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Computed tomography texture analysis in patients with gastric cancer: a quantitative imaging biomarker for preoperative evaluation before neoadjuvant chemotherapy treatment

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Japanese Journal of Radiology Aims and scope Submit manuscript

Abstract

Purpose

The aim of the study is to explore the role of computed tomography texture analysis (CT-TA) for predicting clinical T and N stages and tumor grade before neoadjuvant chemotherapy treatment in gastric cancer (GC) patients during the preoperative period.

Materials and methods

CT images of 114 patients with GC were included in this retrospective study. Following pre-processing steps, textural features were extracted using MaZda software in the portal venous phase. We evaluated and analyzed texture features of six principal categories for differentiating between T stages (T1,2 vs T3,4), N stages (N+ vs N–) and grades (low-intermediate vs. high). Classification was performed based on texture parameters with high model coefficients in linear discriminant analysis (LDA).

Results

Dimension-reduction steps yielded five textural features for T stage, three for N stage and two for tumor grade. The discriminatory capacities of T stage, N stage and tumor grade were 90.4%, 81.6% and 64.5%, respectively, when LDA algorithm was employed.

Conclusion

CT-TA yields potentially useful imaging biomarkers for predicting the T and N stages of patients with GC and can be used for preoperative evaluation before neoadjuvant treatment planning.

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Abbreviations

AGC:

Advanced gastric cancer

AJCC:

American Joint Committee on Cancer

AUC:

Area under the curve

CG:

Gastric cancer

HU:

Hounsfield unit

ICC:

Intraclass correlation coefficient

LDA:

Linear discriminant analysis

ROI:

Region of interest

ROIs:

Regions of interests

MDCT:

Multidetector computed tomography

CE-MDCT:

Contrast-enhanced multidetector computed tomography

CT-TA:

Computed tomography texture analysis

DFS:

Disease-free survival

OS:

Overall survival

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Authors and Affiliations

  1. Department of Radiology, Istanbul Training and Research Hospital, Kasap İlyas Mah., Org. Abdurrahman Nafiz Gürman Cd., Fatih, 34098, Istanbul, Turkey

    Aytul Hande Yardimci, Ipek Sel, Ceyda Turan Bektas & Ozgur Kilickesmez

  2. Department of Pathology, Istanbul Training and Research Hospital, Istanbul, Turkey

    Enver Yarikkaya & Nevra Dursun

  3. Department of General Surgery, Istanbul Training and Research Hospital, Istanbul, Turkey

    Hasan Bektas

  4. Department of Medical Oncology, Acıbadem Mehmet Ali Aydınlar University Medical Faculty, Istanbul, Turkey

    Cigdem Usul Afsar

  5. Department of Medical Oncology, Istanbul Training and Research Hospital, Istanbul, Turkey

    Rıza Umar Gursu

  6. Institute of Health Sciences, Istanbul Gelisim University, Istanbul, Turkey

    Veysi Hakan Yardimci

  7. Department of Biostatistics, Mersin University, Mersin, Turkey

    Elif Ertas

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  1. Aytul Hande Yardimci
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Correspondence to Aytul Hande Yardimci.

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The authors declare no conflict of interest.

Ethics statement

This single-institution retrospective study followed the Declaration of Helsinki and Good Clinical Practice Guidelines and the institutional review board of our hospital approved this retrospective study. Our Ethical approval number/ID: 1750.

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Yardimci, A.H., Sel, I., Bektas, C.T. et al. Computed tomography texture analysis in patients with gastric cancer: a quantitative imaging biomarker for preoperative evaluation before neoadjuvant chemotherapy treatment. Jpn J Radiol 38, 553–560 (2020). https://doi.org/10.1007/s11604-020-00936-2

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  • DOI: https://doi.org/10.1007/s11604-020-00936-2

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