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T2* and quantitative susceptibility mapping in an equine model of post-traumatic osteoarthritis: assessment of mechanical and structural properties of articular cartilage.
Abstract: To investigate the potential of quantitative susceptibility mapping (QSM) and T2* relaxation time mapping to determine mechanical and structural properties of articular cartilage via univariate and multivariate analysis. Samples were obtained from a cartilage repair study, in which surgically induced full-thickness chondral defects in the stifle joints of seven Shetland ponies caused post-traumatic osteoarthritis (14 samples). Control samples were collected from non-operated joints of three animals (6 samples). Magnetic resonance imaging (MRI) was performed at 9.4 T, using a 3-D multi-echo gradient echo sequence. Biomechanical testing, digital densitometry (DD) and polarized light microscopy (PLM) were utilized as reference methods. To compare MRI parameters with reference parameters (equilibrium and dynamic moduli, proteoglycan content, collagen fiber angle and -anisotropy), depth-wise profiles of MRI parameters were acquired at the biomechanical testing locations. Partial least squares regression (PLSR) and Spearman's rank correlation were utilized in data analysis. PLSR indicated a moderate-to-strong correlation (ρ = 0.49-0.66) and a moderate correlation (ρ = 0.41-0.55) between the reference values and T2* relaxation time and QSM profiles, respectively (excluding superficial-only results). PLSR correlations were noticeably higher than direct correlations between bulk MRI and reference parameters. 3-D parametric surface maps revealed spatial variations in the MRI parameters between experimental and control groups. Quantitative parameters from 3-D multi-echo gradient echo MRI can be utilized to predict the properties of articular cartilage. With PLSR, especially the T2* relaxation time profile appeared to correlate with the properties of cartilage. Furthermore, the results suggest that degeneration affects the QSM-contrast in the cartilage. However, this change in contrast is not easy to quantify.
Copyright © 2019 The Author(s). Published by Elsevier Ltd.. All rights reserved.
Publication Date: 2019-07-02 PubMed ID: 31276818DOI: 10.1016/j.joca.2019.06.009Google Scholar: Lookup The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
- Journal Article
- Research Support
- Non-U.S. Gov't
- Animal Models
- Animal Studies
- Articular Cartilage
- Biomechanics
- Cartilage
- Clinical Study
- Diagnosis
- Disease Diagnosis
- Disease Treatment
- Equine Health
- Equine model
- Experimental Methods
- Imaging Techniques
- Magnetic Resonance Imaging
- Osteoarthritis
- Pathophysiology
- Regression Analysis
- Shetland Ponies
- Stifle Joint
- Veterinary Medicine
- Veterinary Research
Summary
This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.
The research paper is a study on how quantitative susceptibility mapping (QSM) and T2* relaxation time mapping can be used to evaluate the structural and mechanical conditions of articular cartilage, in relation to post-traumatic osteoarthritis in an equine model.
Research Objectives
- The study aims to assess the capacity of two magnetic resonance imaging (MRI) techniques – namely, T2* relaxation time mapping and quantitative susceptibility mapping (QSM) – to derive accurate understanding of the mechanical and structural properties of articular cartilage.
- These techniques are particularly used in the context of post-traumatic osteoarthritis, as observed in full-thickness chondral defects-induced Shetland ponies.
Methods
- The researchers obtained samples from two different scenarios- one where the stifle joints of seven Shetland ponies were surgically inflicted with full-thickness chondral defects triggering post-traumatic osteoarthritis (14 samples), and another where samples were collected non-operatively from three ponies (6 samples).
- Using a 3-D multi-echo gradient echo sequence, MRI was carried out at 9.4 T.
- Biomechanical testing, digital densitometry (DD), and polarized light microscopy (PLM) were used as reference methods.
- Depth-wise MRI parameters profiles were developed at the biomechanical testing locations in order to compare MRI parameters with the reference parameters like equilibrium and dynamic moduli, proteoglycan content and collagen fiber angle and -anisotropy.
- Partial least squares regression (PLSR) and Spearman’s rank correlation were utilised in data analysis.
Findings
- PLSR showed a moderate-to-strong correlation (ρ = 0.49-0.66) and a moderate correlation (ρ = 0.41-0.55) between the reference values and T2* relaxation time and QSM profiles, respectively, except in the case of superficial-only results.
- The correlations observed through PLSR were significantly higher than the direct correlations between aggregate MRI and reference parameters.
- 3-D parametric surface maps showed spatial variations in MRI parameters between the experimental and control groups.
Conclusions
- The results suggested that quantitative parameters derived from a 3-D multi-echo gradient echo MRI can be effectively leveraged to predict the properties of the articular cartilage.
- The T2* relaxation time profile, more than anything else, appeared to show a strong correlation with the properties of the cartilage as observed through PLSR.
- It was also indicated that degeneration influences QSM-contrast in cartilage, although such contrast changes are not easy to quantify.
Cite This Article
APA
Nykänen O, Sarin JK, Ketola JH, Leskinen H, Te Moller NCR, Tiitu V, Mancini IAD, Visser J, Brommer H, van Weeren PR, Malda J, Töyräs J, Nissi MJ.
(2019).
T2* and quantitative susceptibility mapping in an equine model of post-traumatic osteoarthritis: assessment of mechanical and structural properties of articular cartilage.
