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...

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Publicado en:Academic Radiology Vol. 16; no. 12; pp. 1518 - 1531
Autores principales: 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
Formato: research Journal Article
Publicado: Elsevier B.V. Dec2009
Acceso en línea:Ver este registro en EBSCOhost
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        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
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