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Reproducibility Analysis of Radiomic Features from T2-weighted MRI after Processing and Segmentation Alternations in Neuroblastoma Tumors.

Diana Veiga-CanutoMatías Fernández PatónLeonor Cerdà AlberichAna Jiménez PastorArmando Gomis-MayaJose Miguel Carot SierraCinta Sangüesa NebotBlanca Martínez de Las HerasUlrike PötschgerSabine Taschner-MandlEmanuele NeriAdela Cañete NietoRuth LadensteinBarbara HeroÁngel Alberich-BayarriLuis Martí-Bonmatí
Published in: Radiology. Artificial intelligence (2024)
"Just Accepted" papers have undergone full peer review and have been accepted for publication in Radiology: Artificial Intelligence . This article will undergo copyediting, layout, and proof review before it is published in its final version. Please note that during production of the final copyedited article, errors may be discovered which could affect the content. Purpose To evaluate the reproducibility of radiomics features extracted from T2-weighted MRI in patients with neuroblastoma. Materials and Methods A retrospective study included 419 patients (mean (SD) age, 29 (34) years; 220 male, 199 female) with neuroblastic tumors, diagnosed between 2002-2023, within the scope of the PRIMAGE-project, involving 746 MRI T2/T2*-weighted sequences at diagnosis and/or after initial chemotherapy. Images underwent processing steps (denoising, inhomogeneity bias field correction, normalization, and resampling). Tumors were automatically segmented and 107 shape, first-order and second-order radiomic features were extracted, considered as the reference standard. Subsequently, the previous image processing settings were modified, and volumetric masks were applied. New radiomics features were extracted and compared with the reference standard. Reproducibility was assessed using the concordance correlation coefficient (CCC), intrasubject repeatability was measured using the coefficient of variation (CoV). Results When normalization was omitted, only 5% of the radiomics features demonstrated high reproducibility. Statistical analysis revealed significant changes in the normalization and resampling processes ( P < .001). Inhomogeneities removal had the least impact on radiomics (83% of parameters remained stable). Shape features remained stable after mask modifications, with a CCC > 0.90. Mask modifications were the most favorable changes for achieving high CCC values, with stability of 70% of the radiomics features. Only 7% of second-order radiomics features showed an excellent CoV of < 0.10. Conclusion Modifications in the T2-weighted MRI preparation process in patients with neuroblastoma resulted in changes in radiomics features, with normalization identified as the most influential factor for reproducibility. Inhomogeneities removal had the least impact on radiomics features. ©RSNA, 2024.
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