Detection of Small Peripheral Lung Cancer by Digital Chest Radiography

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Abstract
Purpose: To clarify whether processed digital chest radiography can improve the detection rate for small peripheral lung cancer. 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. 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 (ppConclusion: 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.

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