Literature DB >> 33566165

Role of CT in the prediction of pathological complete response in gastric cancer after neoadjuvant chemotherapy.

Zhi-Long Wang1, Yan-Ling Li1, Xiao-Ting Li1, Lei Tang1, Zi-Yu Li2, Ying-Shi Sun3.   

Abstract

OBJECTIVE: To explore which computed tomography (CT) features can predict pathological complete response (pCR) (ypT0N0) after neoadjuvant chemotherapy (NAC) in patients with gastric adenocarcinoma (GC).
MATERIALS AND METHODS: This study reviewed an institutional database of patients who underwent resection of GC after NAC and identified patients with pCR from January 2010 to December 2013. The correlations between pre-chemotherapy and post-chemotherapy CT features and pCR were analyzed.
RESULTS: Eleven of 199 patients with GC who achieved ypT0N0 status after NAC were classified as the pCR group in this study. After matching pCR (n = 11) and non-pCR patients (n = 44) in the ratio of 1:4, a total of 55 cases were analyzed. The binary logistic regression analysis showed that the post-chemotherapy short diameter of the largest lymph node and tumor thickness ratio reduction were independent predictors of pCR, with an area under the curve (AUC) of 0.94 on the receiver operating characteristic (ROC) curve analysis.
CONCLUSION: Two CT features, including the short diameter of the largest lymph node post-chemotherapy and tumor thickness ratio reduction, are good predictors of pCR after NAC in patients with GC.

Entities:  

Keywords:  Computed tomography; Gastric cancer; Neoadjuvant chemotherapy; Pathological complete response

Mesh:

Year:  2021        PMID: 33566165     DOI: 10.1007/s00261-021-02967-3

Source DB:  PubMed          Journal:  Abdom Radiol (NY)


  1 in total

1.  Predicting Response to Systemic Chemotherapy for Advanced Gastric Cancer Using Pre-Treatment Dual-Energy CT Radiomics: A Pilot Study.

Authors:  Yi-Yang Liu; Huan Zhang; Lan Wang; Shu-Shen Lin; Hao Lu; He-Jun Liang; Pan Liang; Jun Li; Pei-Jie Lv; Jian-Bo Gao
Journal:  Front Oncol       Date:  2021-09-15       Impact factor: 6.244

  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.