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

  • Gastrointestinal
  • Published:
European Radiology Aims and scope Submit manuscript

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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Abbreviations

AUC:

Area under the curve

CT:

Computed tomography

HU:

Hounsfield unit

ICC:

Intraclass correlation coefficient

ROC:

Receiver operating characteristic

ROI:

Region of interest

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Author notes

    Authors and Affiliations

    1. Department of Radiology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, No. 321 Zhongshan Road, Nanjing, Jiangsu Province, China, 210008

      Shunli Liu, Song Liu, Changfeng Ji, Huanhuan Zheng, Xia Pan, Yujuan Zhang, Jian He & Zhengyang Zhou

    2. Department of Gastrointestinal Surgery, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, Nanjing, China, 210008

      Wenxian Guan

    3. Department of Pathology, Nanjing Drum Tower Hospital, The Affiliated Hospital of Nanjing University Medical School, No. 321 Zhongshan Road, Nanjing, Jiangsu Province, China, 210008

      Ling Chen

    4. School of Electronic Science and Engineering, Nanjing University, No. 163 Xianlin Avenue, Nanjing, China, 210046

      Yue Guan, Weifeng Li & Yun Ge

    Authors
    1. Shunli Liu
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    Corresponding authors

    Correspondence to Jian He, Yun Ge or Zhengyang Zhou.

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    Guarantor

    The scientific guarantor of this publication is Zhengyang Zhou.

    Conflict of interest

    The authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.

    Funding

    This study has received funding by the National Natural Science Foundation of China (ID: 81371516, 81501441), Foundation of National Health and Family Planning Commission of China (W201306), Social Development Foundation of Jiangsu Province (BE2015605), the Natural Science Foundation of Jiangsu Province (ID: BK20131281, BK20150109), Jiangsu Province Health and Family Planning Commission Youth Scientific Research Project (ID: Q201508), and Six Talent Peaks Project of Jiangsu Province (ID: 2015-WSN-079).

    Statistics and biometry

    No complex statistical methods were necessary for this paper.

    Ethical approval

    Institutional Review Board approval was obtained.

    Informed consent

    Written informed consent was waived by the Institutional Review Board.

    Methodology

    • retrospective

    • diagnostic or prognostic study

    • performed at one institution

    Additional information

    Shunli Liu and Song Liu contributed equally to this work.

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    Cite this article

    Liu, S., Liu, S., Ji, C. et al. Application of CT texture analysis in predicting histopathological characteristics of gastric cancers. Eur Radiol 27, 4951–4959 (2017). https://doi.org/10.1007/s00330-017-4881-1

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