title: Quantitative CT: technique dependence of volume estimation on pulmonary nodules.
abstract: Current estimation of lung nodule size typically relies on uni- or bi-dimensional techniques. While new three-dimensional volume estimation techniques using MDCT have improved size estimation of nodules with irregular shapes, the effect of acquisition and reconstruction parameters on accuracy (bias) and precision (variance) of the new techniques has not been fully investigated. To characterize the volume estimation performance dependence on these parameters, an anthropomorphic chest phantom containing synthetic nodules was scanned and reconstructed with protocols across various acquisition and reconstruction parameters. Nodule volumes were estimated by a clinical lung analysis software package, LungVCAR. Precision and accuracy of the volume assessment were calculated across the nodules and compared between protocols via a generalized estimating equation analysis. Results showed that the precision and accuracy of nodule volume quantifications were dependent on slice thickness, with different dependences for different nodule characteristics. Other parameters including kVp, pitch, and reconstruction kernel had lower impact. Determining these technique dependences enables better volume quantification via protocol optimization and highlights the importance of consistent imaging parameters in sequential examinations.
authors.affiliation: Medical Physics Graduate Program, Duke University, Durham, NC 27705, USA.
authors.forename: Baiyu
authors.initials: B
authors.lastname: Chen
authors.forename: Huiman
authors.initials: H
authors.lastname: Barnhart
authors.forename: Samuel
authors.initials: S
authors.lastname: Richard
authors.forename: James
authors.initials: J
authors.lastname: Colsher
authors.forename: Maxwell
authors.initials: M
authors.lastname: Amurao
authors.forename: Ehsan
authors.initials: E
authors.lastname: Samei
mesh_terms: D000886:Anthropometry; D004867:Equipment Design; D006801:Humans; D021621:Imaging, Three-Dimensional; D008168:Lung / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000175:diagnosis / Q000000981:diagnostic imaging; D015233:Models, Statistical; D019047:Phantoms, Imaging; D011126:Polypropylenes / Q000737:chemistry; D015203:Reproducibility of Results; D012984:Software; D003074:Solitary Pulmonary Nodule / Q000175:diagnosis / Q000000981:diagnostic imaging*; D013909:Thorax / Q000473:pathology; D014057:Tomography, X-Ray Computed / Q000379:methods*
chemical_list: D011126:Polypropylenes