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Fractal analysis of CE CT lung tumours images

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posted on 2023-06-07, 14:46 authored by Omar S Al-Kadi, Des Watson
AIM The fractal dimension (FD) of a structure provides a measure of its complexity. This pilot study aims to determine FD values for lung cancers visualised on Computed Tomography (CT) and to assess the potential for tumour FD measurements to provide an index of tumour aggression. METHOD Pre-and post-contrast CT images of the thorax acquired from 15 patients with lung cancers of greater than 10mm were transformed to fractal dimension images using a box-counting algorithm at various scales. A region of interest (ROI) was determined covering tumour locations, which were more apparent on FD images as compared to images before processing. The average tumour FD (FDavg) was computed and compared with the intensity average before FD processing. FD values were correlated with 2 markers of tumour aggression: tumour stage and tumour uptake of fluorodeoxyglucose (FDG) as determined by Positron Emission Tomography. RESULTS For pre-contrast images, the tumour FDavg correlated with tumour stage (r = 0.537, p = 0.0387) and FDG uptake (r= 0.64, p< 0.001). FDavg decreased following contrast enhancement for most tumours. CONCLUSION Fractal analysis of CT images of lung tumours could potentially provide additional information about likely tumour aggression and so impact on clinical management decisions and choice of treatment.


Publication status

  • Published

Event name

9th Great British R&D Show

Event location

London, UK

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  • Informatics Publications

Full text available

  • Yes

Peer reviewed?

  • Yes

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