title: Evaluation of a projection-domain lung nodule insertion technique in thoracic computed tomography.
abstract: Task-based assessment of computed tomography (CT) image quality requires a large number of cases with ground truth. Prospective case acquisition can be time-consuming. Inserting lesions into existing cases to simulate positive cases is a promising alternative. The aim was to evaluate a recently developed projection-based lesion insertion technique in thoracic CT. In total, 32 lung nodules of various attenuations were segmented from 21 patient cases, forward projected, inserted into projections, and reconstructed. Two experienced radiologists and two residents independently evaluated these nodules in two substudies. First, the 32 inserted and the 32 original nodules were presented in a randomized order and each received a score from 1 to 10 (1 = absolutely artificial to 10 = absolutely realistic). Second, the inserted and the corresponding original lesions were presented side-by-side to each reader. For the randomized evaluation, discrimination of real versus inserted nodules was poor with areas under the receiver operative characteristic curves being 0.57 [95% confidence interval (CI): 0.46 to 0.68], 0.69 (95% CI: 0.58 to 0.78), and 0.62 (95% CI: 0.54 to 0.69) for the two residents, two radiologists, and all four readers, respectively. Our projection-based lung nodule insertion technique provides a robust method to artificially generate positive cases that prove to be difficult to differentiate from real cases.
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Chi
authors.initials: C
authors.lastname: Ma
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Lifeng
authors.initials: L
authors.lastname: Yu
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Baiyu
authors.initials: B
authors.lastname: Chen
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Chi Wan
authors.initials: CW
authors.lastname: Koo
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Edwin A
authors.initials: EA
authors.lastname: Takahashi
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Joel G
authors.initials: JG
authors.lastname: Fletcher
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: David L
authors.initials: DL
authors.lastname: Levin
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Ronald S
authors.initials: RS
authors.lastname: Kuzo
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Lyndsay D
authors.initials: LD
authors.lastname: Viers
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Stephanie A
authors.initials: SA
authors.lastname: Vincent-Sheldon
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Shuai
authors.initials: S
authors.lastname: Leng
authors.affiliation: Mayo Clinic , Department of Radiology, Rochester, Minnesota, United States.
authors.forename: Cynthia H
authors.initials: CH
authors.lastname: McCollough
keywords: image quality assessment; lesion insertion; lesion simulation; lung nodule; observer study; radiation dose reduction; thoracic computed tomography