Osteoarthritis Cartilage, 27(10), 1481-1490.
https://doi.org/10.1016/j.joca.2019.06.009 Publication
Researcher Affiliations
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland. Electronic address: olli.nykanen@uef.fi.
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland. Electronic address: jaakko.sarin@uef.fi.
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland. Electronic address: juuso.ketola@oulu.fi.
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland. Electronic address: henriles@uef.fi.
- Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands. Electronic address: N.C.R.teMoller@uu.nl.
- Institute of Biomedicine, Anatomy, University of Eastern Finland, Kuopio, Finland. Electronic address: virpi.tiitu@uef.fi.
- Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands. Electronic address: I.A.D.Mancini@uu.nl.
- Department of Orthopaedics, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: jetzevisser.jv@gmail.com.
- Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands. Electronic address: H.Brommer@uu.nl.
- Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands. Electronic address: r.vanweeren@uu.nl.
- Department of Equine Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands; Department of Orthopaedics, University Medical Center Utrecht, Utrecht, The Netherlands. Electronic address: J.Malda@umcutrecht.nl.
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland; School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia. Electronic address: j.toyras@uq.edu.au.
- Department of Applied Physics, University of Eastern Finland, Kuopio, Finland; Research Unit of Medical Imaging, Physics and Technology, University of Oulu, Oulu, Finland. Electronic address: mikko.nissi@uef.fi.
MeSH Terms
- Animals
- Biomechanical Phenomena
- Cartilage, Articular / diagnostic imaging
- Cartilage, Articular / injuries
- Cartilage, Articular / pathology
- Cartilage, Articular / physiopathology
- Disease Models, Animal
- Disease Susceptibility
- Female
- Horses
- Magnetic Resonance Imaging
- Male
- Osteoarthritis / diagnostic imaging
- Osteoarthritis / etiology
- Osteoarthritis / pathology
- Osteoarthritis / physiopathology
Citations
This article has been cited 10 times.- Zhang Q, Geng J, Zhang M, Kan T, Wang L, Ai S, Wei H, Zhang L, Liu C. Cartilage morphometry and magnetic susceptibility measurement for knee osteoarthritis with automatic cartilage segmentation. Quant Imaging Med Surg 2023 Jun 1;13(6):3508-3521.
- Dimov AV, Li J, Nguyen TD, Roberts AG, Spincemaille P, Straub S, Zun Z, Prince MR, Wang Y. QSM Throughout the Body. J Magn Reson Imaging 2023 Jun;57(6):1621-1640.
- Zhang M, Li Z, Wang H, Chen T, Lu Y, Yan F, Zhang Y, Wei H. Simultaneous Quantitative Susceptibility Mapping of Articular Cartilage and Cortical Bone of Human Knee Joint Using Ultrashort Echo Time Sequences. Front Endocrinol (Lausanne) 2022;13:844351.
- Hananouchi T, Chen Y, Jerban S, Teramoto M, Ma Y, Dorthe EW, Chang EY, Du J, D'Lima DD. A Useful Combination of Quantitative Ultrashort Echo Time MR Imaging and a Probing Device for Biomechanical Evaluation of Articular Cartilage. Biosensors (Basel) 2021 Feb 17;11(2).
- Kajabi AW, Casula V, Sarin JK, Ketola JH, Nykänen O, Te Moller NCR, Mancini IAD, Visser J, Brommer H, René van Weeren P, Malda J, Töyräs J, Nieminen MT, Nissi MJ. Evaluation of articular cartilage with quantitative MRI in an equine model of post-traumatic osteoarthritis. J Orthop Res 2021 Jan;39(1):63-73.
- Brinkhof S, Te Moller N, Froeling M, Brommer H, van Weeren R, Ito K, Klomp D. T2* mapping in an equine articular groove model: Visualizing changes in collagen orientation. J Orthop Res 2020 Nov;38(11):2383-2389.
- Guermazi A, Eckstein F, Gold G, Hayashi D, Jarraya M, Kogan F, Li X, Link TM, Nebelung S, Oei EHG, Omoumi P, Saarakkala S, Trattnig S, Wirth W, Roemer FW. Advances in cartilage imaging techniques. Nat Rev Rheumatol 2026 Feb 3;.
- Champagne AA, Zuleger TM, Smith DR, Slutsky-Ganesh AB, Warren SM, Ramirez ME, Sengkhammee LM, Mandava S, Wei H, Bardana DD, Lamplot JD, Myer GD, Diekfuss JA. Quantitative susceptibility and T1 ρ mapping of knee articular cartilage at 3T. Osteoarthr Cartil Open 2024 Sep;6(3):100509.
- Casula V, Kajabi AW. Quantitative MRI methods for the assessment of structure, composition, and function of musculoskeletal tissues in basic research and preclinical applications. MAGMA 2024 Dec;37(6):949-967.
- Hananouchi T, Satake S, Sakao K, Katsuda H, Shimada N, Dorthe EW, D'Lima DD. Determining the Relationship between Mechanical Properties and Quantitative Magnetic Resonance Imaging of Joint Soft Tissues Using Patient-Specific Templates. Bioengineering (Basel) 2023 Sep 7;10(9).
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