Patient-based Performance Assessment for Pediatric Abdominal CT: An Automated Monitoring System Based on Lesion Detectability and Radiation Dose.

Journal Article (Journal Article)

RATIONALE AND OBJECTIVE: To deploy an automated tool for evaluating pediatric body computed tomography (CT) performance utilizing metrics of radiation dose and image quality for the task of liver lesion detection. MATERIALS AND METHODS: This IRB approved retrospective investigation used 507 IV-contrast-enhanced abdominopelvic CT scans of pediatric patients (<18 years) between June 2014 and November 2017 acquired on three scanner models from two manufacturers. The scans were evaluated in terms of radiation metrics (CTDIvol, DLP, and SSDE) as well as task-based performance based on the clinical task of detecting a 5 mm liver lesion with a 10 HU attenuation difference from background liver. An informatics algorithm extracted a previously-validated quantitative detectability index (d') from each case reflective of the likelihood of detecting a liver lesion. The results were analyzed in terms of the relationship between d' and radiation dose metrics. RESULTS: There was minimal SSDE variability by age. Median SSDE at 100 kV on one scanner model was 5.2 mGy (5.0-5.4 mGy interquartile range). However, when assessing image quality by applying d', the age groups separated such that the younger patients had higher d' values than older patients. Similar trends were seen in all scanners. CONCLUSIONS: An automated method to assess clinical image quality for pediatric CT provided a metric of image quality that varied as expected across ages (i.e., higher quality for younger patients). This tool affords the establishment of a quality reference level that, in addition to dose estimations currently available, would allow for enhanced assessment (e.g., facilitated audit) of CT imaging performance.

Full Text

Duke Authors

Cited Authors

  • Lacy, T; Ding, A; Minkemeyer, V; Frush, D; Samei, E

Published Date

  • February 2021

Published In

Volume / Issue

  • 28 / 2

Start / End Page

  • 217 - 224

PubMed ID

  • 32063494

Electronic International Standard Serial Number (EISSN)

  • 1878-4046

Digital Object Identifier (DOI)

  • 10.1016/j.acra.2020.01.018


  • eng

Conference Location

  • United States