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Reproducibility Analysis of Radiomic Features on T2-weighted MR Images after Processing and Segmentation Alterations in Neuroblastoma Tumors

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Reproducibility Analysis of Radiomic Features on T2-weighted MR Images after Processing and Segmentation Alterations in Neuroblastoma Tumors

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dc.contributor.author Veiga Canuto, Diana es_ES
dc.contributor.author Fernandez Patón, Matías es_ES
dc.contributor.author Cerdá-Alberich, Leonor es_ES
dc.contributor.author Jimenez-Pastor, Ana Maria es_ES
dc.contributor.author Gomis Maya, Armando es_ES
dc.contributor.author Carot Sierra, José Miguel es_ES
dc.contributor.author Sanguesa Nebot, Cinta es_ES
dc.contributor.author Martínez de las Heras, Blanca es_ES
dc.contributor.author Pötschger, Ulrike es_ES
dc.contributor.author Taschner-Mandl, Sabine es_ES
dc.contributor.author Neri, Emanuele es_ES
dc.contributor.author Cañete, Adela es_ES
dc.contributor.author Ladenstein, Ruth es_ES
dc.contributor.author Hero, Barbara es_ES
dc.contributor.author Alberich-Bayarri, Ángel es_ES
dc.contributor.author Martí-Bonmatí, Luis es_ES
dc.date.accessioned 2024-10-24T18:03:29Z
dc.date.available 2024-10-24T18:03:29Z
dc.date.issued 2024-07 es_ES
dc.identifier.uri http://hdl.handle.net/10251/210863
dc.description.abstract [EN] Purpose: To evaluate the reproducibility of radiomics features extracted from T2-weighted MR images in patients with neuroblastoma. Materials and Methods: A retrospective study included 419 patients (mean age, 29 months +/- 34 [SD]; 220 male, 199 female) with neuroblastic tumors diagnosed between 2002 and 2023, within the scope of the PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers (ie, PRIMAGE) project, involving 746 T2/T2*-weighted MRI 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 radiomics 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 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 greater than 0.90. Mask modifications were the most favorable changes for achieving high CCC values, with a radiomics features stability of 70%. Only 7% of second-order radiomics features showed an excellent CoV of less than 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. es_ES
dc.description.sponsorship This project has received funding from the European Union Horizon 2020 research and innovation program under grant agreement number 826494. This study was funded by PRIMAGE (PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers), a Horizon 408 2020 research and innovation action project (topic SC1-DTH-07-2018), grant agreement number 826494. es_ES
dc.language Inglés es_ES
dc.publisher Radiological Society of North America es_ES
dc.relation.ispartof RADIOLOGY-ARTIFICIAL INTELLIGENCE es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Pediatrics es_ES
dc.subject MR Imaging es_ES
dc.subject Oncology es_ES
dc.subject Radiomics es_ES
dc.subject Reproducibility es_ES
dc.subject Repeatability es_ES
dc.subject Neuroblastic tumors es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Reproducibility Analysis of Radiomic Features on T2-weighted MR Images after Processing and Segmentation Alterations in Neuroblastoma Tumors es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1148/ryai.230208 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/826494/EU/PRedictive In-silico Multiscale Analytics to support cancer personalized diaGnosis and prognosis, Empowered by imaging biomarkers/ es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Escuela Técnica Superior de Ingenieros Industriales - Escola Tècnica Superior d'Enginyers Industrials es_ES
dc.description.bibliographicCitation Veiga Canuto, D.; Fernandez Patón, M.; Cerdá-Alberich, L.; Jimenez-Pastor, AM.; Gomis Maya, A.; Carot Sierra, JM.; Sanguesa Nebot, C.... (2024). Reproducibility Analysis of Radiomic Features on T2-weighted MR Images after Processing and Segmentation Alterations in Neuroblastoma Tumors. RADIOLOGY-ARTIFICIAL INTELLIGENCE. 6(4). https://doi.org/10.1148/ryai.230208 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1148/ryai.230208 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 6 es_ES
dc.description.issue 4 es_ES
dc.identifier.eissn 2638-6100 es_ES
dc.identifier.pmid 38864742 es_ES
dc.identifier.pmcid PMC11294951 es_ES
dc.relation.pasarela S\527290 es_ES
dc.contributor.funder European Commission es_ES


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