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MRI-based synthetic CT of the hip: can it be an alternative to conventional CT in the evaluation of osseous morphology?



MRI is the gold standard for soft tissue evaluation in the hip joint. However, CT is superior to MRI in providing clear visualization of bony morphology. The aim of this study is to test the equivalency of MRI-based synthetic CT to conventional CT in quantitatively assessing bony morphology of the hip.

Materials and methods

A prospective study was performed. Adult patients who underwent MRI and CT of the hips were included. Synthetic CT images were generated from MRI using a deep learning–based image synthesis method. Two readers independently performed clinically relevant measurements for hip morphology, including anterior and posterior acetabular sector angle, acetabular version angle, joint space width, lateral center–edge angle, sharp angle, alpha angle, and femoral head-neck offset on synthetic CT and CT. Inter-method, inter-reader, and intra-reader reliability and agreement were assessed using calculations of intraclass correlation coefficient, standard error of measurement, and smallest detectable change. The equivalency among CT and synthetic CT was evaluated using equivalency statistical testing.


Fifty-four hips from twenty-seven participants were included. There was no reported hip pathology in the subjects. The observed agreement based on reliability and agreement parameters indicated a strong degree of concordance between CT and synthetic CT. Equivalence statistical testing showed that all synthetic CT measurements are equivalent to the CT measurements at the considered margins.


In healthy individuals, we demonstrated equivalency of MRI-based synthetic CT to conventional CT for the quantitative evaluation of osseous hip morphology, thus obviating the radiation exposure of a pelvic CT examination.

Key Points

MRI-based synthetic CT images can be generated from MRI using a deep learning–based image synthesis method.

MRI-based synthetic CT is equivalent to CT in the quantitative assessment of bony hip morphology in healthy individuals.

MRI-based synthetic CT is promising for use in preoperative diagnosis and surgery planning.

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3-Dimensional T1-weighted radio-frequency-spoiled multiple gradient echo


Alpha angle


Anterior acetabular sector angle


Acetabular version angle


Femoral offset


Gradient echo


Intraclass correlation coefficient


Joint space width


Lateral center–edge angle


Posterior acetabular sector angle


Sharp angle


Synthetic CT


Smallest detectable change


Standard error of measurement


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

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Corresponding author

Correspondence to Lieve Morbée.

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The scientific guarantor of this publication is Prof. Dr. Lennart Jans.

Conflict of interest

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

Statistics and biometry

Stefanie De Buyser from Biostatistics Unit of University of Ghent provided statistical advice for this manuscript.

Informed consent

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

Ethical approval

Institutional review board approval was obtained.

Study subjects or cohorts overlap

Although images of the sacro-iliac joint of seventeen of the twenty-seven study subjects were partially already reported on in the study of Jans et al. [1], we emphasize that in the same patients, fully different body regions were scanned and a different algorithm was used. There is no overlap here as no part of this study has ever been reported.

[1] Jans L, Chen M, Elewaut D, et al. (2020) MRI-based synthetic CT for the detection of structural lesions in patients with suspected sacroiliitis: comparison with MRI. Radiology 298(2):343–349.



•cross-sectional study/observational study

•single-center study

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Morbée, L., Chen, M., Van Den Berghe, T. et al. MRI-based synthetic CT of the hip: can it be an alternative to conventional CT in the evaluation of osseous morphology?. Eur Radiol 32, 3112–3120 (2022).

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  • Tomography, X-ray computed
  • Magnetic resonance imaging
  • Deep learning
  • Femur head
  • Acetabulum