Improved marking and characterizing of pulmonary nodules on digital radiographs using a computer-aided diagnosis system.
OBJECTIVE
To evaluate and reduce inter-observer variations in the detection and characterization of pulmonary nod-ules on digital radiograph (DR) chest images.


METHODS
Two hundreds and thirty-two new posterior-anterior DR chest images were collected from out-patient screening patients. Consensus was reached by two experienced radiologists on the marking, rating, and segmentation of small actionable nodules ranged from 5 to 15 mm in diameter using a computer-aided diagnosis (CAD) system. Both their own nodule findings and the computer's automatic nodule detection results were analyzed to make the consensus. Nodules identified together with corresponding likelihood rating and segmentation results were referred as "Gold Standard". Two un-experienced radiologists were asked to first mark and characterize suspicious nodules independently, then were allowed to consult the computer nodule detection results and change their decisions.


RESULTS
Large inter-observer variations in pulmonary nodule identification and characterization on DR chest images were observed between un-experienced radiologists. Un-experienced radiologists could greatly benefit from the CAD system, including substantial decrease of inter-observer variation and improvement of nodule detection rates. Moreover, radiologists with different levels of skillfulness could achieve similar high level performance after using the CAD system.


CONCLUSIONS
The CAD system shows a high potential for providing a valuable assistance to the examination of DR chest images.
Song
Wei
W
Department of Radiology, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100730.
Xu
Ying
Y
Xie
Yong-ming
YM
Fan
Li
L
Qian
Jian-zhong
JZ
Jin
Zheng-yu
ZY
D003936:Diagnosis, Computer-Assisted; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D011856:Radiographic Image Enhancement