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Applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort

BACKGROUND: Predicting pathological complete response (pCR) in patients affected by locally advanced rectal cancer (LARC) who undergo neoadjuvant chemoradiotherapy (nCRT) is a challenging field of investigation, but many of the published models are burdened by a lack of reliable external validation....

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Autores principales: Boldrini, Luca, Lenkowicz, Jacopo, Orlandini, Lucia Clara, Yin, Gang, Cusumano, Davide, Chiloiro, Giuditta, Dinapoli, Nicola, Peng, Qian, Casà, Calogero, Gambacorta, Maria Antonietta, Valentini, Vincenzo, Lang, Jinyi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013126/
https://www.ncbi.nlm.nih.gov/pubmed/35428267
http://dx.doi.org/10.1186/s13014-022-02048-9
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author Boldrini, Luca
Lenkowicz, Jacopo
Orlandini, Lucia Clara
Yin, Gang
Cusumano, Davide
Chiloiro, Giuditta
Dinapoli, Nicola
Peng, Qian
Casà, Calogero
Gambacorta, Maria Antonietta
Valentini, Vincenzo
Lang, Jinyi
author_facet Boldrini, Luca
Lenkowicz, Jacopo
Orlandini, Lucia Clara
Yin, Gang
Cusumano, Davide
Chiloiro, Giuditta
Dinapoli, Nicola
Peng, Qian
Casà, Calogero
Gambacorta, Maria Antonietta
Valentini, Vincenzo
Lang, Jinyi
author_sort Boldrini, Luca
collection PubMed
description BACKGROUND: Predicting pathological complete response (pCR) in patients affected by locally advanced rectal cancer (LARC) who undergo neoadjuvant chemoradiotherapy (nCRT) is a challenging field of investigation, but many of the published models are burdened by a lack of reliable external validation. Aim of this study was to evaluate the applicability of a magnetic resonance imaging (MRI) radiomic-based pCR model developed and validated in Europe, to a different cohort of patients from an intercontinental cancer center. METHODS: The original model was based on two clinical and two radiomics features extracted from T2-weighted 1.5 T MRI of 161 LARC patients acquired before nCRT, considered as training set. Such model is here validated using the T2-w 1.5 and 3 T staging MRI of 59 LARC patients with different clinical characteristics consecutively treated in mainland Chinese cancer center from March 2017 to January 2018. Model performance were evaluated in terms of area under the receiver operator characteristics curve (AUC) and relative parameters, such as accuracy, specificity, negative and positive predictive value (NPV and PPV). RESULTS: An AUC of 0.83 (CI 95%, 0.71–0.96) was achieved for the intercontinental cohort versus a value of 0.75 (CI 95%, 0.61–0.88) at the external validation step reported in the original experience. Considering the best cut-off threshold identified in the first experience (0.26), the following predictive performance were obtained: 0.65 as accuracy, 0.64 as specificity, 0.70 as sensitivity, 0.91 as NPV and 0.28 as PPV. CONCLUSIONS: Despite the introduction of significant different factors, the proposed model appeared to be replicable on a real-world data extra-European patients’ cohort, achieving a TRIPOD 4 level. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13014-022-02048-9.
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spelling pubmed-90131262022-04-17 Applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort Boldrini, Luca Lenkowicz, Jacopo Orlandini, Lucia Clara Yin, Gang Cusumano, Davide Chiloiro, Giuditta Dinapoli, Nicola Peng, Qian Casà, Calogero Gambacorta, Maria Antonietta Valentini, Vincenzo Lang, Jinyi Radiat Oncol Research BACKGROUND: Predicting pathological complete response (pCR) in patients affected by locally advanced rectal cancer (LARC) who undergo neoadjuvant chemoradiotherapy (nCRT) is a challenging field of investigation, but many of the published models are burdened by a lack of reliable external validation. Aim of this study was to evaluate the applicability of a magnetic resonance imaging (MRI) radiomic-based pCR model developed and validated in Europe, to a different cohort of patients from an intercontinental cancer center. METHODS: The original model was based on two clinical and two radiomics features extracted from T2-weighted 1.5 T MRI of 161 LARC patients acquired before nCRT, considered as training set. Such model is here validated using the T2-w 1.5 and 3 T staging MRI of 59 LARC patients with different clinical characteristics consecutively treated in mainland Chinese cancer center from March 2017 to January 2018. Model performance were evaluated in terms of area under the receiver operator characteristics curve (AUC) and relative parameters, such as accuracy, specificity, negative and positive predictive value (NPV and PPV). RESULTS: An AUC of 0.83 (CI 95%, 0.71–0.96) was achieved for the intercontinental cohort versus a value of 0.75 (CI 95%, 0.61–0.88) at the external validation step reported in the original experience. Considering the best cut-off threshold identified in the first experience (0.26), the following predictive performance were obtained: 0.65 as accuracy, 0.64 as specificity, 0.70 as sensitivity, 0.91 as NPV and 0.28 as PPV. CONCLUSIONS: Despite the introduction of significant different factors, the proposed model appeared to be replicable on a real-world data extra-European patients’ cohort, achieving a TRIPOD 4 level. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13014-022-02048-9. BioMed Central 2022-04-15 /pmc/articles/PMC9013126/ /pubmed/35428267 http://dx.doi.org/10.1186/s13014-022-02048-9 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Boldrini, Luca
Lenkowicz, Jacopo
Orlandini, Lucia Clara
Yin, Gang
Cusumano, Davide
Chiloiro, Giuditta
Dinapoli, Nicola
Peng, Qian
Casà, Calogero
Gambacorta, Maria Antonietta
Valentini, Vincenzo
Lang, Jinyi
Applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort
title Applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort
title_full Applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort
title_fullStr Applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort
title_full_unstemmed Applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort
title_short Applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort
title_sort applicability of a pathological complete response magnetic resonance-based radiomics model for locally advanced rectal cancer in intercontinental cohort
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9013126/
https://www.ncbi.nlm.nih.gov/pubmed/35428267
http://dx.doi.org/10.1186/s13014-022-02048-9
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