Effect of CAD on radiologists' detection of lung nodules on thoracic CT scans: analysis of an observer performance study by nodule size.
Rationale and Objectives: To retrospectively investigate the effect of a computer-aided detection (CAD) system on radiologists' performance for detecting small pulmonary nodules in computed tomography (CT) examinations, with a panel of expert radiologists serving as the reference standard.Materials...
| Publicado en: | Academic Radiology Vol. 16; no. 12; pp. 1518 - 1531 |
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| Autores principales: | , , , , , , , , , , , , , , , , , , , |
| Formato: | research Journal Article |
| Publicado: |
Elsevier B.V.
Dec2009
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=105240251&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 105240251 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 10766332 T4X jtl: Academic Radiology issn: 10766332 maglogo: N pubinfo: dt: Dec2009 vid: 16 iid: 12 pid: 467 pub: Elsevier B.V. place: New York, New York artinfo: ui: 105240251 NLM19896069 2010465723 10.1016/j.acra.2009.08.006 NLM19896069 PMC2810535 105240251 ppf: 1518 ppct: 13 formats: tig: atl: Effect of CAD on radiologists' detection of lung nodules on thoracic CT scans: analysis of an observer performance study by nodule size. aug: au: Sahiner B Chan HP Hadjiiski LM Cascade PN Kazerooni EA Chughtai AR Poopat C Song T Frank L Stojanovska J Attili A Sahiner, Berkman Chan, Heang-Ping Hadjiiski, Lubomir M Cascade, Philip N Kazerooni, Ella A Chughtai, Aamer R Poopat, Chad Song, Thomas Frank, Luba affil: Department of Radiology, The University of Michigan, MIB C480A, 1500 East Medical Center Drive, Ann Arbor, MI 48109, USA sug: subj: Lung Neoplasms Radiography Information Science Methods Radiographic Image Interpretation, Computer-Assisted Methods Radiography, Thoracic Methods Tomography, X-Ray Computed Methods Aged Female Human Male Middle Age Observer Bias Radiographic Image Enhancement Methods Reproducibility of Results Sensitivity and Specificity Aged: 65+ years Middle Aged: 45-64 years Female Male ab: Rationale and Objectives: To retrospectively investigate the effect of a computer-aided detection (CAD) system on radiologists' performance for detecting small pulmonary nodules in computed tomography (CT) examinations, with a panel of expert radiologists serving as the reference standard.Materials and Methods: Institutional review board approval was obtained. Our dataset contained 52 CT examinations collected by the Lung Image Database Consortium, and 33 from our institution. All CTs were read by multiple expert thoracic radiologists to identify the reference standard for detection. Six other thoracic radiologists read the CT examinations first without and then with CAD. Performance was evaluated using free-response receiver operating characteristics (FROC) and the jackknife FROC analysis methods (JAFROC) for nodules above different diameter thresholds.Results: A total of 241 nodules, ranging in size from 3.0 to 18.6 mm (mean, 5.3 mm) were identified as the reference standard. At diameter thresholds of 3, 4, 5, and 6 mm, the CAD system had a sensitivity of 54%, 64%, 68%, and 76%, respectively, with an average of 5.6 false positives (FPs) per scan. Without CAD, the average figures of merit (FOMs) for the six radiologists, obtained from JAFROC analysis, were 0.661, 0.729, 0.793, and 0.838 for the same nodule diameter thresholds, respectively. With CAD, the corresponding average FOMs improved to 0.705, 0.763, 0.810, and 0.862, respectively. The improvement achieved statistical significance for nodules at the 3 and 4 mm thresholds (P = .002 and .020, respectively), and did not achieve significance at 5 and 6 mm (P = .18 and .13, respectively). At a nodule diameter threshold of 3 mm, the radiologists' average sensitivity and FP rate were 0.56 and 0.67, respectively, without CAD, and 0.67 and 0.78 with CAD.Conclusion: CAD improves thoracic radiologists' performance for detecting pulmonary nodules smaller than 5 mm on CT examinations, which are often overlooked by visual inspection alone. pubtype: Academic Journal doctype: research Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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