Hu, Yu-Chuan
Yan, Wei-Qiang
Yan, Lin-Feng
Xiao, Gang
Han, Yu
Liu, Chen-Xi
Wang, Sheng-Zhong
Li, Gang-Feng
Wang, Shu-Mei
Yang, Guang
Duan, Shi-Jun
Li, Bo
Wang, Wen
Cui, Guang-Bin http://orcid.org/0000-0002-7935-9803
Funding for this research was provided by:
Science and Technology Innovation Development Foundation of Tangdu Hospital (No. 2017LCYJ004)
Article History
Received: 29 October 2020
Revised: 14 January 2021
Accepted: 11 February 2021
First Online: 2 July 2021
Declarations
:
: The scientific guarantor of this publication is Guang-bin Cui.
: 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.
: One of the authors has significant statistical expertise.
: Written informed consent was waived by the Institutional Review Board.
: Institutional Review Board approval was obtained.
: Some study subjects or cohorts have been previously reported in 77, 57, 189 and 182 thymic epithelial tumour patients, respectively [1–4]. Four previous articles explored the values of intravoxel incoherent motion DWI [1], DWI texture parameters [2] and MRI radiomics [3], and combined radiomics nomogram [4] in predicting the pathological classification of thymic epithelial tumours, whereas in this manuscript we reported the usefulness of CFPs in differentiating thymic tumours.1. Li GF, Duan SJ, Yan LF et al (2017) Intravoxel incoherent motion diffusion-weighted MR imaging parameters predict pathological classification in thymic epithelial tumours. Oncotarget 8:44579-445922. Li B, Xin YK, Xiao G et al (2019) Predicting pathological subtypes and stages of thymic epithelial tumours using DWI: value of combining ADC and texture parameters. Eur Radiol 29:5330-53403. Xiao G, Rong WC, Hu YC et al (2019) MRI Radiomics Analysis for Predicting the Pathologic Classification and TNM Staging of Thymic Epithelial Tumors: A Pilot Study. AJR Am J Roentgenol. 10.2214/AJR.19.21696:1-134. Xiao G, Hu YC, Ren JL et al (2020) MR imaging of thymomas: a combined radiomics nomogram to predict histologic subtypes. Eur Radiol. 10.1007/s00330-020-07074-3.
: • Retrospective• Diagnostic or prognostic study• Performed at one institution