Literature DB >> 27178777

Assessment of metastatic risk of gastric GIST based on treatment-naïve CT features.

A C O'Neill1, A B Shinagare2, V Kurra1, S H Tirumani1, J P Jagannathan1, A D Baheti1, J L Hornick3, S George4, N H Ramaiya1.   

Abstract

OBJECTIVE: To study whether the CT features of treatment-naïve gastric GIST may be used to assess metastatic risk.
METHODS: In this IRB approved retrospective study, with informed consent waived, contrast enhanced CT images of 143 patients with pathologically confirmed treatment-naïve gastric GIST (74 men, 69 women; mean age 61 years, SD ± 14) were reviewed in consensus by two oncoradiologists blinded to clinicopathologic features and clinical outcome and morphologic features were recorded. The metastatic spread was recorded using available imaging studies and electronic medical records (median follow up 40 months, interquartile range, IQR, 21-61). The association of maximum size in any plane (≤10 cm or >10 cm), outline (smooth or irregular/lobulated), cystic areas (≤50% or >50%), exophytic component (≤50% or >50%), and enhancing solid component (present or absent) with metastatic disease were analyzed using univariate (Fisher's exact test) and multivariate (logistic regression) analysis.
RESULTS: Metastatic disease developed in 42 (29%) patients (28 at presentation, 14 during follow-up); 23 (16%) patients died. On multivariate analysis, tumor size >10 cm (p = 0.0001, OR 9.9), irregular/lobulated outline (p = 0.001, OR 5.6) and presence of a enhancing solid component (p < 0.0001, OR 9.1) were independent predictors of metastatic disease. On subgroup analysis, an irregular/lobulated outline and an enhancing solid component were more frequently associated with metastases in tumors ≤5 cm and >5-≤10 cm (p < 0.05).
CONCLUSION: CT morphologic features can be used to assess the metastatic risk of treatment-naïve gastric GIST. Risk assessment based on pretreatment CT is especially useful for patients receiving neoadjuvant tyrosine kinase inhibitors and those with tumors <5 cm in size.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  CT; Gastrointestinal stromal tumor; Metastasis; Risk stratification; Stomach

Mesh:

Substances:

Year:  2016        PMID: 27178777     DOI: 10.1016/j.ejso.2016.03.032

Source DB:  PubMed          Journal:  Eur J Surg Oncol        ISSN: 0748-7983            Impact factor:   4.424


  8 in total

1.  A novel CT-based radiomic nomogram for predicting the recurrence and metastasis of gastric stromal tumors.

Authors:  Weiqun Ao; Guohua Cheng; Bin Lin; Rong Yang; Xuebin Liu; Sheng Zhou; Wenqi Wang; Zhaoxing Fang; Fengjuan Tian; Guangzhao Yang; Jian Wang
Journal:  Am J Cancer Res       Date:  2021-06-15       Impact factor: 6.166

2.  The roles of CT and EUS in the preoperative evaluation of gastric gastrointestinal stromal tumors larger than 2 cm.

Authors:  Tao Chen; Lili Xu; Xiaoyu Dong; Yue Li; Jiang Yu; Wei Xiong; Guoxin Li
Journal:  Eur Radiol       Date:  2019-01-07       Impact factor: 5.315

Review 3.  Update on Gastrointestinal Stromal Tumors for Radiologists.

Authors:  Sree Harsha Tirumani; Akshay D Baheti; Harika Tirumani; Ailbhe O'Neill; Jyothi P Jagannathan
Journal:  Korean J Radiol       Date:  2017-01-05       Impact factor: 3.500

4.  A correlation research of Ki67 index, CT features, and risk stratification in gastrointestinal stromal tumor.

Authors:  Huali Li; Gang Ren; Rong Cai; Jian Chen; Xiangru Wu; Jianxi Zhao
Journal:  Cancer Med       Date:  2018-08-19       Impact factor: 4.452

5.  Evaluation of computed tomography vascular reconstruction for the localization diagnosis of perigastric mass.

Authors:  Ping Wang; Cheng-Zhou Zhang; Guang-Bin Wang; Yang-Yang Li; Xing-Yue Jiang; Fang-Jun Fang; Xiao-Xiao Li; Jia Bian; Xin-Shan Cao; Xiao-Fei Zhong
Journal:  Medicine (Baltimore)       Date:  2018-06       Impact factor: 1.889

6.  Preoperative CT-Based Deep Learning Model for Predicting Risk Stratification in Patients With Gastrointestinal Stromal Tumors.

Authors:  Bing Kang; Xianshun Yuan; Hexiang Wang; Songnan Qin; Xuelin Song; Xinxin Yu; Shuai Zhang; Cong Sun; Qing Zhou; Ying Wei; Feng Shi; Shifeng Yang; Ximing Wang
Journal:  Front Oncol       Date:  2021-09-17       Impact factor: 6.244

Review 7.  New advances in radiomics of gastrointestinal stromal tumors.

Authors:  Roberto Cannella; Ludovico La Grutta; Massimo Midiri; Tommaso Vincenzo Bartolotta
Journal:  World J Gastroenterol       Date:  2020-08-28       Impact factor: 5.742

8.  Correlation analysis of multi-slice computed tomography (MSCT) findings, clinicopathological factors, and prognosis of gastric gastrointestinal stromal tumors.

Authors:  Dong Xu; Guang-Yan Si; Qi-Zhou He
Journal:  Transl Cancer Res       Date:  2020-03       Impact factor: 1.241

  8 in total

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