Abstract
The publisher regrets to miss the abstract of the above article. Please find the details below: Abstract Background. Radiomics has emerged as a promising tool for extracting large amounts of quantitative features from conventional biomedical imaging. Multicentre studies have investigated reproducibility and repeatability of radiomic features for different approaches in acquisition and image reconstruction for several imaging modalities. This study aimed to compare the impact of scanners and centre-specific parameter settings on the radiomic features calculated on images of a phantom. Methods. This is a MRI multicentre phantom study gathering ten centres and 19 scanners of the Italian “Alleanza contro il Cancro” network. The participant centres were asked to acquire repeated T2-weighted images of a dedicated pelvis-shaped phantom filled with silicon oil with four embedded inserts filled with polyethylene spheres and an agar solution, resulting in different heterogeneity textures. Each centre acquired the images using the local protocol for female pelvis investigation. For each MRI acquisition, radiomic features were extracted with and without image preprocessing. Results. Feature repeatability was assessed by calculating the coefficient of variation, while the agreement between different scanners was evaluated through the intraclass correlation coefficient. The coefficient of variation was lower than 7% for all the families of features and turned out to be unaffected by image preprocessing. Most families of features showed higher reproducibility when images underwent the preprocessing steps typically employed in an MR radiomic study. Discussion. Preliminary tests on phantoms can be preparatory to multicenter clinical radiomic studies to quantify the inherent variability in feature extraction due to the use of different MR scanners, sequences and image processing. The publisher would like to apologise for any inconvenience caused.
| Original language | English |
|---|---|
| Pages (from-to) | N/A-N/A |
| Journal | Physica Medica |
| Volume | 132 |
| Issue number | 132 |
| DOIs | |
| Publication status | Published - 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Biophysics
- Radiology Nuclear Medicine and imaging
- General Physics and Astronomy
Keywords
- Radiomic features
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