What is it about?
Differentiating between aggressive and non-aggressive CT lung tumors by fractal analysis.
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Why is it important?
This paper presents the potential for fractal analysis of time sequence contrast-enhanced (CE) computed tomography (CT) images to differentiate between aggressive and nonaggressive malignant lung tumors (i.e., high and low metabolic tumors). The aim is to enhance CT tumor staging prediction accuracy through identifying malignant aggressiveness of lung tumors. As branching of blood vessels can be considered a fractal process, the research examines vascularized tumor regions that exhibit strong fractal characteristics. The analysis is performed after injecting 15 patients with a contrast agent and transforming at least 11 time sequence CE CT images from each patient to the fractal dimension and determining corresponding lacunarity. The fractal texture features were averaged over the tumor region and quantitative classification showed up to 83.3% accuracy in distinction between advanced (aggressive) and early-stage (nonaggressive) malignant tumors. Also, it showed strong correlation with corresponding lung tumor stage and standardized tumor uptake value of fluoro deoxyglucose as determined by positron emission tomography.
Perspectives
The results indicate that fractal analysis of time sequence CE CT images of malignant lung tumors could provide additional information about likely tumor aggression that could potentially impact on clinical management decisions in choosing the appropriate treatment procedure.
Dr Omar S Al-Kadi
University of Jordan
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This page is a summary of: Texture Analysis of Aggressive and Nonaggressive Lung Tumor CE CT Images, IEEE Transactions on Biomedical Engineering, July 2008, Institute of Electrical & Electronics Engineers (IEEE),
DOI: 10.1109/tbme.2008.919735.
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Texture Analysis of Aggressive and Nonaggressive Lung Tumor CE CT Images
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Texture Analysis of Aggressive and non-Aggressive Lung Tumor CE CT Images
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Software code for generating fractal dimension parametric image
The fractal dimension (FD) image is generated by considering each pixel in the original CT image as a single fractal dimension estimated from its 7x7 neighbours. The FD generated image remarkably enhances the tissue texture, and the internal subtle structures become more obvious as compared to the original CT image. This could help the physician's eyes in better delineating the tumour from the surrounding normal tissue; furthermore, the mean Fractal Dimension value of the tumour region of interest can give an indication of tumour aggressiveness. See the following reference: O. S. Al-Kadi and D. Watson, “Texture Analysis of Aggressive and non-Aggressive Lung Tumor CE CT Images,” IEEE Transactions on Biomedical Engineering, vol. 55, pp. 1822-1830, 2008.
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