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Dose length product to effective dose coefficients in adults

  • Computed Tomography
  • Published:
European Radiology Aims and scope Submit manuscript

Abstract

Objectives

The most accurate method for estimating patient effective dose (a principal metric for tracking patient radiation exposure) from computed tomography (CT) requires time-intensive Monte Carlo simulation. A simpler method multiplies a scalar coefficient by the widely available scanner-reported dose length product (DLP) to estimate effective dose. We developed new adult effective dose coefficients using actual patient scans and assessed their agreement with Monte Carlo simulation.

Methods

A multicenter sample of 216,906 adult CT scans was prospectively assembled in 2015–2020 from the University of California San Francisco International CT Dose Registry and the University of Florida library of computational phantoms. We generated effective dose coefficients for eight body regions, stratified by patient sex, diameter, and scanner manufacturer. We applied the new coefficients to DLPs to calculate effective doses and assess their correlations with Monte Carlo radiation transport-generated effective dose.

Results

Effective dose coefficients varied by body region and decreased in magnitude with increasing patient diameter. Coefficients were approximately twofold higher for torso scans in smallest compared with largest diameter categories. For example, abdomen and pelvis coefficients decreased from 0.027 to 0.013 mSv/mGy-cm between the 16–20 cm and 41+ cm categories. There were modest but consistent differences by sex and manufacturer. Diameter-based coefficients used to estimate effective dose produced strong correlations with the reference standard (Pearson correlations 0.77–0.86). The reported conversion coefficients differ from previous studies, particularly in neck CT.

Conclusions

New effective dose coefficients derived from empirical clinical scans can be used to easily estimate effective dose using scanner-reported DLP.

Clinical relevance statement

Scalar coefficients multiplied by DLP offer a simple approximation to effective dose, a key radiation dose metric. New effective dose coefficients from this study strongly correlate with gold standard, Monte Carlo–generated effective dose, and differ somewhat from previous studies.

Key Points

• Previous effective dose coefficients were derived from theoretical models rather than real patient data.

• The new coefficients (from a large registry/phantom library) differ from previous studies.

• The new coefficients offer reasonably reliable values for estimating effective dose.

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Abbreviations

CT:

Computed tomography

CTDI-vol:

Computed tomography dose index volume

DICOM:

Digital Imaging and Communications in Medicine

DLP:

Dose length product

GE:

General Electric

ICRP:

International Commission on Radiation Protection

NCI:

National Cancer Institute

TCM:

Tube current modulation

UCSF:

University of California San Francisco

UF:

University of Florida

WED:

Water equivalent diameter

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Funding

This study received funding by the US National Institutes of Health (R01-CA181191) and the Patient-Centered Outcomes Research Institute (CD-1304-7043 and DI-2018C1-11375). Funders had no role in study design, collection, analysis, interpretation, and reporting of data, or decision to publish. The views in this article are solely the responsibility of the authors and do not necessarily represent the views of the Patient-Centered Outcomes Research Institute, its Board of Governors or Methodology Committee, or other funders.

Author information

Authors and Affiliations

  1. Department of Epidemiology and Biostatistics, University of California San Francisco, 550 16th Street, Box 0560, San Francisco, CA, 94143, USA

    Philip W. Chu, Yifei Wang, Cameron A. Chu, Carly Stewart & Rebecca Smith-Bindman

  2. Department of Radiology, The University of Chicago, Chicago, IL, USA

    Cameron Kofler

  3. Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA

    Brian Haas

  4. Radiation Epidemiology Branch, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    Choonsik Lee

  5. Department of Pediatrics, Division of Pediatric Critical Care, UCSF Benioff Children’s Hospital, University of California at San Francisco, San Francisco, USA

    Malini Mahendra

  6. Philip R. Lee Institute for Health Policy Studies, University of California, San Francisco, CA, USA

    Malini Mahendra & Rebecca Smith-Bindman

  7. Department of Diagnostic, Molecular and Interventional Radiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Bradley N. Delman

  8. Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA

    Wesley E. Bolch

  9. Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, CA, USA

    Rebecca Smith-Bindman

Authors
  1. Philip W. Chu
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  2. Cameron Kofler
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  3. Brian Haas
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  8. Malini Mahendra
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  10. Wesley E. Bolch
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  11. Rebecca Smith-Bindman
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Corresponding author

Correspondence to Rebecca Smith-Bindman.

Ethics declarations

Guarantor

The scientific guarantor of this publication is Rebecca Smith-Bindman.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: Dr. Smith-Bindman is a co-founder of Alara Imaging, a company focused on collecting and reporting radiation dose and imaging quality information for computed tomography. Alara had no role in the study, and Dr. Smith-Bindman has not received funding from Alara Imaging. Other authors have no relationships with Alara and no conflicts of interests relevant to this article to disclose.

Statistics and biometry

Multiple authors have significant statistical expertise, and no complex statistical methods were necessary for this paper.

Informed consent

The UCSF Committee on Human Research provided a waiver of individual informed consent. Collaborating institutions obtained local Institutional Review Board approval or relied on the UCSF approval to contribute data to the Registry.

Ethical approval

Institutional Review Board approval was not required because the paper uses anonymized data.

Study subjects or cohorts overlap

Some study subjects or cohorts overlap with several studies that use the same dose registry, but for different purposes, including:

Chu PW, Yu S, Wang Y, et al Reference phantom selection in pediatric computed tomography using data from a large, multicenter registry. Pediatr Radiol. 2022 Mar;52(3):445–452. https://doi.org/10.1007/s00247-021-05227-0. Epub 2021 Dec 6. PMID: 34866159; PMCID: PMC8857172.

Smith-Bindman R, Chu P, Wang Y, et al Comparison of the effectiveness of single-component and multicomponent interventions for reducing radiation doses in patients undergoing computed tomography: a randomized clinical trial. JAMA Intern Med. 2020 May 1;180(5):666–675. https://doi.org/10.1001/jamainternmed.2020.0064. PMID: 32227142; PMCID: PMC7105953.

Smith-Bindman R, Wang Y, Chu P, et al International variation in radiation dose for computed tomography examinations: prospective cohort study. BMJ. 2019 Jan 2;364:k4931. https://doi.org/10.1136/bmj.k4931. PMID: 30602590; PMCID: PMC6314083.

The CT data derive from the UCSF International CT Dose Registry, some parts of which have been used in prior publications, including approximately 1 million CTs in a randomized trial to assess whether participation in a learning collaborative results in meaningful reduction in radiation doses.

Methodology

• prospective

• observational

• multicenter study

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Philip W. Chu and Cameron Kofler are joint first authors.

Wesley E. Bolch and Rebecca Smith-Bindman are joint senior authors.

Supplementary Information

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Supplementary file1 (PDF 108 KB)

Supplementary file2 (PDF 88 KB)

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Chu, P.W., Kofler, C., Haas, B. et al. Dose length product to effective dose coefficients in adults. Eur Radiol 34, 2416–2425 (2024). https://doi.org/10.1007/s00330-023-10262-6

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