English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

In this study we investigated the repeatability and reproducibility ofradiomic features extracted from MRI images and provide a workflow to identifyrobust features. 2D and 3D T$_2$-weighted images of a pelvic phantom wereacquired on three scanners of two manufacturers and two magnetic fieldstrengths. The repeatability and reproducibility of the radiomic features wereassessed respectively by intraclass correlation coefficient (ICC) andconcordance correlation coefficient (CCC), considering repeated acquisitionswith or without phantom repositioning, and with different scanner/acquisitiontype, and acquisition parameters. The features showing ICC/CCC > 0.9 wereselected, and their dependence on shape information (Spearman's $\rho$> 0.8)was analyzed. They were classified for their ability to distinguish textures,after shuffling voxel intensities. From 944 2D features, 79.9% to 96.4% showedexcellent repeatability in fixed position across all scanners. Much lower range(11.2% to 85.4%) was obtained after phantom repositioning. 3D extraction didnot improve repeatability performance. Excellent reproducibility betweenscanners was observed in 4.6% to 15.6% of the features, at fixed imagingparameters. 82.4% to 94.9% of features showed excellent agreement whenextracted from images acquired with TEs 5 ms apart (values decreased whenincreasing TE intervals) and 90.7% of the features exhibited excellentreproducibility for changes in TR. 2.0% of non-shape features were identifiedas providing only shape information. This study demonstrates that radiomicfeatures are affected by specific MRI protocols. The use of our radiomic pelvicphantom allowed to identify unreliable features for radiomic analysis onT$_2$-weighted images. This paper proposes a general workflow to identifyrepeatable, reproducible, and informative radiomic features, fundamental toensure robustness of clinical studies.

A multicenter study on radiomic features from T$_2$-weighted images of a  customized MR pelvic phantom setting the basis for robust radiomic models in  clinics