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13 results on '"Martínez de las Heras, Blanca"'

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

Author

Veiga-Canuto, Diana, primary, Fernández-Patón, Matías, additional, Cerdà Alberich, Leonor, additional, Jiménez Pastor, Ana, additional, Gomis Maya, Armando, additional, Carot Sierra, Jose Miguel, additional, Sangüesa Nebot, Cinta, additional, Martínez de las Heras, Blanca, additional, Pötschger, Ulrike, additional, Taschner-Mandl, Sabine, additional, Neri, Emanuele, additional, Cañete, Adela, additional, Ladenstein, Ruth, additional, Hero, Barbara, additional, Alberich-Bayarri, Ángel, additional, and Martí-Bonmatí, Luis, additional

Published
2024
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5. Independent Validation of a Deep Learning nnU-Net Tool for Neuroblastoma Detection and Segmentation in MR Images

Author

Veiga-Canuto, Diana, primary, Cerdà-Alberich, Leonor, additional, Jiménez-Pastor, Ana, additional, Carot Sierra, José Miguel, additional, Gomis-Maya, Armando, additional, Sangüesa-Nebot, Cinta, additional, Fernández-Patón, Matías, additional, Martínez de las Heras, Blanca, additional, Taschner-Mandl, Sabine, additional, Düster, Vanessa, additional, Pötschger, Ulrike, additional, Simon, Thorsten, additional, Neri, Emanuele, additional, Alberich-Bayarri, Ángel, additional, Cañete, Adela, additional, Hero, Barbara, additional, Ladenstein, Ruth, additional, and Martí-Bonmatí, Luis, additional

Published
2023
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6. PRIMAGE project: predictive in silico multiscale analytics to support childhood cancer personalised evaluation empowered by imaging biomarkers

Author

Martí-Bonmatí, Luis, Alberich-Bayarri, Ángel, Ladenstein, Ruth, Blanquer, Ignacio, Segrelles, J. Damian, Cerdá-Alberich, Leonor, Gkontra, Polyxeni, Hero, Barbara, García-Aznar, J. M., Keim, Daniel, Jentner, Wolfgang, Seymour, Karine, Jiménez-Pastor, Ana, González-Valverde, Ismael, Martínez de las Heras, Blanca, Essiaf, Samira, Walker, Dawn, Rochette, Michel, Bubak, Marian, Mestres, Jordi, Viceconti, Marco, Martí-Besa, Gracia, Cañete, Adela, Richmond, Paul, Wertheim, Kenneth Y., Gubala, Tomasz, Kasztelnik, Marek, Meizner, Jan, Nowakowski, Piotr, Gilpérez, Salvador, Suárez, Amelia, Aznar, Mario, Restante, Giuliana, and Neri, Emanuele

Published
2020
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7. Comparative Multicentric Evaluation of Inter-Observer Variability in Manual and Automatic Segmentation of Neuroblastic Tumors in Magnetic Resonance Images

Author

Veiga-Canuto, Diana, primary, Cerdà-Alberich, Leonor, additional, Sangüesa Nebot, Cinta, additional, Martínez de las Heras, Blanca, additional, Pötschger, Ulrike, additional, Gabelloni, Michela, additional, Carot Sierra, José Miguel, additional, Taschner-Mandl, Sabine, additional, Düster, Vanessa, additional, Cañete, Adela, additional, Ladenstein, Ruth, additional, Neri, Emanuele, additional, and Martí-Bonmatí, Luis, additional

Published
2022
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8. Methodological advances in the discovery of novel neuroblastoma therapeutics

Author

Segura, Miguel F., primary, Soriano, Aroa, additional, Roma, Josep, additional, Piskareva, Olga, additional, Jiménez, Carlos, additional, Boloix, Ariadna, additional, Fletcher, Jamie I., additional, Haber, Michelle, additional, Gray, Juliet C., additional, Cerdá-Alberich, Leonor, additional, Martínez de Las Heras, Blanca, additional, Cañete, Adela, additional, Gallego, Soledad, additional, and Moreno, Lucas, additional

Published
2021
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10. Methodological advances in the discovery of novel neuroblastoma therapeutics

Author

Segura, Miguel F., Soriano, Aroa, Roma, Josep, Piskareva, Olga, Jiménez, Carlos, Boloix, Ariadna, Fletcher, Jamie I., Haber, Michelle, Gray, Juliet C., Cerdá-Alberich, Leonor, Martínez de Las Heras, Blanca, Cañete, Adela, Gallego, Soledad, and Moreno, Lucas

Abstract

ABSTRACTIntroductionNeuroblastoma is a cancer of the sympathetic nervous system that causes up to 15% of cancer-related deaths among children. Among the ~1,000 newly diagnosed cases per year in Europe, more than half are classified as high-risk, with a 5-year survival rate <50%. Current multimodal treatments have improved survival among these patients, but relapsed and refractory tumors remain a major therapeutic challenge. A number of new methodologies are paving the way for the development of more effective and safer therapies to ultimately improve outcomes for high-risk patients.Areas coveredThe authors provide a critical review on methodological advances aimed at providing new therapeutic opportunities for neuroblastoma patients, including preclinical models of human disease, generation of omics data to discover new therapeutic targets, and artificial intelligence-based technologies to implement personalized treatments.Expert opinionWhile survival of childhood cancer has improved over the past decades, progress has been uneven. Still, survival is dismal for some cancers, including high-risk neuroblastoma. Embracing new technologies (e.g. molecular profiling of tumors, 3D in vitromodels, etc.), international collaborative efforts and the incorporation of new therapies (e.g. RNA-based therapies, epigenetic therapies, immunotherapy) will ultimately lead to more effective and safer therapies for these subgroups of neuroblastoma patients.

Published
2022
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13. Reproducibility Analysis of Radiomic Features on T2-weighted MR Images after Processing and Segmentation Alterations in Neuroblastoma Tumors.

Author

Veiga-Canuto D, Fernández-Patón M, Cerdà Alberich L, Jiménez Pastor A, Gomis Maya A, Carot Sierra JM, Sangüesa Nebot C, Martínez de Las Heras B, Pötschger U, Taschner-Mandl S, Neri E, Cañete A, Ladenstein R, Hero B, Alberich-Bayarri Á, and Martí-Bonmatí L

Subjects
Humans, Male, Female, Retrospective Studies, Reproducibility of Results, Child, Preschool, Child, Infant, Image Interpretation, Computer-Assisted methods, Radiomics, Neuroblastoma diagnostic imaging, Neuroblastoma pathology, Magnetic Resonance Imaging methods
Abstract

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 < .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. Keywords: Pediatrics, MR Imaging, Oncology, Radiomics, Reproducibility, Repeatability, Neuroblastic Tumors Supplemental material is available for this article. © RSNA, 2024 See also the commentary by Safdar and Galaria in this issue.

Published
2024
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