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CT-like MRI: a qualitative assessment of ZTE sequences for knee osseous abnormalities

Skeletal Radiology Aims and scope Submit manuscript

Abstract

Objective

To qualitatively evaluate the utility of zero echo-time (ZTE) MRI sequences in identifying osseous findings and to compare ZTE with optimized spoiled gradient echo (SPGR) sequences in detecting knee osseous abnormalities.

Materials and methods

ZTE and standard knee MRI sequences were acquired at 3T in 100 consecutive patients. Three radiologists rated confidence in evaluating osseous abnormalities and image quality on a 5-grade Likert scale in ZTE compared to standard sequences. In a subset of knees (n = 57) SPGR sequences were also obtained, and diagnostic confidence in identifying osseous structures was assessed, comparing ZTE and SPGR sequences. Statistical significance of using ZTE over SPGR was characterized with a paired t-test.

Results

Image quality of the ZTE sequences was rated high by all reviewers with 278 out of 299 (100 studies, 3 radiologists) scores ≥ 4 on the Likert scale. Diagnostic confidence in using ZTE sequences was rated “very high confidence” in 97%, 85%, 71%, and 73% of the cases for osteophytosis, subchondral cysts, fractures, and soft tissue calcifications/ossifications, respectively. In 74% of cases with osseous findings, reviewer scores indicated confidence levels (score ≥ 3) that ZTE sequences improved diagnostic certainty over standard sequences. The diagnostic confidence in using ZTE over SPGR sequences for osseous structures as well as abnormalities was favorable and statistically significant (p < 0.01).

Conclusion

Incorporating ZTE sequences in the standard knee MRI protocol was technically feasible and improved diagnostic confidence for osseous findings in relation to standard MR sequences. In comparison to SPGR sequences, ZTE improved assessment of osseous abnormalities.

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References

  1. Gold GE, Han E, Stainsby J, Wright G, Brittan J, Beaulieu C. Musculoskeletal MRI at 3.0 T: relaxation times and image contrast. AJR Am J Roentgenol. 2004;183:343–51.

    Article  Google Scholar 

  2. Du J, Bydder GM. Qualitative and quantitative ultrashort-TE MRI of cortical bone. NMR Biomed. 2012;26(5):489–506.

    Article  Google Scholar 

  3. Du J, Carl M, Bydder M, Takahashi A, Chung CB, Bydder GM. Qualitative and quantitative ultrashort echo time (UTE) imaging of cortical bone. J Magn Reson. 2010;207(2):304–11.

    Article  CAS  Google Scholar 

  4. Krug R, Larson PEZ, Wang C, Burghardt AJ, Kelley DAC, Link TM, et al. Ultrashort echo time MRI of cortical bone at 7 tesla field strength: a feasibility study. J Magn Reson Imaging. 2011;34(3):691–5.

    Article  Google Scholar 

  5. Larson PEZ, Han M, Krug R, Jakary A, Nelson SJ, Vigneron DB, et al. Ultrashort echo time and zero echo time MRI at 7T. MAGMA. 2016;29(3):359–70.

    Article  Google Scholar 

  6. Ma Y-J, Jerban S, Jang H, Chang D, Chang EY, Du J. Quantitative ultrashort echo time (UTE) magnetic resonance imaging of bone: an update. Front Endocrinol (Lausanne). 2020; 11

  7. Reichert ILH, Robson MD, Gatehouse PD, He T, Chappell KE, Holmes J, et al. Magnetic resonance imaging of cortical bone with ultrashort TE pulse sequences. Magn Reson Imaging. 2005;23(5):611–8.

    Article  Google Scholar 

  8. Weiger M, Stampanoni M, Pruessmann KP. Direct depiction of bone microstructure using MRI with zero echo time. Bone. 2013;54(1):44–7.

    Article  Google Scholar 

  9. Abbasi-Rad S, Rad HS. Quantification of human cortical bone bound and free water in vivo with ultrashort echo time MR imaging: a model-based approach. Radiology. 2017;283(3):862–72.

    Article  Google Scholar 

  10. Stillwater L, Koenig J, Maycher B, Davidson M. 3D-MR vs. 3D-CT of the shoulder in patients with glenohumeral instability. Skeletal Radiol. 2017; 46(3):325–331.

  11. Mohankumar R, White LM, Naraghi A. Pitfalls and pearls in MRI of the knee. AJR Am J Roentgenol. 2014;203(3):516–30.

    Article  Google Scholar 

  12. Argentieri EC, Koff MF, Breighner RE, Endo Y, Shah PH, Sneag DB. Diagnostic accuracy of zero-echo time MRI for the evaluation of cervical neural foraminal stenosis. Spine (Phila Pa 1976). 2018;43(13):928–33.

    Article  Google Scholar 

  13. Breighner RE, Bogner EA, Lee SC, Koff MF, Potter HG. Evaluation of osseous morphology of the hip using zero echo time magnetic resonance imaging. Am J Sports Med. 2019;47(14):3460–8.

    Article  Google Scholar 

  14. Breighner RE, Endo Y, Konin GP, Gulotta LV, Koff MF, Potter HG. Technical developments: zero echo time imaging of the shoulder: enhanced osseous detail by using MR imaging. Radiology. 2018;286(3):960–6.

    Article  Google Scholar 

  15. Cho SB, Baek HJ, Ryu KH, Choi BH, Moon JI, Kim TB, et al. Clinical feasibility of zero TE skull MRI in patients with head trauma in comparison with CT: a single-center study. Am J Neuroradiol. 2019;40(1):109–15.

