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01-12-2017 | Gastrointestinal

Application of CT texture analysis in predicting histopathological characteristics of gastric cancers

Authors: Shunli Liu, Song Liu, Changfeng Ji, Huanhuan Zheng, Xia Pan, Yujuan Zhang, Wenxian Guan, Ling Chen, Yue Guan, Weifeng Li, Jian He, Yun Ge, Zhengyang Zhou

Published in: European Radiology | Issue 12/2017

Abstract

Objectives

To explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers.

Methods

Preoperative contrast-enhanced CT images and postoperative histopathological features of 107 patients (82 men, 25 women) with gastric cancers were retrospectively reviewed. CT texture analysis generated: (1) mean attenuation, (2) standard deviation, (3) max frequency, (4) mode, (5) minimum attenuation, (6) maximum attenuation, (7) the fifth, 10th, 25th, 50th, 75th and 90th percentiles, and (8) entropy. Correlations between CT texture parameters and histopathological features were analysed.

Results

Mean attenuation, maximum attenuation, all percentiles and mode derived from portal venous CT images correlated significantly with differentiation degree and Lauren classification of gastric cancers (r, −0.231 ~ −0.324, 0.228 ~ 0.321, respectively). Standard deviation and entropy derived from arterial CT images also correlated significantly with Lauren classification of gastric cancers (r = −0.265, −0.222, respectively). In arterial phase analysis, standard deviation and entropy were significantly lower in gastric cancers with than those without vascular invasion; however, minimum attenuation was significantly higher in gastric cancers with than those without vascular invasion.

Conclusion

CT texture analysis held great potential in predicting differentiation degree, Lauren classification and vascular invasion status of gastric cancers.

Key Points

• CT texture analysis is noninvasive and effective for gastric cancer.

• Portal venous CT images correlated significantly with differentiation degree and Lauren classification.

• Standard deviation, entropy and minimum attenuation in arterial phase reflect vascular invasion.

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Title: Application of CT texture analysis in predicting histopathological characteristics of gastric cancers
Authors: Shunli Liu
Song Liu
Changfeng Ji
Huanhuan Zheng
Xia Pan
Yujuan Zhang
Wenxian Guan
Ling Chen
Yue Guan
Weifeng Li
Jian He
Yun Ge
Zhengyang Zhou
Publication date: 01-12-2017
Publisher: Springer Berlin Heidelberg
Published in: European Radiology / Issue 12/2017
Print ISSN: 0938-7994
Electronic ISSN: 1432-1084
DOI: https://doi.org/10.1007/s00330-017-4881-1

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Application of CT texture analysis in predicting histopathological characteristics of gastric cancers

Abstract

Objectives

Methods

Results

Conclusion

Key Points

At a glance: The ONWARDS insulin icodec trials

Springer Medicine

Abstract

Objectives

Methods

Results

Conclusion

Key Points

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