Quantitative CT: Technique dependency of volume assessment for pulmonary nodules

Baiyu Chen, Samuel Richard, Huiman Barnhart, James Colsher, Maxwell Amurao, Ehsan Samei

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Current lung nodule size assessment methods typically rely on one-dimensional estimation of lesions. While new 3D volume assessment techniques using MSCT scan data have enabled improved estimation of lesion size, the effect of acquisition and reconstruction parameters on accuracy and precision of such estimation has not been adequately investigated. To characterize such dependencies, we scanned an anthropomorphic thoracic phantom containing synthetic nodules with different protocols, including various acquisition and reconstruction parameters. We also scanned the phantom repeatedly with the same protocol to investigate repeatability. The nodule's volume was estimated by a clinical lung analysis software package, LungVCAR. Accuracy (bias) and precision (variance) of the volume assessment were calculated across the nodules and compared between protocols via Generalized Estimating Equation analysis. Results suggest a strong dependence of accuracy and precision on dose level but little dependence on reconstruction thickness, thus providing possible guidelines for protocol optimization for quantitative tasks.

Original languageEnglish
Title of host publicationMedical Imaging 2010
Subtitle of host publicationPhysics of Medical Imaging
EditionPART 2
DOIs
StatePublished - 2010
EventMedical Imaging 2010: Physics of Medical Imaging - San Diego, CA, United States
Duration: Feb 15 2010Feb 18 2010

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
NumberPART 2
Volume7622
ISSN (Print)1605-7422

Conference

ConferenceMedical Imaging 2010: Physics of Medical Imaging
Country/TerritoryUnited States
CitySan Diego, CA
Period02/15/1002/18/10

Keywords

  • 3D volume assessment
  • Anthropomorphic thoracic phantom
  • MSCT
  • Pulmonary nodules

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