European Radiology

, Volume 28, Issue 2, pp 468–477 | Cite as

Diagnostic value of MRI-based 3D texture analysis for tissue characterisation and discrimination of low-grade chondrosarcoma from enchondroma: a pilot study

  • Catharina S. Lisson
  • Christoph G. Lisson
  • Kerstin Flosdorf
  • Regine Mayer-Steinacker
  • Markus Schultheiss
  • Alexandra von Baer
  • Thomas F. E. Barth
  • Ambros J. Beer
  • Matthias Baumhauer
  • Reinhard Meier
  • Meinrad Beer
  • Stefan A. Schmidt



To explore the diagnostic value of MRI-based 3D texture analysis to identify texture features that can be used for discrimination of low-grade chondrosarcoma from enchondroma.


Eleven patients with low-grade chondrosarcoma and 11 patients with enchondroma were retrospectively evaluated. Texture analysis was performed using mint Lesion: Kurtosis, entropy, skewness, mean of positive pixels (MPP) and uniformity of positive pixel distribution (UPP) were obtained in four MRI sequences and correlated with histopathology. The Mann-Whitney U-test and receiver operating characteristic (ROC) analysis were performed to identify most discriminative texture features. Sensitivity, specificity, accuracy and optimal cut-off values were calculated.


Significant differences were found in four of 20 texture parameters with regard to the different MRI sequences (p<0.01). The area under the ROC curve values to discriminate chondrosarcoma from enchondroma were 0.876 and 0.826 for kurtosis and skewness in contrast-enhanced T1 (ceT1w), respectively; in non-contrast T1, values were 0.851 and 0.822 for entropy and UPP, respectively. The highest discriminatory power had kurtosis in ceT1w with a cut-off ≥3.15 to identify low-grade chondrosarcoma (82 % sensitivity, 91 % specificity, accuracy 86 %).


MRI-based 3D texture analysis might be able to discriminate low-grade chondrosarcoma from enchondroma by a variety of texture parameters.

Key Points

MRI texture analysis may assist in differentiating low-grade chondrosarcoma from enchondroma.

Kurtosis in the contrast-enhanced T1w has the highest power of discrimination.

Tools provide insight into tumour characterisation as a non-invasive imaging biomarker.


Magnetic resonance imaging Texture analysis Tissue characterisation Chondrosarcoma Enchondroma 



Area under the curve




Mean of positive pixels


Receiver operating characteristic


Short tau inversion–recovery


Turbo spin echo


Uniformity of distribution of positive pixels


Compliance with ethical standards


The scientific guarantor of this publication is Lisson, CS.

Conflict of interest

M. Baumhauer is CEO of Mint Medical. The company distributes the software used in our study, but there was no financial support/benefit for our department.

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


The authors state that this work has not received any funding.

Statistics and biometry

Two of the authors (CGL, SAS) have significant statistical expertise.

Informed consent

Written informed consent was waived by the Institutional Review Board.

Ethical approval

Institutional Review Board approval was obtained.


• retrospective

• cross-sectional study

• performed at one institution


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Copyright information

© European Society of Radiology 2017

Authors and Affiliations

  • Catharina S. Lisson
    • 1
  • Christoph G. Lisson
    • 1
  • Kerstin Flosdorf
    • 1
  • Regine Mayer-Steinacker
    • 2
  • Markus Schultheiss
    • 3
  • Alexandra von Baer
    • 3
  • Thomas F. E. Barth
    • 4
  • Ambros J. Beer
    • 5
  • Matthias Baumhauer
    • 6
  • Reinhard Meier
    • 1
  • Meinrad Beer
    • 1
  • Stefan A. Schmidt
    • 1
  1. 1.Department of Diagnostic and Interventional RadiologyUniversity Hospital of UlmUlmGermany
  2. 2.Department of Internal Medicine IIIUniversity Hospital of UlmUlmGermany
  3. 3.Department of Trauma SurgeryUniversity Hospital of UlmUlmGermany
  4. 4.Institute of PathologyUniversity of UlmUlmGermany
  5. 5.Department of Nuclear MedicineUniversity Hospital of UlmUlmGermany
  6. 6.Mint MedicalDossenheimGermany

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