European Radiology

, Volume 29, Issue 1, pp 13–21 | Cite as

Evaluation of MR-derived CT-like images and simulated radiographs compared to conventional radiography in patients with benign and malignant bone tumors

  • Alexandra S. GersingEmail author
  • Daniela Pfeiffer
  • Felix K. Kopp
  • Benedikt J. Schwaiger
  • Carolin Knebel
  • Bernhard Haller
  • Peter B. Noël
  • Marcus Settles
  • Ernst J. Rummeny
  • Klaus Woertler



To evaluate the diagnostic value of MR-derived CT-like images and simulated radiographs compared with conventional radiographs in patients with benign and malignant bone tumors.


In 32 patients with a benign or malignant bone lesion (mean age 33.9 ± 18.5 years, 17 females), 3-T MR imaging was performed including a 3D T1-weighted gradient echo sequence as the basis for the CT-like images. From these, intensity-inverted MR image volumes were converted into 2D images via a forward projection to obtain simulated radiographs. Two radiologists assessed these images as well as conventional radiographs for the type of periosteal reaction, matrix mineralization and destruction pattern. Agreement between the modalities was calculated using Cohen’s κ.


The agreement between conventional radiographs and MR-derived CT-like images in combination with simulated radiographs was substantial (periosteal reaction, κ = 0.67; destruction pattern, κ = 0.75), and the sensitivity of both modalities for the final diagnosis of the lesion (aggressive vs. nonaggressive) was high (MR-derived CT-like images, 86.2% vs. conventional radiographs, 90.0%). Additional information on soft tissue extension (MR-derived CT-like images, 21.9% vs. conventional radiographs, 12.5%; p = 0.009) and lobulation (9.4% vs. 0%; p < 0.001) was significantly more often found on MR-derived CT-like images compared with conventional radiographs.


The assessment of the destruction patterns, periosteal reaction and distinction between aggressive and nonaggressive tumors was feasible using MR-derived CT-like images and simulated radiographs and is comparable to that of conventional radiographs. Moreover, MR-derived CT-like images provided additional information on soft tissue extension and tumor architecture.

Key Points

• CT-like images and simulated radiographs can be generated from 3D MRI.

• Evaluation of bone tumors is feasible with MR-derived images.

• CT-like images and simulated radiographs provide additional information on bone tumors


Bone neoplasms Magnetic resonance imaging Musculoskeletal system Diagnostic imaging Joints 





Field of view


Graphic processing unit


Echo time


Repetition time



This work was presented as a scientific presentation at the 4th Annual Meeting of the German Society of Musculoskeletal Radiology in Berlin (April 2018).


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

Compliance with ethical standards


The scientific guarantor of this publication is Dr. Klaus Woertler, M.D.

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, Dr. Bernhard Haller, Ph.D., has significant statistical expertise.

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


  1. 1.
    Mintz DN, Hwang S (2014) Bone tumor imaging, then and now: review article. HSS J 10:230–239CrossRefGoogle Scholar
  2. 2.
    Morrison WB, Weissman BN, Kransdorf MJ et al (2013) ACR Appropriateness Criteria®; primary bone tumorsGoogle Scholar
  3. 3.
    Madewell JE, Ragsdale BD, Sweet DE (1981) Radiologic and pathologic analysis of solitary bone lesions. Part I: internal margins. Radiol Clin North Am 19:715–748PubMedGoogle Scholar
  4. 4.
    Ragsdale BD, Madewell JE, Sweet DE (1981) Radiologic and pathologic analysis of solitary bone lesions. Part II: periosteal reactions. Radiol Clin North Am 19:749–783PubMedGoogle Scholar
  5. 5.
    Sweet DE, Madewell JE, Ragsdale BD (1981) Radiologic and pathologic analysis of solitary bone lesions. Part III: matrix patterns. Radiol Clin North Am 19:785–814PubMedGoogle Scholar
  6. 6.
    Miller TT (2008) Bone tumors and tumorlike conditions: analysis with conventional radiography. Radiology 246:662–674CrossRefGoogle Scholar
  7. 7.
    Nordeck SM, Koerper CE, Adler A et al (2017) Simulated radiographic bone and joint modeling from 3D ankle MRI: feasibility and comparison with radiographs and 2D MRI. Skeletal Radiol 46:651–664CrossRefGoogle Scholar
  8. 8.
    He K, Sun J, Tang X (2013) Guided image filtering. IEEE Trans Pattern Anal Mach Intell 35:1397–1409CrossRefGoogle Scholar
  9. 9.
    Lodwick GS, Wilson AJ, Farrell C, Virtama P, Dittrich F (1980) Determining growth rates of focal lesions of bone from radiographs. Radiology 134:577–583CrossRefGoogle Scholar
  10. 10.
    Fleiss JL, Cohen J (1973) The Equivalence of Weighted Kappa and the Intraclass Correlation Coefficient as Measures of Reliability. Educational and Psychological Measurement 33:613–619CrossRefGoogle Scholar
  11. 11.
    Fleiss JL (1971) Measuring nominal scale agreement among many raters. Psychological Bulletin 76:378–382CrossRefGoogle Scholar
  12. 12.
    Schmalbrock P (2000) Comparison of three-dimensional fast spin echo and gradient echo sequences for high-resolution temporal bone imaging. J Magn Reson Imaging 12:814–825CrossRefGoogle Scholar
  13. 13.
    Woertler K (2003) Benign bone tumors and tumor-like lesions: value of cross-sectional imaging. Eur Radiol 13:1820–1835CrossRefGoogle Scholar
  14. 14.
    Panicek DM, Gatsonis C, Rosenthal DI et al (1997) CT and MR imaging in the local staging of primary malignant musculoskeletal neoplasms: Report of the Radiology Diagnostic Oncology Group. Radiology 202:237–246CrossRefGoogle Scholar
  15. 15.
    Norton KI, Hermann G, Abdelwahab IF, Klein MJ, Granowetter LF, Rabinowitz JG (1991) Epiphyseal involvement in osteosarcoma. Radiology 180:813–816CrossRefGoogle Scholar
  16. 16.
    Nemec SF, Donat MA, Mehrain S et al (2007) CT-MR image data fusion for computer assisted navigated neurosurgery of temporal bone tumors. Eur J Radiol 62:192–198CrossRefGoogle Scholar

Copyright information

© European Society of Radiology 2018

Authors and Affiliations

  • Alexandra S. Gersing
    • 1
    Email author
  • Daniela Pfeiffer
    • 1
    • 2
  • Felix K. Kopp
    • 1
  • Benedikt J. Schwaiger
    • 1
  • Carolin Knebel
    • 3
  • Bernhard Haller
    • 4
  • Peter B. Noël
    • 1
    • 2
  • Marcus Settles
    • 1
  • Ernst J. Rummeny
    • 1
  • Klaus Woertler
    • 1
  1. 1.Department of Radiology, Klinikum rechts der IsarTechnical University of MunichMunichGermany
  2. 2.Chair for Biomedical Physics, Department of Physics & Munich School of BioEngineeringTechnical University of MunichGarchingGermany
  3. 3.Department of Orthopaedic Surgery, Klinikum rechts der IsarTechnical University of MunichMunichGermany
  4. 4.Institute of Medical Informatics, Statistics and EpidemiologyTechnical University of MunichMunichGermany

Personalised recommendations