Lung nodule conspicuity using unsharp mask filters with storage-phosphor-based computed radiography.
OBJECTIVE
To compare the performance of various types of unsharp mask filter applied in storage-phosphor-based computed radiography (SR), and to improve the detection of faint nodules of the lung cancer type.


METHODS
A total of 120 SR radiographs were obtained by means of an anthropomorphous chest phantom and a combination of 3 types of small simulated nodule (5-mm sphere-shaped, and 5-mm and 10-mm hemisphere-shaped) placed on the phantom's surface. Eight combinations of nodule site were selected from 16 predetermined chosen sites, and 5 types of parameter were used for unsharp mask filtering. Eight observers evaluated the images, and the detectability of the lung nodules was evaluated from the images by a ROC analysis.


RESULTS
The visibility of the 10-mm hemispherical nodules was nearly equivalent at each site when 5 types of unsharp mask filter were used. The detection of the 5-mm nodules with mid-frequency suppressing and very-low-frequency enhancing filters was better than with a conventional (department standard) mid-frequency enhancing filter.


CONCLUSIONS
Mid-frequency suppressing versions of the filter helped to demonstrate faint nodular opacity, which is often shown by early bronchogenic carcinoma. This filter could replace conventional filters in the detection of lung nodules.
Li
F
F
Department of Radiology, Shinshu University School of Medicine, Matsumoto, Japan.
Sone
S
S
Kiyono
K
K
D002283:Carcinoma, Bronchogenic / Q000000981:diagnostic imaging*; D005374:Filtration / Q000295:instrumentation / Q000379:methods; D006801:Humans; D008168:Lung / Q000000981:diagnostic imaging; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D015588:Observer Variation; D019047:Phantoms, Imaging; D011856:Radiographic Image Enhancement / Q000295:instrumentation / Q000379:methods; D003074:Solitary Pulmonary Nodule / Q000000981:diagnostic imaging*; D014057:Tomography, X-Ray Computed / Q000295:instrumentation* / Q000379:methods / Q000706:statistics & numerical data