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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 |