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Preliminary Application of Different Image Fusion Technology in Dual Energy CT for Improving Visualization of Gastric Cancer / 中国医学影像学杂志
Chinese Journal of Medical Imaging ; (12): 947-950, 2015.
Article in Chinese | WPRIM | ID: wpr-487890
ABSTRACT
PurposeConventional gastric CT provides poor contrast for gastric cancer lesions, the purpose of this study is to investigate the application value of dual energy CT image fusion technology in the improvement of lesion contrast in gastric cancer.Materials and Methods Abdominal dual energy contrast-enhanced CT images of 30 gastric cancer patients were retrospectively analyzed, dual-energy images were reconstructed with different linear and nonlinear fusion settings, contrast between lesions and normal gastric wall, lesion contrast to noise ratio (CNR) were compared among 100 kVp, 140 kVp and different fusion groups, and image quality was evaluated subjectively.Results There were statistically significant differences among the gastric cancer contrast and CNR of 100 kVp, 140 kVp and three linear blending images (F=29.6 and 26.1,P<0.001), with M=0.7 linear fusion group showing the highest CNR. The gastric cancer contrast and CNR was signiifcantly higher with a bandwidth (BW) of 0 HU when compared among the three groups of nonlinear blending images (F=268.5 and 49.5,P<0.001). Moreover, the nonlinear group with a width of 0 HU had a 36% and 47% increase in lesion contrast and CNR over that of a linear blending image. In the subjective evaluation of images, the BW=0 HU nonlinear fusion image was most frequently estimated as the most preferred images for lesion observation of gastric cancer.Conclusion Nonlinear blending with a BW of 0 HU improves display of gastric cancer, and has the potential clinical value to increase the accuracy of staging.

Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Medical Imaging Year: 2015 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Language: Chinese Journal: Chinese Journal of Medical Imaging Year: 2015 Type: Article