Detección automática de nódulos pulmonares en tomografía computarizada. Un estudio preliminar

Abstract

Recent years have seen growing interest in the development of algorithms for computer-assisted diagnosis (CAD) for the detection of pulmonary nodules on both plain-film radiographs and computed tomography (CT) studies. The purpose of CAD algorithms in this context is to alert radiologists to suspicious radioopacities that might represent cancer in the images. We are developing a CAD system for the detection of pulmonary nodules on helical CT images. We collected cases of patients with pulmonary nodules examined with helical CT. A total of 64 nodules, including both calcified and noncalcified lesions, ranging from 3 to 30 mm in diameter were included in the study. Studies were acquired on one 4-slice and one 64-slice CT scanners. Three chest radiologists at two institutions interpreted the studies to determine whether pulmonary nodules were present. We calculated the sensitivity and the number of false positives per image to evaluate the CAD system. We have developed and evaluated an algorithm for the automatic detection of pulmonary nodules on CT images. For a sensitivity of 76%, the false-positive rate was 1.3 per image. Our preliminary results suggest that the system might be useful for radiologists in the detection of pulmonary nodules on helical CT images.