European Radiology

, Volume 28, Issue 6, pp 2397–2405 | Cite as

Proton density fat fraction (PDFF) MRI for differentiation of benign and malignant vertebral lesions

  • Frederic Carsten Schmeel
  • Julian Alexander Luetkens
  • Peter Johannes Wagenhäuser
  • Michael Meier-Schroers
  • Daniel Lloyd Kuetting
  • Andreas Feißt
  • Jürgen Gieseke
  • Leonard Christopher Schmeel
  • Frank Träber
  • Hans Heinz Schild
  • Guido Matthias Kukuk
Magnetic Resonance



To investigate whether proton density fat fraction (PDFF) measurements using a six-echo modified Dixon sequence can help to differentiate between benign and malignant vertebral bone marrow lesions.


Sixty-six patients were prospectively enrolled in our study. In addition to conventional MRI at 3.0-Tesla including at least sagittal T2-weighted/spectral attenuated inversion recovery and T1-weighted sequences, all patients underwent a sagittal six-echo modified Dixon sequence of the spine. The mean PDFF was calculated using regions of interest and compared between vertebral lesions. A cut-off value of 6.40% in PDFF was determined by receiver operating characteristic curves and used to differentiate between malignant (< 6.40%) and benign (≥ 6.40%) vertebral lesions.


There were 77 benign and 44 malignant lesions. The PDFF of malignant lesions was statistically significant lower in comparison with benign lesions (p < 0.001) and normal vertebral bone marrow (p < 0.001). The areas under the curves (AUC) were 0.97 for differentiating benign from malignant lesions (p < 0.001) and 0.95 for differentiating acute vertebral fractures from malignant lesions (p < 0.001). This yielded a diagnostic accuracy of 96% in the differentiation of both benign lesions and acute vertebral fractures from malignancy.


PDFF derived from six-echo modified Dixon allows for differentiation between benign and malignant vertebral lesions with a high diagnostic accuracy.

Key Points

Establishing a diagnosis of indeterminate vertebral lesions is a common clinical problem

Benign bone marrow processes may mimic the signal alterations observed in malignancy

PDFF differentiates between benign and malignant lesions with a high diagnostic accuracy

PDFF of non-neoplastic vertebral lesions is significantly higher than that of malignancy

PDFF from six-echo modified Dixon may help avoid potentially harmful bone biopsy


Proton density fat fraction Modified Dixon method Chemical shift encoded imaging MRI Bone marrow malignancy 

Abbreviations and acronyms


Area Under the Curve


Diffusion-Weighted Imaging


Modified Dixon


Six-Echo Modified Dixon


Negative Predictive Value


Proton Density Fat Fraction


Positron Emission Tomography/Computed Tomography


Positive Predictive Value


Receiver Operating Characteristic


Region Of Interest


Spin Echo


Sensitivity Encoding


Spectral Attenuated Inversion Recovery


Short-Tau Inversion Recovery


Echo Time


Repetition Time



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

Compliance with ethical standards


The scientific guarantor of this publication is Priv.-Doz. Dr. med. Guido Matthias Kukuk at Bonn University Hospital.

Conflict of interest

The authors of this manuscript declare relationships with the following companies: Dr. Jürgen Gieseke is an employee of Philips Healthcare (Best, The Netherlands) but had no control of inclusion of any data or data analysis. 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.

Statistics and biometry

No complex statistical methods were necessary for this paper.

Informed consent

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

Ethical approval

Institutional review board approval was obtained.


• prospective

• diagnostic or prognostic study

• performed at one institution


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Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  • Frederic Carsten Schmeel
    • 1
  • Julian Alexander Luetkens
    • 1
  • Peter Johannes Wagenhäuser
    • 1
  • Michael Meier-Schroers
    • 1
  • Daniel Lloyd Kuetting
    • 1
  • Andreas Feißt
    • 1
  • Jürgen Gieseke
    • 2
  • Leonard Christopher Schmeel
    • 1
  • Frank Träber
    • 1
  • Hans Heinz Schild
    • 1
  • Guido Matthias Kukuk
    • 1
  1. 1.Department of Radiology and Radiation OncologyUniversity Hospital Bonn, Rheinische-Friedrich-Wilhelms-Universität BonnBonnGermany
  2. 2.Philips HealthcareBestThe Netherlands

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