Diffuse nodular lung disease on chest radiographs: a pilot study of characterization by fractal dimension.
OBJECTIVE
We present a computer-aided diagnostic technique for identifying nodular interstitial lung disease on chest radiographs. The fractal dimension was used as a numerical measure of image texture on digital chest radiographs to distinguish patients with normal lung from those with a diffuse nodular interstitial abnormality.


METHODS
Twenty digitized chest radiographs were classified as normal (n = 10) or as containing diffuse nodular abnormality (n = 10) on the basis of readings assigned according to the classification of the International Labour Organization. Regions of interest (ROIs) measuring 1.28 cm2 were selected from the intercostal spaces of these radiographs. The fractal dimension of these ROIs was estimated by power spectrum analysis. The cases were not subtle.


RESULTS
The fractal dimension provided statistically significant discrimination between normal parenchyma and nodular interstitial lung disease. The area under the receiver operating characteristic curve was 0.90 (+/- 0.02). One operating point provides sensitivity of 88% with a specificity of 80%.


CONCLUSIONS
The fractal dimension can provide a measure of lung parenchymal texture and shows promise as an element of computer-aided diagnosis, characterization, and follow-up of interstitial lung disease.
Department of Radiology (DUMC3949), Duke University, Medical Center, Durham, NC 27710, USA.
C E
CE
Floyd
E F
EF
Patz
J Y
JY
Lo
N F
NF
Vittitoe
L E
LE
Stambaugh
D017709:Fractals; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008168:Lung / Q000000981:diagnostic imaging; D017563:Lung Diseases, Interstitial / Q000000981:diagnostic imaging*; D015588:Observer Variation; D010865:Pilot Projects; D012372:ROC Curve; D011856:Radiographic Image Enhancement; D013902:Radiography, Thoracic / Q000379:methods; D012680:Sensitivity and Specificity