Wavelet compression of low-dose chest CT data: effect on lung nodule detection.

Abstract

To assess the effect of using a lossy Joint Photographic Experts Group standard for wavelet image compression, JPEG2000, on pulmonary nodule detection at low-dose computed tomography (CT). One hundred sets of lung CT data ("cases") were compressed to 30:1, 20:1, and 10:1 levels by using a wavelet-based JPEG2000 method, resulting in 400 test cases. Each case consisted of nine 1.25-mm sections that had been obtained with 20-40 mAs. Four thoracic radiologists independently interpreted the test case images. Performance was measured by using area under the receiver operating characteristic (ROC) curve (Az) and conventional sensitivity and specificity analyses. There were 51 cases with and 49 without lung nodules. Az values were 0.984, 0.988, 0.972, 0.921, respectively, for original and 10:1, 20:1, and 30:1 compressed images. Az values decreased significantly at 30:1 (P =.014) but not at 10:1 compression, with a trend toward significant decrease at 20:1 (P =.051). Specificity values were unaffected by compression (>98.0% at all compression levels). Sensitivity values were 86.3% (176 of 204 test cases with nodules), 77.9% (159 of 204 cases), 76.5% (156 of 204 cases), and 70.1% (143 of 204 cases), respectively, for original and 10:1, 20:1, and 30:1 compressed images. Results of logistic regression model analysis confirmed the significant effects of compression rate and nodule attenuation, size, and location on sensitivity (P <.05). While no reduction in nodule detection at 10:1 compression levels was demonstrated by using ROC analysis, a significant decrease in sensitivity was identified. Further investigation is needed before widespread use of image compression technology in low-dose chest CT can be recommended.