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A method for comparing intra-tumoural radioactivity uptake heterogeneity in preclinical positron emission tomography studies.

Grafström J, Ahlzén HS, Stone-Elander S - EJNMMI Phys (2015)

Bottom Line: Histograms visualising the spread and frequency of contributions to the heterogeneity were also generated.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.

View Article: PubMed Central - PubMed

Affiliation: Division of Biochemistry, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-17177, Stockholm, Sweden. hannastina@gmail.com.

ABSTRACT

Background: Non-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.

Methods: The 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.

Results: Using 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.

Conclusions: The 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.

No MeSH data available.


Related in: MedlinePlus

PET transaxial images (a, b, the colour scales are the same), histograms (c, d) of the heterogeneity contributions (the mean intensity deviation per distance calculated according to Eq. 2) and surface plots (e, f) of the uptake of AnxA5 and mTrx-GFP in a FaDu xenograft. The imaging was performed in the same animal >2 h apart on the same day. In e and f, the X- and Y-axes represent spatial dimensions and the Z-axis is the mean tracer uptake (SUVmean)
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Fig3: PET transaxial images (a, b, the colour scales are the same), histograms (c, d) of the heterogeneity contributions (the mean intensity deviation per distance calculated according to Eq. 2) and surface plots (e, f) of the uptake of AnxA5 and mTrx-GFP in a FaDu xenograft. The imaging was performed in the same animal >2 h apart on the same day. In e and f, the X- and Y-axes represent spatial dimensions and the Z-axis is the mean tracer uptake (SUVmean)

Mentions: Both the maximum uptake (SUVmax) and the mean uptake (SUVmean) for AnxA5 were higher than for mTrx-GFP (2.67 and 1.76 vs. 1.95 and 1.13, respectively). In the two images through one plane (Fig. 3a, b or, alternatively, Fig. 3e, f) the uptake of mTrx-GFP appeared varied and patchy while that of AnxA5 was more uniformly distributed throughout the tumour. The uptake of mTrx-GFP showed more deviations from the mean (i.e. more frequent and larger peak-to-valley variations). Applying the algorithm, the HF for mTrx-GFP was calculated to be about 85 % higher than that for AnxA5. The plots of the histograms of the heterogeneity contributions in the whole tumour volume (Fig. 3c, d) illustrate that there are more deviations from the mean or a larger frequency in the deviations for mTrx-GFP compared to AnxA5.Fig. 3


A method for comparing intra-tumoural radioactivity uptake heterogeneity in preclinical positron emission tomography studies.

Grafström J, Ahlzén HS, Stone-Elander S - EJNMMI Phys (2015)

PET transaxial images (a, b, the colour scales are the same), histograms (c, d) of the heterogeneity contributions (the mean intensity deviation per distance calculated according to Eq. 2) and surface plots (e, f) of the uptake of AnxA5 and mTrx-GFP in a FaDu xenograft. The imaging was performed in the same animal >2 h apart on the same day. In e and f, the X- and Y-axes represent spatial dimensions and the Z-axis is the mean tracer uptake (SUVmean)
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4562910&req=5

Fig3: PET transaxial images (a, b, the colour scales are the same), histograms (c, d) of the heterogeneity contributions (the mean intensity deviation per distance calculated according to Eq. 2) and surface plots (e, f) of the uptake of AnxA5 and mTrx-GFP in a FaDu xenograft. The imaging was performed in the same animal >2 h apart on the same day. In e and f, the X- and Y-axes represent spatial dimensions and the Z-axis is the mean tracer uptake (SUVmean)
Mentions: Both the maximum uptake (SUVmax) and the mean uptake (SUVmean) for AnxA5 were higher than for mTrx-GFP (2.67 and 1.76 vs. 1.95 and 1.13, respectively). In the two images through one plane (Fig. 3a, b or, alternatively, Fig. 3e, f) the uptake of mTrx-GFP appeared varied and patchy while that of AnxA5 was more uniformly distributed throughout the tumour. The uptake of mTrx-GFP showed more deviations from the mean (i.e. more frequent and larger peak-to-valley variations). Applying the algorithm, the HF for mTrx-GFP was calculated to be about 85 % higher than that for AnxA5. The plots of the histograms of the heterogeneity contributions in the whole tumour volume (Fig. 3c, d) illustrate that there are more deviations from the mean or a larger frequency in the deviations for mTrx-GFP compared to AnxA5.Fig. 3

Bottom Line: Histograms visualising the spread and frequency of contributions to the heterogeneity were also generated.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.

View Article: PubMed Central - PubMed

Affiliation: Division of Biochemistry, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, SE-17177, Stockholm, Sweden. hannastina@gmail.com.

ABSTRACT

Background: Non-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.

Methods: The 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.

Results: Using 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.

Conclusions: The 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.

No MeSH data available.


Related in: MedlinePlus