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Assessment of Radiologist Performance in the Detection of Lung Nodules

2008; Elsevier BV; Volume: 16; Issue: 1 Linguagem: Inglês

10.1016/j.acra.2008.05.022

1878-4046

Samuel G. Armato, Rachael Y. Roberts, Masha Kocherginsky, Denise R. Aberle, Ella A. Kazerooni, Heber MacMahon, Edwin J.R. van Beek, David F. Yankelevitz, Geoffrey McLennan, Michael F. McNitt‐Gray, Charles R. Meyer, Anthony P. Reeves, Philip Caligiuri, Leslie E. Quint, Baskaran Sundaram, Barbara Y. Croft, Laurence P. Clarke,

Atomic and Subatomic Physics Research

Rationale and Objectives Studies that evaluate the lung nodule detection performance of radiologists or computerized methods depend on an initial inventory of the nodules within the thoracic images (the "truth"). The purpose of this study was to analyze ( 1 Wormanns D. Ludwig K. Beyer F. et al. Detection of pulmonary nodules at multirow-detector CT: effectiveness of double reading to improve sensitivity at standard-dose and low-dose chest CT. Eur Radiol. 2005; 15: 14-22 Crossref PubMed Scopus (105) Google Scholar ) variability in the "truth" defined by different combinations of experienced thoracic radiologists and ( 2 Leader J.K. Warfel T.E. Fuhrman C.R. et al. Pulmonary nodule detection with low-dose CT of the lung: agreement among radiologists. Am J Roentgenol. 2005; 185: 973-978 Crossref PubMed Scopus (74) Google Scholar ) variability in the performance of other experienced thoracic radiologists based on these definitions of "truth" in the context of lung nodule detection in computed tomographic (CT) scans. Materials and Methods Twenty-five thoracic CT scans were reviewed by four thoracic radiologists, who independently marked lesions they considered to be nodules ≥3 mm in maximum diameter. Panel "truth" sets of nodules were then derived from the nodules marked by different combinations of two and three of these four radiologists. The nodule detection performance of the other radiologists was evaluated based on these panel "truth" sets. Results The number of "true" nodules in the different panel "truth" sets ranged from 15 to 89 (mean 49.8 ± 25.6). The mean radiologist nodule detection sensitivities across radiologists and panel "truth" sets for different panel "truth" conditions ranged from 51.0 to 83.2%; mean false-positive rates ranged from 0.33 to 1.39 per case. Conclusions Substantial variability exists across radiologists in the task of lung nodule identification in CT scans. The definition of "truth" on which lung nodule detection studies are based must be carefully considered, because even experienced thoracic radiologists may not perform well when measured against the "truth" established by other experienced thoracic radiologists. Studies that evaluate the lung nodule detection performance of radiologists or computerized methods depend on an initial inventory of the nodules within the thoracic images (the "truth"). The purpose of this study was to analyze ( 1 Wormanns D. Ludwig K. Beyer F. et al. Detection of pulmonary nodules at multirow-detector CT: effectiveness of double reading to improve sensitivity at standard-dose and low-dose chest CT. Eur Radiol. 2005; 15: 14-22 Crossref PubMed Scopus (105) Google Scholar ) variability in the "truth" defined by different combinations of experienced thoracic radiologists and ( 2 Leader J.K. Warfel T.E. Fuhrman C.R. et al. Pulmonary nodule detection with low-dose CT of the lung: agreement among radiologists. Am J Roentgenol. 2005; 185: 973-978 Crossref PubMed Scopus (74) Google Scholar ) variability in the performance of other experienced thoracic radiologists based on these definitions of "truth" in the context of lung nodule detection in computed tomographic (CT) scans. Twenty-five thoracic CT scans were reviewed by four thoracic radiologists, who independently marked lesions they considered to be nodules ≥3 mm in maximum diameter. Panel "truth" sets of nodules were then derived from the nodules marked by different combinations of two and three of these four radiologists. The nodule detection performance of the other radiologists was evaluated based on these panel "truth" sets. The number of "true" nodules in the different panel "truth" sets ranged from 15 to 89 (mean 49.8 ± 25.6). The mean radiologist nodule detection sensitivities across radiologists and panel "truth" sets for different panel "truth" conditions ranged from 51.0 to 83.2%; mean false-positive rates ranged from 0.33 to 1.39 per case. Substantial variability exists across radiologists in the task of lung nodule identification in CT scans. The definition of "truth" on which lung nodule detection studies are based must be carefully considered, because even experienced thoracic radiologists may not perform well when measured against the "truth" established by other experienced thoracic radiologists.