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Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review

INTRODUCTION: Gastric cancer (GC) is an aggressive and clinically heterogeneous tumor, and better risk stratification of lymph node metastasis (LNM) could lead to personalized treatments. The role of radiomics in the prediction of nodal involvement in GC has not yet been systematically assessed. Thi...

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Autores principales: Miccichè, Francesco, Rizzo, Gianluca, Casà, Calogero, Leone, Mariavittoria, Quero, Giuseppe, Boldrini, Luca, Bulajic, Milutin, Corsi, Domenico Cristiano, Tondolo, Vincenzo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469447/
https://www.ncbi.nlm.nih.gov/pubmed/37663653
http://dx.doi.org/10.3389/fmed.2023.1189740
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author Miccichè, Francesco
Rizzo, Gianluca
Casà, Calogero
Leone, Mariavittoria
Quero, Giuseppe
Boldrini, Luca
Bulajic, Milutin
Corsi, Domenico Cristiano
Tondolo, Vincenzo
author_facet Miccichè, Francesco
Rizzo, Gianluca
Casà, Calogero
Leone, Mariavittoria
Quero, Giuseppe
Boldrini, Luca
Bulajic, Milutin
Corsi, Domenico Cristiano
Tondolo, Vincenzo
author_sort Miccichè, Francesco
collection PubMed
description INTRODUCTION: Gastric cancer (GC) is an aggressive and clinically heterogeneous tumor, and better risk stratification of lymph node metastasis (LNM) could lead to personalized treatments. The role of radiomics in the prediction of nodal involvement in GC has not yet been systematically assessed. This study aims to assess the role of radiomics in the prediction of LNM in GC. METHODS: A PubMed/MEDLINE systematic review was conducted to assess the role of radiomics in LNM. The inclusion criteria were as follows: i. original articles, ii. articles on radiomics, and iii. articles on LNM prediction in GC. All articles were selected and analyzed by a multidisciplinary board of two radiation oncologists and one surgeon, under the supervision of one radiation oncologist, one surgeon, and one medical oncologist. RESULTS: A total of 171 studies were obtained using the search strategy mentioned on PubMed. After the complete selection process, a total of 20 papers were considered eligible for the analysis of the results. Radiomics methods were applied in GC to assess the LNM risk. The number of patients, imaging modalities, type of predictive models, number of radiomics features, TRIPOD classification, and performances of the models were reported. CONCLUSIONS: Radiomics seems to be a promising approach for evaluating the risk of LNM in GC. Further and larger studies are required to evaluate the clinical impact of the inclusion of radiomics in a comprehensive decision support system (DSS) for GC.
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spelling pubmed-104694472023-09-01 Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review Miccichè, Francesco Rizzo, Gianluca Casà, Calogero Leone, Mariavittoria Quero, Giuseppe Boldrini, Luca Bulajic, Milutin Corsi, Domenico Cristiano Tondolo, Vincenzo Front Med (Lausanne) Medicine INTRODUCTION: Gastric cancer (GC) is an aggressive and clinically heterogeneous tumor, and better risk stratification of lymph node metastasis (LNM) could lead to personalized treatments. The role of radiomics in the prediction of nodal involvement in GC has not yet been systematically assessed. This study aims to assess the role of radiomics in the prediction of LNM in GC. METHODS: A PubMed/MEDLINE systematic review was conducted to assess the role of radiomics in LNM. The inclusion criteria were as follows: i. original articles, ii. articles on radiomics, and iii. articles on LNM prediction in GC. All articles were selected and analyzed by a multidisciplinary board of two radiation oncologists and one surgeon, under the supervision of one radiation oncologist, one surgeon, and one medical oncologist. RESULTS: A total of 171 studies were obtained using the search strategy mentioned on PubMed. After the complete selection process, a total of 20 papers were considered eligible for the analysis of the results. Radiomics methods were applied in GC to assess the LNM risk. The number of patients, imaging modalities, type of predictive models, number of radiomics features, TRIPOD classification, and performances of the models were reported. CONCLUSIONS: Radiomics seems to be a promising approach for evaluating the risk of LNM in GC. Further and larger studies are required to evaluate the clinical impact of the inclusion of radiomics in a comprehensive decision support system (DSS) for GC. Frontiers Media S.A. 2023-08-16 /pmc/articles/PMC10469447/ /pubmed/37663653 http://dx.doi.org/10.3389/fmed.2023.1189740 Text en Copyright © 2023 Miccichè, Rizzo, Casà, Leone, Quero, Boldrini, Bulajic, Corsi and Tondolo. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Medicine
Miccichè, Francesco
Rizzo, Gianluca
Casà, Calogero
Leone, Mariavittoria
Quero, Giuseppe
Boldrini, Luca
Bulajic, Milutin
Corsi, Domenico Cristiano
Tondolo, Vincenzo
Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review
title Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review
title_full Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review
title_fullStr Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review
title_full_unstemmed Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review
title_short Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review
title_sort role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review
topic Medicine
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469447/
https://www.ncbi.nlm.nih.gov/pubmed/37663653
http://dx.doi.org/10.3389/fmed.2023.1189740
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