Predicting pathological subtypes and stages of thymic epithelial tumors using DWI: value of combining ADC and texture parameters

  • Bo Li
  • Yong-kang Xin
  • Gang Xiao
  • Gang-feng Li
  • Shi-jun Duan
  • Yu Han
  • Xiu-long Feng
  • Wei-qiang Yan
  • Wei-cheng Rong
  • Shu-mei Wang
  • Yu-chuan HuEmail author
  • Guang-bin CuiEmail author



To explore the value of combining apparent diffusion coefficients (ADC) and texture parameters from diffusion-weighted imaging (DWI) in predicting the pathological subtypes and stages of thymic epithelial tumors (TETs).


Fifty-seven patients with TETs confirmed by pathological analysis were retrospectively enrolled. ADC values and optimal texture feature parameters were compared for differences among low-risk thymoma (LRT), high-risk thymoma (HRT), and thymic carcinoma (TC) by one-way ANOVA, and between early and advanced stages of TETs were tested using the independent samples t test. Receiver operating characteristic (ROC) curve analysis was performed to determine the differentiating efficacy.


The ADC values in LRT and HRT were significantly higher than the values in TC (p = 0.004 and 0.001, respectively), also in early stage, values were significantly higher than ones in advanced stage of TETs (p < 0.001). Among all texture parameters analyzed in order to differentiate LRT from HRT and TC, the V312 achieved higher diagnostic efficacy with an AUC of 0.875, and combination of ADC and V312 achieved the highest diagnostic efficacy with an AUC of 0.933, for differentiating the LRT from HRT and TC. Furthermore, combination of ADC and V1030 achieved a relatively high differentiating ability with an AUC of 0.772, for differentiating early from advanced stages of TETs.


Combination of ADC and DWI texture parameters improved the differentiating ability of TET grades, which could potentially be useful in clinical practice regarding the TET evaluation before treatment.

Key Points

• DWI texture analysis is useful in differentiating TET subtypes and stages.

• Combination of ADC and DWI texture parameters may improve the differentiating ability of TET grades.

• DWI texture analysis could potentially be useful in clinical practice regarding the TET evaluation before treatment.


Thymic epithelial tumors Neoplasm staging Diffusion magnetic resonance imaging Texture analysis 



Apparent diffusion coefficient


Computed tomography


Diffusion-weighted imaging


Field of view


High-risk thymoma


Low-risk thymoma


Magnetic resonance imaging


Number of excitations


Receiver operating characteristic


Region of interest


Thymic carcinoma


Echo time


Thymic epithelial tumors


Repetition time


Volume of interest


World Health Organization



We would like to thank Dr. Xiao-Cheng Wei in GE Healthcare China for providing technical support regarding the application of Analysis-Kit software and supplementary Material (Texture Parameters Description.PDF).


This study has received funding from the Science and Technology Innovation Development Foundation of Tangdu Hospital (no. 2017LCYJ004).

Compliance with ethical standards


The scientific guarantor of this publication is Guang-bin Cui.

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.

Statistics and biometry

Lei Shang kindly provided statistical advice for this manuscript.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.

Study subjects or cohorts overlap

Some study subjects or cohorts have been previously reported in Li GF, Duan SJ, Yan LF, et al Intravoxel incoherent motion diffusion-weighted MR imaging parameters predict pathological classification in thymic epithelial tumors. Oncotarget 2017;8(27):44579–44592.


• retrospective

• diagnostic or prognostic study

• performed at one institution

Supplementary material

330_2019_6080_MOESM1_ESM.docx (125 kb)
ESM 1 (DOCX 124 kb)


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Copyright information

© European Society of Radiology 2019

Authors and Affiliations

  • Bo Li
    • 1
  • Yong-kang Xin
    • 1
  • Gang Xiao
    • 1
  • Gang-feng Li
    • 1
  • Shi-jun Duan
    • 1
  • Yu Han
    • 1
  • Xiu-long Feng
    • 1
  • Wei-qiang Yan
    • 1
  • Wei-cheng Rong
    • 1
  • Shu-mei Wang
    • 2
  • Yu-chuan Hu
    • 1
    Email author
  • Guang-bin Cui
    • 1
    Email author
  1. 1.Department of Radiology and Functional and Molecular Imaging Key Lab of Shaanxi Province, Tangdu HospitalMilitary Medical University of PLA Airforce (Fourth Military Medical University)Xi’anPeople’s Republic of China
  2. 2.Department of Pathology, Tangdu HospitalMilitary Medical University of PLA Airforce (Fourth Military Medical University)Xi’anPeople’s Republic of China

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