dc.contributor.author | Chiesa Estomba, Carlos Miguel | |
dc.contributor.author | Echaniz Beneitez, Oier | |
dc.contributor.author | Larruscain Sarasola, Ekhiñe | |
dc.contributor.author | González García, José Ángel | |
dc.contributor.author | Sistiaga Suárez, Jon Alexander | |
dc.contributor.author | Graña Romay, Manuel María | |
dc.date.accessioned | 2020-01-15T08:28:32Z | |
dc.date.available | 2020-01-15T08:28:32Z | |
dc.date.issued | 2019-09-20 | |
dc.identifier.citation | Cancers 11(10) : (2019) // Article ID 1409 | es_ES |
dc.identifier.issn | 2072-6694 | |
dc.identifier.uri | http://hdl.handle.net/10810/38464 | |
dc.description.abstract | Radiomics and texture analysis represent a new option in our biomarkers arsenal. These techniques extract a large number of quantitative features, analyzing their properties to incorporate them in clinical decision-making. Laryngeal cancer represents one of the most frequent cancers in the head and neck area. We hypothesized that radiomics features can be included as a laryngeal cancer precision medicine tool, as it is able to non-invasively characterize the overall tumor accounting for heterogeneity, being a prognostic and/or predictive biomarker derived from routine, standard of care, imaging data, and providing support during the follow up of the patient, in some cases avoiding the need for biopsies. The larynx represents a unique diagnostic and therapeutic challenge for clinicians due to its complex tridimensional anatomical structure. Its complex regional and functional anatomy makes it necessary to enhance our diagnostic tools in order to improve decision-making protocols, aimed at better survival and functional results. For this reason, this technique can be an option for monitoring the evolution of the disease, especially in surgical and non-surgical organ preservation treatments. This concise review article will explain basic concepts about radiomics and discuss recent progress and results related to laryngeal cancer. | es_ES |
dc.language.iso | eng | es_ES |
dc.publisher | MDPI | es_ES |
dc.rights | info:eu-repo/semantics/openAccess | es_ES |
dc.rights.uri | http://creativecommons.org/licenses/by/3.0/es/ | * |
dc.subject | larynx | es_ES |
dc.subject | cancer | es_ES |
dc.subject | radiomics | es_ES |
dc.subject | texture analysis | es_ES |
dc.subject | cell lung-cancer | es_ES |
dc.subject | local tumor-control | es_ES |
dc.subject | prognostic value | es_ES |
dc.subject | pet radiomics | es_ES |
dc.subject | response prediction | es_ES |
dc.subject | CT texture | es_ES |
dc.subject | head | es_ES |
dc.subject | images | es_ES |
dc.subject | heterogeneity | es_ES |
dc.subject | survival | es_ES |
dc.title | Radiomics and Texture Analysis in Laryngeal Cancer. Looking for New Frontiers in Precision Medicine through Imaging Analysis | es_ES |
dc.type | info:eu-repo/semantics/article | es_ES |
dc.rights.holder | This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0) | es_ES |
dc.rights.holder | Atribución 3.0 España | * |
dc.relation.publisherversion | https://www.mdpi.com/2072-6694/11/10/1409 | es_ES |
dc.identifier.doi | 10.3390/cancers11101409 | |
dc.departamentoes | Ciencia de la computación e inteligencia artificial | es_ES |
dc.departamentoeu | Konputazio zientziak eta adimen artifiziala | es_ES |