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A novel phantom technique for evaluating the performance of PET auto-segmentation methods in delineating heterogeneous and irregular lesions

Overview of attention for article published in EJNMMI Physics, June 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#20 of 181)
  • Good Attention Score compared to outputs of the same age (78th percentile)
  • Average Attention Score compared to outputs of the same age and source

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Title
A novel phantom technique for evaluating the performance of PET auto-segmentation methods in delineating heterogeneous and irregular lesions
Published in
EJNMMI Physics, June 2015
DOI 10.1186/s40658-015-0116-1
Pubmed ID
Authors

B Berthon, C Marshall, R Holmes, E Spezi

Abstract

Positron Emission Tomography (PET)-based automatic segmentation (PET-AS) methods can improve tumour delineation for radiotherapy treatment planning, particularly for Head and Neck (H&N) cancer. Thorough validation of PET-AS on relevant data is currently needed. Printed subresolution sandwich (SS) phantoms allow modelling heterogeneous and irregular tracer uptake, while providing reference uptake data. This work aimed to demonstrate the usefulness of the printed SS phantom technique in recreating complex realistic H&N radiotracer uptake for evaluating several PET-AS methods. Ten SS phantoms were built from printouts representing 2mm-spaced slices of modelled H&N uptake, printed using black ink mixed with 18F-fluorodeoxyglucose, and stacked between 2mm thick plastic sheets. Spherical lesions were modelled for two contrasted uptake levels, and irregular and spheroidal tumours were modelled for homogeneous, and heterogeneous uptake including necrotic patterns. The PET scans acquired were segmented with ten custom PET-AS methods: adaptive iterative thresholding (AT), region growing, clustering applied to 2 to 8 clusters, and watershed transform-based segmentation. The difference between the resulting contours and the ground truth from the image template was evaluated using the Dice Similarity Coefficient (DSC), Sensitivity and Positive Predictive value. Realistic H&N images were obtained within 90 min of preparation. The sensitivity of binary PET-AS and clustering using small numbers of clusters dropped for highly heterogeneous spheres. The accuracy of PET-AS methods dropped between 4% and 68% for irregular lesions compared to spheres of the same volume. For each geometry and uptake modelled with the SS phantoms, we report the number of clusters resulting in optimal segmentation. Radioisotope distributions representing necrotic uptakes proved most challenging for most methods. Two PET-AS methods did not include the necrotic region in the segmented volume. Printed SS phantoms allowed identifying advantages and drawbacks of the different methods, determining the most robust PET-AS for the segmentation of heterogeneities and complex geometries, and quantifying differences across methods in the delineation of necrotic lesions. The printed SS phantom technique provides key advantages in the development and evaluation of PET segmentation methods and has a future in the field of radioisotope imaging.

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Mendeley readers

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The data shown below were compiled from readership statistics for 33 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 6%
Unknown 31 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 24%
Student > Ph. D. Student 6 18%
Other 3 9%
Student > Master 3 9%
Student > Bachelor 1 3%
Other 6 18%
Unknown 6 18%
Readers by discipline Count As %
Physics and Astronomy 14 42%
Medicine and Dentistry 5 15%
Engineering 3 9%
Social Sciences 2 6%
Computer Science 1 3%
Other 1 3%
Unknown 7 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 October 2019.
All research outputs
#4,522,371
of 22,828,180 outputs
Outputs from EJNMMI Physics
#20
of 181 outputs
Outputs of similar age
#56,922
of 263,205 outputs
Outputs of similar age from EJNMMI Physics
#4
of 7 outputs
Altmetric has tracked 22,828,180 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 181 research outputs from this source. They receive a mean Attention Score of 2.6. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 263,205 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 78% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.