title: Predictive features of CT for risk stratifications in patients with primary gastrointestinal stromal tumour.
abstract: OBJECTIVE
  To determine the predictive CT imaging features for risk stratifications in patients with primary gastrointestinal stromal tumours (GISTs).
  
  
  METHODS
  One hundred and twenty-nine patients with histologically confirmed primary GISTs (diameter >2 cm) were enrolled. CT imaging features were reviewed. Tumour risk stratifications were determined according to the 2008 NIH criteria where GISTs were classified into four categories according to the tumour size, location, mitosis count, and tumour rupture. The association between risk stratifications and CT features was analyzed using univariate analysis, followed by multinomial logistic regression and receiver operating characteristic (ROC) curve analysis.
  
  
  RESULTS
  CT imaging features including tumour margin, size, shape, tumour growth pattern, direct organ invasion, necrosis, enlarged vessels feeding or draining the mass (EVFDM), lymphadenopathy, and contrast enhancement pattern were associated with the risk stratifications, as determined by univariate analysis (P < 0.05). Only lesion size, growth pattern and EVFDM remained independent risk factors in multinomial logistic regression analysis (OR = 3.480-100.384). ROC curve analysis showed that the area under curve of the obtained multinomial logistic regression model was 0.806 (95 % CI: 0.727-0.885).
  
  
  CONCLUSIONS
  CT features including lesion size, tumour growth pattern, and EVFDM were predictors of the risk stratifications for GIST.
  
  
  CONCLUSIONS
  • CT features were of predictive value for risk stratification of GISTs. • Tumour size, growth patterns, and EVFDM were risk predictors of GISTs. • Large size, mixed growth pattern, or EVFDM indicated high risk GIST.
authors.affiliation: Department of Radiology, The Huizhou Central municipal Hospital, No. 41 Eling Rood North, Huizhou, 516001, Guangdong, China.
authors.forename: Cuiping
authors.initials: C
authors.lastname: Zhou
authors.affiliation: Department of Radiology, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China.
authors.forename: Xiaohui
authors.initials: X
authors.lastname: Duan
authors.affiliation: Department of Radiology, The Huizhou Central municipal Hospital, No. 41 Eling Rood North, Huizhou, 516001, Guangdong, China.
authors.forename: Xiang
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Radiology, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China.
authors.forename: Huijun
authors.initials: H
authors.lastname: Hu
authors.affiliation: Department of Radiology, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China.
authors.forename: Dongye
authors.initials: D
authors.lastname: Wang
authors.affiliation: Department of Radiology, Sun Yat-Sen Memorial Hospital, SunYat-Sen University, No. 107 Yanjiang Road West, Guangzhou, 510120, Guangdong, China. shenjun@mail.sysu.edu.cn.
authors.forename: Jun
authors.initials: J
authors.lastname: Shen
mesh_terms: D000328:Adult; D000368:Aged; D003110:Colonic Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology; D004812:Epidemiologic Methods; D005260:Female; D046152:Gastrointestinal Stromal Tumors / Q000000981:diagnostic imaging* / Q000473:pathology; D006801:Humans; D008297:Male; D008875:Middle Aged; D012004:Rectal Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology; D013274:Stomach Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology; D014057:Tomography, X-Ray Computed / Q000379:methods
keywords: Abdominal neoplasm; Computed tomography; Gastrointestinal stromal tumour, primary; Prognosis; Risk factors