Detection of Small Peripheral Lung Cancer by Digital Chest Radiography

<jats:p> Purpose: To clarify whether processed digital chest radiography can improve the detection rate for small peripheral lung cancer. </jats:p><jats:p> Material and Methods: Five radiologists independently interpreted 54 digitized chest radiographs of 18 patients with small peripheral lung cancers measuring less than 20 mm, which were displayed following 3 types of digital processing: 1) an original version; 2) unsharp mask processing with a type 1 filter (very low-frequency-enhancing, mid-frequency-suppressing, and high-frequency-enhancing filter); and 3) unsharp mask processing with a type 2 filter (very low— and high-frequency-enhancing filter). A total of 1,620 pooled observations were evaluated by receiver operating characteristic (ROC) analysis. </jats:p><jats:p> Results: the mean area under the ROC curves was 0.68 for the type 1 filter, 0.68 for the type 2 filter, and 0.65 for the unprocessed (original) image. There were no statistically significant differences among these 3 kinds of image processing ( p>0.05). In all types of images, the small lung cancer with an alveolar lining tumor growth was less visible than a solid tumor growth ( p<0.01); the sensitivity increased with tumor size when the 3 groups of cancers, those measuring less than 10 mm, 11–15 mm, and 16–20 mm, were compared ( p<0.01). </jats:p><jats:p> Conclusion: Unsharp mask-image processing of digital chest radiography will not improve the detection rate of small peripheral lung cancer, probably due to a substantial drawback: the limited conspicuity of cancer lesions in the surrounding lung and superposition of structures. </jats:p>