not be clearly or consistently labeled. For example, “arterial” could refer to the arterial phase of the triple liver CT or the arterial phase of a CT angiogram. To address this problem, we have designed an intelligent algorithm to parse dose sheets for multi-series CT examinations and correctly separate the total DLP into its anatomic components. The algorithm uses information from the departmental PACS to determine how many distinct CT examinations were concurrently performed. Then, it matches the number of distinct accession numbers to the series that were acquired and anatomically matches individual series DLPs to their appropriate CT examinations. This algorithm allows for more accurate dose analytics, but there remain instances where automatic sorting is not feasible. To ultimately improve radiology patient care, we must standardize series names and exam names to unequivocally sort exams by anatomy and correctly estimate whole-body effective dose.

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Authors and Affiliations

  1. Department of Radiology, Hospital of the University of Pennsylvania, 1 Silverstein 3400 Spruce Street, Philadelphia, PA, 19104, USA

    Tessa S. Cook, Scott R. Steingall, William W. Boonn & Woojin Kim

  2. Department of Radiology, Johns Hopkins University, Baltimore, MD, USA

    Stefan L. Zimmerman

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  1. Tessa S. Cook
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  2. Stefan L. Zimmerman
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  3. Scott R. Steingall
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  4. William W. Boonn
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  5. Woojin Kim
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Correspondence to Tessa S. Cook.

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Cook, T.S., Zimmerman, S.L., Steingall, S.R. et al. An Algorithm for Intelligent Sorting of CT-Related Dose Parameters. J Digit Imaging 25, 179–188 (2012). https://doi.org/10.1007/s10278-011-9410-1

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  • DOI: https://doi.org/10.1007/s10278-011-9410-1

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