2020
DOI: 10.1002/mp.14038
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T2w‐MRI signal normalization affects radiomics features reproducibility

Abstract: Purpose: Despite its increasing application, radiomics has not yet demonstrated a solid reliability, due to the difficulty in replicating analyses. The extraction of radiomic features from clinical MRI (T1w/T2w) presents even more challenges because of the absence of well-defined units (e.g. HU). Some preprocessing steps are required before the estimation of radiomic features and one of this is the intensity normalization, that can be performed using different methods. The aim of this work was to evaluate the … Show more

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Cited by 97 publications
(77 citation statements)
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“…Nevertheless, post‐acquisition image processing, such as image coregistration, interpolation, intensity discretization and normalization, filtering and segmentation, is also important and necessary for applying radiomics in clinical use, and could greatly impact the feature repeatability in addition to image acquisition. Much more studies have been conducted to investigate the impact of post‐acquisition image processing on the radiomics repeatability 16–19,55–58 . It is desirable to identify those features that are repeatable and robust to both image acquisition and post‐acquisition processing.…”
Section: Discussionmentioning
confidence: 99%
“…Nevertheless, post‐acquisition image processing, such as image coregistration, interpolation, intensity discretization and normalization, filtering and segmentation, is also important and necessary for applying radiomics in clinical use, and could greatly impact the feature repeatability in addition to image acquisition. Much more studies have been conducted to investigate the impact of post‐acquisition image processing on the radiomics repeatability 16–19,55–58 . It is desirable to identify those features that are repeatable and robust to both image acquisition and post‐acquisition processing.…”
Section: Discussionmentioning
confidence: 99%
“…Variation in imaging acquisition parameters, and preprocessing techniques have shown a significant effect on imaging feature calculations, not only affecting their reproducibility, but also making the features inconsistent within a single dataset. Where appropriate, methods for intensity standardization, such as through referencing of healthy tissue, or more robust methods based on statistical learning, should be considered [90].…”
Section: Feature Reproducibilitymentioning
confidence: 99%
“…To our knowledge, this is the first study systematically investigating the effects of intensity standardization in head and neck region imaging. Moreover, while many MRI intensity standardization studies implement test-retest data for individual patients to determine the effects of standardization 29,38,[46][47][48] , our analysis is unique by investigating the impact of standardization within a given cohort of patients. We propose this approach is more relevant to downstream cohort-level model construction often implemented in quantitative imaging studies.…”
Section: Discussionmentioning
confidence: 99%