European Radiology

, Volume 28, Issue 9, pp 3872–3881 | Cite as

MR-based radiomics signature in differentiating ocular adnexal lymphoma from idiopathic orbital inflammation

  • Jian Guo
  • Zhenyu Liu
  • Chen Shen
  • Zheng Li
  • Fei Yan
  • Jie TianEmail author
  • Junfang XianEmail author
Head and Neck



To assess the value of the MR-based radiomics signature in differentiating ocular adnexal lymphoma (OAL) and idiopathic orbital inflammation (IOI).


One hundred fifty-seven patients with pathology-proven OAL (84 patients) and IOI (73 patients) were divided into primary and validation cohorts. Eight hundred six radiomics features were extracted from morphological MR images. The least absolute shrinkage and selection operator (LASSO) procedure and linear combination were used to select features and build radiomics signature for discriminating OAL from IOI. Discriminating performance was assessed by the area under the receiver-operating characteristic curve (AUC). The predictive results were compared with the assessment of radiologists by chi-square test.


Five radiomics features were included in the radiomics signature, which differentiated OAL from IOI with an AUC of 0.74 and 0.73 in the primary and validation cohorts respectively. There was a significant difference between the classification results of the radiomics signature and those of a radiology resident (p < 0.05), although there was no significant difference between the results of the radiomics signature and those of a more experienced radiologist (p > 0.05).


Radiomics features have the potential to differentiate OAL from IOI.

Key Points

• Clinical and imaging findings of OAL and IOI often overlap, which makes diagnosis difficult.

• Radiomics features can potentially differentiate OAL from IOI non invasively.

• The radiomics signature discriminates OAL from IOI at the same level as an experienced radiologist.


Radiomics Inflammation Lymphoma Orbital neoplasms Magnetic resonance imaging (MRI) 



Apparent diffusion coefficient


Area under the ROC curve


Dynamic contrast enhanced


Diffusion-weighted imaging


Echo train length


Fat saturation


Fast spin echo


Grey level co-occurrence matrix


Grey level run length matrix


Intraclass correlation coefficient


Idiopathic orbital inflammation


Least absolute shrinkage and selection operators procedure


Magnetic resonance imaging


Number of excitations


Ocular adnexal lymphoma


Receiver-operating characteristic


Short-run high-grey emphasis


T1-weighted images


T2-weighted image


Echo time


Repetition time



The authors would like to express their sincere appreciation to all reviewers for their kind comments.

This work was presented in part at the 2017 International Society of Magnetic Resonance Imaging in Medicine Annual Meeting.


This study has received funding from the High Level Health Technical Personnel of Bureau of Health in Beijing under grant no. 2014-2-005; Beijing Municipal Administration of Hospitals Clinical Medicine Development of Special Funding Support under grant no. ZYLX201704; Key Talent Project of Beijing under Grant no. 2014001; The Priming Scientific Research Foundation for the Senior Researcher in Beijing Tongren Hospital, Capital Medical University, under grant no. 2016-YJJ-GGL-011.

Compliance with ethical standards


The scientific guarantor of this publication is Junfang Xian.

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

One of the authors has significant statistical expertise.

Informed consent

Written informed consent was obtained from all subjects (patients) in this study.

Ethical approval

Institutional Review Board approval was obtained.


• retrospective

• diagnostic study

• performed at one institution


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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  1. 1.Department of Radiology, Beijing Tongren HospitalCapital Medical UniversityBeijingChina
  2. 2.CAS Key Laboratory of Molecular ImagingInstitute of AutomationBeijingChina
  3. 3.School of Life Science and TechnologyXidian UniversityXi’anChina
  4. 4.University of Chinese Academy of SciencesBeijingChina

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