    Article  CAS  Google Scholar 

  16. Lu A, Gorny KR, Ho M-L. Zero TE MRI for craniofacial bone imaging. Am J Neuroradiol. 2019;40(9):1562–6.

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Patel KB, Eldeniz C, Skolnick GB, Jammalamadaka U, Commean PK, Goyal MS, et al. 3D pediatric cranial bone imaging using high-resolution MRI for visualizing cranial sutures: a pilot study. J Neurosurg Pediatr. 2020;26(3):311–7.

    Article  Google Scholar 

  18. Chavhan GB, Babyn PS, Jankharia BG, Cheng H-LM, Shroff MM. Steady-state MR imaging sequences: physics, classification, and clinical applications. Radiographics. 2008;28(4):1147–60.

    Article  Google Scholar 

  19. Link TM, Majumdar S, Grampp S, Guglielmi G, Kuijk Cv, Imhof H, et al. Imaging of trabecular bone structure in osteoporosis. Eur Radiol. 1999;9(9):1781–8.

    Article  CAS  Google Scholar 

  20. Majumdar S, Genant HK, Grampp S, Newitt DC, Truong VH, Lin JC, et al. Correlation of trabecular bone structure with age, bone mineral density, and osteoporotic status: in vivo studies in the distal radius using high resolution magnetic resonance imaging. J Bone Miner Res. 1997;12(1):111–8.

    Article  CAS  Google Scholar 

  21. Yang X, Li Z, Cao Y, Xu Y, Wang H, Wen L, et al. Efficacy of magnetic resonance imaging with an SPGR sequence for the early evaluation of knee cartilage degeneration and the relationship between cartilage and other tissues. J Orthop Surg Res. 2019;14:152.

    Article  Google Scholar 

  22. Hsu H, Lachenbruch PA. Paired t test. Wiley StatsRef: Statistics Reference Online.

  23. Landis JR, Koch GG. The measurement of observer agreement for categorical data. Biometrics. 1977;33(1):159–74.

    Article  CAS  Google Scholar 

  24. Virtanen P, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nature Methods. 2020;17:261–72.

    Article  CAS  Google Scholar 

  25. Sell CA, Masi JN, Burghardt A, Newitt D, Link TM, Majumdar S. Quantification of trabecular bone structure using magnetic resonance imaging at 3 Tesla—calibration studies using microcomputed tomography as a standard of reference. Calcif Tissue Int. 2005;76(5):355–64.

    Article  CAS  Google Scholar 

  26. Yoshioka H, Stevens K, Hargreaves BA, Steines D, Genovese M, Dillingham MF, et al. Magnetic resonance imaging of articular cartilage of the knee: comparison between fat-suppressed three-dimensional SPGR imaging, fat-suppressed FSE imaging, and fat-suppressed three-dimensional DEFT imaging, and correlation with arthroscopy. J Magn Reson Imaging. 2004;20(5):857864.

    Article  Google Scholar 

  27. deMello RAF, Ma Y-J, Ashir A, Jerban S, Hoenecke H, Carl M, et al. Three-dimensional zero echo time magnetic resonance imaging versus 3-dimensional computed tomography for glenoid bone assessment. Arthroscopy. 2020;36(9):2391–400.

    Article  Google Scholar 

  28. Lansdown DA, Pedoia V. Editorial commentary: can we evaluate glenoid bone with magnetic resonance imaging? Yes, if you have the right sequence. Arthroscopy. 2020;36(9):2401–2.

    Article  Google Scholar 

  29. Weiger M, Wu M, Wurnig MC, Kenkel D, Boss A, Andreisek G, et al. ZTE imaging with long-T2 suppression. NMR Biomed. 2015;28(2):241–54.

    Article  Google Scholar 

  30. Silva A, Pinto E, Sampaio R. Rotational alignment in patient-specific instrumentation in TKA: MRI or CT? Knee Surg Sports Traumatol Arthrosc. 2016;24(11):3648–52.

    Article  Google Scholar 

  31. Jerban S, Chang DG, Ma Y, Jang H, Chang EY, Du J. An update in qualitative imaging of bone using ultrashort echo time magnetic resonance. Front Endocrinol. 2020;11:777.

    Article  Google Scholar 

  32. Li Y, Li W, Xiong J, Xia J, Xie Y. Comparison of supervised and unsupervised deep learning methods for medical image synthesis between computed tomography and magnetic resonance images. Biomed Res Int. 2020; 5193707.

  33. Florkow MC, Zijlstra F, Willemsen K, Maspero M, Berg CATvd, Kerkmeijer LGW, et al. Deep learning-based MR-to-CT synthesis: the influence of varying gradient echo-based MR images as input channels. Magn Reson Med. 2020;83(4):1429–41.

    Article  CAS  Google Scholar 

  34. Geiger D, Bae WC, Statum S, Du J, Chung CB. Quantitative 3D ultrashort time-to-echo (UTE) MRI and micro-CT (μCT) evaluation of the temporomandibular joint (TMJ) condylar morphology. Skeletal Radiol. 2014;43(1):19–25.

    Article  Google Scholar 

  35. Deniz CM, Xiang S, Hallyburton RS, Welbeck A, Babb JS, Honig S, et al. Segmentation of the proximal femur from MR images using deep convolutional neural networks. Sci Rep. 2018;8(1):16485.

    Article  Google Scholar 

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Correspondence to Upasana Upadhyay Bharadwaj.

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Bharadwaj, U.U., Coy, A., Motamedi, D. et al. CT-like MRI: a qualitative assessment of ZTE sequences for knee osseous abnormalities. Skeletal Radiol 51, 1585–1594 (2022). https://doi.org/10.1007/s00256-021-03987-2

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  • DOI: https://doi.org/10.1007/s00256-021-03987-2

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