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Association of visual and quantitative heterogeneity of 18F-FDG PET images with treatment response in locally advanced rectal cancer: A feasibility study.

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dc.affiliation.dptoUC3M. Departamento de Bioingenieríaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Biomedical Imaging and Instrumentation Groupes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: BSEL - Laboratorio de Ciencia e Ingeniería Biomédicaes
dc.contributor.authorMartín-González, Paula
dc.contributor.authorGómez de Mariscal, Estíbaliz
dc.contributor.authorMartino, M. Elena
dc.contributor.authorMacías Gordaliza, Pedro
dc.contributor.authorPeligros, Isabel
dc.contributor.authorCarreras, José Luis
dc.contributor.authorCalvo, Felipe A
dc.contributor.authorPascau González-Garzón, Javier
dc.contributor.authorDesco Menéndez, Manuel
dc.contributor.authorMuñoz Barrutia, María Arrate
dc.contributor.funderEuropean Commissionen
dc.contributor.funderMinisterio de Economía y Competitividad (España)es
dc.date.accessioned2021-03-02T09:11:12Z
dc.date.available2021-03-02T09:11:12Z
dc.date.issued2020-11-30
dc.description.abstractBackground and purposeFew tools are available to predict tumor response to treatment. This retrospective study assesses visual and automatic heterogeneity from 18F-FDG PET images as predictors of response in locally advanced rectal cancer.MethodsThis study included 37 LARC patients who underwent an 18F-FDG PET before their neoadjuvant therapy. One expert segmented the tumor from the PET images. Blinded to the patient¿s outcome, two experts established by consensus a visual score for tumor heterogeneity. Metabolic and texture parameters were extracted from the tumor area. Multivariate binary logistic regression with cross-validation was used to estimate the clinical relevance of these features. Area under the ROC Curve (AUC) of each model was evaluated. Histopathological tumor regression grade was the ground-truth.ResultsStandard metabolic parameters could discriminate 50.1% of responders (AUC = 0.685). Visual heterogeneity classification showed correct assessment of the response in 75.4% of the sample (AUC = 0.759). Automatic quantitative evaluation of heterogeneity achieved a similar predictive capacity (73.1%, AUC = 0.815).ConclusionA response prediction model in LARC based on tumor heterogeneity (assessed either visually or with automatic texture measurement) shows that texture features may complement the information provided by the metabolic parameters and increase prediction accuracy.en
dc.description.sponsorshipThis work was partially supported by the Spanish Ministry of Economy and Competitiveness (TEC2016–78052-R, PID2019-109820RB-I00) (to AMB) and TEC2013-48251-C2 (to JP), Instituto de Salud Carlos III and European Regional Development Fund (FEDER) Funds from the European Commission, “A way of making Europe” (PI15/02121) and a Leonardo grant to Researchers and Cultural Creators 2017, BBVA Foundation (to AMB). PMG is supported by ‘Beca de Colaboración’ of the Spanish Ministry of Education, Culture and Sports. The CNIC is supported by the Ministry of Economy, Industry and Competitiveness (MEIC) and the Pro CNIC Foundation, and is a Severo Ochoa Center of Excellence (SEV-2015-0505).en
dc.format.extent18
dc.identifier.bibliographicCitationMartín-González, P., Mariscal E. G., Martino, M. E., Gordaliza, P.M., Peligros, I., Carreras, J.L., ..., Muñoz Barrutia, A. (2020) Association of visual and quantitative heterogeneity of 18F-FDG PET images with treatment response in locally advanced rectal cancer: A feasibility study. PLoS ONE, 15(11), e0242597.en
dc.identifier.doihttps://doi.org/10.1371/journal.pone.0242597
dc.identifier.issn1932-6203
dc.identifier.publicationfirstpagee0242597
dc.identifier.publicationissue11
dc.identifier.publicationtitlePLoS Oneen
dc.identifier.publicationvolume15
dc.identifier.urihttps://hdl.handle.net/10016/32064
dc.identifier.uxxiAR/0000026497
dc.language.isoengen
dc.publisherJason Chia-Hsun Hsieh, Chang Gung Memorial Hospital at Linkou, TAIWANen
dc.relation.projectIDGobierno de España. TEC2016–78052-Res
dc.relation.projectIDGobierno de España. PID2019-109820RB-I00es
dc.relation.projectIDGobierno de España. TEC2013-48251-C2es
dc.rights© 2020 Martín-González et al.es
dc.rightsAtribución 3.0 España*
dc.rights.accessRightsopen access
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.titleAssociation of visual and quantitative heterogeneity of 18F-FDG PET images with treatment response in locally advanced rectal cancer: A feasibility study.en
dc.typeresearch article*
dc.type.hasVersionVoR*
dspace.entity.typePublication
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