Computer-Aided Detection of Malignant Lung Nodules on Chest Radiographs: Effect on Observers' Performance

Objective To evaluate the effect of computer-aided detection (CAD) system on observer performance in the detection of malignant lung nodules on chest radiograph. Materials and Methods Two hundred chest radiographs (100 normal and 100 abnormal with malignant solitary lung nodules) were evaluated. With CT and histological confirmation serving as a reference, the mean nodule size was 15.4 mm (range, 7-20 mm). Five chest radiologists and five radiology residents independently interpreted both the original radiographs and CAD output images using the sequential testing method. The performances of the observers for the detection of malignant nodules with and without CAD were compared using the jackknife free-response receiver operating characteristic analysis. Results Fifty-nine nodules were detected by the CAD system with a false positive rate of 1.9 nodules per case. The detection of malignant lung nodules significantly increased from 0.90 to 0.92 for a group of observers, excluding one first-year resident (p = 0.04). When lowering the confidence score was not allowed, the average figure of merit also increased from 0.90 to 0.91 (p = 0.04) for all observers after a CAD review. On average, the sensitivities with and without CAD were 87% and 84%, respectively; the false positive rates per case with and without CAD were 0.19 and 0.17, respectively. The number of additional malignancies detected following true positive CAD marks ranged from zero to seven for the various observers. Conclusion The CAD system may help improve observer performance in detecting malignant lung nodules on chest radiographs and contribute to a decrease in missed lung cancer.

[1]  Elmar Kotter,et al.  Comparison of Radiologist and CAD Performance in the Detection of CT-confirmed Subtle Pulmonary Nodules on Digital Chest Radiographs , 2008, Investigative radiology.

[2]  Jean Jeudy,et al.  Use of a computer-aided detection system to detect missed lung cancer at chest radiography. , 2009, Radiology.

[3]  M. Giger,et al.  Anniversary paper: History and status of CAD and quantitative image analysis: the role of Medical Physics and AAPM. , 2008, Medical physics.

[4]  E. Choi,et al.  Solitary Pulmonary Nodule on Helical Dynamic CT Scans: Analysis of the Enhancement Patterns Using a Computer-Aided Diagnosis (CAD) System , 2000, Korean journal of radiology.

[5]  J. V. van Engelshoven,et al.  Miss rate of lung cancer on the chest radiograph in clinical practice. , 1999, Chest.

[6]  Dev P Chakraborty,et al.  Analysis of location specific observer performance data: validated extensions of the jackknife free-response (JAFROC) method. , 2006, Academic radiology.

[7]  Kunio Doi,et al.  Usefulness of computer-aided diagnosis schemes for vertebral fractures and lung nodules on chest radiographs. , 2008, AJR. American journal of roentgenology.

[8]  Bram van Ginneken,et al.  Computer-aided Detection of Lung Cancer on Chest Radiographs: Effect on Observer Performance , 2012 .

[9]  Kunio Doi,et al.  Computer-aided diagnosis for improved detection of lung nodules by use of posterior-anterior and lateral chest radiographs. , 2007, Academic radiology.

[10]  W. E. Miller,et al.  Lung cancer detected during a screening program using four-month chest radiographs. , 1983, Radiology.

[11]  K. Doi,et al.  Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system. , 2004, AJR. American journal of roentgenology.

[12]  J. Austin,et al.  Missed bronchogenic carcinoma: radiographic findings in 27 patients with a potentially resectable lesion evident in retrospect. , 1992, Radiology.

[13]  J. Goo A Computer-Aided Diagnosis for Evaluating Lung Nodules on Chest CT: the Current Status and Perspective , 2011, Korean journal of radiology.

[14]  Qian He,et al.  Effect of Multiscale Processing in Digital Chest Radiography on Automated Detection of Lung Nodule with a Computer Assistance System , 2008, Journal of Digital Imaging.

[15]  H. Kim,et al.  Usefulness of the CAD System for Detecting Pulmonary Nodule in Real Clinical Practice , 2011, Korean journal of radiology.

[16]  E. V. van Beek,et al.  Evaluation of a real-time interactive pulmonary nodule analysis system on chest digital radiographic images: a prospective study. , 2008, Academic radiology.

[17]  A. Porcel,et al.  Characteristics of missed lung cancer on chest radiographs: a French experience , 2001, European Radiology.

[18]  K. Doi,et al.  Lung cancers missed on chest radiographs: results obtained with a commercial computer-aided detection program. , 2008, Radiology.

[19]  K. Doi,et al.  Investigation of new psychophysical measures for evaluation of similar images on thoracic computed tomography for distinction between benign and malignant nodules. , 2003, Medical physics.