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 strategymentioned on PubMed. After the complete selection process, a total of 20 papers were considered eligible for the analysis of the results. Radiomicsmethods 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.
Miccichè, F., Rizzo, G., Casà, C., Leone, M., Quero, G., Boldrini, L., Bulajic, M., Corsi, D. C., Tondolo, V., Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review, <<FRONTIERS IN MEDICINE>>, 2023; 10 (16): 1-11. [doi:10.3389/fmed.2023.1189740] [https://hdl.handle.net/10807/280138]
Role of radiomics in predicting lymph node metastasis in gastric cancer: a systematic review
Rizzo, Gianluca;Quero, Giuseppe;Boldrini, Luca;Corsi, Domenico Cristiano;Tondolo, Vincenzo
2023
Abstract
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 strategymentioned on PubMed. After the complete selection process, a total of 20 papers were considered eligible for the analysis of the results. Radiomicsmethods 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.File | Dimensione | Formato | |
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