Abstract
BackgroundNon-uniformity influences the interpretation of nuclear medicine based images and consequently their use in treatment planning and monitoring. However, no standardised method for evaluating and ranking heterogeneity exists. Here, we have developed a general algorithm that provides a ranking and a visualisation of the heterogeneity in small animal positron emission tomography (PET) images.MethodsThe code of the algorithm was written using the Matrix Laboratory software (MATLAB). Parameters known to influence the heterogeneity (distances between deviating peaks, gradients and size compensations) were incorporated into the algorithm. All data matrices were mathematically constructed in the same format with the aim of maintaining overview and control. Histograms visualising the spread and frequency of contributions to the heterogeneity were also generated. The construction of the algorithm was tested using mathematically generated matrices and by varying post-processing parameters. It was subsequently applied in comparisons of radiotracer uptake in preclinical images in human head and neck carcinoma and endothelial and ovarian carcinoma xenografts.ResultsUsing the developed algorithm, entire tissue volumes could be assessed and gradients could be handled in an indirect manner. Similar-sized volumes could be compared without modifying the algorithm. Analyses of the distribution of different tracers gave results that were generally in accordance with single plane preclinical images, indicating that it could appropriately handle comparisons of targeting vs. non-targeting tracers and also for different target levels. Altering the reconstruction algorithm, pixel size, tumour ROI volumes and lower cut-off limits affected the calculated heterogeneity factors in expected directions but did not reverse conclusions about which tumour was more or less heterogeneous.ConclusionsThe algorithm constructed is an objective and potentially user-friendly tool for one-to-one comparisons of heterogeneity in whole similar-sized tumour volumes in PET imaging.
Highlights
Non-uniformity influences the interpretation of nuclear medicine based images and their use in treatment planning and monitoring
We develop and examine the application of a texture-based algorithm to assess radioactivity uptake heterogeneity in planes and in the sum of planes through preclinical tumour xenografts studied with small animal positron emission tomography (PET)
The methyl-11Cradiolabelled Annexin A5, [methyl-11C]-His6-AnxA5-ST-CH3, hereafter denoted AnxA5 (~38 kDa), mutated-thioredoxin-green fluorescence protein [methyl-11C]His6-mTrx-GFP-ST-CH3, hereafter denoted mTrx-GFP (~40 kDa) and the AffibodyTM ZHER2:342 ([methyl-11C]-ZHER2:342-ST-CH3) hereafter denoted ZHER2:342 (~7 kDa) proteins had been expressed with a C-terminus selenocysteine tag (ST) and site labelled with a positron-emitting carbon-11 (11C) (t1/2 ≈ 20 min) methyl group (CH3)
Summary
Non-uniformity influences the interpretation of nuclear medicine based images and their use in treatment planning and monitoring. No standardised method for evaluating and ranking heterogeneity exists. Non-uniformity or heterogeneity in radiotracer uptake in tissues is visually perceived as areas of high as well as low uptake. Random and systematic factors such as the Poisson distribution of the radioactive decay and noise in addition to the processing parameters used to generate the images [1,2,3,4,5,6] can contribute to image heterogeneity as well as variations in uptake due to the non-homogenous features of the tissues being analysed There is no standardised method available for analysing heterogeneity
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