Published September 2016 | Version v1
Journal article

Predictive features of CT for risk stratifications in patients with primary gastrointestinal stromal tumour

  • 1. The Huizhou Central municipal Hospital, Department of Radiology, Huizhou, Guangdong (China)
  • 2. SunYat-Sen University, Department of Radiology, Sun Yat-Sen Memorial Hospital, Guangzhou, Guangdong (China)

Description

To determine the predictive CT imaging features for risk stratifications in patients with primary gastrointestinal stromal tumours (GISTs). 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. 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). CT features including lesion size, tumour growth pattern, and EVFDM were predictors of the risk stratifications for GIST. (orig.)

Availability note (English)

Available from: http://dx.doi.org/10.1007/s00330-015-4172-7

Additional details

Identifiers

Publishing Information

Journal Title
European Radiology
Journal Volume
26
Journal Issue
9
Journal Page Range
p. 3086-3093
ISSN
0938-7994
CODEN
EURAE3