Clinical significance of lymphatic invasion in the esophageal region in patients with adenocarcinoma of the esophagogastric junction

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. 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.

Can we predict mediastinal lymph nodes metastasis in esophagogastric junction cancer? Results of a systematic review and meta-analysis

PURPOSE

The aim of this systematic review and meta-analysis was to define clinical indicator that predicts mediastinal lymph nodes metastasis (MLNM) in patients with Esophagogastric junction cancer (EGJC) to select patient population requiring esophagectomy.

METHODS

A systematic and electronic search of several electronic databases was performed up to August 2020. Studies containing information on risk factors for MLNM in patients diagnosed with EJGC and who underwent curative surgery were included.

RESULTS

Two predictors, including undifferentiated type (OR = 1.82, 95% CI = 1.07-3.10, p = 0.03) and esophageal invasion length (EIL) (OR = 10.95, 95% CI = 6.37-18.82, p < 0.00001) were identified as significant predictors for the risk of MLNM.

CONCLUSION

Knowledge of the associations of these clinicopathological features with MLNM can be useful in determining operative strategy for EGJC.