Abstract
Abstract
Background
The most accurate method for estimating effective dose (the most widely understood 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.
Objective
Develop pediatric effective dose coefficients and assess their agreement with Monte Carlo simulation.
Materials and methods
Multicenter, population-based sample of 128,397 pediatric diagnostic CT scans prospectively assembled in 2015–2020 from the University of California San Francisco International CT Dose Registry and the University of Florida library of highly realistic hybrid computational phantoms. We generated effective dose coefficients for seven body regions, stratified by patient age, diameter, and scanner manufacturer. We applied the new coefficients to DLPs to calculate effective doses and assessed their correlations with Monte Carlo radiation transport-generated effective doses.
Results
The reported effective dose coefficients, generally higher than previous studies, varied by body region and decreased in magnitude with increasing age. Coefficients were approximately 4 to 13-fold higher (across body regions) for patients <1 year old compared with patients 15–21 years old. For example, head CT (54% of scans) dose coefficients decreased from 0.039 to 0.003 mSv/mGy-cm in patients <1 year old vs. 15–21 years old. There were minimal differences by manufacturer. Using age-based conversion coefficients to estimate effective dose produced moderate to strong correlations with Monte Carlo results (Pearson correlations 0.52–0.80 across body regions).
Conclusions
New pediatric effective dose coefficients update existing literature and can be used to easily estimate effective dose using scanner-reported DLP.
Funder
National Institutes of Health
Patient-Centered Outcomes Research Institute
Publisher
Springer Science and Business Media LLC
Subject
Radiology, Nuclear Medicine and imaging,Pediatrics, Perinatology and Child Health
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