Pulmonary nodules: Estimation of malignancy at thin-section helical CT - Effect of computer-aided diagnosis on performance of radiologists

被引:74
作者
Awai, K
Murao, K
Ozawa, A
Nakayama, Y
Nakaura, T
Liu, D
Kawanaka, K
Funama, Y
Morishita, S
Yamashita, Y
机构
[1] Kumamoto Univ, Grad Sch Med Sci, Dept Diagnost Radiol, Kumamoto 8608556, Japan
[2] Kumamoto Univ, Sch Hlth Sci, Dept Radiol Technol, Kumamoto 8608556, Japan
[3] Bio IT Business Dev Grp, Chiba, Japan
关键词
D O I
10.1148/radiol.2383050167
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 [临床医学]; 100207 [影像医学与核医学]; 1009 [特种医学];
摘要
Purpose: To evaluate the effect of a computer-aided diagnosis (CAD) system on the diagnostic performance of radiologists for the estimation of the malignancy of pulmonary nodules on thin-section helical computed tomographic (CT) scans. Materials and Methods: The institutional review board approved use of the CT database; informed specific study-related consent was waived. The institutional review board approved participation of radiologists; informed consent was obtained from all observers. Thirty-three (18 malignant, 15 benign) pulmonary nodules of less than 3.0 cm in maximal diameter were evaluated. Receiver operating characteristic (ROC) analysis with a continuous rating scale was used to compare observer performance for the estimation of the likelihood of malignancy first without and then with the CAD system. The participants were 10 board-certified radiologists and nine radiology residents. Results: For all 19 participants, the mean area under the best-fit ROC curve (A(z)) values achieved without and with the CAD system were 0.843 +/- 0.097 (standard deviation) and 0.924 +/- 0.043, respectively. The difference was significant (P = .021). The mean A(z) values achieved without and with the CAD system were 0.910 +/- 0.052 and 0.944 +/- 0.040, respectively, for the 10 board-certified radiologists (P = .190) and 0.768 +/- 0.078 and 0.901 +/- 0.036, respectively, for the nine radiology residents (P = .009). Conclusion: Use of the CAD system significantly (P = .009) improved the diagnostic performance of radiology residents for assessment of the malignancy of pulmonary nodules; however, it did not improved that of board-certified radiologists. (c) RSNA, 2006.
引用
收藏
页码:276 / 284
页数:9
相关论文
共 54 条
[1]
Computerized scheme for determination of the likelihood measure of malignancy for pulmonary nodules on low-dose CT images [J].
Aoyama, M ;
Li, Q ;
Katsuragawa, S ;
Li, F ;
Sone, S ;
Doi, K .
MEDICAL PHYSICS, 2003, 30 (03) :387-394
[2]
Automated lung nodule classification following automated nodule detection on CT: A serial approach [J].
Armato, SG ;
Altman, MB ;
Wilkie, J ;
Sone, S ;
Li, F ;
Doi, K ;
Roy, AS .
MEDICAL PHYSICS, 2003, 30 (06) :1188-1197
[3]
Computerized detection of pulmonary nodules on CT scans [J].
Armato, SG ;
Giger, ML ;
Moran, CJ ;
Blackburn, JT ;
Doi, K ;
MacMahon, H .
RADIOGRAPHICS, 1999, 19 (05) :1303-1311
[4]
Automated detection of lung nodules in CT scans:: Effect of image reconstruction algorithm [J].
Armato, SG ;
Altman, MB ;
La Rivière, PJ .
MEDICAL PHYSICS, 2003, 30 (03) :461-472
[5]
Lung cancer: Performance of automated lung nodule detection applied to cancers missed in a CT screening program [J].
Armato, SG ;
Li, F ;
Giger, ML ;
MacMahon, H ;
Sone, S ;
Doi, K .
RADIOLOGY, 2002, 225 (03) :685-692
[6]
Automated detection of lung nodules in CT scans: Preliminary results [J].
Armato, SG ;
Giger, ML ;
MacMahon, H .
MEDICAL PHYSICS, 2001, 28 (08) :1552-1561
[7]
POTENTIAL USEFULNESS OF AN ARTIFICIAL NEURAL NETWORK FOR DIFFERENTIAL-DIAGNOSIS OF INTERSTITIAL LUNG-DISEASES - PILOT-STUDY [J].
ASADA, N ;
DOI, K ;
MACMAHON, H ;
MONTNER, SM ;
GIGER, ML ;
ABE, C ;
WU, YZ .
RADIOLOGY, 1990, 177 (03) :857-860
[8]
Pulmonary nodules at chest CT: Effect of computer-aided diagnosis on radiologists' detection performance [J].
Awai, K ;
Murao, K ;
Ozawa, A ;
Komi, M ;
Hayakawa, H ;
Hori, S ;
Nishimura, Y .
RADIOLOGY, 2004, 230 (02) :347-352
[9]
Histopathological and CT features of pulmonary sclerosing haemangiomas [J].
Cheung, YC ;
Ng, SH ;
Chang, JWC ;
Tan, CF ;
Huang, SF ;
Yu, CT .
CLINICAL RADIOLOGY, 2003, 58 (08) :630-635
[10]
PULMONARY NODULES - IMPROVED DETECTION WITS VASCULAR SEGMENTATION AND EXTRACTION WITH SPIRAL CT [J].
CROISILLE, P ;
SOUTO, M ;
COVA, M ;
WOOD, S ;
AFEWORK, Y ;
KUHLMAN, JE ;
ZERHOUNI, EA .
RADIOLOGY, 1995, 197 (02) :397-401