Computer-Aided Diagnosis of Lung Nodules on CT Scans: ROC Study of Its Effect on Radiologists' Performance

被引：39

作者：

Way, Ted ^{[1
]}

Chan, Heang-Ping ^{[1
]}

Hadjiiski, Lubomir ^{[1
]}

Sahiner, Berkman ^{[1
]}

Chughtai, Aamer ^{[1
]}

Song, Thomas K. ^{[2
]}

Poopat, Chad ^{[2
]}

Stojanovska, Jadranka ^{[1
]}

Frank, Luba ^{[1
]}

Attili, Anil ^{[1
]}

Bogot, Naama ^{[1
]}

Cascade, Philip N. ^{[1
]}

Kazerooni, Ella A. ^{[1
]}

机构：

[1] Univ Michigan, Dept Radiol, Ann Arbor, MI 48109 USA

[2] Henry Ford Hosp, Dept Radiol, Detroit, MI 48202 USA

来源：

ACADEMIC RADIOLOGY | 2010年 / 17卷 / 03期

关键词：

Computer-aided diagnosis; pulmonary nodule; observer study; computed tomography; HIGH-RESOLUTION CT; LOW-DOSE CT; SOLITARY PULMONARY NODULES; ARTIFICIAL NEURAL-NETWORK; DIFFERENTIATING BENIGN; MALIGNANT NODULES; SPIRAL CT; BASE-LINE; CANCER; CLASSIFICATION;

D O I：

10.1016/j.acra.2009.10.016

中图分类号：

R8 [特种医学]; R445 [影像诊断学];

学科分类号：

1002 ; 100207 ; 1009 ;

摘要：

Rationale and Objectives: The aim of this study was to evaluate the effect of computer-aided diagnosis (CAD) on radiologists' estimates of the likelihood of malignancy of lung nodules on computed tomographic (CT) imaging. Methods and Materials: A total of 256 lung nodules (124 malignant, 132 benign) were retrospectively collected from the thoracic CT scans of 152 patients. An automated CAD system was developed to characterize and provide malignancy ratings for lung nodules on CT volumetric images. An observer study was conducted using receiver-operating characteristic analysis to evaluate the effect of CAD on radiologists' characterization of lung nodules. Six fellowship-trained thoracic radiologists served as readers. The readers rated the likelihood of malignancy on a scale of 0% to 100% and recommended appropriate action first without CAD and then with CAD. The observer ratings were analyzed using the Dorfman-Berbaum-Metz multireader, multicase method. Results: The CAD system achieved a test area under the receiver-operating characteristic curve (A(z)) of 0.857 +/- 0.023 using the perimeter, two nodule radii measures, two texture features, and two gradient field features. All six radiologists obtained improved performance with CAD. The average A(z) of the radiologists improved significantly (P < .01) from 0.833 (range, 0.817-0.847) to 0.853 (range, 0.834-0.887). Conclusion: CAD has the potential to increase radiologists' accuracy in assessing the likelihood of malignancy of lung nodules on CT imaging.

引用

页码：323 / 332

页数：10

共 45 条

[1] Computerized scheme for determination of the likelihood measure of malignancy for pulmonary nodules on low-dose CT images [J].