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2D and 3D texture analysis to differentiate brain metastases on MR images: proceed with caution

Magnetic Resonance Materials in Physics, Biology and Medicine volume 31, pages 285–294 (2018)Cite this article

Abstract

Objective

To find structural differences between brain metastases of lung and breast cancer, computing their heterogeneity parameters by means of both 2D and 3D texture analysis (TA).

Materials and methods

Patients with 58 brain metastases from breast (26) and lung cancer (32) were examined by MR imaging. Brain lesions were manually delineated by 2D ROIs on the slices of contrast-enhanced T1-weighted (CET1) images, and local binary patterns (LBP) maps were created from each region. Histogram-based (minimum, maximum, mean, standard deviation, and variance), and co-occurrence matrix-based (contrast, correlation, energy, entropy, and homogeneity) 2D, weighted average of the 2D slices, and true 3D TA were obtained on the CET1 images and LBP maps.

Results

For LBP maps and 2D TA contrast, correlation, energy, and homogeneity were identified as statistically different heterogeneity parameters (SDHPs) between lung and breast metastasis. The weighted 3D TA identified entropy as an additional SDHP. Only two texture indexes (TI) were significantly different with true 3D TA: entropy and energy. All these TIs discriminated between the two tumor types significantly by ROC analysis. For the CET1 images there was no SDHP at all by 3D TA.

Conclusion

Our results indicate that the used textural analysis methods may help with discriminating between brain metastases of different primary tumors.

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Acknowledgements

This work was supported in part by the Spanish Ministerio de Economía y Competitividad (MINECO) and FEDER funds under Grant BFU2015-64380-C2-2-R, by the “Richter Gedeon Talentum Alapítvány” and by the Campus Hungary Mobility Program. Andrés Larroza was funded by the Spanish Ministerio de Educación, Cultura y Deporte (MECD) under Grant FPU12/01140. The authors also thank to the continuous help of Dr. Joaquin Gavila from Fundación IVO.

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Authors and Affiliations

  1. Division of Radiology, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Nagyerdei krt. 98, Debrecen, 4032, Hungary

    Monika Béresová

  2. Department of Medicine, Universitat de València, Valencia, Spain

    Andrés Larroza

  3. Department of Radiology, Fundación Instituto Valenciano de Oncología, Valencia, Spain

    Estanislao Arana

  4. Division of Nuclear Medicine, Department of Medical Imaging, Faculty of Medicine, University of Debrecen, Debrecen, Hungary

    Monika Béresová, József Varga & László Balkay

  5. Center for Biomaterials and Tissue Engineering, Universitat Politècnica de València, Valencia, Spain

    David Moratal

Authors
  1. Monika Béresová
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  2. Andrés Larroza
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  3. Estanislao Arana
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  4. József Varga
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  5. László Balkay
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  6. David Moratal
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Contributions

Protocol/project development: David Moratal, Estanislao Arana, Monika Béresová. Data collection or management: David Moratal, Estanislao Arana, László Balkay. Andrés Larroza, Monika Béresová. Data analysis: David Moratal, Estanislao Arana, Balkay László, József Varga, Monika Béresová.

Corresponding author

Correspondence to Monika Béresová.

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The authors declare that they have no conflict of interest.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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All exams came from individuals who gave informed consent at admission for research and follow-up, in accordance with Institutional Board Review (IBR) approval.

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Béresová, M., Larroza, A., Arana, E. et al. 2D and 3D texture analysis to differentiate brain metastases on MR images: proceed with caution. Magn Reson Mater Phy 31, 285–294 (2018). https://doi.org/10.1007/s10334-017-0653-9

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  • DOI: https://doi.org/10.1007/s10334-017-0653-9

Keywords

  • Computer-assisted
  • Image processing
  • Texture analysis
  • Magnetic resonance imaging
  • Brain neoplasms
  • Metastasis
  • Breast cancer
  • Lung cancer